TWI827889B - Methods and apparatuses for managing transducer array placement and relevant non-transitory computer readable medium - Google Patents

Abstract

Methods, systems, and apparatuses are described for managing placement of transducer arrays on a subject/patient.

Description

Methods and apparatus for managing sensor array placement and related non-transitory computer-readable media

The present application relates to methods, systems and devices for managing sensor array placement.

Tumor Treating Fields (TTFields) are low-intensity (eg, 1-3V/cm) alternating electric fields within the mid-frequency range (100-300kHz). This non-invasive treatment targets solid tumors and is described in US Patent No. 7,565,205, which is incorporated herein by reference in its entirety. Tumor treatment electric fields interfere with cell division through physical interactions with key molecules during mitosis. Tumor Treating Fields therapy is an approved monotherapy for recurrent glioblastoma multiforme and an approved combination therapy with chemotherapy for newly diagnosed patients. These electric fields are introduced non-invasively via an array of sensors (ie, an array of electrodes) placed directly on the patient's scalp. Tumor treatment electric fields also appear to be beneficial in treating tumors in other parts of the body.

The efficacy of tumor treatment electric field therapy increases with the intensity of the electric field. Changing the positioning of the sensor array on the patient's scalp (and/or other parts of the body) will affect the strength of the electric field in a target area. Determining how the positioning of the sensor array should change while maintaining the target intensity of the electric field in the target area is a difficult, labor-intensive and time-consuming process.

Disclosed is a method that includes generating a three-dimensional (3D) model of a body part of a subject, determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions, and determining a plurality of sensor array layouts from the plurality of simulated electric field distributions. A sensor array layout is used to determine one or more sets of sensor array layouts, wherein each set of sensor array layouts represents at least two sensor array layouts having non-overlapping positions for a plurality of pairs of positions of the sensor array arrangement, where The at least two sensor array layouts meet a standard, and the one or more groups of sensor array layouts are displayed.

A method is also disclosed, which includes generating a three-dimensional (3D) model of a part of a subject's body, determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions, and receiving data from the plurality of sensor arrays. a first sensor array layout selected from the sensor array layout, wherein the first sensor array layout satisfies a criterion and one or more related sensor array layouts are determined from the plurality of sensor array layouts, wherein each associated sensor array layout includes a location for a sensor array arrangement that does not overlap a location for a sensor array arrangement of said first sensor array layout, and wherein each associated sensor array layout satisfies the requirements The standard is used to receive a second sensor array layout selected from the one or more related sensor array layouts, and display of the first sensor array layout and the second sensor array layout is performed.

A method is also disclosed, which includes generating a three-dimensional (3D) model of a part of a subject's body, determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions, and receiving data from the plurality of sensor arrays. The first sensor array layout and the second sensor array layout selected in the sensor array layout, determining the overlapping status according to the first sensor array layout and the second sensor array layout, and performing the overlapping Status display.

Additional advantages will be set forth in part in the description that follows, or may be implemented by learned. Said advantages will be realized and achieved by means of elements and combinations particularly pointed out in the appended claims. It will be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive.

100:Equipment

102: Electric field generator

104, 104a, 104b: sensor array

106: Processor

108: Signal generator

110:Control software

112: Conductive lead

114:Output

116:Electrode

118:Circuit board

120, 120a, 120b: Adhesive bandage

302:Skin surface

304:Tumor

306: Bone tissue

308: Brain tissue

310:Alternating electric field

600:System

602:Patient support system

606: Electric Field Generator (EFG) Configuration Application

608:Build Patient Model Application

610: Imaging data

800:Array layout diagram

1000:System

1001:Patient Support Module

1008: Processor

1010:Memory

1012:I/O interface

1014:Network interface

1018:Operating system

1020: User device

1022:Interface module

1023: Communication module

1030: User device

1100:User interface

1101:Screen

1102:Information

1103:Interactive elements

1104:Interactive elements

1105:Panel

1106:Image

1107:Window

1108:Element

1109:Area

1110:Interactive elements

1111:Screen

1112:Interactive elements

1113:Interactive elements

1114:Screen

1115:Interactive elements

1116:Region

1117:Region

1200:Method

1210: Steps

1220: Steps

1230: Steps

1240:Step

1300:Method

1310: Steps

1320: Steps

1330: Steps

1340: Steps

1350: Steps

1360: steps

1400:Method

1410: Steps

1420: Steps

1430: Steps

1440: Steps

1450: Steps

To easily identify any particular component or act being discussed, the most significant digit or digits in a component symbol is referenced to the drawing number in which the component is first introduced.

[Figure 1] shows an example device for electrotherapy treatment.

[Figure 2] shows an example sensor array.

[Fig. 3] A and 3B depict an example application of the device for electrotherapy treatment.

[Fig. 4] A shows a sensor array arranged on a patient's head.

[Fig. 4] B shows a sensor array arranged on the abdomen of a patient.

[Fig. 5] A shows a sensor array arranged on a patient's torso.

[Fig. 5] B shows a sensor array arranged on a patient's pelvis.

[Fig. 6] is a block diagram of a system for managing sensor array placement.

[Figure 7] depicts the electric field magnitude and distribution (in V/cm) from a finite element method simulation model shown in coronal view.

[Fig. 8] A is a three-dimensional array layout diagram 800.

[Fig. 8] B shows the arrangement of the sensor array on the scalp of a patient.

[Figure 9] A shows an axial T1 sequence section including the topmost image, which includes the orbit used to measure head dimensions.

[Figure 9] B shows a coronal T1 sequence section, which is selected to measure the head size at the height of the ear canal.

[Figure 9] C shows a pair of post-contrast T1 axial images, which are used to measure tumor location. The maximum enhanced tumor diameter.

[Figure 9] D shows a post-contrast T1 coronal image that was used to measure the maximum enhanced tumor diameter at the tumor location.

[Fig. 10] is a system showing an example of managing sensor array arrangement.

[Figure 11] A to 11D show an example user interface for managing sensor array placement.

[Fig. 12] is a method showing an example for managing sensor array arrangement.

[Fig. 13] is a method showing an example for managing sensor array arrangement.

[Fig. 14] is a method showing an example for managing sensor array arrangement.

Before the present methods and systems are disclosed and described, it will be understood that the methods and systems are not limited to specific methods, specific components, or specific implementations. It will also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

As used in the specification and the appended claims, the singular forms "a", "an" and "the" include plural referents unless the context clearly requires otherwise. Ranges may be expressed herein as from "about" one particular value and/or to "about" another particular value. When such a range is expressed, another embodiment includes from the one particular value and/or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent "about," it will be understood that the particular values constitute another embodiment. It will further be understood that both the endpoints of each of the stated ranges are significant with respect to the other endpoint, as well as independently of the other endpoint.

"Optional" or "optionally" means that the subsequently described event or circumstance may or may not occur, and thus the description includes instances in which the stated event or circumstance occurs, and instances in which it does not instances of occurrence.

Throughout the description and claims in this specification, the word "include" and its conjugations (such as "includes" and "includes") mean "including but not limited to" and are not intended to exclude, for example, Other components, integers or steps. "Exemplary" means "one example" and is not intended to convey an indication of a preferred or ideal embodiment. "For example" is not used in a restrictive sense but for explanatory purposes.

Disclosed are components that can be utilized to perform the disclosed methods and systems. As with all methods and systems, these and other components are disclosed herein, and it is understood that while combinations, sub-sets, interactions, groups, etc. of these components are disclosed, notwithstanding the various aspects of each of these Specific references to individual and collective combinations and arrangements may not be explicitly disclosed, but each is clearly contemplated and is therefore described here. This applies to all features of this application, including but not limited to steps in the disclosed methods. Accordingly, if there are various additional steps that may be performed, it is understood that each of these additional steps may be performed with any particular embodiment or combination of embodiments of the disclosed methods.

The present method and system may be more readily understood by reference to the following detailed description of the preferred embodiments and the examples contained therein, and by reference to the drawings and their preceding and subsequent descriptions.

As those skilled in the art will appreciate, the methods and systems may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware features. Furthermore, the methods and systems may take the form of a computer program product on a computer-readable storage medium having computer-readable program instructions (e.g., computer software) embodied in the storage medium. ). More specifically, the methods and systems may take the form of network-implemented computer software. Any suitable computer-readable storage medium may be utilized, including hard drives, CD-ROMs, optical storage devices, or magnetic storage devices.

Embodiments of the methods and systems are described below with reference to block diagrams and flowchart illustrations of methods, systems, apparatus, and computer program products. It will be understood that each block of the block diagram and flowchart diagrams, and combinations of blocks in the block diagram and flowchart diagrams, respectively, can be implemented by computer program instructions. These computer program instructions can be loaded into a general purpose computer, a special purpose computer, or other programmable data processing equipment to produce a machine that operates on the computer or other programmable data processing equipment. The instructions that execute on produce a means for performing the functions specified in the flowchart block or blocks.

These computer program instructions can also be stored in a computer-readable memory, which can instruct a computer or other programmable data processing equipment to act in a specific manner, so that the instructions stored in the computer-readable memory The instructions in the memory produce a product that includes computer-readable instructions for performing the functions specified in the flowchart block or blocks. The computer program instructions can also be loaded onto a computer or other programmable data processing equipment, so that a series of operating steps are executed on the computer or other programmable equipment to generate a computer A program is implemented such that the instructions executing on the computer or other programmable device provide steps for performing the functions specified in the flowchart block or blocks.

Thus, blocks of the block diagram and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions, and combinations of steps for performing the specified functions. Program instruction means. It will also be understood that each block of the block diagram and flowchart diagrams, and combinations of blocks in the block diagram and flowchart diagrams, can be configured to perform the functions specified or The steps are implemented by a computer system based on special purpose hardware, or a combination of special purpose hardware and computer instructions.

Tumor therapeutic electric fields (also referred to here as alternating electric fields) are established as an anti-mitotic cancer treatment modality because they interfere with proper microtubule assembly during metaphase and ultimately destroy all microtubules during telophase and cytoplasmic division. Describe cells. The efficacy increases with increasing field strength, and The optimal frequency is line-dependent for cancer cells, and 200kHz is the frequency that inhibits the growth of glioma cells the most due to the tumor treatment electric field. For cancer treatment, non-invasive devices have been developed in which capacitively coupled sensors are placed directly on the skin area close to the tumor, such as for patients with glioblastoma multiforme (GBM), which is the human The most common major malignant brain tumor.

Because the effects of tumor treatment electric fields are directional, where cell divisions parallel to the electric field are more affected than cell divisions in other directions, and because cells divide in all directions, tumor treatment electric fields generally It is delivered through two pairs of sensor arrays, which generate vertical fields within the tumor being treated. More specifically, one pair of sensor arrays may be located to the left and right (LR) of the tumor, while another pair of sensor arrays may be located to the anterior and posterior (AP) of the tumor. Cycling the electric field between these two directions (ie, LR and AP) ensures that a maximum range of cell orientations is targeted. In addition to vertical fields, other sensor array locations are also considered. In one embodiment, an asymmetric positioning of three sensor arrays is contemplated, wherein one pair of the three sensor arrays can transmit an alternating electric field, and then the other pair of the three sensor arrays The alternating electric field may be transmitted while the remaining pairs of the three sensor arrays may transmit the alternating electric field.

In vivo and in vitro studies have shown that the efficacy of tumor treatment electric field therapy increases with the intensity of the electric field. Therefore, it is standard practice for Optune systems to optimize array placement on the patient's scalp to increase intensity in diseased areas of the brain. Optimization of array placement can be performed by "rules of thumb" (e.g., place the array on the scalp as close as possible to the tumor) measurements that describe the patient's head geometry, tumor size , and/or tumor location. The measurements used as input can be derived from imaging data. Imaging data is intended to include any type of visual data, such as single photon emission computed tomography (SPECT) image data, X-ray computed tomography (X-ray CT) data, magnetic resonance imaging (MRI) data, positron emission Computed tomography (PET) data is data captured by optical equipment (eg, cameras, charge-coupled device (CCD) cameras, infrared cameras, etc.), and the like. In some embodiments, the image data may include images from 3D 3D data (for example, point cloud data) obtained by a scanner or generated by a 3D scanner. Optimization may depend on how the electric field is distributed within the head as a function of the position of the array, and in some features, consider the distribution of electrical properties within the head of different patients. understanding of change. A plurality of sensor array patterns may be determined that indicate optimal positioning of the sensor array on a patient's body that satisfies various criteria (e.g., provides an electric field within a region of interest (ROI) minimum and/or maximum intensity, power density within the ROI, etc.).

Because the positioning of the sensor array on a patient's scalp (and/or other parts of the body) affects the electric field strength in an ROI and/or target area, the positioning of the sensor array can be changed while maintaining the A sensor array pattern of a target intensity of the electric field in the ROI and/or target area may be determined.

Figure 1 illustrates an example device 100 for electrotherapy treatment. Generally speaking, the device 100 may be a portable battery or power supply-operated device that uses a non-invasive surface sensor array to generate an alternating electric field within the body. The device 100 may include an electric field generator 102 and one or more sensor arrays 104. The device 100 may be configured to generate tumor treatment electric fields (TTFields) via the electric field generator 102 (eg, at 150 kHz) and to deliver the tumor treatment electric fields through the one or more sensor arrays 104 to the device. Describe an area of the body. The electric field generator 102 may be a device operated by a battery and/or a power supply. In one embodiment, the one or more sensor arrays 104 are uniformly shaped. In one embodiment, the one or more sensor arrays 104 are not uniformly shaped.

The electric field generator 102 may include a processor 106 in communication with a signal generator 108 . The electric field generator 102 may include control software 110 configured to control execution of the processor 106 and the signal generator 108 .

The signal generator 108 can generate one or more electrical signals having the shape of a waveform or a pulse train. The signal generator 108 may be configured to generate a signal ranging from about 50 KHz to about 500 KHz An AC voltage waveform within a frequency (preferably from about 100KHz to about 300KHz) (eg, the tumor treatment electric field). The voltage is such that the electric field strength in the tissue to be treated is in the range of about 0.1 V/cm to about 10 V/cm.

One or more outputs 114 of the electric field generator 102 may be coupled to one or more conductive leads 112 that are attached at one end thereof to the signal generator 108 . Opposite ends of the conductive leads 112 are connected to the one or more sensor arrays 104, which are activated by the electrical signal (eg, waveform). The conductive leads 112 may comprise standard isolated conductors with flexible metal shields, and may be grounded to avoid the spread of electric fields generated by the conductive leads 112 . The one or more outputs 114 may be operated sequentially. Output parameters of the signal generator 108 may include, for example, the strength of the field, the frequency of the waves (eg, treatment frequency), and the maximum allowable temperature of the one or more sensor arrays 104 . The output parameters may be set and/or determined by the control software 110 in conjunction with the processor 106 . After determining a desired (eg, optimal) treatment frequency, the control software 110 can cause the processor 106 to send a control signal to the signal generator 108, which causes the signal generator 108 to output the desired the treatment frequency to the one or more sensor arrays 104.

The one or more sensor arrays 104 may be configured in various shapes and positions to generate an electric field in a target volume with the desired configuration, direction, and intensity to facilitate focused therapy. The one or more sensor arrays 104 may be configured to deliver two vertical field directions across a volume of interest.

The one or more sensor arrays 104 may include one or more electrodes 116 . The one or more electrodes 116 may be made of any material with a high dielectric constant. The one or more electrodes 116 may include, for example, one or more insulating ceramic disks. The electrode 116 may be biocompatible and coupled to a flexible circuit board 118 . The electrodes 116 may be configured so as not to come into direct contact with the skin because the electrodes 116 are separated from the skin by a layer of conductive hydrogel (not shown) (similar to the hydrogel found on EKG pads).

The electrodes 116, the hydrogel, and the flexible circuit board 118 may be attached to a hypo-allergenic medical adhesive bandage 120 to attach the one or more The sensor array 104 remains in place on the body and is in constant direct contact with the skin. Each sensor array 104 may include one or more thermistors (not shown), such as 8 thermistors (accuracy ±1°C), to measure the skin temperature beneath the sensor array 104 . The thermistor may be configured to measure skin temperature periodically (eg, every second). The thermistor can be read by the control software 110 when the tumor treatment electric field is not being delivered, in order to avoid any interference with the temperature measurement.

If the temperature measured between two consecutive measurements is lower than a preset maximum temperature (Tmax), such as 38.5-40.0℃±0.3℃, the control software 110 can increase the current until the current until the maximum treatment current is reached (e.g., 4 amps peak to peak). If the temperature reaches Tmax+0.3°C and continues to rise, the control software 110 can reduce the current. If the temperature rises to 41° C., the control software 110 may turn off the therapy of the tumor treatment electric field, and an overheating alarm may be triggered.

The one or more sensor arrays 104 may vary in size and may include a different number of electrodes 116 depending on patient body size and/or different treatments. For example, in the context of a patient's chest, small sensor arrays may each include 13 electrodes, while large sensor arrays may each include 20 electrodes, with the electrodes in each array being interconnected in series. For example, as shown in Figure 2, in the context of a patient's head, each sensor array may include 9 electrodes, wherein the electrodes in each array are interconnected in series.

The status of the device 100 and the monitored parameters may be stored in a memory (not shown) and may be transmitted to a computing device through a wired or wireless connection. The device 100 may include a display (not shown) for displaying visual indicators such as power on, treatment in progress, alarm, and low battery.

Figures 3A and 3B depict an example application of the device 100. A sensor array 104a And a sensor array 104b is shown incorporated into a hypoallergenic medical adhesive bandage 120a and 120b respectively. The hypoallergenic medical adhesive bandages 120a and 120b are applied to the skin surface 302. A tumor 304 is located beneath the skin surface 302 and bone tissue 306 and within brain tissue 308 . The electric field generator 102 causes the sensor array 104a and the sensor array 104b to generate an alternating electric field 310 within the brain tissue 308, which interferes with the rapid cell division exhibited by the cancer cells of the tumor 304. . The alternating electric field 310 has been shown in non-clinical experiments to prevent the spread of tumor cells and/or destroy tumor cells. The use of the alternating electric field 310 takes advantage of the special characteristics, geometry, and velocity of dividing cancer cells, which make them susceptible to the effects of the alternating electric field 310 . The alternating electric field 310 changes its polarity at an intermediate frequency (on the order of 100-300 kHz). The frequency used for a particular treatment may be specific to the cell type being treated (eg, 150 kHz for MPM). The alternating electric field 310 has been shown to disrupt mitotic spindle microtubule assembly during cytokinesis and cause dielectrophoretic misalignment of macromolecules and organelles within the cell. These processes lead to physical disturbance of cell membranes and programmed cell death (apoptosis).

Because the effect of the alternating electric field 310 is directional, where cell division parallel to the electric field is more affected than cell division in other directions, and because cells divide in all directions, therefore The alternating electric field 310 can be delivered through two pairs of sensor arrays 104, which generates a vertical field within the tumor being treated. More specifically, one pair of sensor arrays 104 may be positioned to the left and right (LR) of the tumor, while the other pair of sensor arrays 104 may be positioned to the anterior and posterior (AP) of the tumor. Cycling the alternating electric field 310 between these two directions (eg, LR and AP) ensures that a maximum range of cell orientations is targeted. In one embodiment, the alternating electric field 310 may be transmitted according to a symmetrical arrangement of sensor arrays 104 (eg, a total of four sensor arrays 104, two matched pairs). In another embodiment, the alternating electric field 310 may be delivered according to an asymmetric arrangement of sensor arrays 104 (eg, three sensor arrays 104 in total). An asymmetric arrangement of sensor array 104 may So that two of the three sensor arrays 104 transmit the alternating electric field 310, and then switch to the other two of the three sensor arrays 104 to transmit the alternating electric field 310, and the like. .

In vivo and in vitro studies have shown that the efficacy of tumor treatment electric field therapy increases with the intensity of the electric field. The methods, systems, and devices are configured for optimizing array placement on a patient's scalp to increase intensity in diseased areas of the brain.

As shown in Figure 4A, the sensor array 104 may be positioned on a patient's head. As shown in Figure 4B, the sensor array 104 may be disposed on a patient's abdomen. As shown in Figure 5A, the sensor array 104 may be disposed on a patient's torso. As shown in Figure 5B, the sensor array 104 may be positioned on a patient's pelvis. The placement of the sensor array 104 on other parts of a patient's body (eg, arms, feet, etc.) is expressly contemplated.

6 is a block diagram depicting a non-limiting example of a system 600 that includes a patient support system 602. The patient support system 602 may include one or more computers configured to operate and/or store an electric field generator (EFG) configuration application 606, a patient modeling application 608, and/or imaging data 610. The patient support system 602 may include a computing device, for example. The patient support system 602 may include, for example, a laptop computer, a desktop computer, a mobile phone (eg, a smartphone), a tablet computer, and the like.

The patient model application 608 may be configured to generate a three-dimensional model (eg, a patient model) of a portion of a patient's body based on the imaging data 610 . The imaging data 610 may include any type of visual data, such as single photon emission computed tomography (SPECT) image data, X-ray computed tomography (X-ray CT) data, and magnetic resonance imaging (MRI) data. , positron emission computed tomography (PET) data, data that can be captured by optical equipment (e.g., cameras, charge-coupled device (CCD) cameras, infrared cameras, etc.), and the like. In some embodiments, the image data may include 3D data (eg, point cloud data) obtained from or generated by a 3D scanner. The patient modeling application 608 may also be configured to The patient model and one or more electric field simulations are used to generate a three-dimensional array layout.

In order to properly optimize array placement on a portion of a patient's body, the imaging data 610 (eg, MRI imaging data) can be analyzed by the patient modeling application 608 to identify a tumor that includes a tumor. area of concern. In the context of a patient's head, in order to describe how electric fields behave and are distributed within the human head, a modeling framework based on an anatomical head model simulated using the finite element method (FEM) can be used . These simulations are based on magnetic resonance imaging (MRI) measurements to produce realistic head models and classify tissue types within the head, such as skull, white matter, gray matter, and cerebrospinal fluid (CSF). Each tissue type can be assigned dielectric properties with respect to relative conductivity and permittivity, and simulations can be performed whereby different sensor array configurations are applied to the surface of the model to understand a predetermined How an externally applied electric field of given frequency will spread throughout any part of a patient's body (eg, brain). The results of these simulations using a paired array configuration, a fixed current, and a preset frequency of 200 kHz have demonstrated that the electric field distribution throughout the brain is quite non-uniform, and that electric field strengths exceeding 1 V/cm are generated in In most tissue compartments except CSF. These results were obtained assuming a peak-to-peak total current of 1800 milliamps (mA) at the sensor array-scalp interface. This critical value of electric field strength is sufficient to inhibit cell proliferation in glioblastoma cell lines. Furthermore, by manipulating the configuration of the paired sensor arrays, it is possible to achieve almost three times the electric field strength in a specific area of the brain as shown in Figure 7. Figure 7 depicts the electric field magnitude and distribution (in V/cm) from a finite element method simulation model shown in a coronal view. This simulation utilizes a left-right paired sensor array configuration.

In one feature, the patient modeling application 608 can be configured to determine the desired (eg, optimal) sensor array layout for a patient based on the location and extent of the tumor. For example, initial morphometric head size measurements can be determined from a T1 sequence brain MRI using axial and coronal views. Postcontrast axial and coronal MRI sections can be selected to show the maximum diameter of the enhancing lesion. Using head dimensions and distance from preset fiducial markers to tumor edge Measurement, different arrangements and combinations of paired array layouts can be evaluated in order to produce a configuration that delivers maximum electric field strength to the tumor location. As shown in Figure 8A, the output may be a three-dimensional array layout 800. As shown in Figure 8B, the three-dimensional array layout 800 (eg, a sensor array layout) may be used by patients and/or caregivers to place the array on the scalp during normal tumor treatment electric field therapy. superior.

In one feature, the patient modeling application 608 can be configured to determine a three-dimensional array layout for a patient. MRI measurements of the portion of the patient that will receive the sensor array can be determined. For example, the MRI measurements may be received via a standard Digital Imaging Protocol in Medicine (DICOM) viewer. The determination of MRI measurements may be performed automatically, such as by artificial intelligence techniques, or may be performed manually, such as by a physician.

Manual determination of MRI measurements may include receiving and/or providing MRI data via a DICOM viewer. The MRI data may include scans of the portion of the patient that contains a tumor. For example, in the context of a patient's head, the MRI data may include scans of the head including right frontotemporal tumors, right parietotemporal tumors, left frontotemporal tumors, left parieto-occipital tumors, and /or one or more of the multifocal midline tumors. Figures 9A, 9B, 9C and 9D are exemplary MRI data showing scans of a patient's head. Figure 9A shows an axial T1 sequence view with the most apical image, including the orbit used to measure head dimensions. Figure 9B shows a coronal T1 sequence section, which selects images at the height of the ear canal and is used to measure head size. Figure 9C shows a post-contrast T1 axial image showing the maximum enhanced tumor diameter used to measure tumor location. Figure 9D shows a post-contrast T1 coronal image showing the maximum enhanced tumor diameter used to measure tumor location. MRI measurements can begin from fiducial markers at the lateral edge of the scalp and extend tangentially from a right, anterior, and superior origin. Morphometric head size can be estimated from selection of axial T1 MRI sequences that still contain the apical-most image of the orbit (or the image directly above the upper edge of the orbit).

In one feature, the MRI measurements may include, for example, head size measurements and/or tumor One or more of the measurements. In one feature, one or more MRI measurements can be rounded to the nearest millimeter and provided to a sensor array deployment module (eg, software) for analysis. The MRI measurements may then be used to generate the three-dimensional array layout (eg, three-dimensional array layout 800).

The MRI measurements may include one or more head dimensional measurements, for example: a maximum anteroposterior (A-P) head dimension, measured from the lateral edge of the scalp; The greatest width measured: the left and right transverse distance; and/or the distance from the farthest right edge of the scalp to the anatomical midline.

The MRI measurements may include one or more cephalometric measurements, such as coronal view cephalometric measurements. Head dimension measurements in the coronal view can be obtained on a T1 MRI sequence with the image selected at the height of the ear canal (Fig. 9B). The coronal view cephalometric measurements may include one or more of the following: a vertical measurement from the top of the scalp to an orthogonal line delineating the inferior edge of the temporal lobe; a maximum lateral measurement from right to left. Head width; and/or the distance from the rightmost edge of the scalp to the anatomical midline.

The MRI measurements may include one or more tumor measurements, such as tumor location measurements. The tumor location measurement can be made using a T1 post-contrast MRI sequence first on the axial image showing the largest enhancing tumor diameter (Fig. 9C). The tumor location measurements may include one or more of the following: a maximum A-P head dimension excluding the nose; a maximum right-to-left lateral diameter measured perpendicular to the A-P distance; A distance from the right edge to the anatomical midline; a distance parallel to the left and right lateral distances and perpendicular to the A-P measurement from the right edge of the scalp to the closest tumor edge; parallel to the The left and right lateral distance, the distance perpendicular to the A-P measurement from the right edge of the scalp to the farthest edge of the tumor; the distance parallel to the A-P measurement from the front end of the head to the closest A distance from the edge of the tumor; and/or a distance from the front end of the head to the farthest edge of the tumor measured parallel to the A-P measurement.

The one or more tumor measurements may include coronal view tumor measurements. The coronal view Tumor measurement may include identification of post-contrast T1 MRI sections characterized by tumor enhancement of maximum diameter (Figure 9D). The coronal view tumor measurements may include one or more of the following: a maximum distance from the top of the scalp to the lower edge of the cerebrum. In the anterior view, this will be demarcated by a horizontal line drawn on the inferior border of the frontal or temporal lobes, and it will extend posteriorly to the lowest height of the visible tentorium; a Maximum width of the head in the right to left transverse direction; a distance from the right edge of the scalp to the anatomical midline; a distance measured parallel to the left and right transverse direction from the right edge of the scalp to the closest tumor A distance from the edge; a distance from the right edge of the scalp to the farthest edge of the tumor, measured parallel to the left and right transverse distances; a distance from the top of the head to the farthest edge, measured parallel to the upper tip to lower brain line A distance from the proximal tumor edge; and/or a distance from the top of the head to the farthest tumor edge measured parallel to the superior apical to inferior brain line.

Other MRI measurements may be utilized, especially if the tumor is present in another part of the patient's body.

The MRI measurements may be utilized by the patient modeling application 608 to generate a patient model. The patient model may then be used to determine a three-dimensional array layout (eg, three-dimensional array layout 800). Continuing with the example of a tumor within a patient's head, a healthy head model can be generated, which serves as a deformable template from which the patient model can be generated. When a patient model is generated, the tumor can be segmented from the patient's MRI data (eg, one or more MRI measurements). Segmenting the MRI data identifies the tissue type in each voxel, and electrical properties can be assigned to each tissue type based on empirical data. Table 1 shows the electrical characteristics of standard tissues that can be used in simulations. Tumor areas may be occluded in the patient's MRI data, so non-rigid registration algorithms can be used to register the remaining areas of the patient's head to a deformable representation of the healthy head model. version of the 3D discrete image. This process produces a non-rigid transformation that maps the healthy part of the patient's head into template space, and an inverse transformation that maps the template into patient space. The inverse transformation is applied to the 3D deformable template to generate the patient head An approximation without tumors. Finally, the tumor, known as a region of interest (ROI), is transplanted back into the deformed template to create a complete patient model. The patient model may be a digital representation of a portion of the patient's body (including internal structures, such as tissues, organs, tumors, etc.) in three-dimensional space.

The delivery of tumor treatment electric fields can then be simulated using the patient model by the patient model application 608 . Simulated electric field distribution, dose, and simulation-based analysis are described in U.S. Patent Publication No. 20190117956 A1 and publication "Correlation of Tumor treating Fields Dosimetry to Survival Outcomes in Newly Diagnosed Glioblastoma: A" by Ballo et al. (2019) Large-Scale Numerical Simulation-based Analysis of Data from the Phase 3 EF-14 randomized Trial", which is incorporated herein by reference in its entirety.

To ensure systematic positioning of the sensor array relative to the tumor location, a reference coordinate system can be defined. For example, a transversal plane may initially be defined by the conventional LR and anterior-posterior (AP) positioning of the sensor array. The left-right direction may be defined as the x-axis, the AP direction may be defined as the y-axis, and the cranio-caudal direction perpendicular to the xy plane may be defined as the z-axis.

After defining the coordinate system, the sensor array can actually be arranged on the patient model with its center and longitudinal axis in the xy plane. A pair of sensor arrays can be systematically rotated about the z-axis of the head model, that is, from 0 to 180 degrees in the xy plane, thereby (symmetrically) covering the entire circumference of the head. The rotation interval may be, for example, 15 degrees, which corresponds to a translation of approximately 2 cm, which results in a total of twelve different positions in a range of 180 degrees. Other rotation intervals are also considered. Electric field distribution calculations can be performed for each sensor array position relative to the tumor's coordinates.

The electric field distribution in the patient model may be determined by the patient model application 608 using a finite element (FE) approximation of electrical potential. In general, the quantities defining a time-varying electromagnetic field are given by the complex Maxwell equations. However, in biological tissue and at low to medium frequency tumor treatment electric fields (f=200kHz), the electromagnetic wavelength is much larger than the size of the head, and the dielectric coefficient ε compared to the real-valued conductivity σ is Negligible, that is, where ω = 2πf is the angular frequency. This means that the electromagnetic propagation effect and capacitance effect in the tissue are negligible, so the scalar potential can be well determined by the static Laplace equation ▽ under appropriate boundary conditions between the electrode and the skin. (σ▽Φ)=0 to approximate. Therefore, the complex impedance is treated as resistive (that is, the reactance is negligible), and the current flowing within the volume conductor is therefore primarily a free (ohmic) current. The FE approximation of Laplace's equation can be calculated using software such as SimNIBS software (simnibs.org). according to Calculations of the Galerkin method and the residuals for the conjugate gradient solver need to be <1E-9. Dirichlet boundary conditions are used when the potential of each set of electrode arrays is set to an (arbitrarily chosen) fixed value. The electric (vector) field can be calculated as the gradient of the magnitude of the potential, and the current density (vector field) can be calculated from the electric field using Ohm's law. The potential difference of the electric field values and the current density can be linearly rescaled to ensure a total peak-to-peak amplitude of 1.8A for each array pair, which is calculated for all triangular surfaces on the active electrode disk. The (numerical) area integral of the normal current density component over an element. The "dose" of a tumor-treating electric field can be calculated as the intensity of the electric field vector (L2 norm). The current being modeled can be assumed to be provided by two separate and sequential sources, each connected to a pair of 3×3 sensor arrays. The left and rear arrays may be defined in the simulation as sources, while the right and front arrays are respectively the corresponding sinks. However, since tumor treatment electric fields utilize alternating fields, this choice is arbitrary and does not affect the results.

An average electric field strength generated by an array of sensors positioned at multiple locations on the patient may be determined for one or more tissue types by the patient modeling application 608 . In one feature, the sensor array location corresponding to the highest average electric field strength in the tumor tissue type may be selected as a desired (eg, optimal) sensor array location for the patient.

In some examples, sensor array placement (eg, optimized sensor array placement) may be determined for effective and/or optimized tumor treatment electric field treatment and/or therapy. For example, one or more users (e.g., physicians, nurses, assistants, staff, physicists, dosimetrists, etc.) may use a user interface to determine and/or generate sensor array layouts (e.g., three-dimensional array layout diagram, etc.) for positioning the sensor array on the body (e.g., head, torso, etc.) of a person (e.g., patient, subject, etc.) that will optimize tumor treatment Electric field treatments and/or therapies while avoiding and/or limiting skin toxicity. For example, a plurality of sensor array layouts (e.g., groups, profiles, etc.) may be determined, each of which contains sensor array layouts that meet one or more criteria. Bureau map. A criterion may include a potential magnitude of an electric field distributed within a region of interest (ROI) associated with a person (e.g., patient, subject, etc.), and a potential magnitude distributed within the ROI. A potential power density associated with the electric field, an estimate of skin toxicity associated with the part of the human body (eg, head, torso, etc.), and/or any other criteria. A plurality of sets of sensor array layouts in the plurality of sets of sensor array layouts may be determined, which include two or more sensor array layouts containing non-overlapping locations for sensor array placement. The plurality of sets of sensor array layouts may, for example, be displayed to the user and/or may be selectable, for example, via a user interface. The user interface may be used to select a sensor array layout, and based on the selection, be presented with a plurality of sets of sensor array layouts in the plurality of sets of sensor array layouts that are associated with the selected sensor. Array layout related (eg, according to a criterion, according to non-overlapping positions, overlapping positions, etc.).

An example method may include providing a plurality of images of an anatomical volume to at least one user, and receiving from the at least one user selected images from the anatomical volume that should be used to generate a plurality of sensor array layouts. image. The method may include generating a model (3D model) of electrical characteristics of the anatomical volume based on the selected images and determining a plurality of sensor array layouts. It is then evaluated based on the generated model which of the decided sensor array layouts satisfy at least one criterion. The method may include providing a plurality of sensor array layouts that meet the at least one criterion to the at least one user, and receiving the sensor array from the at least one user for presentation to the at least one user. A selection of one of the layouts. A report describing the selected sensor array layout can be generated. In some examples, the model may also be based on at least one additional image. In some examples, generating the model may include performing segmentation based on input received from the at least one user. In some examples, the at least one user may include a first user and a second user. The method may also include accepting input from the first user identifying the area of interest and outputting data describing the area of interest to the second user. In some examples, generating the model may include performing segmentation based on input received from the second user. In some instances, the method may include The method includes receiving input confirming gross segmentation from the first user and outputting data describing the gross segmentation to the second user. In some examples, generating the model may include performing segmentation based on input received from the second user. In some examples, the method may include accepting at least one note from the first user and outputting the at least one note to the second user. In some examples, generating the model may include performing segmentation based on input received from the second user. In some examples, the method may include accepting input from the first user identifying an avoidance area and outputting data describing the avoidance area to the second user. In some examples, generating the model may include performing segmentation based on input received from the second user.

Figure 10 is a block diagram depicting an example system 1000 for managing sensor array placement. In some examples, the components of system 1000 may be implemented as a single device and/or the like. In some examples, the components of system 1000 may be implemented as individual devices/components, and/or in collective communications. The system 1000 and/or components of the system 1000 may be implemented as hardware, software, or a combination of both hardware and software. In one feature, some or all of the steps of any method described herein may be performed on and/or via components of the system 1000 . The system 1000 may be used to determine the location (location) for sensor array placement on the body of a person (eg, a patient, a subject, etc.). The location (positioning) for sensor array placement may be indicated by one or more sensor array layout diagrams. Users (eg, physicians, nurses, assistants, staff, physicists, dosimetrists, etc.) may use the system 1000 to generate and/or evaluate a plurality of sensor array layouts. The system 1000 enables users, who may be relatively high-cost and/or highly skilled personnel (e.g., physicians, etc.), to provide guidance and/or instructions for determining and/or generating sensor array layouts to lower-level users. Cost of personnel (e.g., dosimetrists, physicists, etc.). For example, image data (eg, one or more images related to CT, MRI, ultrasound, SPECT, X-ray CT, PET, etc.) can be segmented via a user device, and the segmented image data can be transferred to another for use The device is used for analysis, used to generate three-dimensional (3D) models, and/or used to generate a plurality of sensor array layouts. The determined and/or generated sensor array layout may be reviewed and/or selected to generate a report that may be used for effective tumor treatment electric field treatment and/or therapy.

The system 1000 may include a patient support module 1001. The patient support module 1001 may include a processor 1008. The processor 1008 may be a hardware device for executing software, particularly stored in the memory 1010 . The processor 1008 may be any custom or commercially available processor, a central processing unit (CPU), an auxiliary processor among several processors associated with the patient support module 1001, a semiconductor A microprocessor based on a microprocessor (which takes the form of a microchip or chipset), or generally any device for executing software instructions. When the patient support module 1001 is in operation, the processor 1008 may be configured to execute software stored within the memory 1010 , communicate data to and from the memory 1010 , and generally act as described. software to control the operation of the patient support module 1001.

The I/O interface 1012 may be used to receive user input from one or more devices or components (eg, user devices 1020 and 1030) and/or to provide system output to one or more devices or components. User input may be provided, for example, via a keyboard, mouse, data/information communication interface, and/or the like. The I/O interface 1012 may include, for example, a serial port, a parallel port, a small computer system interface (SCSI), an IR interface, an RF interface, and/or a universal serial bus (USB) interface.

A network interface 1014 may be used to send and receive data/information from the patient support module 1001. The network interface 1014 may include, for example, a 10BaseT Ethernet adapter, a 100BaseT Ethernet adapter, a LAN PHY Ethernet adapter, a beacon ring adapter, and a wireless network adapter. (e.g., WiFi), or any other suitable network interface device. The network interface 1014 may include address, control, and/or data connections to enable appropriate communications.

The memory 1010 (memory system) may include volatile memory elements (eg, random access memory (RAM, such as DRAM, SRAM, SDRAM, etc.)) and non-volatile memory elements. Any one or combination of memory components (eg, ROM, hard drive, magnetic tape, CDROM, DVDROM, etc.). Furthermore, the memory 1010 may incorporate electronic, magnetic, optical, and/or other types of storage media. In some examples, the memory 1010 may have a distributed architecture in which various components are located remotely from each other but are accessible by the processor 1008 .

The memory 1010 may include one or more software programs, each software program including an ordered list of executable instructions for implementing logical functions. For example, the memory 1010 may include an EFG configuration application 606 as described in Figure 6, a patient modeling application 608, imaging data 610, and an appropriate operating system (O/S) 1018. The operating system 1018 can substantially control the execution of other computer programs, and provide scheduling, input-output control, file and data management, memory management, and communication control and related services.

For purposes of illustration, applications and other executable program components (such as the operating system 1018) are depicted here as discrete blocks, although it is recognized that such programs and components may exist at various times. in different storage components of the patient support system 602 . An implementation of the EFG configuration application 606, the patient modeling application 608, the imaging data 610, and/or the control software 110 may be stored on some form of computer-readable media. , or sent across media. Any of the disclosed methods may be performed by computer-readable instructions embodied on computer-readable media. Computer-readable media can be any available media that can be accessed by a computer. By way of example, and not by way of limitation, computer-readable media may include "computer storage media" and "communication media." "Computer storage media" may include volatile and non-volatile, removable and non-removable media implemented in any method or technology for use with, for example, computer-readable instructions, data structures, programs Storage of information about modules or other data. Examples of computer storage media may include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, disk storage, or other magnetic storage devices, or any other device that can be used to store the required information and can be stored electronically Brain-accessible media.

The system 1000 may include the user devices 1020 and 1030. The user devices 1020 and 1030 may be an electronic device, such as a computer, smartphone, laptop, tablet, and/or the like, which can communicate with a patient support module 1001 . Although there are only user devices 1020 and 1030, the system 1000 may include a plurality of such devices.

The user devices 1020 and 1030 may include an interface module 1022. The interface module 1022 may provide an interface for users to interact with the user devices 1020 and 1030 and/or the patient support module 1001 . The interface module 1022 may include one or more input devices/interfaces, such as a keyboard, a pointing device (eg, a computer mouse, a remote control), a microphone, a joystick, a scanner, tactile sensing and/or tactile input. devices, and/or the like.

The interface module 1022 may include one or more interfaces for presenting and/or receiving information to and from users (eg, physicians, nurses, assistants, staff, physicists, dosimetrists, etc.), such as User feedback. The interface module 1022 may include any software, hardware, and/or interfaces that are provided to the user and the user devices 1020 and 1030 , the patient support module 1001 , and/or the system. 1000 and/or any other components associated with the system 1000. The interface module 1022 may include one or more displays (eg, monitor, head-up display, head-mounted display, liquid crystal display, organic light-emitting diode display, active matrix organic light-emitting diode display, stereoscopic display, etc. etc.) for displaying/presenting information to the user. The interface module 1022 may include one or more audio devices (eg, stereo, speaker, microphone, etc.) for capturing/obtaining audio information and transmitting audio information, such as audio information captured/obtained from a user. , and/or be transmitted to the user. The interface module 1022 may include a graphical user interface (GUI), a web browser (eg, Internet Explorer®, Mozilla Firefox®, Google Chrome®, Safari®, or the like), an application/API . The interface module 1022 may request and/or query various information from a local source and/or a remote source (eg, the patient support module 1001 ). kind of files.

The interface module 1022 can send/transmit data/information to a local and/or remote device/component of the system 1000, such as the patient support module 1001 and/or another user device (e.g. , the user device 1020, the user device 1030, etc.). The user devices 1020 and 1030 may include a communication module 1023. The communication module 1023 can enable the user devices 1020 and 1030 to communicate with components of the system 1000 (such as the patient support module 1001 and/or another user via wired and/or wireless communication technologies). device) communication. For example, the communication module 1023 may utilize any suitable wired communication technology, such as Ethernet, coaxial cable, optical fiber, and/or the like. The communication module 1023 may utilize any suitable long-range communication technology, such as Wi-Fi (IEEE 802.11), BLUETOOTH®, cellular, satellite, infrared, and/or the like. The communication module 1023 may utilize any suitable short-range communication technology, such as BLUETOOTH®, near field communication, infrared, and the like.

As previously described, the system 1000 may be used to determine the location (positioning) of a sensor array for placement on the body of a person (eg, a patient, a subject, etc.). The location (positioning) for the sensor array arrangement may be indicated by one or more sensor array layout diagrams. A user (eg, physician, nurse, assistant, clerk, physicist, dosimeter, etc.) may use the system 1000 to generate and/or evaluate a plurality of sensor array layouts. The system 1000 enables users, who may be relatively high-cost and/or highly skilled personnel (e.g., physicians, etc.), to provide guidance and/or instructions for determining and/or generating sensor array layouts to lower-level users. Cost of personnel (e.g., dosimetrists, physicists, etc.). For example, the higher cost and/or highly skilled personnel may use the user device 1020 to provide guidance and/or instructions for determining and/or generating sensor array layouts to the lower cost personnel ( For example, a dosimetrist, a physicist, etc.), who may be the user of the user device 1030.

Figures 11A-11D illustrate an example interface for managing sensor array placement (e.g. For example, the screen of the interface module 1022, etc.). For example, one or more images of a portion of a subject/patient's body (eg, head, torso, anatomical volume, etc.) from the image data 610 may be segmented and used to generate a three-dimensional (3D )Model. Figure 11A shows an example screen 1101 of a user interface 1100. The screen 1101 may include confirmation subject/patient information 1102 . The identification information 1102 may identify a subject/patient associated with one or more images used to generate a 3D model. Progress through the user interface 1100 may be enabled and/or indicated by interactive elements 1103 (eg, labels, etc.). As indicated by the interactive element 1103, the screen 1101 may be used for segmentation of image data.

The screen 1101 is a screen that enables a user (e.g., the user of the user devices 1020 and 1030, etc.) to enter and examine a portion of a subject/patient's body (e.g., head, torso, anatomical volume, etc. etc.) and determine whether the image should be used to generate a 3D model. The image may be input, for example, from the patient support module 1001 by interacting with an interactive element 1104 (eg, a button, etc.). Interacting with an interactive element 1104 may cause a menu to be opened that enables the user to search for related images and/or upload related images. After an image has been input, such as from the image data 610, a representation of the image may be displayed in a panel 1105. Figure 11B shows an example screen 1101 of the user interface 1100 when an image has been input and represented by the image 1106 in the panel 1105. The user can view and examine the input images 1106, such as by using an interactive element (eg, mouse, trackpad, etc.) to drag one or more of the images 1106 to the One or more windows 1107 of screen 1101. The user can identify the images (eg, one or more images, image groups, etc.) that are best suited for the treatment plan of the tumor treatment electric field. As shown in FIG. 11B , one or more of the images 1106 are represented in the window 1107 .

After viewing/examining the image 1106, the user can select an image or group of images to be segmented and used to generate a 3D model. In some instances, the user device 1020 The user can select an image or image group, and the user device 1020 can transmit the selected image or image group (e.g., information related to the selected image or image group, etc.) to the user device 1030 for segmentation and 3D model generation. In some examples, the user of the user device 1030 can select an image or set of images, and the user device 1030 can transmit the selected image or set of images (e.g., and the selected image or set of images related information, etc.) to the user device 1020 for segmentation and 3D model generation. When an image or group of images is selected, an image may be marked with an element 1108, such as an "anchor" image, which indicates that the image is to be used to generate the 3D model for the calculation and/or or a primary ("anchor") image of the sensor array layout. Other images may be labeled "auxiliary images" to indicate that the user has optionally selected the image to assist in generating the 3D model and/or sensor array layout. The auxiliary image can be registered to the primary image to improve the accuracy of the 3D model. In some examples, the quality of a 3D model and/or sensor array layout may be proportional to the number of images used to generate the 3D model and/or sensor array layout.

The user can select images to be displayed in the one or more windows 1107 . After the image has been selected, the image may be segmented to identify/determine/select features and/or regions of interest within the image, which may be, for example, representative of tumors and/or abnormal tissue structures. The user interface 1100 may utilize segmentation tools (eg, semi-automatic segmentation tools, manual segmentation tools, etc.), and/or enable the user to mark features, structures, and/or features within the image. Region of interest (ROI) algorithm to configure. For example, the segmentation tool may enable a user to mark regions of an image as enhancing tumor, necrotic core, resection cavity, craniotomy, and/or the like. Area 1109 of screen 1101 shows examples of user-definable structures in the image, such as tissue type, ROI, and avoidance structures/regions. An avoidance structure/area may be any area on the surface of a subject/patient's body where the sensor array should not be deployed, such as areas of scar tissue, medical device implants, and/or the like.

As mentioned previously, the user can specify the tissue type to be used to generate the 3D model and/or Or an image of a sensor array layout. When the user assigns a tissue type to a particular voxel of an image, a corresponding voxel in a 3D model is assigned the same tissue type dielectric and/or electrical properties associated with the tissue type. . Each ROI determined and/or selected by the user can be assigned a unique label. The user interface 1100 enables any determined and/or selected ROI to be optionally marked on the image used to generate a 3D model and/or sensor array layout. In some examples, any determined and/or selected ROI can be utilized by an electric field distribution simulation and/or optimization algorithm to generate a sensor array layout. In some examples, the ROI may be input to the system 1000 from an external source (eg, a third party's software used to plan radiation therapy, etc.). After the user completes segmentation and editing of the image, an interactive element 1110 can be used to interact and/or select to generate a 3D model.

FIG. 11C is an example screen 1111 showing the user interface 1100. The screen 1111 may be a progressed screen of the screen 1101 . As shown in the figure, the interactive element 1103 is set as a "model" to indicate the progress of the user interface 1100. The screen 1111 may display any abnormal tissue noted on the screen 1101, as well as any normal body tissue within the image (eg, gray matter, white matter, skull, scalp, and CSF). The user interface 1100 may be configured to automatically add and/or include any normal body tissue when generating a 3D model.

A resulting 3D model can model any electrical feature at every point in space within a subject/patient's body part (eg, head, torso, anatomical volume, etc.). For example, the system 1000 can map electrical characteristics to a 3D model. Mapping electrical features to a 3D model may be based on diffusion tensor imaging MRI data (DTI), hydroelectric properties computed tomography (wEPT), machine learning, and/or any other method used to correlate electrical features based on image data to organizational types of methods/techniques. Once a 3D model is generated, the user interface 1100 enables the user to position the simulated sensor array at various positions (locations) on the 3D model, simulate the application of AC voltage to the simulated sensor array, Perform a simulation that determines the body shape of a subject/patient represented by the 3D model A resulting electric field distribution and/or power density at each point within a body part (eg, head, torso, anatomical volume, etc.). The 3D model can be displayed to the user. If the user is not satisfied with the displayed model, for example, an interactive element 1112 "view split" can be used to return to a previous screen, such as a split input screen of the user interface 1100 . If the user is satisfied with the displayed model, for example an interactive element 1113 "Generate Plan" can be used to advance to the next screen of the user interface 1100.

FIG. 11D shows an example screen 1114 of the user interface 1100. The user may, for example, interact with the interactive element 1103 "Plan" to progress to the screen 1114. For example, the screen 1114 may be used to analyze, evaluate, and/or select a tumor treatment electric field treatment plan. For example, after a 3D model is generated and simulated electric field distributions are determined based on the 3D model, a plurality of sensor array layouts may be generated. In some examples, the system 1000 may determine the plurality of sensor array layouts from, for example, standard sensor array layouts in a library, records, data volumes, and/or the like. In some examples, the system 1000 may, for example, determine the plurality of sensor array layouts, which enables a user to use the user interface 1100 to change the position of one or more arrays to converge on a sensor array layout. , which provides the desired and/or optimal (e.g., best suited to meet a criterion, etc.) results. Based on changing the position of one or more arrays as previously described, the system 1000 may determine one or more of a plurality of sensor array layouts (e.g., grouped sensor array layouts, etc. ), which optimizes the electric field distribution within a target ROI while also satisfying the constraints imposed by the avoidance structure and related to the sensor array placement. For example, one or more sets of sensor array layouts may be determined (e.g., automatically, manually selected, etc.) from the plurality of sensor array layouts, each representing at least two sensor arrays with non-overlapping locations. Layout diagram and/or meet a standard. As previously stated, a criterion may include the magnitude of a simulated electric field distribution within a ROI associated with a 3D model, the power density associated with a simulated electric field distribution within the ROI, and/or Similar. In some instances, a criterion may be based on

and an estimation of skin toxicity associated with a portion of a subject/patient's body where the sensor array will be deployed and/or an avoidance area.

The optimal sensor array layout for a desired tumor treatment electric field treatment plan can be determined to generate composite data (eg, a report, a plan, a summary, etc.). For example, the composite data may include information related to the sensor array layout and related simulated electric field distribution. The composite data may be displayed via the user interface 1100 , for example. Returning to FIG. 11D , the screen 1114 may display the electric field distribution associated with each of the plurality of sensor array layouts (eg, represented as one or more color maps, etc.). For example, interactive element 1115 can be used to view the electric field distribution for each of the sensor array layouts (TAL) by interacting with a corresponding TAL element (eg, TAL 1 through TAL 5). As shown, TAL 1 of the interactive element 1115 is selected, and a color map of the electric field distribution and the associated sensor array layout are displayed in areas 1116 and 1117 respectively. A table summarizing the electric field dose delivered to the target ROI for each of the plurality of sensor array layouts may be displayed to enable the user to select a treatment plan for the tumor treatment electric field. In some examples, an overall score may be determined and displayed for each sensor array layout and/or a group of sensor array layouts of the plurality of sensor array layouts. A score may represent the extent to which a criterion or criteria are met by an associated sensor array layout. Scores may be color coded (eg, green for the highest scores, yellow for intermediate scores, and red for low scores). The plurality of sensor array layouts and/or groups of sensor array layouts in the plurality of sensor array layouts may be ranked according to any method, algorithm, and/or criterion, and the ranking may be displayed to the user.

The user interface 1100 enables the plurality of sensor array layouts and/or groups of sensor array layouts to be evaluated, for example, by a user. An evaluation of the sensor array topography is based on and/or the determination is used to generate the sensor array topography (e.g., the tumor treatment electric field Treatment planning, etc.) of a 3D model. The user can evaluate and select one or more sensor array layouts and/or groups of sensor array layouts among the plurality of sensor array layouts.

Figure 12 is a flowchart illustrating a method 1200 for managing sensor array placement. One or more of the device 100 , the patient support system 602 , the patient modeling application 608 , the system 1000 , and/or any other devices/components described herein may be configured to perform A method 1200 includes generating 1210 a three-dimensional (3D) model of a portion of the subject's body. The 3D model may be generated from imaging from any modality, such as one or more images associated with CT, MRI, ultrasound, SPECT, X-ray CT, PET, a combination thereof, and/or the like. image data. In some examples, one or more user devices may display multiple images of the portion of the subject's body. One or more images selected from the plurality of images may be received based on a region of interest (ROI), and a 3D model may be generated based on the one or more images. For example, a ROI may be based on features and/or structures within the one or more images, such as an enhancing tumor, a necrotic core, a resection chamber, a craniotomy, and/or the like. In some examples, receiving information related to the ROI may be received from a first user device of the one or more user devices, and the selected one or more images may be received from a first user device of the one or more user devices. received by a second user device of the one or more user devices.

At 1220, a plurality of sensor array layouts are determined based on the 3D model and a plurality of simulated electric field distributions. Determining the plurality of sensor array layouts may include determining a plurality of pairs of positions for sensor array placement based on the 3D model. In some examples, the plurality of pair positions for sensor array placement may be determined from a standard sensor array layout from a library, record, data volume, and/or the like. In some examples, the plurality of pairs of locations for sensor array placement may be determined and/or selected to avoid one or more areas within the 3D model (eg, avoidance areas, etc.) and/or Or something like that. For each of the plurality of pairs of positions, a simulated electric field distribution among the plurality of simulated electric field distributions may be determined. For the complex number pair position Determining the simulated electric field distribution for each pair of positions may include simulating the first electric field generated by the first sensor array at a first position of the pair of positions, and simulating the first electric field generated by the second sensor array at a second position of the pair of positions. The second electric field generated by the sensor array. The second position may be opposite the first position. In some examples, a third electric field generated by the first sensor array can be simulated at a third location, and a fourth electric field generated by the second sensor array can be simulated at a third location opposite the third location. The fourth position is simulated, and according to the third electric field and the fourth electric field, the simulated electric field distribution can be determined. The simulated electric field distribution may be determined based on the first electric field and the second electric field and/or the third electric field and the fourth electric field. The plurality of sensor array layouts may be determined based on the plurality of simulated electric field distributions.

At 1230, one or more sets of sensor array layouts are determined from the plurality of sensor array layouts, wherein each set of sensor array layouts represents at least two sensor array layouts having a plurality of pairs for sensor array arrangements. Non-overlapping locations of locations where the at least two sensor array layouts satisfy a criterion. The criteria may include the magnitude of one of the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model, and the magnitude of the simulated electric field distribution within the ROI. a power density associated with one of the plurality of simulated electric field distributions, and an estimate of skin toxicity associated with the portion of the subject's body.

At 1240, the one or more groups of sensor array layouts are displayed. The one or more sets of sensor array layouts may be displayed through an interface of the one or more user devices. The selected set of sensor array layouts from the one or more sets of sensor array layouts may, for example, be received via an interface of the one or more user devices. Composite data (eg, a report, a plan, a summary, etc.) can be generated based on the selected set of sensor array layouts. The composite data may include information related to the selected set of sensor array layouts, and the simulated electric field distributions of the plurality of simulated electric field distributions related to the selected set of sensor array layouts. The composite data may be transmitted to the one or more user devices.

Figure 13 is a flowchart illustrating a method 1300 for managing sensor array placement. One or more of the device 100 , the patient support system 602 , the patient modeling application 608 , the system 1000 , and/or any other devices/components described herein may be configured to perform A method 1300 includes generating 1310 a three-dimensional (3D) model of a portion of the subject's body. The 3D model may be generated from imaging from any modality, such as one or more images associated with CT, MRI, ultrasound, SPECT, X-ray CT, PET, a combination thereof, and/or the like. image data. In some examples, one or more user devices may display multiple images of the portion of the subject's body. One or more images selected from the plurality of images may be received based on a region of interest (ROI), and a 3D model may be generated based on the one or more images. For example, a ROI may be based on features and/or structures within the one or more images, such as an enhancing tumor, a necrotic core, a resection chamber, a craniotomy, and/or the like. In some examples, receiving information related to the ROI may be received from a first user device of the one or more user devices, and the selected one or more images may be received from a first user device of the one or more user devices. received by a second user device of the one or more user devices.

At 1320, a plurality of sensor array layouts are determined based on the 3D model and a plurality of simulated electric field distributions. Determining the plurality of sensor array layouts may include determining a plurality of pairs of positions for sensor array placement based on the 3D model. In some examples, the plurality of pair positions for sensor array placement may be determined from a standard sensor array layout from a library, record, data volume, and/or the like. In some examples, the plurality of pairs of locations for sensor array placement may be determined and/or selected to avoid one or more areas within the 3D model (eg, avoidance areas, etc.) and/or Or something like that. For each of the plurality of pairs of positions, a simulated electric field distribution among the plurality of simulated electric field distributions may be determined. Determining the simulated electric field distribution for each of the plurality of pairs of positions may include simulating a first electric field generated by a first sensor array at a first position of the pair of positions, and simulating a first electric field generated by a first sensor array at a third position of the pair of positions. Two position simulation by second The second electric field generated by the sensor array. The second position may be opposite the first position. In some examples, a third electric field generated by the first sensor array can be simulated at a third location, and a fourth electric field generated by the second sensor array can be simulated at a third location opposite the third location. The fourth position is simulated, and according to the third electric field and the fourth electric field, the simulated electric field distribution can be determined. The simulated electric field distribution may be determined based on the first electric field and the second electric field and/or the third electric field and the fourth electric field. The plurality of sensor array layouts may be determined based on the plurality of simulated electric field distributions.

At 1330, a first sensor array layout selected from the plurality of sensor array layouts is received, wherein the first sensor array layout satisfies a criterion. The selection of the first sensor array layout may be received from one or more user devices. The criteria may include the magnitude of one of the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model, and the magnitude of the simulated electric field distribution within the ROI. a power density associated with one of the plurality of simulated electric field distributions, and an estimate of skin toxicity associated with the portion of the subject's body.

At 1340, one or more related sensor array layouts are determined from the plurality of sensor array layouts. Each associated sensor array layout may contain locations for a sensor array arrangement that do not overlap locations for a sensor array arrangement of the first sensor array layout. In some instances, each associated sensor array layout may meet the criteria.

At 1350, a selected second sensor array layout is received from the one or more associated sensor array layouts.

At 1360, the first sensor array layout diagram and the second sensor array layout diagram are displayed. In some examples, composite information (eg, a report, a plan, a summary, etc.) may be generated based on the first sensor array layout and the second sensor array layout. The composite data may include, for example, the first sensor array layout diagram and the third sensor array layout diagram. Information related to the two sensor array layouts, and the simulated electric field distribution among the plurality of simulated electric field distributions related to the first sensor array layout and the second sensor array layout.

Figure 14 is a flow diagram illustrating a method 1400 for managing sensor array placement. One or more of the device 100 , the patient support system 602 , the patient modeling application 608 , the system 1000 , and/or any other devices/components described herein may be configured to perform A method 1400 includes generating 1410 a three-dimensional (3D) model of a portion of the subject's body. The 3D model may be generated from imaging from any modality, such as one or more images associated with CT, MRI, ultrasound, SPECT, X-ray CT, PET, a combination thereof, and/or the like. image data. In some examples, one or more user devices may display multiple images of the portion of the subject's body. One or more images selected from the plurality of images may be received based on a region of interest (ROI), and a 3D model may be generated based on the one or more images. For example, a ROI may be based on features and/or structures within the one or more images, such as an enhancing tumor, a necrotic core, a resection chamber, a craniotomy, and/or the like. In some examples, receiving information related to the ROI may be received from a first user device of the one or more user devices, and the selected one or more images may be received from a first user device of the one or more user devices. received by a second user device of the one or more user devices.

At 1420, a plurality of sensor array layouts are determined based on the 3D model and a plurality of simulated electric field distributions. Determining the plurality of sensor array layouts may include determining a plurality of pairs of positions for sensor array placement based on the 3D model. In some examples, the plurality of pair positions for sensor array placement may be determined from a standard sensor array layout from a library, record, data volume, and/or the like. In some examples, the plurality of pairs of locations for sensor array placement may be determined and/or selected to avoid one or more areas within the 3D model (eg, avoidance areas, etc.) and/or Or something like that. For each of the complex pairs of positions, the complex A simulated electric field distribution among several simulated electric field distributions may be determined. Determining the simulated electric field distribution for each of the plurality of pairs of positions may include simulating a first electric field generated by a first sensor array at a first position of the pair of positions, and simulating a first electric field generated by a first sensor array at a third position of the pair of positions. The second position simulates the second electric field generated by the second sensor array. The second position may be opposite the first position. In some examples, a third electric field generated by the first sensor array can be simulated at a third location, and a fourth electric field generated by the second sensor array can be simulated at a third location opposite the third location. The fourth position is simulated, and according to the third electric field and the fourth electric field, the simulated electric field distribution can be determined. The simulated electric field distribution may be determined based on the first electric field and the second electric field and/or the third electric field and the fourth electric field. The plurality of sensor array layouts may be determined based on the plurality of simulated electric field distributions.

At 1430, a first sensor array layout and a second sensor array layout selected from the plurality of sensor array layouts are received. The selected first sensor array layout and the second sensor array layout may be received via an interface of one or more user devices.

At 1440, an overlapping condition is determined based on the first sensor array layout and the second sensor array layout. Each sensor array layout of the plurality of sensor array layouts may include one or more pairs of positions for a sensor array arrangement. The overlapping condition may indicate that the first sensor array layout includes one or more of the plurality of pairs of positions that overlap one of the plurality of pairs of positions associated with the second sensor array layout. or multiple pairs of positions. For example, the first sensor array layout may include locations for sensor arrays that are the same locations indicated on a 3D model (e.g., overlapping, etc.), or the locations are on a 3D model. Locations indicated above satisfy a distance threshold and/or are within a tolerance range relative to each other (e.g., substantially overlap, etc.).

At 1450, display of the overlapping condition is performed. one or more of the user devices One may cause the overlapping condition to be displayed, for example, via an interface, display, and/or the like. In some cases, the overlapping condition may be indicated by an audible sound and/or a notification.

What is described below are some of the more particularly described embodiments of the present invention in view of the apparatus, systems, and methods, and variations thereof. However, these specifically set forth embodiments should not be construed as having any limiting effect on any claim that encompasses different or more general teachings described herein, or that the "particular" embodiments are somehow incompatible with the teachings described herein. Restricted in some way other than the meaning inherent in the language in which its literal meaning is used.

Embodiment 1: A method, which includes: generating a three-dimensional (3D) model of a part of the subject's body, determining a plurality of sensor array layouts according to the 3D model and a plurality of simulated electric field distributions, from the A plurality of sensor array layouts are used to determine one or more sets of sensor array layouts, wherein each set of sensor array layouts represents at least two sensor array layouts having non-overlapping positions for a plurality of pairs of positions of the sensor array arrangement. , wherein the at least two sensor array layouts meet a standard, and the one or more groups of sensor array layouts are displayed.

Embodiment 2: As in any one of the preceding embodiments, wherein the criterion is included in the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model. a magnitude of a simulated electric field distribution, a power density associated with one of the plurality of simulated electric field distributions within the ROI, and skin associated with the portion of the subject's body Toxicity estimates.

Embodiment 3: An embodiment as in any of the preceding embodiments, further comprising receiving a set of sensor array layouts selected from the one or more sets of sensor array layouts.

Embodiment 4: The embodiment is as in Embodiment 3, further comprising generating composite data according to the sensor array layout of the selected group.

Embodiment 5: As in Embodiment 4, the composite data includes information related to the sensor array layout of the selected group, and information related to the sensor array layout of the selected group. The simulated electric field distributions of the plurality of simulated electric field distributions.

Embodiment 6: The embodiment is as in Embodiment 4, further comprising transmitting the composite data to the user device.

Embodiment 7: As in any one of the preceding embodiments, wherein generating the 3D model includes causing one or more user devices to display a plurality of images of the portion of the body of the subject, according to a A region of interest (ROI) is used to receive one or more images selected from the plurality of images, and to generate the 3D model based on the one or more images.

Embodiment 8: The embodiment as in Embodiment 7, further comprising receiving information related to the ROI from a first user device of the one or more user devices, and wherein receiving the selected one The one or more images includes receiving the selected one or more images from a second user device of the one or more user devices.

Embodiment 9: As in any one of the preceding embodiments, wherein determining the plurality of sensor array layouts includes: determining the plurality of pair positions for sensor array arrangement according to the 3D model, for the Each pair of positions of the plurality of positions determines a simulated electric field distribution among the plurality of simulated electric field distributions, and the plurality of sensor array layouts are determined according to the plurality of simulated electric field distributions.

Embodiment 10: An embodiment as in Embodiment 9, wherein determining the simulated electric field distribution for each pair of the plurality of pairs of positions includes: simulating at a first position of the pair of positions by a first A first electric field generated by the sensor array, a second electric field generated by a second sensor array at a second position of the pair of positions, wherein the second position is opposite the first position, and according to the The first electric field and the second electric field are used to determine the simulated electric field distribution.

Embodiment 11: A method, which includes: generating a three-dimensional (3D) model of a part of the body of the subject, determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions, receiving the sensor array layout from the The first sensor array selected in the plurality of sensor array layouts a column layout, wherein the first sensor array layout satisfies a criterion, and one or more related sensor array layouts are determined from the plurality of sensor array layouts, wherein each related sensor array layout includes a at the locations of sensor array arrangements that do not overlap the locations of sensor array arrangements for said first sensor array layout, wherein each associated sensor array layout satisfies said criteria, from said one or more associated sensor array layouts The sensor array layout diagram receives the selected second sensor array layout diagram, and displays the first sensor array layout diagram and the second sensor array layout diagram.

Embodiment 12: The embodiment of Embodiment 11, wherein the criterion is a simulation of the plurality of simulated electric field distributions included within a region of interest (ROI) associated with the 3D model. the magnitude of the electric field distribution, the power density associated with one of the plurality of simulated electric field distributions within the ROI, and the skin toxicity associated with the portion of the subject's body Estimate.

Embodiment 13: Any one of embodiments 11-12, further comprising generating composite data according to the first sensor array layout and the second sensor array layout.

Embodiment 14: As in Embodiment 13, the composite data includes information related to the first sensor array layout and the second sensor array layout, and the plurality of simulated A simulated electric field distribution in the electric field distribution related to the first sensor array layout and the second sensor array layout.

Embodiment 15: The embodiment as in any one of embodiments 11-14, wherein generating the 3D model includes causing one or more user devices to display a plurality of images of the portion of the body of the subject, according to A region of interest (ROI) is used to receive one or more images selected from the plurality of images, and to generate the 3D model based on the one or more images.

Embodiment 16: The embodiment as in Embodiment 15, further comprising selecting from the one or more A first user device of the user devices receives information related to the ROI, and wherein receiving the selected one or more images includes a second user device from the one or more user devices. The selected one or more images are received.

Embodiment 17: As any one of embodiments 11-16, wherein determining the plurality of sensor array layouts includes: determining a plurality of pairs of positions for sensor array arrangement according to the 3D model, for the Each pair of positions of the plurality of positions determines a simulated electric field distribution among the plurality of simulated electric field distributions, and the plurality of sensor array layouts are determined according to the plurality of simulated electric field distributions.

Embodiment 18: The embodiment as in Embodiment 17, wherein determining the simulated electric field distribution for each pair of the plurality of pairs of positions includes: simulating at a first position of the pair of positions by a first sensor a first electric field generated by the array, a second electric field generated by a second sensor array at a second position of the pair of positions, wherein the second position is opposite the first position, and according to the The first electric field and the second electric field determine the simulated electric field distribution.

Embodiment 19: A method, which includes: generating a three-dimensional (3D) model of a part of the body of the subject, determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions, receiving the The first sensor array layout and the second sensor array layout selected from the plurality of sensor array layouts, determining the overlap status according to the first sensor array layout and the second sensor array layout, and performing Display of the overlap status.

Embodiment 20: The embodiment of Embodiment 19, wherein each sensor array layout of the plurality of sensor array layouts is a location that includes one or more pairs of a plurality of pairs of locations for a sensor array arrangement, wherein The overlapping condition indicates that the first sensor array layout includes one or more of the plurality of pairs of positions, which overlaps one of the plurality of pairs of positions associated with the second sensor array layout. or multiple pairs of positions.

Embodiment 21: A method comprising: providing a plurality of images of an anatomical volume to at least one user; receiving from the at least one user selected images of the images of the anatomical volume that should be used to generate the sensor array layout; generating electrical images of the anatomical volume based on the selected images. a model of sexual characteristics; determine a plurality of sensor array layouts; evaluate which of the determined sensor array layouts satisfy at least one criterion based on the generated model; present a plurality of sensor array layouts that satisfy the at least one criterion to all the at least one user; accepting from the at least one user a selected one of the sensor array layouts presented to the at least one user; and generating a report describing the selected sensor array layout.

Embodiment 22: The embodiment of embodiment 21, wherein the model of the electrical characteristics of the anatomical volume is also based on at least one additional image.

Embodiment 23: As in any one of embodiments 21-22, wherein generating the model includes performing segmentation based on input received from the at least one user.

Embodiment 24: As any one of embodiments 21-23, wherein the at least one user includes a first user and a second user, wherein the method further includes (a) confirming that the concerned user The first user of a region accepts an input, and (b) outputs data describing the region of interest to the second user.

Embodiment 25: The embodiment of embodiment 24, wherein generating the model includes performing segmentation based on input received from the second user.

Embodiment 26: As in any one of embodiments 21-25, wherein the at least one user includes a first user and a second user, wherein the method further includes: from confirming a generally segmented The first user accepts an input; and outputs data describing the general segmentation to the second user.

Embodiment 27: The embodiment as in embodiment 26, wherein generating the model includes performing segmentation based on input received from the second user.

Embodiment 28: any one of embodiments 21-27, wherein the at least one The user includes a first user and a second user, wherein the method further includes (a) accepting at least one note from the first user, and (b) outputting the at least one note to the second user. By.

Embodiment 29: The embodiment as in embodiment 28, wherein generating the model includes performing segmentation based on input received from the second user.

Embodiment 30: As in any one of embodiments 21-29, wherein the at least one user includes a first user and a second user, wherein the method further includes (a) from confirming an avoidance area The first user accepts an input, and (b) outputs data describing the avoidance area to the second user.

Embodiment 31: The embodiment of embodiment 30, wherein generating the model includes performing segmentation based on input received from the second user.

Unless otherwise expressly stated, any method set forth herein is in no way intended to be construed as requiring that its steps be performed in a particular order. Thus, in a situation where a method claim does not actually state an order in which its steps are to be followed, or it does not otherwise expressly state in the claim or description that the steps are limited to a specific order , there is no intention to infer a sequence in any respect. This applies to any possible unspecified basis for the explanation, including: logical matters related to the configuration of steps or operational procedures; ordinary meaning derived from grammatical organization or punctuation; the number of embodiments recited in the description or type.

Although the methods and systems have been described with respect to preferred embodiments and specific examples, the scope is not intended to be limited to the specific embodiments described because the embodiments described herein are intended in all respects. Illustrative, not restrictive.

Unless otherwise expressly stated, any method set forth herein is in no way intended to be construed as requiring that its steps be performed in a particular order. Thus, in a situation where a method claim does not actually state an order in which its steps are to be followed, or it does not otherwise expressly state in the claim or description that the steps are limited to a specific order , there is no intention to infer a sequence in any respect. This applies to any possible unspecified basis for the explanation, including: logical matters related to the configuration of steps or operational procedures; ordinary meaning derived from grammatical organization or punctuation; the number of embodiments recited in the description or type.

It will be apparent to those skilled in the art that various modifications and variations can be made without departing from the scope or spirit of the invention. Other embodiments will be apparent to those skilled in the art from consideration of the specification and practice disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit being indicated by the following claims.

600:System

602:Patient support system

606: Electric Field Generator (EFG) Configuration Application

608:Build Patient Model Application

610: Imaging data

Claims (60)

A method for managing sensor array layout, which includes: generating a three-dimensional (3D) model of a body part of a subject; determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions; from The plurality of sensor array layouts are used to determine one or more groups of sensor array layouts, wherein each group of sensor array layouts represents at least two sensor array layouts having non-linear pairs of positions for the sensor array arrangement. overlapping positions, wherein the at least two sensor array layouts satisfy a criterion; and displaying the one or more sets of sensor array layouts, wherein the criterion is included in a concern associated with the 3D model The size of one of the plurality of simulated electric field distributions within the region (ROI). The method of claim 1, wherein the criterion further includes a power density associated with a simulated electric field distribution of the plurality of simulated electric field distributions within the ROI, and a power density associated with all of the body of the subject. Estimates of skin toxicity associated with the above sections. The method of claim 1, further comprising receiving a set of sensor array layouts selected from the one or more sets of sensor array layouts. The method of claim 3 further includes generating composite data based on the selected sensor array layout. The method of claim 4, wherein the composite data includes information related to the selected set of sensor array layouts, and the plurality of simulated electric field distributions related to the selected set of sensor array layouts. simulated electric field distribution. The method of claim 4, further comprising transmitting the composite data to the user device. The method of claim 1, wherein generating the 3D model includes: causing one or more user devices to display a plurality of images of the portion of the subject's body; receiving data from the subject according to a region of interest (ROI) One or more images selected from the plurality of images; and generating the 3D model based on the one or more images. The method of claim 7, further comprising receiving information related to the ROI from a first user device of the one or more user devices, and wherein receiving the selected one or more images includes from A second user device of the one or more user devices receives the selected one or more images. The method of claim 1, wherein determining the plurality of sensor array layouts includes: determining the plurality of pairs of positions for sensor array arrangement according to the 3D model; for each pair of the plurality of pairs of positions, Determine a simulated electric field distribution among the plurality of simulated electric field distributions; and determine the plurality of sensor array layouts according to the plurality of simulated electric field distributions. The method of claim 9, wherein determining the simulated electric field distribution for each pair of the plurality of pairs of positions includes: simulating the first electric field generated by the first sensor array at a first position of the pair of positions; Simulating a second electric field generated by a second sensor array at a second position of the pair of positions, wherein the second position is opposite the first position; and determined based on the first electric field and the second electric field The simulated electric field distribution. An apparatus for managing a sensor array arrangement, comprising: one or more processors; and a memory that stores instructions executable by the processor. When the instructions are executed by the one or more processors, When executed, the device is caused to: generate a three-dimensional (3D) model of a body part of a subject; determine a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions; and determine a plurality of sensor array layouts from the plurality of sensors. The array layout determines one or more sets of sensor array layouts, wherein each set of sensor array layouts represents at least two sensor array layouts having non-overlapping positions in a plurality of pairs of positions for the sensor array arrangement, wherein the The at least two sensor array layouts satisfy a criterion; and performing display of the one or more sets of sensor array layouts, wherein the criterion is included within a region of interest (ROI) associated with the 3D model. The magnitude of one of the plurality of simulated electric field distributions. The apparatus of claim 11, wherein the criteria further include a power density associated with one of the plurality of simulated electric field distributions within the ROI, and a power density associated with all of the body of the subject. Estimates of skin toxicity associated with the above sections. The device of claim 11, wherein when the processor-executable instructions are executed by the one or more processors, they further cause the device to receive the selected sensor array layout from the one or more sets of sensor arrays. A set of sensor array layout diagram. The device of claim 13, wherein when the processor-executable instructions are executed by the one or more processors, they further cause the device to generate composite data according to the selected set of sensor array layouts. . The device of claim 14, wherein the composite data includes information related to the selected set of sensor array layouts, and the plurality of simulated electric field distributions related to the selected set of sensor array layouts. simulated electric field distribution. The apparatus of claim 14, wherein when instructions executable by said processor are When executed, one or more processors further cause the device to transmit the composite data to the user device. The device of claim 11, wherein when the processor-executable instructions are executed by the one or more processors, the device is caused to generate the 3D model, which further causes the device to: cause one or more display a plurality of images of the portion of the subject's body on a user device; receive one or more images selected from the plurality of images based on a region of interest (ROI); and based on the One or more images are used to generate the 3D model. The apparatus of claim 17, wherein the processor-executable instructions, when executed by the one or more processors, further cause the apparatus to access the first user device from the one or more user devices. A device receives information related to the ROI, and wherein receiving the selected one or more images includes receiving the selected one or more images from a second user device of the one or more user devices. image. The device of claim 11, wherein when instructions executable by the processor are executed by the one or more processors, the device is caused to determine the plurality of sensor array layouts, further causing the device to: according to the 3D model to determine the plurality of pairs of positions for a sensor array arrangement; determining one of the plurality of simulated electric field distributions for each pair of the plurality of pairs of positions; and according to the A plurality of simulated electric field distributions are used to determine the plurality of sensor array layouts. The apparatus of claim 19, wherein the processor-executable instructions, when executed by the one or more processors, cause the apparatus to determine the simulation for each pair of the plurality of pairs of positions. The electric field distribution further enables the device to: A first electric field generated by a first sensor array is simulated at a first position of the pair of positions; a second electric field generated by a second sensor array is simulated at a second position of the pair of positions, wherein the second position is the same as the first electric field generated by the second sensor array. The first position is relative; and the simulated electric field distribution is determined according to the first electric field and the second electric field. A non-transitory computer-readable medium configured to store information, wherein: a processor coupled to the non-transitory computer-readable medium is configured to: generate a body of an object a three-dimensional (3D) model of a part of a plurality of sensor array layouts; determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions; determining one or more groups of sensor array layouts from the plurality of sensor array layouts, wherein each set of sensor array layouts represents at least two sensor array layouts having non-overlapping positions in a plurality of pairs of positions for sensor array arrangements, wherein the at least two sensor array layouts satisfy a criterion; and Performing display of the one or more sets of sensor array layouts, wherein the criterion includes a simulation of the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model the size of the electric field distribution. The non-transitory computer-readable medium of claim 21, wherein said criteria further comprise a power density associated with one of said plurality of simulated electric field distributions within said ROI, and an estimate of skin toxicity associated with said part of the subject's body. The non-transitory computer-readable medium of claim 21, wherein the processor coupled to the non-transitory computer-readable medium is further configured to receive data from the one or more sets of sensors. A set of sensor array layouts selected in the array layout. The non-transitory computer-readable medium of claim 23, wherein said The processor of the non-transitory computer readable medium is further configured to generate composite data based on the selected set of sensor array layouts. The non-transitory computer-readable medium of claim 24, wherein the composite data includes information related to the selected set of sensor array layouts, and information related to the selected set of sensor array layouts. A simulated electric field distribution among the plurality of simulated electric field distributions. The non-transitory computer-readable medium of claim 24, wherein the processor coupled to the non-transitory computer-readable medium is further configured to transmit the composite data to a user device. The non-transitory computer-readable medium of claim 21, wherein the processor coupled to the non-transitory computer-readable medium is further configured to: enable one or more user devices display a plurality of images of the portion of the subject's body; receive one or more images selected from the plurality of images based on a region of interest (ROI); and based on the one or more images to generate the 3D model. The non-transitory computer-readable medium of claim 27, wherein the processor coupled to the non-transitory computer-readable medium is further configured to receive data from the one or more users. A first user device of the device receives information related to the ROI, and wherein receiving the selected one or more images includes receiving the selected image from a second user device of the one or more user devices. the one or more images. The non-transitory computer-readable medium of claim 21, wherein the processor coupled to the non-transitory computer-readable medium is configured to determine the plurality of sensor array layouts, It is further configured to: determine the plurality of pairs of positions for a sensor array arrangement based on the 3D model; and determine, for each of the plurality of pairs of positions, one of the plurality of simulated electric field distributions. a simulated electric field distribution; and determining the plurality of sensor array layouts based on the plurality of simulated electric field distributions. The non-transitory computer-readable medium of claim 29, wherein the processor coupled to the non-transitory computer-readable medium is configured to target each of the plurality of pairs of locations. The simulated electric field distribution is determined by a pair of positions, and is further configured to: simulate the first electric field generated by the first sensor array at a first position of the pair of positions; simulate the first electric field generated by the second sensor array at a second position of the pair of positions. a second electric field generated by the sensor array, wherein the second position is opposite to the first position; and the simulated electric field distribution is determined based on the first electric field and the second electric field. A method for managing sensor array layout, which includes: generating a three-dimensional (3D) model of a body part of a subject; determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions; receiving a first sensor array layout selected from the plurality of sensor array layouts, wherein the first sensor array layout satisfies a criterion; one or more relevant sensor array layouts are determined from the plurality of sensor array layouts a sensor array layout, wherein each associated sensor array layout includes locations for a sensor array arrangement that do not overlap locations for a sensor array arrangement of said first sensor array layout, wherein each associated sensor an array layout meeting the criteria; receiving a second sensor array layout selected from the one or more associated sensor array layouts; and performing the first sensor array layout and the second sensor array Display of a layout diagram, wherein the criterion includes a magnitude of one of the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model. The method of claim 31, wherein the criterion further includes a power density associated with a simulated electric field distribution of the plurality of simulated electric field distributions within the ROI, and a power density associated with all of the body of the subject. Estimates of skin toxicity associated with the above sections. The method of claim 31, further comprising generating composite data based on the first sensor array layout and the second sensor array layout. The method of claim 33, wherein the composite data includes information related to the first sensor array layout and the second sensor array layout, and the plurality of simulated electric field distributions related to the The simulated electric field distribution associated with the first sensor array layout and the second sensor array layout. The method of claim 31, wherein generating the 3D model includes: causing one or more user devices to display a plurality of images of the portion of the subject's body; receiving data from the subject based on a region of interest (ROI) One or more images selected from the plurality of images; and generating the 3D model based on the one or more images. The method of claim 35, further comprising receiving information related to the ROI from a first user device of the one or more user devices, and wherein receiving the selected one or more images includes from A second user device of the one or more user devices receives the selected one or more images. The method of claim 31, wherein determining the plurality of sensor array layouts includes: determining a plurality of pairs of positions for sensor array arrangement according to the 3D model; determining the plurality of pairs of positions for each of the plurality of pairs of positions. A simulated electric field distribution among a plurality of simulated electric field distributions; and determining the plurality of sensor array layouts according to the plurality of simulated electric field distributions. The method of claim 37, wherein determining the simulated electric field distribution for each of the plurality of pairs of positions includes: simulating a first electric field generated by a first sensor array at a first position of the pair of positions; Simulating a second electric field generated by a second sensor array at a second position of the pair of positions, wherein the second position is opposite the first position; and determined based on the first electric field and the second electric field The simulated electric field distribution. An apparatus for managing a sensor array arrangement, comprising: one or more processors; and a memory storing processor-executable instructions that, when executed by the one or more processors, cause the The apparatus: generates a three-dimensional (3D) model of a body part of a subject; determines a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions; receives the plurality of sensor array layouts from the plurality of sensor array layouts a selected first sensor array layout, wherein the first sensor array layout satisfies a criterion; determining one or more related sensor array layouts from the plurality of sensor array layouts, wherein each related sensor an array layout including locations for sensor array arrangements that do not overlap locations for sensor array arrangements for said first sensor array layout, wherein each associated sensor array layout satisfies said criteria; receiving from all a second sensor array layout selected from the one or more related sensor array layouts; and displaying the first sensor array layout and the second sensor array layout, wherein the standard is included in The magnitude of one of the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model. The apparatus of claim 39, wherein said criteria further include a power density associated with a simulated electric field distribution of said plurality of simulated electric field distributions within said ROI, and a power density associated with all of said subject's body Estimates of skin toxicity associated with the above sections. The device of claim 39, wherein when the processor-executable instructions are executed by the one or more processors, they further cause the device to operate according to the first sensor array layout and the second sensor Array layout diagram to generate composite data. The device of claim 41, wherein the composite data includes information related to the first sensor array layout and the second sensor array layout, and the plurality of simulated electric field distributions related to the The simulated electric field distribution associated with the first sensor array layout and the second sensor array layout. The device of claim 39, wherein the processor-executable instructions, when executed by the one or more processors, cause the device to generate the 3D model, which further causes the device to: cause one or more display a plurality of images of the portion of the subject's body on a user device; receive one or more images selected from the plurality of images based on a region of interest (ROI); and based on the One or more images are used to generate the 3D model. The apparatus of claim 43, wherein the processor-executable instructions, when executed by the one or more processors, further cause the apparatus to access the first user device from the one or more user devices. A device receives information related to the ROI, and wherein receiving the selected one or more images includes receiving the selected one or more images from a second user device of the one or more user devices. image. The apparatus of claim 39, wherein the processor-executable instructions, when executed by the one or more processors, cause the apparatus to determine the plurality of sensor array layouts, wherein Further causing the device to: determine a plurality of pairs of positions for sensor array arrangement according to the 3D model; and determine a simulated electric field distribution among the plurality of simulated electric field distributions for each pair of the plurality of pairs of positions. ; and determining the plurality of sensor array layouts according to the plurality of simulated electric field distributions. The apparatus of claim 45, wherein the processor-executable instructions, when executed by the one or more processors, cause the apparatus to determine the simulation for each pair of the plurality of pairs of positions. The electric field distribution further enables the device to: simulate the first electric field generated by the first sensor array at the first position of the pair of positions; simulate the third electric field generated by the second sensor array at the second position of the pair of positions. Two electric fields, wherein the second position is opposite to the first position; and the simulated electric field distribution is determined based on the first electric field and the second electric field. A non-transitory computer-readable medium configured to store information, wherein: a processor coupled to the non-transitory computer-readable medium is configured to: generate a body of an object A three-dimensional (3D) model of a part of the system; determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions; receiving a first sensor array layout selected from the plurality of sensor array layouts Figure, wherein the first sensor array layout meets a criterion; and one or more related sensor array layouts are determined from the plurality of sensor array layouts, wherein each related sensor array layout includes information for a sensor Locations of array arrangements that do not overlap locations of sensor array arrangements for said first sensor array layout, wherein each associated sensor array layout satisfies said criteria; receiving a second sensor array layout selected from the one or more related sensor array layouts; and performing display of the first sensor array layout and the second sensor array layout, wherein the The criteria include the magnitude of one of the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model. The non-transitory computer-readable medium of claim 47, wherein said criteria further comprise a power density associated with one of said plurality of simulated electric field distributions within said ROI, and an estimate of skin toxicity associated with said part of the subject's body. The non-transitory computer-readable medium of claim 47, wherein the non-transitory computer-readable medium is further configured to operate according to the first sensor array layout diagram and the second sensor array layout. graph to generate composite data. The non-transitory computer-readable medium of claim 49, wherein the composite data includes information related to the first sensor array layout and the second sensor array layout, and the plurality of A simulated electric field distribution associated with the first sensor array layout and the second sensor array layout among the simulated electric field distributions. The non-transitory computer-readable medium of claim 47, wherein the non-transitory computer-readable medium configured to generate the 3D model is further configured to: enable one or more users The device displays a plurality of images of the portion of the subject's body; receives one or more images selected from the plurality of images based on a region of interest (ROI); and based on the one or more images to generate the 3D model. The non-transitory computer-readable medium of claim 51, wherein the non-transitory computer-readable medium is configured to receive from a first user device of the one or more user devices and the ROI-related information, and wherein receiving the selected one or more images includes from the one or a second user device of the plurality of user devices receives the selected one or more images. The non-transitory computer-readable medium of claim 47, wherein the non-transitory computer-readable medium configured to determine the layout of the plurality of sensor arrays is further configured to: according to the a 3D model to determine a plurality of pairs of positions for a sensor array arrangement; determining, for each pair of said plurality of pairs of positions, one of said plurality of simulated electric field distributions; and according to said plurality of simulated electric field distributions The electric field distribution determines the layout of the plurality of sensor arrays. The non-transitory computer-readable medium of claim 53, wherein the non-transitory computer-readable medium is configured to determine the simulated electric field distribution for each of the plurality of pairs of positions. The obtained medium is further configured to: simulate a first electric field generated by the first sensor array at a first position of the pair of positions; simulate a second electric field generated by the second sensor array at a second position of the pair of positions, The second position is opposite to the first position; and the simulated electric field distribution is determined according to the first electric field and the second electric field. A method for managing sensor array layout, which includes: generating a three-dimensional (3D) model of a body part of a subject; determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions; receiving Select the first sensor array layout and the second sensor array layout from the plurality of sensor array layouts; determine the overlapping status according to the first sensor array layout and the second sensor array layout; and displaying the overlapping status. The method of claim 55, wherein each sensor array layout of the plurality of sensor array layouts includes one or more pairs of positions for a sensor array arrangement, wherein the overlapping condition indicates that the A first sensor array layout includes one or more pairs of positions of the plurality of pairs of positions that overlap one or more pairs of positions of the plurality of pairs of positions associated with the second sensor array layout. An apparatus for managing a sensor array arrangement, comprising: one or more processors; and a memory storing processor-executable instructions that, when executed by the one or more processors, cause the The apparatus: generates a three-dimensional (3D) model of a body part of a subject; determines a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions; receives the plurality of sensor array layouts from the plurality of sensor array layouts Select the first sensor array layout and the second sensor array layout; determine the overlap status based on the first sensor array layout and the second sensor array layout; and display the overlap status. The apparatus of claim 57, wherein each of the plurality of sensor array layouts includes one or more pairs of positions for a sensor array arrangement, wherein the overlapping condition indicates that the The first sensor array layout includes one or more of the plurality of pairs of positions that overlap one or more of the plurality of pairs of positions associated with the second sensor array layout. A non-transitory computer-readable medium configured to store information where: A processor coupled to the non-transitory computer-readable medium is configured to: generate a three-dimensional (3D) model of a body portion of a subject; generate a plurality of simulated electric fields based on the 3D model and a plurality of simulated electric fields distribution to determine a plurality of sensor array layouts; receiving a first sensor array layout and a second sensor array layout selected from the plurality of sensor array layouts; according to the first sensor array layout and the The second sensor array layout is used to determine the overlapping status; and the overlapping status is displayed. The non-transitory computer-readable medium of claim 59, wherein each of the plurality of sensor array layouts includes one or more pairs of positions for a sensor array arrangement. , wherein the overlapping condition indicates that the first sensor array layout includes one or more pairs of the plurality of pairs of positions that overlap one or more of the plurality of pairs of positions associated with the second sensor array layout. One or more pairs of positions.