EP4780538A1

EP4780538A1 - Positioning and tracking a radiation treatment bolus

Info

Publication number: EP4780538A1
Application number: EP23777168.8A
Authority: EP
Inventors: Kajetan Berlinger; Philipp FREISLEDERER
Original assignee: Brainlab SE
Current assignee: Brainlab SE
Priority date: 2023-09-21
Filing date: 2023-09-21
Publication date: 2026-07-29
Also published as: WO2025061283A1

Abstract

Disclosed is a computer-implemented method of determining the position of a radiation treatment bolus. The disclosed method encompasses acquisition of a planning image of a bolus and of a live surface image of the bolus. The planning image describes both a surface (i.e. outer contour or outer contour surface) and a position of the surface of the bolus. In preparation of radiation treatment, the bolus is positioned so that a difference between the planned position of the bolus and the position of the bolus determined from the live image are at last substantially identical. The disclosed method encompasses also a method for positioning, together with the bolus, a patient and a method for monitoring the position of the patient and the bolus in preparation for radiation treatment, which are both based on acquiring live surface images of the patient and the bolus.

Description

POSITIONING AND TRACKING A RADIATION TREATMENT BOLUS

FIELD OF THE INVENTION

The present invention relates to a computer-implemented method of determining the position of a radiation treatment bolus, a corresponding computer program, a computer-readable storage medium storing such a program and a computer executing the program, as well as a medical system comprising an electronic data storage device and the aforementioned computer.

TECHNICAL BACKGROUND

A bolus is used in radiation treatment (radiotherapy) to the increase of surface dose when having a radiotherapy target close to the surface. In most cases, the bolus is a sheet of tissue equivalent material (e.g. silicon) with a thickness of about 5 mm. A bolus is used for daily treatments for e.g. mastectomised patients, and typically covers the surgical scar. Typically, the bolus is not scanned when generating the computed X-ray tomography planning image of the patient but is virtually added in the treatment planning software. When it comes to treatment, a physical equivalent to the virtual bolus has to be available and has to be placed on the patient in planned position, in order to get the planned dosimetric effect. For positioning the bolus on the patient, clinical staff have so far been working with markings applied to the patient’s skin e.g. using a pen which is associated with high degree of imprecision.

The present invention has the object of providing improved means for positioning a bolus in preparation of radiation treatment. The present invention can be used for procedures e.g. in connection with a system for image-guided radiotherapy such as VERO® and ExacTrac Dynamic®, both products of Brainlab AG.

Aspects of the present invention, examples and exemplary steps and their embodiments are disclosed in the following. Different exemplary features of the invention can be combined in accordance with the invention wherever technically expedient and feasible.

EXEMPLARY SHORT DESCRIPTION OF THE INVENTION

In the following, a short description of the specific features of the present invention is given which shall not be understood to limit the invention only to the features or a combination of the features described in this section.

The disclosed method encompasses acquisition of a planning image of a bolus and of a live surface image of the bolus. The planning image describes both a surface (i.e. outer contour or outer contour surface) and a position of the surface of the bolus. In preparation of radiation treatment, the bolus is positioned so that a difference between the planned position of the bolus and the position of the bolus determined from the live image are at last substantially identical. The disclosed method encompasses also a method for positioning, together with the bolus, a patient and a method for monitoring the position of the patient and the bolus in preparation for radiation treatment, which are both based on acquiring live surface images of the patient and the bolus.

GENERAL DESCRIPTION OF THE INVENTION

In this section, a description of the general features of the present invention is given for example by referring to possible embodiments of the invention.

In general, the invention reaches the aforementioned object by providing, in a first aspect, a computer-implemented medical method of determining the position of a radiation treatment bolus. The method comprises executing, on at least one processor of at least one computer (for example at least one computer being part of a navigation system), the following exemplary steps which are executed by the at least one processor.

In a (for example first) exemplary step, bolus planning image data is acquired which describes a digital planning image representation of the bolus and a planned position of the bolus. The representation of the bolus may be a planning (i.e. virtual) representation, i.e. a digital model of a bolus (for example, constructional data or a representation of the surface of the bolus in thermal image values for example at a predetermined temperature such as room temperature), or have been generated from image data generated by imaging a real bolus with an imaging method such as computed X-ray tomography or magnetic resonance tomography or thermal imaging (for example at a predetermined temperature such as room temperature). The position of the bolus is defined for example relative to anatomical body part of the patient, for example an anatomical body part on which the bolus shall be placed, and/or in an reference system in which positions for conducting the radiation treatment to be planned and conducted using the bolus are defined, and in which for example also the position of the anatomical body part is defined.

A bolus is a device which attenuates treatment radiation and is generally placed on a patient’s body in place of a resected body part, for example part of the breast after breast cancer surgery, and/or on the patient’s skin to allow for radiation treatment of an anatomical body part lying inside the body close to the skin surface. The bolus increases the distance over which the treatment radiation can interact with matter with a certain probability compared to a situation in which the bolus is not used, the probability of interaction depending on the distance in matter travelled by the treatment radiation. The bolus therefore increases the probability with which the treatment radiation interacts with the patient’s body so that a maximum of radiation dose can be delivered to body parts lying just below the skin surface, for example residual tumour tissue after breast cancer surgery, e.g. mastectomy. The bolus is for example made of a material which has properties equivalent to body tissue when irradiated with treatment radiation. The bolus is mouldable to fill the missing tissue space. Certain types of bolus are loosely packed in polyethylene bags, which is suitable as the bolus bags take the shape of the skin surface these bags are easily smoothed to achieve a flat surface. The bolus material should be pliable and easily moulded to the skin surface but retain a constant thickness. One example of such a material is paraffin gauze.

In a (for example second) exemplary step, bolus surface data is acquired which describes an actual position of a surface of the bolus. The bolus surface data has been generated for example using a surface imaging technique for imaging the real bolus, for example by imaging it with a surface camera, for example a stereoscopic surface camera, or a laser scanner, or a thermal camera (for example at substantially the same predetermined temperature such as substantially room temperature used for generating the bolus planning image data). When this imaging is conducted, the bolus has been placed at least substantially at the desired position on the patient’s body.

In a (for example third) exemplary step, bolus position data is determined based on the planning image data and the bolus surface data, wherein the bolus position data describes a difference between the planned position and the actual position of the bolus. For example, the bolus surface data describes an image representation of the surface of the bolus and the bolus position data is determined by matching a representation of the surface of the bolus extracted from the bolus planning image data with the image representation of the bolus, i.e. mapping the representation of the surface of the bolus extracted from the bolus planning image data onto the image representation of the bolus

In an example of the method according to the first aspect, body part planning image data is acquired which describes a digital planning image of an anatomical body part of a patient and a planned position of the anatomical body part, and patient surface data is acquired which describes an actual position of a surface of the anatomical body part. The body part planning image data has been generated from image data generated by imaging anatomical body part with an imaging method such as computed X-ray tomography or magnetic resonance tomography or thermal imaging, and preferably by using the same imaging modality as for generating the bolus planning image data (however, a combination of different imaging modalities is also within the framework of the present disclosure). If thermal imaging is used for generating the body part planning image data, the position of the anatomical body part is indicated by parts of the image defined by a body temperature value. For example, the patient surface data describes an image representation of the surface of the anatomical body part and wherein the body part position data is determined by matching a representation of the surface of the anatomical body part extracted from the body part planning image data with the image representation of the surface of the anatomical body part, i.e. by mapping representation of the surface of the anatomical body part extracted from the body part planning image data onto the image representation of the surface of the anatomical body part. Body part position data is then determined based on the planning image data and the patient surface data. The body part position data describes a difference between the planned position and the actual position of the surface of the anatomical body part. To that end, the planned position of the surface of the anatomical body part is extracted from the data describing the planned position of the anatomical body part, and then used as an input for determining the aforementioned difference. For example, the patient surface data is generated by a surface-generating device, for example a surface camera or a laser scanner or a thermal camera (the position of the surface of the anatomical body part is then indicated by parts of the image defined by a body temperature value). For example, the difference between the planned position and the actual position of the surface of the anatomical body part and the planned position and the actual position of the surface of the anatomical body part is described by a positional transformation between the planned position and the actual position of the surface of the anatomical body part and the planned position and the actual position of the surface of the anatomical body part. For example, the difference between the planned position and the actual position of the bolus is described by at least one of a positional transformation between the planned position and the actual position of the bolus or a visual, for example colour- coded, rendering of the difference.

The method according to the first aspect includes for example, as far as it includes acquiring the body part planning image data and the patient surface data and determining the body part position data, determining, based on the body part position data, body part control data describing at least one control signal for controlling a patient positioning device to move the anatomical body part to its planed position. The method according to the first aspect then for example comprises issuing the body part control data to the patient positioning device. The method according to the first aspect includes for example determining, based on the bolus position data, bolus control data describing at least one control signal for controlling a patient positioning device to move the bolus to its planned position. The method according to the first aspect then for example comprises for example issuing the bolus control data to the patient positioning device, for example to move the bolus to its planned position.

For example, the method according to the first aspect includes determining, based on the bolus surface data, expected actual dose data describing an expected dose of treatment radiation to an anatomical body part of the patient if the anatomical body part is irradiated with the treatment radiation while the bolus is at its actual position, for example irrespective of the alignment of the bolus to the planned position of the bolus. For example, planned dose data is acquired which describes a planned dose of treatment radiation to the anatomical body part, and for example the bolus control data is determined based on the expected actual dose data and the planned dose data. For example, a value of a threshold for a difference between the planned and the expected dose is acquired, the difference between the planned and the expected dose is determined and compared to the value its threshold, and the bolus control data is determined on the basis of result of that comparison, for example by determining whether a predetermined relationship between the difference and the value of the threshold is fulfilled.

For example, the method according to the first aspect includes acquiring bolus difference threshold data describing a value of a threshold for the difference between the planned position and the actual position of the bolus, and determining, based on the bolus position data and the bolus difference threshold data (for example, if a predetermined relationship between the difference and the value of the threshold is fulfilled), irradiation control data for controlling a beam of treatment radiation, for example at least one of issue and position of the beam. This allows controlling the treatment beam in dependence of the position of the bolus.

For example, the method according to the first aspect includes acquiring body part difference threshold data describing a value of a threshold for the difference between the planned position and the actual position of the anatomical body part, and determining, based on the body part position data and the body part difference threshold data (for example, if a predetermined relationship between the difference and the value of the threshold is fulfilled), irradiation control data for controlling a beam of treatment radiation, for example at least one of issue and position of the treatment beam. This allows controlling the treatment beam in dependence of the position of the anatomical body part, i.e. the patient.

For example, the method according to the first aspect includes acquiring bolus body part difference threshold data describing a value of a threshold for the difference between the combined planned positions and the combined actual positions of the anatomical body part and the bolus (i.e. the combined planned and actual outer contours of the surface of the anatomical body part and the surface of the bolus), i.e. a difference between the set of the planned positions of the anatomical body part and the bolus and the set of the actual position of the anatomical body part and the bolus. Then, irradiation control data for controlling a beam of treatment radiation (for example at least one of issue and position of the treatment beam) is of example determined based on the patient surface data and the body part planning image data and the bolus planning image data and the bolus body part difference threshold data. This supports correct determination of the patient position in case a difference between the combined surface of the bolus and the anatomical body part deviate from the planned position of the combined surface of the anatomical body part and the bolus to such an extent that at least part of the surface of the bolus imaged during generation of the patient surface data is interpreted as part of the surface of the anatomical body part, i.e. in case the patient surface data accidentally describes a representation of at least part of the surface of the bolus. Also, a deviation between the actual relative position between the anatomical body part and the bolus and the planned relative position between the anatomical body part and the bolus can be taken into account for controlling the treatment beam.

In a second aspect, the invention is directed to a computer program comprising instructions which, when the program is executed by at least one computer, causes the at least one computer to carry out method according to the first aspect. The invention may alternatively or additionally relate to a (physical, for example electrical, for example technically generated) signal wave, for example a digital signal wave, such as an electromagnetic carrier wave carrying information which represents the program, for example the aforementioned program, which for example comprises code means which are adapted to perform any or all of the steps of the method according to the first aspect. The signal wave is in one example a data carrier signal carrying the aforementioned computer program. A computer program stored on a disc is a data file, and when the file is read out and transmitted it becomes a data stream for example in the form of a (physical, for example electrical, for example technically generated) signal. The signal can be implemented as the signal wave, for example as the electromagnetic carrier wave which is described herein. For example, the signal, for example the signal wave is constituted to be transmitted via a computer network, for example LAN, WLAN, WAN, mobile network, for example the internet. For example, the signal, for example the signal wave, is constituted to be transmitted by optic or acoustic data transmission. The invention according to the second aspect therefore may alternatively or additionally relate to a data stream representative of the aforementioned program, i.e. comprising the program.

In a third aspect, the invention is directed to a computer-readable storage medium on which the program according to the second aspect is stored. The program storage medium is for example non-transitory.

In a fourth aspect, the invention is directed to at least one computer (for example, a computer), comprising at least one processor (for example, a processor), wherein the program according to the second aspect is executed by the processor, or wherein the at least one computer comprises the computer-readable storage medium according to the third aspect.

In a fifth aspect, the invention is directed a medical system, comprising: a) the at least one computer according to the fourth aspect, wherein the instructions, when the program is executed by the computer, cause the computer to determine the bolus control data or the body part control data; and b) a patient positioning device (e.g. a movable and controllably motorized couch) for positioning the patient for radiation treatment, wherein the at least one computer is operably coupled to the patient positioning device for issuing the control signal to the patient positioning device for controlling the operation of the patient positioning device on the basis of the at least one control signal.

In an example, the system according to the fifth aspect, comprises a radiation treatment device for issuing a beam of treatment radiation, wherein for example the instructions, when the program is executed by the computer, cause the computer to determine the irradiation control data and the radiation treatment device is configured to be controlled based on the irradiation control data.

DEFINITIONS

In this section, definitions for specific terminology used in this disclosure are offered which also form part of the present disclosure.

The method in accordance with the invention is for example a computer-implemented method. For example, all the steps or merely some of the steps (i.e. less than the total number of steps) of the method in accordance with the invention can be executed by a computer (for example, at least one computer). An embodiment of the computer implemented method is a use of the computer for performing a data processing method. An embodiment of the computer implemented method is a method concerning the operation of the computer such that the computer is operated to perform one, more or all steps of the method.

The computer for example comprises at least one processor and for example at least one memory in order to (technically) process the data, for example electronically and/or optically. The processor being for example made of a substance or composition which is a semiconductor, for example at least partly n- and/or p-doped semiconductor, for example at least one of II-, III-, IV-, V-, Vl-sem iconductor material, for example (doped) silicon and/or gallium arsenide. The calculating or determining steps described are for example performed by a computer. Determining steps or calculating steps are for example steps of determining data within the framework of the technical method, for example within the framework of a program. A computer is for example any kind of data processing device, for example electronic data processing device. A computer can be a device which is generally thought of as such, for example desktop PCs, notebooks, netbooks, etc., but can also be any programmable apparatus, such as for example a mobile phone or an embedded processor. A computer can for example comprise a system (network) of "sub-computers", wherein each sub-computer represents a computer in its own right. The term "computer" includes a cloud computer, for example a cloud server. The term computer includes a server resource. The term "cloud computer" includes a cloud computer system which for example comprises a system of at least one cloud computer and for example a plurality of operatively interconnected cloud computers such as a server farm. Such a cloud computer is preferably connected to a wide area network such as the world wide web (WWW) and located in a so-called cloud of computers which are all connected to the world wide web. Such an infrastructure is used for "cloud computing", which describes computation, software, data access and storage services which do not require the end user to know the physical location and/or configuration of the computer delivering a specific service. For example, the term "cloud" is used in this respect as a metaphor for the Internet (world wide web). For example, the cloud provides computing infrastructure as a service (laaS). The cloud computer can function as a virtual host for an operating system and/or data processing application which is used to execute the method of the invention. The cloud computer is for example an elastic compute cloud (EC2) as provided by Amazon Web Services™. A computer for example comprises interfaces in order to receive or output data and/or perform an analogue-to-digital conversion. The data are for example data which represent physical properties and/or which are generated from technical signals. The technical signals are for example generated by means of (technical) detection devices (such as for example devices for detecting marker devices) and/or (technical) analytical devices (such as for example devices for performing (medical) imaging methods), wherein the technical signals are for example electrical or optical signals. The technical signals for example represent the data received or outputted by the computer. The computer is preferably operatively coupled to a display device which allows information outputted by the computer to be displayed, for example to a user. One example of a display device is a virtual reality device or an augmented reality device (also referred to as virtual reality glasses or augmented reality glasses) which can be used as "goggles" for navigating. A specific example of such augmented reality glasses is Google Glass (a trademark of Google, Inc.). An augmented reality device or a virtual reality device can be used both to input information into the computer by user interaction and to display information outputted by the computer. Another example of a display device would be a standard computer monitor comprising for example a liquid crystal display operatively coupled to the computer for receiving display control data from the computer for generating signals used to display image information content on the display device. A specific embodiment of such a computer monitor is a digital lightbox. An example of such a digital lightbox is Buzz®, a product of Brainlab AG. The monitor may also be the monitor of a portable, for example handheld, device such as a smart phone or personal digital assistant or digital media player.

The invention also relates to a computer program comprising instructions which, when on the program is executed by a computer, cause the computer to carry out the method or methods, for example, the steps of the method or methods, described herein and/or to a computer-readable storage medium (for example, a non-transitory computer- readable storage medium) on which the program is stored and/or to a computer comprising said program storage medium and/or to a (physical, for example electrical, for example technically generated) signal wave, for example a digital signal wave, such as an electromagnetic carrier wave carrying information which represents the program, for example the aforementioned program, which for example comprises code means which are adapted to perform any or all of the method steps described herein. The signal wave is in one example a data carrier signal carrying the aforementioned computer program. The invention also relates to a computer comprising at least one processor and/or the aforementioned computer-readable storage medium and for example a memory, wherein the program is executed by the processor.

Within the framework of the invention, computer program elements can be embodied by hardware and/or software (this includes firmware, resident software, micro-code, etc.). Within the framework of the invention, computer program elements can take the form of a computer program product which can be embodied by a computer-usable, for example computer-readable data storage medium comprising computer-usable, for example computer-readable program instructions, "code" or a "computer program" embodied in said data storage medium for use on or in connection with the instructionexecuting system. Such a system can be a computer; a computer can be a data processing device comprising means for executing the computer program elements and/or the program in accordance with the invention, for example a data processing device comprising a digital processor (central processing unit or CPU) which executes the computer program elements, and optionally a volatile memory (for example a random access memory or RAM) for storing data used for and/or produced by executing the computer program elements. Within the framework of the present invention, a computer-usable, for example computer-readable data storage medium can be any data storage medium which can include, store, communicate, propagate or transport the program for use on or in connection with the instruction-executing system, apparatus or device. The computer-usable, for example computer-readable data storage medium can for example be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared or semiconductor system, apparatus or device or a medium of propagation such as for example the Internet. The computer-usable or computer-readable data storage medium could even for example be paper or another suitable medium onto which the program is printed, since the program could be electronically captured, for example by optically scanning the paper or other suitable medium, and then compiled, interpreted or otherwise processed in a suitable manner. The data storage medium is preferably a non-volatile data storage medium. The computer program product and any software and/or hardware described here form the various means for performing the functions of the invention in the example embodiments. The computer and/or data processing device can for example include a guidance information device which includes means for outputting guidance information. The guidance information can be outputted, for example to a user, visually by a visual indicating means (for example, a monitor and/or a lamp) and/or acoustically by an acoustic indicating means (for example, a loudspeaker and/or a digital speech output device) and/or tactilely by a tactile indicating means (for example, a vibrating element or a vibration element incorporated into an instrument). For the purpose of this document, a computer is a technical computer which for example comprises technical, for example tangible components, for example mechanical and/or electronic components. Any device mentioned as such in this document is a technical and for example tangible device.

The expression "acquiring data" for example encompasses (within the framework of a computer implemented method) the scenario in which the data are determined by the computer implemented method or program. Determining data for example encompasses measuring physical quantities and transforming the measured values into data, for example digital data, and/or computing (and e.g. outputting) the data by means of a computer and for example within the framework of the method in accordance with the invention. A step of “determining” as described herein for example comprises or consists of issuing a command to perform the determination described herein. For example, the step comprises or consists of issuing a command to cause a computer, for example a remote computer, for example a remote server, for example in the cloud, to perform the determination. Alternatively or additionally, a step of “determination” as described herein for example comprises or consists of receiving the data resulting from the determination described herein, for example receiving the resulting data from the remote computer, for example from that remote computer which has been caused to perform the determination. The meaning of "acquiring data" also for example encompasses the scenario in which the data are received or retrieved by (e.g. input to) the computer implemented method or program, for example from another program, a previous method step or a data storage medium, for example for further processing by the computer implemented method or program. Generation of the data to be acquired may but need not be part of the method in accordance with the invention. The expression "acquiring data" can therefore also for example mean waiting to receive data and/or receiving the data. The received data can for example be inputted via an interface. The expression "acquiring data" can also mean that the computer implemented method or program performs steps in order to (actively) receive or retrieve the data from a data source, for instance a data storage medium (such as for example a ROM, RAM, database, hard drive, etc.), or via the interface (for instance, from another computer or a network). The data acquired by the disclosed method or device, respectively, may be acquired from a database located in a data storage device which is operably to a computer for data transfer between the database and the computer, for example from the database to the computer. The computer acquires the data for use as an input for steps of determining data. The determined data can be output again to the same or another database to be stored for later use. The database or database used for implementing the disclosed method can be located on network data storage device or a network server (for example, a cloud data storage device or a cloud server) or a local data storage device (such as a mass storage device operably connected to at least one computer executing the disclosed method). The data can be made "ready for use" by performing an additional step before the acquiring step. In accordance with this additional step, the data are generated in order to be acquired. The data are for example detected or captured (for example by an analytical device). Alternatively or additionally, the data are inputted in accordance with the additional step, for instance via interfaces. The data generated can for example be inputted (for instance into the computer). In accordance with the additional step (which precedes the acquiring step), the data can also be provided by performing the additional step of storing the data in a data storage medium (such as for example a ROM, RAM, CD and/or hard drive), such that they are ready for use within the framework of the method or program in accordance with the invention. The step of "acquiring data" can therefore also involve commanding a device to obtain and/or provide the data to be acquired. In particular, the acquiring step does not involve an invasive step which would represent a substantial physical interference with the body, requiring professional medical expertise to be carried out and entailing a substantial health risk even when carried out with the required professional care and expertise. In particular, the step of acquiring data, for example determining data, does not involve a surgical step and in particular does not involve a step of treating a human or animal body using surgery or therapy. In order to distinguish the different data used by the present method, the data are denoted (i.e. referred to) as "XY data" and the like and are defined in terms of the information which they describe, which is then preferably referred to as "XY information" and the like.

In the field of medicine, imaging methods (also called imaging modalities and/or medical imaging modalities) are used to generate image data (for example, two- dimensional or three-dimensional image data) of anatomical structures (such as soft tissues, bones, organs, etc.) of the human body. The term "medical imaging methods" is understood to mean (advantageously apparatus-based) imaging methods (for example so-called medical imaging modalities and/or radiological imaging methods) such as for instance computed tomography (CT) and cone beam computed tomography (CBCT, such as volumetric CBCT), X-ray tomography, magnetic resonance tomography (MRT or MRI), conventional X-ray, sonography and/or ultrasound examinations, and positron emission tomography. For example, the medical imaging methods are performed by the analytical devices. Examples for medical imaging modalities applied by medical imaging methods are: X-ray radiography, magnetic resonance imaging, medical ultrasonography or ultrasound, endoscopy, elastography, tactile imaging, thermography, medical photography and nuclear medicine functional imaging techniques as positron emission tomography (PET) and Single-photon emission computed tomography (SPECT), as mentioned by Wikipedia. The image data thus generated is also termed “medical imaging data”. Analytical devices for example are used to generate the image data in apparatusbased imaging methods. The imaging methods are for example used for medical diagnostics, to analyse the anatomical body in order to generate images which are described by the image data. The imaging methods are also for example used to detect pathological changes in the human body. However, some of the changes in the anatomical structure, such as the pathological changes in the structures (tissue), may not be detectable and for example may not be visible in the images generated by the imaging methods. A tumour represents an example of a change in an anatomical structure. If the tumour grows, it may then be said to represent an expanded anatomical structure. This expanded anatomical structure may not be detectable; for example, only a part of the expanded anatomical structure may be detectable. Primary/high- grade brain tumours are for example usually visible on MRI scans when contrast agents are used to infiltrate the tumour. MRI scans represent an example of an imaging method. In the case of MRI scans of such brain tumours, the signal enhancement in the MRI images (due to the contrast agents infiltrating the tumour) is considered to represent the solid tumour mass. Thus, the tumour is detectable and for example discernible in the image generated by the imaging method. In addition to these tumours, referred to as "enhancing" tumours, it is thought that approximately 10% of brain tumours are not discernible on a scan and are for example not visible to a user looking at the images generated by the imaging method.

Mapping describes a transformation (for example, linear transformation) of an element (for example, a pixel or voxel), for example the position of an element, of a first data set in a first coordinate system to an element (for example, a pixel or voxel), for example the position of an element, of a second data set in a second coordinate system (which may have a basis which is different from the basis of the first coordinate system). In one embodiment, the mapping is determined by comparing (for example, matching) the color values (for example grey values) of the respective elements by means of an elastic or rigid fusion algorithm. The mapping is embodied for example by a transformation matrix (such as a matrix defining an affine transformation).

Image fusion can be elastic image fusion or rigid image fusion. In the case of rigid image fusion, the relative position between the pixels of a 2D image and/or voxels of a 3D image is fixed, while in the case of elastic image fusion, the relative positions are allowed to change.

In this application, the term "image morphing" is also used as an alternative to the term "elastic image fusion", but with the same meaning.

Elastic fusion transformations (for example, elastic image fusion transformations) are for example designed to enable a seamless transition from one dataset (for example a first dataset such as for example a first image) to another dataset (for example a second dataset such as for example a second image). The transformation is for example designed such that one of the first and second datasets (images) is deformed, for example in such a way that corresponding structures (for example, corresponding image elements) are arranged at the same position as in the other of the first and second images. The deformed (transformed) image which is transformed from one of the first and second images is for example as similar as possible to the other of the first and second images. Preferably, (numerical) optimisation algorithms are applied in order to find the transformation which results in an optimum degree of similarity. The degree of similarity is preferably measured by way of a measure of similarity (also referred to in the following as a "similarity measure"). The parameters of the optimisation algorithm are for example vectors of a deformation field. These vectors are determined by the optimisation algorithm in such a way as to result in an optimum degree of similarity. Thus, the optimum degree of similarity represents a condition, for example a constraint, for the optimisation algorithm. The bases of the vectors lie for example at voxel positions of one of the first and second images which is to be transformed, and the tips of the vectors lie at the corresponding voxel positions in the transformed image. A plurality of these vectors is preferably provided, for instance more than twenty or a hundred or a thousand or ten thousand, etc. Preferably, there are (other) constraints on the transformation (deformation), for example in order to avoid pathological deformations (for instance, all the voxels being shifted to the same position by the transformation). These constraints include for example the constraint that the transformation is regular, which for example means that a Jacobian determinant calculated from a matrix of the deformation field (for example, the vector field) is larger than zero, and also the constraint that the transformed (deformed) image is not self-intersecting and for example that the transformed (deformed) image does not comprise faults and/or ruptures. The constraints include for example the constraint that if a regular grid is transformed simultaneously with the image and in a corresponding manner, the grid is not allowed to interfold at any of its locations. The optimising problem is for example solved iteratively, for example by means of an optimisation algorithm which is for example a first-order optimisation algorithm, such as a gradient descent algorithm. Other examples of optimisation algorithms include optimisation algorithms which do not use derivations, such as the downhill simplex algorithm, or algorithms which use higher-order derivatives such as Newton-like algorithms. The optimisation algorithm preferably performs a local optimisation. If there is a plurality of local optima, global algorithms such as simulated annealing or generic algorithms can be used. In the case of linear optimisation problems, the simplex method can for instance be used.

In the steps of the optimisation algorithms, the voxels are for example shifted by a magnitude in a direction such that the degree of similarity is increased. This magnitude is preferably less than a predefined limit, for instance less than one tenth or one hundredth or one thousandth of the diameter of the image, and for example about equal to or less than the distance between neighbouring voxels. Large deformations can be implemented, for example due to a high number of (iteration) steps.

The determined elastic fusion transformation can for example be used to determine a degree of similarity (or similarity measure, see above) between the first and second datasets (first and second images). To this end, the deviation between the elastic fusion transformation and an identity transformation is determined. The degree of deviation can for instance be calculated by determining the difference between the determinant of the elastic fusion transformation and the identity transformation. The higher the deviation, the lower the similarity, hence the degree of deviation can be used to determine a measure of similarity. A measure of similarity can for example be determined on the basis of a determined correlation between the first and second datasets.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following, the invention is described with reference to the appended figures which give background explanations and represent specific embodiments of the invention. The scope of the invention is however not limited to the specific features disclosed in the context of the figures, wherein

Fig. 1 illustrates the basic steps of the method according to the first aspect;

Fig. 2 shows an embodiment of the present invention, specifically the method according to the first aspect;

Fig. 3 is a flow diagram in which the method according to the first aspect is used for positioning a patient and a bolus in preparation for radiation treatment;

Fig. 4 is a flow diagram in which the method according to the first aspect is used for monitoring the position of the patient;

Fig. 5 is a schematic illustration of the system according to the fifth aspect; and

Fig. 6 shows placement of a bolus on an anatomical body part.

DESCRIPTION OF EMBODIMENTS

Fig. 1 illustrates the basic steps of the method according to the first aspect, in which step S11 encompasses acquisition of the bolus planning image data, step S12 encompasses acquisition of the bolus surface data, and subsequent step S13 encompasses determination of the bolus position data.

Fig. 2 illustrates an embodiment of the present invention that includes all essential features of the invention. In this embodiment, the entire data processing which is part of the method according to the first aspect is performed by a computer 2. Reference sign 1 denotes the input of data acquired by the method according to the first aspect into the computer 2 and reference sign 3 denotes the output of data determined by the method according to the first aspect.

Fig. 3 shows an example of using the method according to the first aspect for positioning a patient and a bolus in preparation for radiation treatment. In step S31 , the patient is placed on a couch of a radiation treatment device. Step S32 continues with determining that the patient and the bolus are each not positionally aligned to the planning. In step S33, the camera observing the patient generates a live image of the surface of the patient’s body, corresponding to acquisition of the patient surface data. In step S35, this live image is compared by surface matching to a reference surface of an anatomical body part of the patient available from the boy part planning image data to determine the difference between the planned position and the actual position of the surface of the anatomical body part described by the body part position data and called Transformation_1 . In step S36, body part control data is determined and by executing the body part control data, Transform ation_1 is applied to the couch. In step S37 it is then determined that the patient is aligned with the planned position of the anatomical body part and that the bolus is not aligned with its planned position. In step S38, the bolus is initially placed on the patient, and the reference for further positioning is set to the planned position of the surface of the bolus in step S39. In step S311 , surface matching is conducted between a live image of the surface of the bolus and the planned position of the surface of the bolus to determine Transform ation_2 corresponding to the difference between the planned position and the actual position of the bolus stored as the bolus position data. In optionally simultaneously executed step S312, a colour-coded distance surface view can be presented to the operator on a display device visually indicating the difference between the planned position and the actual position of the bolus stored as the bolus position data. In step S313, the operator optimizes the position of the bolus by re-positioning it on the patient until Transformation_2 reaches at least substantially identity and, if optionally displayed, the colour-coded live surface is displayed in green colour meaning that the patient is in place in accordance with the planning. In step S314, it is then determined that both the patient and the bolus are aligned. Fig. 4 illustrates use of the method according to the first aspect for monitoring the position of the patient and the bolus. In step S41 , the patient is placed on the couch with bolus placed on the patient. In step S42, it is determined that the positions of both the patient and the bolus are aligned with the planning, for example by executing the flow diagram shown in Fig. 3. In step S43, the reference for determining the alignment of the patient and the bolus is called ReferenceSurface_1 and set to the combination of the surface of the anatomical body part and the bolus, i.e. the combined outer contours of the surface of the anatomical body part and the surface of the bolus. In simultaneously executed step S44, a second reference is set as ReferenceSurface_2 to the contour of the bolus In step S45, a surface matching between the positions of the planned outer contours of the anatomical body part and the bolus on the one hand and the actual contours of the anatomical body part and the bolus is determined by taking a live surface image of the patient and the bolus placed on the patient difference, and the result of the matching is determined as Transformation_3. In step S46, the method determines whether Transform ation_3 is out tolerance. If it is determined that this is not the case (“no” after step S46), the method continues with conducting the surface matching of step S45 (i.e. with monitoring the position of the patient and the bolus placed on the patient). If it is determined that Transform ation_3 is out of tolerance, corresponding control data is determined for controlling the treatment beam in step S49. Following the simultaneous monitoring flow, step S47 conducts surface matching between ReferenceSurface_2 and the position of the planned outer contour of the bolus on the one hand and the actual contour of the bolus is determined by taking a live surface image of the bolus placed on the patient, and the result of the matching is determined as Transformation_4. In step S48, the method determines whether Transform ation_4 is out tolerance. If it is determined that this is not the case (“no” after step S48), the method continues with conducting the surface matching of step S47 (i.e. with monitoring the position of the bolus placed on the patient). If it is determined that Transformation_3 is out of tolerance, corresponding control data is determined for controlling the treatment beam in step S49.

Fig. 5 is a schematic illustration of the medical system 4 according to the fifth aspect. The system is in its entirety identified by reference sign 4 and comprises a computer 5, an electronic data storage device (such as a hard disc) 6 for storing at least the patient data and a radiation treatment device 7. The components of the medical system 4 have the functionalities and properties explained above with regard to the fifth aspect of this disclosure.

Fig. 6 shows an image of a bolus 8 placed on an anatomical body part 9. In this case, the anatomical body part 9 is the thorax and the bolus 8 is used to compensate for the loss of tissue due to mastectomy of the patient’s left breast.

Claims

1. A computer-implemented medical method of determining the position of a radiation treatment bolus (8), the method comprising the following steps: a) bolus planning image data is acquired (S11 ) which describes a digital planning image representation of the bolus (8) and a planned position of the bolus; b) bolus surface data is acquired (S12) which describes an actual position of a surface of the bolus (8); c) bolus position data is determined (S13) based on the planning image data and the bolus surface data, wherein the bolus position data describes a difference between the planned position and the actual position of the bolus (8).

2. The method according to the preceding claim, comprising acquiring body part planning image data describes a digital planning image of an anatomical body part (7) of a patient and a planned position of the anatomical body part (7); acquiring patient surface data describing an actual position of a surface of the anatomical body part (7); and determining, based on the planning image data and the patient surface data, body part position data describing a difference between the planned position and the actual position of the surface of the anatomical body part (7).

3. The method according to the preceding claim, wherein the difference between the planned position and the actual position of the surface of the anatomical body part (9) and the planned position and the actual position of the surface of the anatomical body part (9) is described by a positional transformation between the planned position and the actual position of the surface of the anatomical body part (9) and the planned position and the actual position of the surface of the anatomical body part (9).

4. The method according to any one of the preceding claims, wherein the difference between the planned position and the actual position of the bolus (8) is described by at least one of a positional transformation between the planned position and the actual position of the bolus (8) or a visual, for example colour-coded, rendering of the difference.

5. The method according to any one of the preceding claims, wherein the bolus surface data and, as fast as the method includes the features of claim 2, the patient surface data is generated by a surface-generating device, for example a surface camera or a laser scanner.

6. The method according to any one of the preceding claims as far as dependent on claim 2, comprising determining, based on the body part position data, body part control data describing at least one control signal for controlling a patient positioning device to move the anatomical body part (9) to its planed position; and for example issuing the body part control data to the patient positioning device.

7. The method according to any one of the preceding claims, comprising determining, based on the bolus position data, bolus control data describing at least one control signal for controlling a patient positioning device to move the bolus (8) to its planned position; and for example issuing the bolus control data to the patient positioning device.

8. The method according to any one of the preceding claims, wherein the bolus surface data describes an image representation of the surface of the bolus (8) and wherein the bolus position data is determined by matching a representation of the surface of the bolus (8) extracted from the bolus planning image data with the image representation of the bolus (8).

9. The method according to any one of the preceding claims as far as dependent on claim 2, wherein the patient surface data describes an image representation of the surface of the anatomical body part (9) and wherein the body part position data is determined by matching a representation of the surface of the anatomical body part (9) extracted from the body part planning image data with the image representation of the surface of the anatomical body part (9).

10. The method according to any one of the preceding claims, comprising determining, based on the bolus surface data, expected actual dose data describing an expected dose of treatment radiation to an anatomical body part (9) of the patient if the anatomical body part is irradiated with the treatment radiation while the bolus is at its actual position, for example acquiring planned dose data describing a planned dose of treatment radiation to the anatomical body part (9), wherein for example as far as the method is dependent on claim 7, the bolus control data is determined based on the expected actual dose data and the planned dose data.

11 . The method according to any of the preceding claims, comprising acquiring bolus difference threshold data describing a value of a threshold for the difference between the planned position and the actual position of the bolus (8); and determining, based on the bolus position data and the bolus difference threshold data, irradiation control data for controlling a beam of treatment radiation.

12. The method according to any of the preceding claims as far as dependent on claim 2, comprising acquiring body part difference threshold data describing a value of a threshold for the difference between the planned position and the actual position of the anatomical body part (9); and determining, based on the body part position data and the body part difference threshold data, irradiation control data for controlling a beam of treatment radiation.

13. The method according to any of the preceding claims as far as dependent on claim 2, comprising acquiring bolus body part difference threshold data describing a value of a threshold for the difference between the combined planned positions and the combined actual positions of the anatomical body part (9) and the bolus (8); and determining, based on the patient surface data and the body part planning image data and the bolus planning image data and the bolus body part difference threshold data, irradiation control data for controlling a beam of treatment radiation.

14. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method according to any one of the preceding claims.

15. A computer-readable storage medium on which the program according to the preceding claim is stored.

16. A computer comprising at least one processor, wherein the program according to claim 14 is executed by the processor.

17. A data carrier signal carrying the program according to claim 14.

18. A data stream comprising the program according to claim 14.

19. A medical system (4), comprising: a) the at least one computer (5) according to claim 13, wherein the instructions, when the program is executed by the computer, cause the computer to carry out the method according to any one of claims 6 or 7; and b) a patient positioning device (6) for positioning the patient for radiation treatment, wherein the at least one computer is operably coupled to the patient positioning device for issuing the control signal to the patient positioning device for controlling the operation of the patient positioning device on the basis of the at least one control signal.

20. The system (4) according to the preceding claim, comprising: a radiation treatment device (7) for issuing a beam of treatment radiation, wherein for example the instructions, when the program is executed by the computer, cause the computer to carry out the method according to any one of claims 11 to 13 and the radiation treatment device (7) is configured to be controlled based on the irradiation control data.