TW202231306A - Methods, systems, and apparatuses for managing transducer array placement - Google Patents

Abstract

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

Description

Method, system, and apparatus for managing sensor array placement

The present application relates to methods, systems and apparatus for managing sensor array arrangements.

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

The efficacy of the therapy of a tumor-treating electric field increases as the strength of the electric field increases. 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 is to be changed to simultaneously maintain the target strength of the electric field in the target area is a difficult, labor-intensive, and time-consuming process.

Disclosed is a method comprising generating a three-dimensional (3D) model of a portion of a body 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 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 locations for a plurality of pairs of locations for the sensor array arrangement, wherein The at least two sensor array layouts satisfy a criterion, and the display of the one or more sets of sensor array layouts is performed.

Also disclosed is a method comprising generating a three-dimensional (3D) model of a portion of a body of a subject, determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions, receiving data from the plurality of a selected first sensor array layout in a 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 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 all The standard is received, a second sensor array layout selected from the one or more associated sensor array layouts is received, and the first sensor array layout and the second sensor array layout are displayed.

Also disclosed is a method comprising generating a three-dimensional (3D) model of a portion of a body of a subject, determining a plurality of sensor array layouts based on the 3D model and a plurality of simulated electric field distributions, receiving data from the plurality of The first sensor array layout diagram and the second sensor array layout diagram selected in the sensor array layout diagram, the overlapping status is determined according to the first sensor array layout diagram and the second sensor array layout diagram, and the overlapping is performed Status display.

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

Before the present method and system is disclosed and described, it is to be understood that the method and system are not limited to particular methods, particular components, or particular implementations. It will also be understood that the terminology used herein is for the purpose of describing particular embodiments 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 dictates 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 value forms another embodiment. It will further be understood that an endpoint of each stated range is important both in relation to the other endpoint, and independently of the other endpoint.

"Optional" or "optionally" means that the subsequently described event or circumstance may or may not occur, and thus that the description includes instances where said event or circumstance occurs and instances where it does not.

Throughout the description and claims of this specification, the word "includes" and conjugations of said word (eg, "includes" and "includes") mean "including but not limited to" and is not intended to exclude, for example, Other components, integers, or steps. "Exemplary" means "an example of" and thus is not intended to convey an indication of a preferred or ideal embodiment. "For example" is not used in a limiting sense, but for purposes of explanation.

Disclosed are components that can be utilized to perform the disclosed methods and systems. For all methods and systems, these and other components are disclosed herein, and it is understood that when combinations, subsets, interactions, groups, etc. of these components are disclosed, although each of these various Specific references to the individual and collective combinations and permutations of may not be expressly disclosed, but each is expressly contemplated and thus described herein. This applies to all features of this application, including but not limited to steps in the disclosed methods. Thus, where there are various additional steps that may be performed, it is understood that each of these additional steps may be performed in conjunction with any particular embodiment or combination of embodiments of the disclosed method.

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

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

Embodiments of the methods and systems are described below with reference to block diagram and flowchart illustrations of methods, systems, apparatus, and computer program products. It will be understood that each block of the block and flowchart illustrations, and combinations of blocks in the block and flowchart illustrations, 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 enables the computer or other programmable data processing equipment The instructions executed on produce a means for implementing the function specified in the block or blocks of the flowchart.

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 such that the computer-readable memory The instructions in the memory produce a product comprising computer-readable instructions for implementing the functions specified in the block or blocks of the flowchart. The computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to generate a computer A program implemented such that the instructions executing on the computer or other programmable device provide steps for implementing the functions specified in the block or blocks of the flowchart.

Thus, the blocks of the block and flowchart diagrams are supporting combinations of means for performing the specified functions, combinations of steps for performing the specified functions, and means for performing the specified functions means of program instructions. It will also be understood that each block of the block and flowchart illustrations, and combinations of blocks in the block and flowchart illustrations, can be used to perform the specified function or The steps are implemented by a special purpose hardware-based computer system, or a combination of special purpose hardware and computer instructions.

Tumor treatment electric fields (also referred to herein as alternating electric fields) are established as a primary anti-mitotic cancer treatment modality because they interfere with proper microtubule assembly in metaphase and ultimately disrupt all metaphases during telophase and cytoplasmic division. described cells. The efficacy increased with increasing field strength and the optimal frequency was cancer cell line dependent, with 200 kHz being the maximum frequency for inhibition of glioma cell growth by 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 a human body The most common major malignant brain tumor.

Because the effects of tumor treatment electric fields are directional, wherein cell division parallel to the electric field is more affected than cell division in other directions, and because cells divide in all directions, tumor treatment electric fields are often It is delivered through two pairs of sensor arrays that generate a vertical field within the tumor being treated. More specifically, one pair of sensor arrays may be positioned to the left and right (LR) of the tumor, while the other pair of sensor arrays may be positioned to the front and rear (AP) of the tumor. Cycling the electric field between these two directions (ie, LR and AP) ensures that a maximum range of cell orientations are targeted. In addition to vertical fields, other sensor array positions are contemplated. In an embodiment, asymmetrical positioning of three sensor arrays is contemplated, wherein one pair of the three sensor arrays can transmit an alternating electric field, and then another 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 therapy with tumor-treating electric fields increases as the strength of the electric field increases. Therefore, optimizing the array placement on the patient's scalp to increase intensity in diseased regions of the brain is standard practice for the Optune system. Optimization of array placement can be performed by "rule of thumb" (eg, place the array on the scalp as close to the tumor as possible) 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 contain any type of visual data, such as single photon emission computed tomography (SPECT) image data, X-ray computed computed tomography (X-ray CT) data, magnetic resonance imaging (MRI) data, positron emission Computed tomography (PET) data, data that can be captured by optical devices (eg, cameras, charge-coupled device (CCD) cameras, infrared cameras, etc.), and the like. In some embodiments, the image data may include 3D data obtained from, or generated by, a 3D scanner (eg, point cloud data). 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 heads of different patients understanding of change. A plurality of sensor array maps may be determined that indicate optimal positioning of the sensor array on a patient's body that meets various criteria (eg, provides an electric field within a region of interest (ROI) minimum and/or maximum intensity, power density within the ROI, etc.).

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

FIG. 1 shows an example apparatus 100 for the treatment of electrotherapy. In general, the apparatus 100 may be a portable battery or power supply operated device that generates an alternating electric field within the body by means of an array of non-invasive surface sensors. The apparatus 100 may include an electric field generator 102 and one or more sensor arrays 104 . The apparatus 100 may be configured to generate tumor treatment fields (TTFields) (eg, at 150 kHz) via the electric field generator 102 and deliver the tumor treatment fields to all via the one or more sensor arrays 104 . an area of the body. The electric field generator 102 may be a battery and/or power supply operated device. 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 the execution of the processor 106 and the signal generator 108 .

The signal generator 108 may generate one or more electrical signals having the shape of a waveform or pulse train. The signal generator 108 may be configured to generate an alternating voltage waveform (eg, the tumor treatment electric field) at frequencies in the range from about 50KHz to about 500KHz, preferably from about 100KHz to about 300KHz. 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 to the signal generator 108 at one end thereof. 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 spreading of the electric field generated by the conductive leads 112 . The one or more outputs 114 may be operated sequentially. The output parameters of the signal generator 108 may include, for example, the strength of the field, the frequency of the wave (eg, the treatment frequency), and the maximum tolerable 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 may cause the processor 106 to transmit a control signal to the signal generator 108 that 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 can be configured in various shapes and positions to facilitate generating an electric field in a target volume having a desired configuration, direction, and intensity to facilitate focused therapy. The one or more sensor arrays 104 may be configured to transmit two perpendicular field directions through 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 having a high dielectric constant. The one or more electrodes 116 may comprise, for example, one or more insulating ceramic disks. The electrodes 116 may be biocompatible and coupled to a flexible circuit board 118 . The electrodes 116 may be configured so as not to directly contact the skin, since the electrodes 116 are separated from the skin by a layer of conductive hydrogel (not shown) (similar to the hydrogels found on ECG pads).

The electrodes 116, the hydrogel, and the flexible circuit board 118 can 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 continues to be in 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 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 disturbance to the temperature measurement.

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

The one or more sensor arrays 104 may vary in size and may include different numbers of electrodes 116 depending on patient body size and/or different treatments. For example, in the context of a patient's thorax, small sensor arrays may each include 13 electrodes, while large sensor arrays may each include 20 electrodes, where the electrodes in each array are 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, respectively, wherein the electrodes in each array are interconnected in series

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

3A and 3B depict an example application of the apparatus 100. A sensor array 104a and a sensor array 104b are 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 the 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 that 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 that make it 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 can be specific to the cell type being treated (eg, 150 kHz for MPM). The alternating electric field 310 has been shown to interfere with mitotic spindle microtubule assembly during cytokinesis and cause dielectrophoretic dislocation of intracellular macromolecules and organelles. These processes lead to physical disturbance of the cell membrane and programmed cell death (apoptosis).

Because the effect of the alternating electric field 310 is directional, 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 the two pairs of sensor arrays 104, which create 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 another pair of sensor arrays 104 may be positioned to the front and rear (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 are targeted. In one embodiment, the alternating electric field 310 may be delivered according to a symmetrical arrangement of sensor arrays 104 (eg, four sensor arrays 104 in total, 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 asymmetrical arrangement of sensor arrays 104 may allow two of the three sensor arrays 104 to 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 therapy with tumor-treating electric fields increases as the strength of the electric field increases. The method, system and apparatus are configured for optimizing array placement on the scalp of a patient to increase intensity in diseased regions of the brain.

As shown in Figure 4A, the sensor array 104 may be arranged on a patient's head. As shown in Figure 4B, the sensor array 104 may be placed 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 disposed 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 explicitly contemplated.

FIG. 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 model application 608 , and/or imaging data 610 . The patient support system 602 may include, for example, a computing device. 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 build 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 from the imaging data 610 . The imaging data 610 may include any type of visual data, such as single photon emission computed tomography (SPECT) imaging data, X-ray computed computed tomography (X-ray CT) data, magnetic resonance imaging (MRI) data , positron emission computed tomography (PET) data, data that can be captured by optical devices (eg, cameras, charge coupled device (CCD) cameras, infrared cameras, etc.), and the like. In some embodiments, the image data may include 3D data obtained from, or generated by, a 3D scanner (eg, point cloud data). The build patient model application 608 can also be configured to generate a three-dimensional array layout based on the patient model and one or more electric field simulations.

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 build patient model application 608 to identify a tumor that includes a tumor area of interest. In the context of a patient's head, in order to characterize how the electric field behaves and spreads within a person's 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 generate realistic head models and partition tissue types within the head, such as skull, white matter, gray matter, and cerebrospinal fluid (CSF). Each tissue type can be assigned dielectric properties for relative conductance and permittivity, and simulations can be performed whereby different sensor array configurations are applied to the surface of the model to facilitate understanding of a How an externally applied electric field of a 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 across the brain is rather non-uniform, and that electric field strengths in excess of 1 V/cm are generated at Most tissue chambers except CSF. These results were obtained assuming a peak-to-peak total current of 1800 milliamperes (mA) at the sensor array-scalp interface. The critical value of this 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 for a particular region of the brain as shown in FIG. 7 . Figure 7 depicts the electric field magnitude and distribution (in V/cm) from a finite element method simulation model shown in coronal view. This simulation utilizes a left-right paired sensor array configuration.

In one feature, the build patient model 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 T1 sequence brain MRI using axial and coronal views. Post-contrast axial and coronal MRI views can be selected to show the largest diameter of the enhancing lesion. Using measurements of head size and distance from a predetermined fiducial marker to the tumor edge, different permutations and combinations of paired array layouts can be evaluated in order to produce a configuration that delivers the greatest 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 FIG. 8B, the three-dimensional array layout 800 (eg, a sensor array layout) may be used by the patient and/or caregiver to deploy the array on the scalp during normal tumor treatment field therapy sessions superior.

In one feature, the build patient model 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 can be received via a standard Digital Image Transmission in Medical (DICOM) viewer. Determination of MRI measurements may be performed automatically, eg, by artificial intelligence techniques, or may be performed manually, eg, by a physician.

Determination of manual MRI measurements may include receiving and/or providing MRI data via a DICOM viewer. The MRI data may include a scan of a portion of the patient containing 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. 9A, 9B, 9C, and 9D are MRI data showing examples showing scans of a patient's head. Figure 9A shows an axial T1 sequence slice with the topmost image including the track used to measure head size. FIG. 9B shows a coronal T1 serial section, which selects the image at the height of the ear canal, and is used to measure the head size. Figure 9C shows a post-contrast T1 axial image showing the largest enhanced tumor diameter used to measure tumor location. Figure 9D shows a post-contrast T1 coronal image showing the largest enhanced tumor diameter used to measure tumor location. MRI measurements can start from fiducial markers at the lateral edge of the scalp and extend tangentially from a right, anterior, upper origin. Morphometric head size can be estimated from selecting an axial T1 MRI sequence that still contains the topmost image of the track (or the image just above the upper edge of the track).

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

The MRI measurements may include one or more head size measurements, such as: a maximum anterior-posterior (A-P) head size measured from the outer edge of the scalp; the head perpendicular to the A-P One of the greatest widths measured: the lateral distance from left to right; and/or the distance from the furthest right edge of the scalp to the midline of the anatomy.

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

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

The one or more tumor measurements may include coronal view tumor measurements. The coronal view tumor measurements may include the identification of post-contrast T1 MRI slices characterized by tumor enhancement of the largest diameter (FIG. 9D). The tumor measurement of the coronal view may include one or more of the following: a maximum distance from the top of the scalp to the lower border of the cerebrum. In 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 right-to-left lateral head width; a distance from the right edge of the scalp to the midline of the anatomy; from the right edge of the scalp to the closest tumor measured parallel to the left-right lateral distance A distance from the edge; a distance from the right edge of the scalp to the furthest tumor edge, measured parallel to the said left-right lateral distance; A distance from the proximal tumor edge; and/or a distance from the apex of the head to the furthest tumor edge measured parallel to the superior apical to inferior brain line.

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

The MRI measurements can be utilized by the Build Patient Model application 608 to generate a patient model. The patient model can then be used to determine a three-dimensional array layout (eg, three-dimensional array layout 800). Continuing with the example of a tumor in a patient's head, a healthy head model can be created that acts as a deformable template from which the patient model can be created. When generating a patient model, the tumor can be segmented from the patient's MRI data (eg, one or more MRI measurements). Segmenting the MRI data is to identify 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 the simulation. Tumor regions in the patient's MRI profile may be obscured, so a non-rigid registration algorithm can be used to register the rest of the patient's head to a deformable sample representing the healthy head model version on 3D discrete images. This process produces a non-rigid transformation that maps the healthy portion 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 produce an approximation of the patient's head without the tumor. Finally, the tumor, referred to as a region of interest (ROI), is implanted back into the deformed template to generate a complete patient model. The patient model may be a digital representation in three-dimensional space of a part of the patient's body that contains internal structures such as tissues, organs, tumors, etc. Table 1 Organization type Conductivity S/m relative permittivity scalp 0.3 5000 skull 0.08 200 cerebrospinal fluid 1.79 110 gray matter 0.25 3000 white matter 0.12 2000 enhance tumor 0.24 2000 Enhanced non-tumor 0.36 1170 resection cavity 1.79 110 Necrotizing tumor 1 110 hematoma 0.3 2000 ischemia 0.18 2500 shrink 1 110 Air 0 0

The delivery of the tumor treatment electric field can then be simulated by the Build Patient Model application 608 using the patient model. The simulated electric field distribution, dose, and simulation-based analysis are described in US Patent Publication No. 20190117956 A1 by Ballo et al. (2019) and the publication "Correlation of Tumor treating Fields Dosimetry to Survival Outcomes in Newly Diagnosed Glioblastoma: A Large-Scale Numerical Simulation-based Analysis of Data from the Phase 3 EF-14 randomized Trial", which is hereby incorporated 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 may actually be arranged on the patient model with its center and longitudinal axis in the xy plane. A pair of sensor arrays can be rotated systematically around the z-axis of the head model, ie in the xy plane, from 0 to 180 degrees, thereby (symmetrically) covering the entire circumference of the head. The rotation interval may be, for example, 15 degrees, which corresponds to a translation of about 2 cm, which results in a total of twelve different positions over a range of 180 degrees. Other rotation intervals are also contemplated. Electric field distribution calculations can be performed for the coordinates of each sensor array location relative to the tumor.

The electric field distribution in the patient model can be determined by the Build Patient Model application 608 using a finite element (FE) approximation of the potential. In general, the quantity that defines a time-varying electromagnetic field is given by the complex Maxwell equations. However, in biological tissue and at low to mid-frequency tumor treatment electric fields (f=200 kHz), the electromagnetic wavelength is much larger than the size of the head, and the permittivity 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 effects as well as capacitive effects in the tissue are negligible, so the scalar potential can be well defined by the static Laplace equation ▽·(σ under appropriate boundary conditions of electrode and skin ▽ϕ)=0 to approximate. Therefore, the complex impedance is treated as resistive (ie, the reactance is negligible), and the current flowing within the bulk conductor is therefore primarily a free (ohmic) current. The FE approximation of the Laplace equation can be calculated using a software such as the SimNIBS software (simnibs.org). Calculations according to the Galerkin method and residuals for the conjugate gradient solver are required to be < 1E-9. Dirichlet boundary conditions are used when the potentials of the electrode arrays of each group are set to (arbitrarily chosen) fixed values. The electric (vector) field can be calculated as a 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, calculated for all triangular surfaces on the active electrode disk The (numerical) area fraction of the normal current density component over the element. The "dose" of the tumor treatment electric field can be calculated as the strength of the electric field vector (L2 norm (norm)). The modeled current can be assumed to be provided by two separate and sequentially acting sources, each connected to a pair of 3x3 sensor arrays. The left and rear arrays may be defined in the simulation as sources, while the right and front arrays are the corresponding sinks, respectively. However, since the tumor treatment electric field utilizes alternating fields, this choice is arbitrary and does not affect the results.

An average electric field strength generated by sensor arrays disposed at multiple locations on the patient can be determined by the Build Patient Model application 608 for one or more tissue types. 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 instances, sensor array placement locations (eg, optimized sensor array placement locations) may be determined for effective and/or optimized tumor treatment electric field treatment and/or therapy. For example, one or more users (eg, physicians, nurses, assistants, staff, physicists, dosimetrists, etc.) may use a user interface to determine and/or generate sensor array layouts (eg, three-dimensional array layout, etc.) for positioning sensor arrays on the body (eg, head, torso, etc.) of a person (eg, patient, subject, etc.) that will optimize tumor treatment Electric field therapy and/or therapy while avoiding and/or limiting skin toxicity. For example, sensor array layouts for complex groups (eg, groups, summaries, etc.) may be determined that each include sensor array layouts that satisfy one or more criteria. A criterion may include a potential magnitude of an electric field distributed within a region of interest (ROI) associated with a person (eg, patient, subject, etc.), and a magnitude of a potential distributed within the ROI A potential power density associated with the electric field, and an estimate of skin toxicity associated with a part of the person's body (eg, head, torso, etc.), and/or any other criteria. Multiple sets of sensor array layouts in the complex set of sensor array layouts may be determined that include two or more sensor array layouts that include non-overlapping locations for sensor array placement. The sensor array layout of the plurality of groups 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, a plurality of sets of sensor array layouts of the plurality of sets of sensor array layouts that are and the selected sensor are presented Array layout diagram-dependent (eg, according to a criterion, according to non-overlapping positions, overlapping positions, etc.).

An exemplary method may include providing a plurality of images of an anatomical volume to at least one user, and accepting from the at least one user a selection 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 from the selected images, and determining a plurality of sensor array layouts. Which of the determined sensor array layouts satisfy at least one criterion is then evaluated based on the generated model. The method may include providing to the at least one user a plurality of sensor array layouts that meet the at least one criterion, and accepting the sensor array from the at least one user to be presented to the at least one user Choice of one of the layouts. A report describing the selected sensor array layout can be generated. In some instances, 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 instances, 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 examples, the method may include accepting input from the first user confirming a gross segmentation, 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.

FIG. 10 is a block diagram of a system 1000 depicting an example of a sensor array arrangement. In some instances, the components of the system 1000 may be implemented as a single device and/or the like. In some instances, the components of the system 1000 may be implemented as individual devices/components, and/or as collective communications. The system 1000 and/or components of the system 1000 may be implemented as hardware, software, or a combination of both. In one feature, some or all of the steps of any of the methods described herein may be performed on and/or via components of the system 1000 . The system 1000 can be used to determine the location (positioning) for sensor array placement on the body of a person (eg, a patient, a subject, etc.). The location (positioning) for the sensor array arrangement can be indicated by one or more sensor array layout diagrams. A user (eg, physician, nurse, assistant, staff member, physicist, dosimetrist, 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 higher cost and/or highly skilled personnel (eg, physicians, etc.) to provide guidance and/or instructions for determining and/or generating sensor array layouts to lower Cost of personnel (eg, dosimetrists, physicists, etc.). For example, image data (eg, one or more images associated with CT, MRI, ultrasound, SPECT, X-ray CT, PET, etc.) may be segmented via a user device, and the segmented image data Can be transmitted to another user device for analysis, used to generate a three-dimensional (3D) model, and/or used to generate a plurality of sensor array layouts. The determined and/or generated sensor array layout can be reviewed and/or selected to generate a report that can be used for treatment and/or therapy of an effective tumor treatment field.

The system 1000 can include a patient support module 1001 . The patient support module 1001 can include a processor 1008 . The processor 1008 may be a hardware device for executing software, in particular, 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 based microprocessor (in the form of a microchip or chip set), or generally any device for executing software instructions. When the patient support module 1001 is in operation, the processor 1008 can be configured to execute software stored within the memory 1010, communicate data to and from the memory 1010, and generally according to the 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/info 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 web interface 1014 can 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, a wireless network adapter (eg WiFi), or any other suitable network interface device. The network interface 1014 may include address, control, and/or data connections to enable proper communication.

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 (eg, ROM, hard drive, magnetic tape, CDROM, DVDROM, etc.) any one or combination. Furthermore, the memory 1010 may incorporate electronic, magnetic, optical, and/or other types of storage media. In some examples, the memory system 1010 may have a decentralized architecture in which various components are located remotely from each other, but are accessible by the processor 1008 .

The memory 1010 may contain 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 the EFG configuration application 606, the build patient model application 608, imaging data 610, and an appropriate operating system (O/S) 1018 as described in FIG. The operating system 1018 may 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 illustrative purposes, applications and other executable program components, such as the operating system 1018, are depicted herein as discrete blocks, although it is recognized that such programs and components may exist at various times in various storage components of the patient support system 104 . An embodiment of the EFG configuration application 606, the build patient model 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 can be performed by computer-readable instructions embodied on a computer-readable medium. 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" as well as "communication media". "Computer storage media" may include volatile and non-volatile, removable and non-removable media implemented in any method or technology for, for example, computer-readable instructions, data structures, programs Storage of information about modules, or other data. Exemplary computer storage media may include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital disc (DVD) or other optical storage, magnetic cartridges, magnetic tape, disk storage, or Other magnetic storage devices, or any other medium that can be utilized to store the desired information and that can be accessed by a computer.

The system 1000 can 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, capable of communicating with a patient support module 1001 . Although there are only the 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 the user 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, pointing device (eg, computer mouse, remote control), microphone, joystick, scanner, tactile sensing and/or tactile input device, 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 interface used to provide the user and the user devices 1020 and 1030, the patient support module 1001, and/or the system 1000 and/or one or more of any other components associated with the system 1000. The interface module 1022 may include one or more displays (eg, monitors, heads-up displays, head-mounted displays, liquid crystal displays, organic light emitting diode displays, active matrix organic light emitting diode displays, stereoscopic displays, etc. etc.) for displaying/presenting information to the user. The interface module 1022 may include one or more audio devices (eg, stereo, speakers, microphones, etc.) for capturing/obtaining and transmitting audio information, such as audio information captured/obtained from a user , and/or are 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 can request and/or query various files from a local source and/or a remote source (eg, the patient support module 1001 ).

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 may enable the user devices 1020 and 1030 to communicate with components of the system 1000 (eg, 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, fiber optics, and/or the like. The communication module 1023 can 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 can be used to determine the location (positioning) for sensor array placement on the body of a person (eg, a patient, a subject, etc.). The location (location) for the sensor array arrangement may be indicated by one or more sensor array layout diagrams. A user (eg, physician, nurse, assistant, staff member, physicist, dosimetrist, 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 higher cost and/or highly skilled personnel (eg, physicians, etc.) to provide guidance and/or instructions for determining and/or generating sensor array layouts to lower Cost of personnel (eg, 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 to the lower cost personnel for determining and/or generating sensor array layouts ( For example, a dosimetrist, a physicist, etc.), who may be the user of the user device 1030.

11A-11D are screens showing an example interface (eg, the interface module 1022, etc.) for managing sensor array arrangements. One or more images, such as 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 three-dimensional (3D) )Model. FIG. 11A shows an example screen 1101 of a user interface 1100 . The screen 1101 may include information 1102 identifying the subject/patient. The validation 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 can be used for segmentation of image data.

The screen 1101 is to enable a user (eg, the user of the user devices 1020 and 1030, etc.) to input and examine a body part (eg, head, torso, anatomical volume, etc.) of a subject/patient etc.) of one or more images, and determine whether the images 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, buttons, etc.). Interacting with an interactive element 1104 may cause a menu to open that enables the user to search for related images and/or upload related images. After an image has been imported, eg, from the image data 610 , a representation of the image may be displayed in a panel 1105 . FIG. 11B shows an example screen 1101 of the user interface 1100 when an image has been entered and represented in the panel 1105 by the image 1106 . The user can view and inspect the entered images 1106, for example, by using an interactive element (eg, mouse, trackpad, etc.) to pull one or more of the images 1106 to the One or more windows 1107 of screen 1101. The user can identify images (eg, one or more images, image sets, etc.) that are best suited for the treatment plan of the tumor treatment field. As shown in FIG. 11B , one or more of the images 1106 are presented in the window 1107 .

After viewing/inspecting the image 1106, the user may select an image or group of images to be segmented and used to generate a 3D model. In some instances, a user of the user device 1020 may select an image or group of images, and the user device 1020 may transmit the selected image or group of images (eg, and the selected image or group of images) related information, etc.) to the user device 1030 for segmentation and 3D model generation. In some instances, the user of the user device 1030 may select an image or group of images, and the user device 1030 may transmit the selected image or group of images (eg, and the selected image or group 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 and/or for the calculation 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 main 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 may select the images displayed in the one or more windows 1107 . After an image has been selected, the image may be segmented to identify/determine/select features and/or areas of interest within the image, such as tissue structures representing tumors and/or abnormalities. 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 all within the image. The algorithm of the region of interest (ROI) is configured. For example, the segmentation tool may enable the user to label regions of the image as enhancing tumors, necrotic cores, resection chambers, craniotomy, and/or the like. Regions 1109 of the screen 1101 are examples of structures shown in the image that can be defined by the user, such as tissue types, ROIs, 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 placed, such as areas of scar tissue, medical device implants, and/or the like.

As previously described, the user can assign tissue types to images that are used to generate 3D models and/or sensor array layouts. When a 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 may 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 instances, any determined and/or selected ROI may be utilized by an electric field distribution simulation and/or optimization algorithm to generate a sensor array layout. In some instances, the ROI may be input to the system 1000 from an external source (eg, a third-party software used to plan radiation therapy, etc.). After the user completes the segmentation editing of the image, an interactive element 1110 may be utilized 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 progress screen of the screen 1101 . As shown, the interactive element 1103 is set to "model" to indicate the progress of the user interface 1100. The screen 1111 can display any abnormal tissue indicated on the screen 1101, as well as any normal body tissue (eg, gray matter, white matter, skull, scalp, and CSF) within the image. The user interface 1100 can be configured to automatically add and/or include any normal body tissue when a 3D model is generated.

A generated 3D model can model any electrical feature at every point in space within a part of an object/patient's body (eg, head, torso, anatomical volume, etc.). For example, the system 1000 can map electrical features to a 3D model. Mapping electrical features to 3D models can be based on diffusion tensor imaging MRI data (DTI), hydroelectric property computed tomography (wEPT), machine learning, and/or any other method for correlating electrical features from image data to the method/technique of the type of organization. Once a 3D model is generated, the user interface 1100 enables the user to position the simulated sensor array at various locations (locations) on the 3D model, simulate the application of AC voltage to the simulated sensor array, performing simulations that determine a resulting electric field distribution for each point within a part of an object/patient's body (eg, head, torso, anatomical volume, etc.) represented by the 3D model and / or power density. The 3D model can be displayed to the user. If the user is not satisfied with the displayed model, an interactive element 1112 "view split" can be utilized to return to a previous screen, such as a split input screen of the user interface 1100, for example. If the user is satisfied with the displayed model, for example an interactive element 1113 "Create Project" may 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 treatment plan for a tumor treatment field. For example, after a 3D model is generated and a plurality of simulated electric field distributions are determined based on the 3D model, a plurality of sensor array layout diagrams can be generated. In some instances, the system 1000 may determine the plurality of sensor array layouts, eg, from a standard sensor array layout of a library, record, data volume, and/or the like. In some instances, 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 map above, it provides the desired and/or optimal (eg, most suitable for meeting a criterion, etc.) result. Based on changing the position of one or more arrays as previously described, the system 1000 can determine one or more sensor array layouts in a plurality of sensor array layouts (eg, groups of sensor array layouts, etc. ), which optimizes the electric field distribution within a target ROI, while also satisfying the constraints imposed by the avoidance structures related to sensor array placement. For example, one or more sets of sensor array layouts may be determined from the plurality of sensor array layouts (eg, automatically, manually selected, etc.), which respectively represent at least two sensor arrays having non-overlapping locations layout and/or meet a standard. As previously described, a criterion may include the magnitude of a simulated electric field distribution within a ROI associated with a 3D model, and 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 an estimate of skin toxicity associated with a portion of a subject/patient's body in which the sensor array is to be disposed and/or an avoidance area.

The optimal sensor array layout for a desired tumor treatment 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 distributions. The composite data can be displayed via the user interface 1100, for example. Returning to FIG. 11D, the screen 1114 can 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, by interacting with a corresponding TAL element (eg, TAL 1 to TAL 5), the interactive element 1115 can be used to view the electric field distribution for each of the sensor array layouts (TALs). As shown, TAL 1 of the interactive element 1115 is selected, and a color map of the electric field distribution and 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 sensor array layout of the plurality of sensor array layouts may be displayed to enable the user to select a treatment plan for a tumor treatment electric field. In some examples, an overall score for each sensor array layout and/or a set of sensor array layouts of the plurality of sensor array layouts may be determined and displayed. A score may represent the degree to which a criterion or criteria are met by an associated sensor array layout. Scores can 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, eg, by a user. The evaluation of a sensor array layout is based on and/or determines the quality of a 3D model used to generate the sensor array layout (eg, the treatment plan of the tumor treatment electric field, etc.). A user may evaluate and select one or more sensor array layouts and/or groups of sensor array layouts from the plurality of sensor array layouts.

FIG. 12 is a flowchart showing a method 1200 for managing sensor array arrangements. One or more of the apparatus 100, the patient support system 602, the build patient model application 608, the system 1000, and/or any other devices/components described herein may be configured to perform A method 1200 includes generating, at 1210, a three-dimensional (3D) model of a portion of a body of the subject. The 3D model can 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 instances, one or more user devices may display a plurality of images of the portion of the subject's body. One or more images selected from the plurality of images may be received according to a region of interest (ROI), and a 3D model may be generated from the one or more images. For example, an 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, 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 from 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 the plurality of simulated electric field distributions. Determining the plurality of sensor array layout drawings may include determining a plurality of pairs of locations for sensor array placement from the 3D model. In some instances, the plurality of pairs of positions for sensor array placement may be determined from a standard sensor array placement of a library, record, data volume, and/or the like. In some examples, the pairs of positions for sensor array placement may be determined and/or selected to avoid one or more regions within the 3D model (eg, avoidance regions, etc.) and/or or similar. For each pair of positions of the plurality of pairs of positions, a simulated electric field distribution of 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 a first electric field at the pair of positions The two positions simulate the second electric field generated by the second sensor array. The second position may be opposite the first position. In some instances, a third electric field generated by the first sensor array may be simulated at a third location, and a fourth electric field generated by the second sensor array may be opposite the third location The fourth position of , is simulated, and based on 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 according to 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 layout diagrams may be determined according to 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 layouts A non-overlapping location of locations wherein the at least two sensor array layouts satisfy a criterion. The criterion may include a magnitude of a simulated electric field distribution of the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model, and a magnitude of a 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, display of the one or more sets of sensor array layouts is performed. The one or more sets of sensor array layouts may be displayed through an interface of the one or more user devices. A selected set of sensor array layouts from the one or more sets of sensor array layouts may be received, for example, via an interface of the one or more user devices. Composite data (eg, a report, a plan, a summary, etc.) can be generated from a selected set of sensor array layouts. The composite data may include information related to the selected set of sensor array layouts, and 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.

FIG. 13 is a flowchart showing a method 1300 for managing sensor array arrangements. One or more of the apparatus 100, the patient support system 602, the build patient model application 608, the system 1000, and/or any other devices/components described herein may be configured to perform A method 1300 includes generating, at 1310, a three-dimensional (3D) model of a portion of a body of the subject. The 3D model can 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 instances, one or more user devices may display a plurality of images of the portion of the subject's body. One or more images selected from the plurality of images may be received according to a region of interest (ROI), and a 3D model may be generated from the one or more images. For example, an 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, 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 from 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 the plurality of simulated electric field distributions. Determining the plurality of sensor array layout drawings may include determining a plurality of pairs of locations for sensor array placement from the 3D model. In some instances, the plurality of pairs of positions for sensor array placement may be determined from a standard sensor array placement of a library, record, data volume, and/or the like. In some examples, the pairs of positions for sensor array placement may be determined and/or selected to avoid one or more regions within the 3D model (eg, avoidance regions, etc.) and/or or similar. For each pair of positions of the plurality of pairs of positions, a simulated electric field distribution of 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 a first electric field at the pair of positions The two positions simulate the second electric field generated by the second sensor array. The second position may be opposite the first position. In some instances, a third electric field generated by the first sensor array may be simulated at a third location, and a fourth electric field generated by the second sensor array may be opposite the third location The fourth position of , is simulated, and based on 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 according to 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 layout diagrams may be determined according to the plurality of simulated electric field distributions.

At 1330, a selected first sensor array layout 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 criterion may include a magnitude of a simulated electric field distribution of the plurality of simulated electric field distributions within a region of interest (ROI) associated with the 3D model, and a magnitude of a 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 include locations for sensor array arrangements that do not overlap locations for the first sensor array layout. In some instances, each associated sensor array layout may satisfy the criteria.

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

At 1360, displaying the first sensor array layout and the second sensor array layout is performed. In some instances, composite data (eg, a report, a plan, a summary, etc.) may be generated from the first sensor array layout and the second sensor array layout. The composite data may include, for example, information related to the first sensor array layout and the second sensor array layout, and the first sensor array layout of the plurality of simulated electric field distributions and a simulated electric field distribution associated with the second sensor array layout.

14 is a flowchart showing a method 1400 for managing sensor array arrangements. One or more of the apparatus 100, the patient support system 602, the build patient model application 608, the system 1000, and/or any other devices/components described herein may be configured to perform A method 1400 includes generating, at 1410, a three-dimensional (3D) model of a portion of a body of the subject. The 3D model can 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 instances, one or more user devices may display a plurality of images of the portion of the subject's body. One or more images selected from the plurality of images may be received according to a region of interest (ROI), and a 3D model may be generated from the one or more images. For example, an 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, 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 from 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 the plurality of simulated electric field distributions. Determining the plurality of sensor array layout drawings may include determining a plurality of pairs of locations for sensor array placement from the 3D model. In some instances, the plurality of pairs of positions for sensor array placement may be determined from a standard sensor array placement of a library, record, data volume, and/or the like. In some examples, the pairs of positions for sensor array placement may be determined and/or selected to avoid one or more regions within the 3D model (eg, avoidance regions, etc.) and/or or similar. For each pair of positions of the plurality of pairs of positions, a simulated electric field distribution of 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 a first electric field at the pair of positions The two positions simulate the second electric field generated by the second sensor array. The second position may be opposite the first position. In some instances, a third electric field generated by the first sensor array may be simulated at a third location, and a fourth electric field generated by the second sensor array may be opposite the third location The fourth position of , is simulated, and based on 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 according to 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 layout diagrams may be determined according to the plurality of simulated electric field distributions.

At 1430, a first sensor array layout map and a second sensor array layout map selected from the plurality of sensor array layout maps 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 overlap condition is determined according to the first sensor array layout and the second sensor array layout. Each sensor array layout of the plurality of sensor array layouts may include locations for one or more of the plurality of pairs of locations for the sensor array arrangement. The overlapping condition may indicate that the first sensor array layout includes one or more pairs of positions 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 locations. For example, the first sensor array layout may include locations for the sensor array that are the same locations indicated on a 3D model (eg, overlap, etc.), or the locations are a 3D model The locations indicated above meet a distance threshold and/or are within a tolerance positioning range (eg, substantially overlap, etc.) with respect to each other.

At 1450, display of the overlap condition occurs. One or more of the user devices may be made to display the overlapping condition, eg, 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.

In view of the apparatus, systems, and methods, and variations thereof, described below are certain more particularly described embodiments of the present invention. However, these specifically set forth embodiments should not be construed to have any limiting effect on any of the various claims encompassing different or more general teachings described herein, or that such "specific" embodiments are somehow Restricted in some way other than the inherent meaning of the language in which it is contextually used.

Embodiment 1: A method comprising: generating a three-dimensional (3D) model of a portion of a body of the subject, determining a plurality of sensor array layouts from the 3D model and a plurality of simulated electric field distributions, a plurality of sensor array layouts 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 locations for a plurality of pairs of locations for the sensor array layout , wherein the at least two sensor array layout diagrams meet a standard, and the one or more sets of sensor array layout diagrams are displayed.

Embodiment 2: An embodiment as in any 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 The magnitude of a simulated electric field distribution, and the power density associated with a simulated electric field distribution of the plurality of simulated electric field distributions within the ROI, and the skin associated with the portion of the subject's body Estimation of toxicity.

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

Embodiment 4: As in Embodiment 3, further comprising generating composite data according to the selected set of sensor array layouts.

Embodiment 5: The embodiment of Embodiment 4, wherein the composite data includes information related to the sensor array layout of the selected group, and the plurality of sensor array layouts related to the selected group The simulated electric field distribution of the simulated electric field distribution.

Embodiment 6: The embodiment of Embodiment 4, further comprising transmitting the composite data to a user device.

Embodiment 7: An embodiment as in any of the preceding embodiments, wherein generating the 3D model comprises causing one or more user devices to display a plurality of images of the portion of the subject's body, according to a A region of interest (ROI) to receive one or more images selected from the plurality of images, and to generate the 3D model from the one or more images.

Embodiment 8: The embodiment of 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 image or images includes receiving the selected one or more images from a second user device of the one or more user devices.

Embodiment 9: The embodiment of any one of the preceding embodiments, wherein determining the plurality of sensor array layout drawings comprises: determining the plurality of pairs of positions for the sensor array layout according to the 3D model, for the Each of the plurality of pairs of positions determines a simulated electric field distribution of 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: The embodiment as in Embodiment 9, wherein determining the simulated electric field distribution for each of the plurality of pairs of positions comprises: simulating at a first position of the pair of positions by a first a first electric field produced by the sensor array, a second electric field produced by the 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 comprising: generating a three-dimensional (3D) model of a portion of a 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 data from all A first sensor array layout selected from the plurality of sensor array layouts, wherein the first sensor array layout satisfies a criterion, and one or more related sensor arrays are determined from the plurality of sensor array layouts a layout map, wherein each relevant sensor array layout map includes locations for sensor array layouts that do not overlap the sensor array layout locations for said first sensor array layout map, wherein each relevant sensor array layout map map satisfies the criteria, receives a selected second sensor array layout from the one or more associated sensor array layouts, and performs an analysis of the first sensor array layout and the second sensor array layout show.

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, and the power density associated with a simulated electric field distribution 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: The embodiment of any of Embodiments 11-12, further comprising generating composite data from the first sensor array layout diagram and the second sensor array layout diagram.

Embodiment 14: The embodiment of Embodiment 13, wherein the composite data includes information related to the first sensor array layout diagram and the second sensor array layout diagram, and the plurality of simulated A simulated electric field distribution in the electric field distribution associated with the first sensor array layout and the second sensor array layout.

Embodiment 15: The embodiment of any of Embodiments 11-14, wherein generating the 3D model comprises: causing one or more user devices to display a plurality of images of the portion of the subject's body, according to A region of interest (ROI) to receive one or more images selected from the plurality of images, and to generate the 3D model from the one or more images.

Embodiment 16: The embodiment of Embodiment 15, 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 image or images includes receiving the selected one or more images from a second user device of the one or more user devices.

Embodiment 17: The embodiment of any one of Embodiments 11-16, wherein determining the plurality of sensor array layout drawings comprises: determining, according to the 3D model, a plurality of pairs of positions for the sensor array layout, for the plurality of sensor array layouts. Each of the plurality of pairs of positions determines a simulated electric field distribution of 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 of Embodiment 17, wherein determining the simulated electric field distribution for each pair of positions of the plurality of positions comprises: simulating by a first sensor at a first position of the pair of positions a first electric field generated by the array, a second position at the pair of positions simulating a second electric field generated by a second sensor array, 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 comprising: generating a three-dimensional (3D) model of a portion of a 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 data from all a first sensor array layout diagram and a second sensor array layout diagram selected from the plurality of sensor array layout diagrams, determining an overlap condition according to the first sensor array layout diagram and the second sensor array layout diagram, and performing Display of the overlapping condition.

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 of the plurality of pairs of locations for the sensor array arrangement, wherein The overlapping condition is a position indicating that the first sensor array layout includes one or more pairs of the plurality of pairs of positions, which overlap a position of the plurality of pairs of positions associated with the second sensor array layout. or multiple pairs of locations.

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 a plurality of images of the anatomical volume should be used to generate the sensor array layout generating a model of the electrical characteristics of the anatomical volume based on the selected images; determining a plurality of sensor array layouts; evaluating from the generated model which of the determined sensor array layouts satisfy at least one criterion; presenting to the at least one user a plurality of sensor array layouts that satisfy the at least one criterion; accepting from the at least one user the sensor array layouts presented to the at least one user a selected one; 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: The embodiment of any of Embodiments 21-22, wherein generating the model comprises performing segmentation based on input received from the at least one user.

Embodiment 24: The embodiment of any one of Embodiments 21-23, wherein the at least one user is comprised of the first user and the second user, wherein the method further comprises (a) identifying the interested user from The first user of the area accepts an input, and (b) outputs data describing the area of interest to the second user.

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

Embodiment 26: The embodiment of any of Embodiments 21-25, wherein the at least one user includes a first user and a second user, wherein the method further comprises: identifying the substantially segmented A first user accepts an input; and outputs data describing the subsection to the second user.

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

Embodiment 28: The embodiment of any of Embodiments 21-27, wherein the at least one user includes a first user and a second user, wherein the method further comprises (a) using the first user the user accepts at least one note, and (b) outputs the at least one note to the second user.

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

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

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

Unless expressly stated otherwise, 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, where a method claim does not actually state an order in which its steps are to be followed, or where it is not otherwise expressly stated in the claim or description that the steps are limited to a particular order , and in no way intend to infer an order in any way. This applies to any possible unspecified basis for explanation, including: logical matters related to the configuration of steps or operational flow; ordinary meaning derived from grammatical organization or punctuation; the number of embodiments recited in the specification or type.

Although the methods and systems have been described in relation to preferred embodiments and specific examples, it is not intended that the scope be limited to the specific embodiments described, as the embodiments described herein are intended in all respects to be Illustrative, not limiting.

Unless expressly stated otherwise, 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, where a method claim does not actually state an order in which its steps are to be followed, or where it is not otherwise expressly stated in the claim or description that the steps are limited to a particular order , and in no way intend to infer an order in any way. This applies to any possible unspecified basis for explanation, including: logical matters related to the configuration of steps or operational flow; ordinary meaning derived from grammatical organization or punctuation; the number of embodiments recited in the specification or type.

It will be apparent to those skilled in the art that various modifications and changes can be made without departing from the scope or spirit of the description. 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 description and examples be regarded as exemplary only, the true scope and spirit of which is to be indicated by the following claims.

100: Equipment 102: Electric Field Generator 104, 104a, 104b: sensor arrays 106: Processor 108: Signal Generator 110: Control software 112: Conductive lead 114: output 116: Electrodes 118: circuit board 120, 120a, 120b: adhesive bandages 302: Skin Surface 304: Tumor 306: Bone tissue 308: Brain Tissue 310: Alternating Electric Field 600: System 602: Patient Support Systems 606: Electric Field Generator (EFG) Configuration Application 608: Build a 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: Web Interface 1018: Operating Systems 1020: User Devices 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: Windows 1108: Elements 1109: Area 1110: Interactive Elements 1111: Screen 1112: Interactive Elements 1113: Interactive Elements 1114: Screen 1115: Interactive Elements 1116: Area 1117: Area 1200: Method 1210: Steps 1220: Steps 1230: Steps 1240: Steps 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 the discussion of any particular element or act, the most significant digit or digits in an element symbol is referenced to the figure number in which the element is first introduced.

[FIG. 1] is an example apparatus showing a treatment for electrotherapy.

[FIG. 2] shows an example sensor array.

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

[FIG. 4] A is a diagram showing a sensor array arranged on a patient's head.

[FIG. 4]B shows the sensor array disposed on the abdomen of a patient.

[FIG. 5] A is a diagram showing a sensor array disposed on the torso of a patient.

[FIG. 5]B shows the sensor array disposed on the pelvis of a patient.

[FIG. 6] is a block diagram of a system for managing the arrangement of sensor arrays.

[FIG. 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 layout diagram 800 showing a three-dimensional array.

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

[FIG. 9]A shows an axial T1 sequence slice including the topmost image, which includes the track used to measure the head size.

[FIG. 9]B is an image showing a coronal T1 serial section selected to measure head size at the height of the ear canal.

[ FIG. 9 ] C is a post-contrast T1-axis image showing the maximum enhanced tumor diameter used to measure the tumor location.

[Fig. 9] D shows a post-contrast T1 coronal image showing the maximum enhanced tumor diameter used to measure the tumor location.

[FIG. 10] is a system showing an example for managing the arrangement of sensor arrays.

[FIG. 11] A to 11D show an example user interface for managing the arrangement of sensor arrays.

[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.

600: System

602: Patient Support Systems

606: Electric Field Generator (EFG) Configuration Application

608: Build a patient model application

610: Imaging data

Claims (60)

A method comprising: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; 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 of positions for the sensor array layout non-overlapping locations, wherein the at least two sensor array layouts satisfy a criterion; and A display of the one or more sets of sensor array layouts is performed. The method of claim 1, wherein said criterion includes a magnitude of a simulated electric field distribution of said plurality of simulated electric field distributions within a region of interest (ROI) associated with said 3D model, and A power density associated with one of the plurality of simulated electric field distributions within the ROI, and an estimate of skin toxicity associated with the portion of the subject's body. The method of claim 1, further comprising receiving a selected set of sensor array layouts from the one or more sets of sensor array layouts. The method of claim 3, further comprising generating composite data based on the selected set of sensor array layouts. 5. The method of claim 4, wherein said composite data includes information related to the selected set of sensor array layouts and said plurality of simulated electric field distributions related to the selected set of sensor array layouts The simulated electric field distribution. The method of claim 4, further comprising transmitting the composite data to a user device. The method of claim 1, wherein generating the 3D model comprises: causing one or more user devices to display a plurality of images of the portion of the subject's body; receiving one or more images selected from the plurality of images according to a region of interest (ROI); and The 3D model is generated from 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 comprises from a first user device of the one or more user devices 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 comprises: determining the plurality of pairs of positions for the sensor array arrangement according to the 3D model; for each pair of positions of the plurality of pairs of positions, determining a simulated electric field distribution of the plurality of simulated electric field distributions; and The plurality of sensor array layout diagrams are determined according to the plurality of simulated electric field distributions. The method of claim 9, wherein determining the simulated electric field distribution for each of the plurality of pairs of locations comprises: simulating a first electric field generated by the first sensor array at a first location of the pair of locations; Simulate 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 The simulated electric field distribution is determined according to the first electric field and the second electric field. A device comprising: one or more processors; and memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; 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 non-identical pairs of positions for the sensor array layout overlapping locations, wherein the at least two sensor array layouts meet a criterion; and A display of the one or more sets of sensor array layouts is performed. The apparatus of claim 11, wherein said criterion includes the magnitude of a simulated electric field distribution of said plurality of simulated electric field distributions within a region of interest (ROI) associated with said 3D model, and A power density associated with one of the plurality of simulated electric field distributions within the ROI, and an estimate of skin toxicity associated with the portion of the subject's body. The apparatus of claim 11, wherein the processor-executable instructions, when executed by the one or more processors, further cause the apparatus to receive a selection from the one or more sets of sensor array layouts A set of sensor array layout diagrams. The apparatus of claim 13, wherein said processor-executable instructions, when executed by said one or more processors, further cause said apparatus to generate composite data according to the selected set of sensor array layouts . The apparatus of claim 14, wherein said composite data includes information related to the selected set of sensor array layouts and said plurality of simulated electric field distributions related to the selected set of sensor array layouts The simulated electric field distribution. The apparatus of claim 14, wherein said processor-executable instructions, when executed by said one or more processors, further cause said apparatus to transmit said composite data to a user device. The apparatus of claim 11, wherein the processor-executable instructions, when executed by the one or more processors, cause the apparatus to generate the 3D model, which further causes the apparatus to: causing one or more user devices to display a plurality of images of the portion of the subject's body; receiving one or more images selected from the plurality of images according to a region of interest (ROI); and The 3D model is generated from the one or more images. 18. The apparatus of claim 17, wherein the processor-executable instructions, when executed by the one or more processors, further cause the apparatus to download the data from the first user of the one or more user devices The 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 11, wherein the processor-executable instructions, when executed by the one or more processors, cause the apparatus to determine the plurality of sensor array layouts, further causing the apparatus to: determining the plurality of pairs of positions for the sensor array arrangement according to the 3D model; determining, for each pair of positions of the plurality of pairs of positions, a simulated electric field distribution of the plurality of simulated electric field distributions; and The plurality of sensor array layout diagrams are determined according to the plurality of simulated electric field distributions. 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: simulating a first electric field generated by the first sensor array at a first location of the pair of locations; Simulate 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 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: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; 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 non-identical pairs of positions for the sensor array layout overlapping locations, wherein the at least two sensor array layouts meet a criterion; and A display of the one or more sets of sensor array layouts is performed. The non-transitory computer-readable medium of claim 21, wherein said criterion comprises the plurality of simulated electric field distributions within a region of interest (ROI) associated with said 3D model The magnitude of a simulated electric field distribution, the power density associated with a simulated electric field distribution of the plurality of simulated electric field distributions within the ROI, and the skin associated with the portion of the subject's body Estimation of toxicity. 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 selected set of sensor array layouts in the array layout. The non-transitory computer-readable medium of claim 23, wherein the processor coupled to the non-transitory computer-readable medium is further configured to arrange the sensor arrays according to the selected set graph to generate composite data. 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 of 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: causing one or more user devices to display a plurality of images of the portion of the subject's body; receiving one or more images selected from the plurality of images according to a region of interest (ROI); and The 3D model is generated from the one or more images. The non-transitory computer-readable medium of claim 27, wherein the processor coupled to the non-transitory computer-readable medium is further configured to retrieve 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 one or more images 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: determining the plurality of pairs of positions for the sensor array arrangement according to the 3D model; for each pair of positions of the plurality of pairs of positions, determining a simulated electric field distribution of the plurality of simulated electric field distributions; and The plurality of sensor array layout diagrams are determined according to 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 for each of the plurality of pairs of locations The simulated electric field distribution is determined for the position, which is further configured to: simulating a first electric field generated by the first sensor array at a first location of the pair of locations; Simulate 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 The simulated electric field distribution is determined according to the first electric field and the second electric field. A method comprising: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; receiving a selected first sensor array layout from the plurality of sensor array layouts, wherein the first sensor array layout satisfies a criterion; One or more related sensor array layouts are determined from the plurality of sensor array layouts, wherein each related sensor array layout includes a location for a sensor array layout that does not overlap for the first the location of the sensor array arrangement of the sensor array layout map, wherein each associated sensor array layout map satisfies the criteria; receiving a second sensor array layout map selected from the one or more associated sensor array layout maps; and The first sensor array layout diagram and the second sensor array layout diagram are displayed. The method of claim 31, wherein said criterion includes the magnitude of a simulated electric field distribution of said plurality of simulated electric field distributions within a region of interest (ROI) associated with said 3D model, and A power density associated with one of the plurality of simulated electric field distributions within the ROI, and an estimate of skin toxicity associated with the portion of the subject's body. The method of claim 31, further comprising generating composite data from the first sensor array layout and the second sensor array layout. 33. The method of claim 33, wherein said composite data includes information related to said first sensor array layout and said second sensor array layout, and one of said plurality of simulated electric field distributions related to said A first sensor array layout and a simulated electric field distribution associated with the second sensor array layout. The method of claim 31, wherein generating the 3D model comprises: causing one or more user devices to display a plurality of images of the portion of the subject's body; receiving one or more images selected from the plurality of images according to a region of interest (ROI); and The 3D model is generated from 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 comprises from a first user device of the one or more user devices 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 comprises: determining from the 3D model a plurality of pairs of positions for the sensor array arrangement; determining, for each pair of positions of the plurality of pairs of positions, a simulated electric field distribution of the plurality of simulated electric field distributions; and The plurality of sensor array layout diagrams are determined 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 locations comprises: simulating a first electric field generated by the first sensor array at a first location of the pair of locations; Simulate 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 The simulated electric field distribution is determined according to the first electric field and the second electric field. A device comprising: one or more processors; and memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; receiving a selected first sensor array layout from the plurality of sensor array layouts, wherein the first sensor array layout satisfies a criterion; One or more related sensor array layouts are determined from the plurality of sensor array layouts, wherein each related sensor array layout includes a location for a sensor array layout that does not overlap for the first sensor the location of the sensor array arrangement of the array layout, wherein each associated sensor array layout satisfies the criteria; receiving a second sensor array layout map selected from the one or more associated sensor array layout maps; and The first sensor array layout diagram and the second sensor array layout diagram are displayed. The apparatus of claim 39, wherein said criterion comprises the magnitude of a simulated electric field distribution of said plurality of simulated electric field distributions within a region of interest (ROI) associated with said 3D model, and A power density associated with one of the plurality of simulated electric field distributions within the ROI, and an estimate of skin toxicity associated with the portion of the subject's body. The apparatus of claim 39, wherein said processor-executable instructions, when executed by said one or more processors, further cause said apparatus to operate according to said first sensor array layout and said second sensor Array layout diagrams to generate composite data. The apparatus of claim 41, wherein said composite data includes information related to said first sensor array layout diagram and said second sensor array layout diagram, and one of said plurality of simulated electric field distributions related to said A first sensor array layout and a simulated electric field distribution associated with the second sensor array layout. The apparatus of claim 39, wherein the processor-executable instructions, when executed by the one or more processors, cause the apparatus to generate the 3D model, which further causes the apparatus to: causing one or more user devices to display a plurality of images of the portion of the subject's body; receiving one or more images selected from the plurality of images according to a region of interest (ROI); and The 3D model is generated from the one or more images. The apparatus of claim 43, wherein said processor-executable instructions, when executed by said one or more processors, further cause said apparatus from a first user of said one or more user devices The 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, which further cause the apparatus to: determining from the 3D model a plurality of pairs of positions for the sensor array arrangement; determining, for each pair of positions of the plurality of pairs of positions, a simulated electric field distribution of the plurality of simulated electric field distributions; and The plurality of sensor array layout diagrams are determined 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, which further enables the device to: simulating a first electric field generated by the first sensor array at a first location of the pair of locations; Simulate 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 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: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; receiving a selected first sensor array layout from the plurality of sensor array layouts, wherein the first sensor array layout satisfies a criterion; One or more related sensor array layouts are determined from the plurality of sensor array layouts, wherein each related sensor array layout includes a location for a sensor array layout that does not overlap for the first the location of the sensor array arrangement of the sensor array layout map, wherein each associated sensor array layout map satisfies the criteria; receiving a second sensor array layout map selected from the one or more associated sensor array layout maps; and The first sensor array layout diagram and the second sensor array layout diagram are displayed. The non-transitory computer-readable medium of claim 47, wherein said criterion comprises the plurality of simulated electric field distributions within a region of interest (ROI) associated with said 3D model The magnitude of a simulated electric field distribution, the power density associated with a simulated electric field distribution of the plurality of simulated electric field distributions within the ROI, and the skin associated with the portion of the subject's body Estimation of toxicity. The non-transitory computer-readable medium of claim 47, wherein the non-transitory computer-readable medium is further configured to layout according to the first sensor array layout 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 diagram and the second sensor array layout diagram 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: causing one or more user devices to display a plurality of images of the portion of the subject's body; receiving one or more images selected from the plurality of images according to a region of interest (ROI); and The 3D model is generated from the one or more images. 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 with the ROI-related information, 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. The non-transitory computer-readable medium of claim 47, wherein the non-transitory computer-readable medium configured to determine the plurality of sensor array layouts is further configured to: determining from the 3D model a plurality of pairs of positions for the sensor array arrangement; determining, for each pair of positions of the plurality of pairs of positions, a simulated electric field distribution of the plurality of simulated electric field distributions; and The plurality of sensor array layout diagrams are determined according to the plurality of simulated electric field distributions. The non-transitory computer-readable medium of claim 53, wherein the non-transitory computer-readable medium configured to determine the simulated electric field distribution for each of the plurality of pairs of locations The fetched media is further configured with: simulating a first electric field generated by the first sensor array at a first location of the pair of locations; Simulate 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 The simulated electric field distribution is determined according to the first electric field and the second electric field. A method comprising: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; receiving a first sensor array layout and a second sensor array layout selected from the plurality of sensor array layouts; determining an overlap condition according to the first sensor array layout diagram and the second sensor array layout diagram; and The display of the overlapping status is performed. The method of claim 55, wherein each sensor array layout of the plurality of sensor array layouts includes locations for one or more pairs of pairs of locations for a sensor array arrangement, wherein the overlapping condition indicates the The first sensor array layout includes one or more pairs of the plurality of pairs of positions that overlap one or more pairs of the plurality of pairs of positions associated with the second sensor array layout. A device comprising: one or more processors; and memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; receiving a first sensor array layout and a second sensor array layout selected from the plurality of sensor array layouts; determining an overlap condition according to the first sensor array layout diagram and the second sensor array layout diagram; and The display of the overlapping status is performed. The apparatus of claim 57, wherein each sensor array layout of the plurality of sensor array layouts includes one or more pairs of locations for a plurality of pairs of locations for a sensor array arrangement, wherein the overlapping condition indicates that the The first sensor array layout includes one or more pairs of the plurality of pairs of positions that overlap one or more pairs of the plurality of pairs of positions associated with the second sensor array layout. A non-transitory computer-readable medium configured to store information, wherein: A processor coupled to the non-transitory computer-readable medium is configured to: generating a three-dimensional (3D) model of a portion of the body of an object; determining a plurality of sensor array layout diagrams according to the 3D model and a plurality of simulated electric field distributions; receiving a first sensor array layout and a second sensor array layout selected from the plurality of sensor array layouts; determining an overlap condition according to the first sensor array layout diagram and the second sensor array layout diagram; and The display of the overlapping status is performed. The non-transitory computer-readable medium of claim 59, wherein each sensor array layout of the plurality of sensor array layouts includes one or more pairs of locations for the plurality of pairs of locations for the 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 that overlap the plurality of pairs of positions associated with the second sensor array layout One or more pairs of locations.

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