Methods, systems, and apparatuses for guiding transducer placements for tumor treating fields

Abstract

To assist transducer placements on a subject's body for applying tumor treating fields.SOLUTION: The method of assisting transducer placements on a subject's body for applying tumor treating fields includes: determining, based on one or more images associated with a portion of a subject's body, first image data, wherein the first image data comprises one or more transducer placement positions; determining, based on the one or more images, second image data, wherein the second image data comprises one or more recommended transducer placement positions; registering the second image data to the first image data; and generating a composite data comprising the one or more transducer placement positions and the one or more recommended transducer array placement positions.SELECTED DRAWING: Figure 19

Description

[Technical Field]

[0001] The present application relates to methods, systems, and devices for guiding transducer placement relative to tumor treatment fields.

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Patent Application No. 17 / 210,339, filed March 23, 2021, U.S. Patent Application No. 63 / 002,937, filed March 31, 2020, and U.S. Patent Application No. 63 / 056,262, filed July 24, 2020, which are incorporated herein by reference. [Background technology]

[0003] Tumor Treating Fields, or TTFields, are low-intensity (e.g., 1-3 V / cm) alternating electric fields in the mid-frequency range (100-300 kHz). This noninvasive treatment targets solid tumors and is described in U.S. Patent No. 7,565,205. TTFields inhibit cell division through physical interactions with key molecules during mitosis. TTFields therapy is an approved monotherapy for recurrent glioblastoma (GBM) and an approved combination therapy with chemotherapy for newly diagnosed patients. These fields are induced noninvasively by a transducer array (i.e., an array of electrodes) placed directly on the patient's scalp. TTFields also appear to be beneficial for treating tumors in other parts of the body.

[0004] Patient-optimized transducer placement may increase and / or improve field exposure to a target region, such as a tumor, improving the efficacy of TTFields therapy. Ensuring proper placement of the transducer array on a patient's body can be challenging due to minimal and / or no visibility of the target portion of the user's body (e.g., head / scalp, torso, etc.). Misaligned and / or improperly placed TAs reduce the effectiveness of TTFields therapy. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] U.S. Patent No. 7,565,205 [Patent Document 2] U.S. Patent Application Publication No. 20190117956 [Non-patent literature]

[0006] [Non-Patent Document 1] Ballo et al., “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,” International Journal of Radiation Oncology, Biology, Physics, 2019, 104(5), pp. 1106–1113. Summary of the Invention [Means for solving the problem]

[0007] One aspect of the invention is directed to a method for assisting in transducer placement on a subject's body for applying tumor treating fields, the method including: determining first image data based on one or more images associated with a portion of the subject's body, the first image data including one or more transducer placement locations; determining second image data based on the one or more images, the second image data including one or more recommended transducer placement locations; registering the first image data to the second image data; and generating composite data including the one or more transducer placement locations and the one or more recommended transducer array placement locations.

[0008] Another aspect of the invention is directed to another method for assisting in transducer placement on a subject's body for applying tumor treating fields, the method including: generating a three-dimensional (3D) model of a portion of the subject's body based on first image data, the 3D model including one or more suggested transducer placement locations; receiving second image data of the portion of the subject's body; determining a representation of one or more placement locations for one or more transducers in three-dimensional (3D) space based on the second image data; comparing the representation of the one or more placement locations for the one or more transducers in the 3D space with the one or more suggested transducer placement locations in the 3D model; and determining and outputting a variance of at least one of the one or more recommended transducer placement locations for the one or more transducers based on the comparison.

[0009] Another aspect of the invention is directed to an apparatus for assisting in transducer placement on a subject's body for applying tumor-treating fields, the apparatus comprising one or more processors and a memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to: determine first image data based on one or more images associated with a portion of the subject's body, the first image data including one or more transducer placement locations; determine second image data based on the one or more images, the second image data including one or more recommended transducer placement locations; register the first image data to the second image data; and generate composite data including the one or more transducer placement locations and the one or more recommended transducer placement locations.

[0010] Additional advantages will be set forth in part in the description which 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 both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 illustrates an exemplary device for electrotherapy treatment. [Figure 2] FIG. 1 illustrates an exemplary transducer array. [Figure 3A] FIG. 1 illustrates an application of the device for electrotherapy treatment. [Figure 3B] FIG. 1 illustrates an application of the device for electrotherapy treatment. [Figure 4A] FIG. 1 illustrates a transducer array placed on a patient's head. [Figure 4B] FIG. 1 illustrates a transducer array placed on the abdomen of a patient. [Figure 5A] FIG. 1 shows a transducer array placed on the patient's torso. [Figure 5B] FIG. 1 illustrates a transducer array placed on the patient's pelvis. [Figure 6] FIG. 1 is a block diagram illustrating an electric field generator and a patient support system. [Figure 7] FIG. 1 illustrates electric field magnitude and distribution (in V / cm) shown in coronal images from a finite element method simulation model. [Figure 8A] FIG. 8 shows a three-dimensional array layout map 800. [Figure 8B] FIG. 1 illustrates placement of a transducer array on a patient's scalp. [Figure 9A] FIG. 1 shows an axial T1 sequence slice containing the most apical image, including the orbits, used to measure head size. [Figure 9B] FIG. 1 shows a coronal T1 sequence slice select image at the level of the ear canal used to measure head size. [Figure 9C] FIG. 1 shows a post-contrast T1 axial image showing the maximum enhanced tumor diameter used to measure tumor location. [Figure 9D] FIG. 1 shows a post-contrast T1 coronal image showing the maximum enhancing tumor diameter used to measure tumor location. [Figure 10] FIG. 1 illustrates an exemplary system for inductive transducer placement for TTFields. [Figure 11A] FIG. 10 illustrates an example of generating a three-dimensional model associated with image data. [Figure 11B] FIG. 10 illustrates an example of generating a three-dimensional model associated with image data. [Figure 12A] FIG. 10 is a diagram illustrating an example of generating composite data associated with image data. [Figure 12B] FIG. 10 is a diagram illustrating an example of generating composite data associated with image data. [Figure 12C] FIG. 10 is a diagram illustrating an example of generating composite data associated with image data. [Figure 12D] FIG. 10 is a diagram illustrating an example of generating composite data associated with image data. [Figure 13A] FIG. 10 shows another example for inductive transducer placement relative to TTFields. [Figure 13B] FIG. 10 shows another example for inductive transducer placement relative to TTFields. [Figure 13C] FIG. 10 shows another example for inductive transducer placement relative to TTFields. [Figure 13D] FIG. 10 shows another example for inductive transducer placement relative to TTFields. [Figure 14A] FIG. 10 shows an example of a visual cue for guided transducer array placement relative to TTFields. [Figure 14B] FIG. 10 shows an example of a visual cue for guided transducer array placement relative to TTFields. [Figure 14C] FIG. 10 shows an example of a visual cue for guided transducer array placement relative to TTFields. [Figure 15] 1 is a flowchart illustrating an example of guided transducer array placement for TTFields. [Figure 16] 10 is a flow chart illustrating another example of inductive transducer array placement for TTFields. [Figure 17] 10 is a flow chart illustrating another example of inductive transducer array placement. [Figure 18] 10 is a flow chart illustrating another example of inductive transducer array placement. [Figure 19] 10 is a flow chart illustrating another example of inductive transducer array placement. [Figure 20] 10 is a flow chart illustrating another example of inductive transducer array placement. [Figure 21]10 is a flowchart illustrating an example of generating shared data. DETAILED DESCRIPTION OF THE INVENTION

[0012] Various embodiments are described in detail below with reference to the accompanying drawings, wherein like reference numerals represent like elements.

[0013] Before the present methods and systems are disclosed and described, it is to be understood that they are not limited to particular methods, components, or implementations. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting.

[0014] As used in this specification and the appended claims, the singular forms "a," "an," and "the" include the plural forms unless the context clearly dictates otherwise. Ranges may be expressed herein using the word "about" as from one approximate particular value and / or to another approximate 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, it will be understood that the use of the antecedent "about" causes the particular value to form another embodiment. Further, it will be understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint.

[0015] "Optional" or "optionally" means that the subsequently described event or circumstance may or may not occur, and that the description includes instances in which said event or circumstance occurs and instances in which said event or circumstance does not occur.

[0016] Throughout the description and claims of this specification, the words "include," "comprise," and conjugations thereof, such as "including," "comprising," etc., mean "including, but not limited to," and are not intended to exclude, for example, other components, integers, or steps. "Exemplary" means "an example of," and is not intended to convey indication of a preferred or ideal embodiment. "Etc." is not used in a limiting sense, but rather for illustrative purposes.

[0017] Disclosed are components that can be used to implement the disclosed methods and systems. These and other components are disclosed herein, and when combinations, subsets, interactions, groups, etc. of these components are disclosed, it is understood that specific reference to each of these various individual and collective combinations and permutations is not expressly disclosed, but is each specifically contemplated and described herein for all methods and systems. This applies to all aspects 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 any specific embodiment or combination of embodiments of the disclosed methods.

[0018] The method and system of the present invention may be more readily understood by reference to the following detailed description of the preferred embodiments and examples contained therein, as well as the figures and their accompanying descriptions.

[0019] As will be appreciated by those skilled in the art, the methods and systems may take the form of an all-hardware embodiment, an all-software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the methods and systems may take the form of a computer program product on a computer-readable storage medium having computer-readable program instructions (e.g., computer software) embodied in the storage medium. More particularly, the methods and systems may take the form of web-implemented computer software. Any suitable computer-readable storage medium may be utilized, including a hard disk, a CD-ROM, an optical storage device, or a magnetic storage device.

[0020] Embodiments of the methods and systems are described below with reference to block diagrams and flowchart illustrations of methods, systems, apparatuses, and computer program products. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by computer program instructions. These computer program instructions can be loaded onto a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to create machine means for implementing the functions specified in one or more of the flowchart blocks.

[0021] These computer program instructions, which may direct a computer or other programmable data processing apparatus to function in a particular manner, may further be stored in a computer-readable memory, thereby creating an article of manufacture containing computer-readable instructions for implementing the functions specified in one or more of the flowchart blocks, with the instructions stored in the computer-readable memory. The computer program instructions may also be loaded into a computer or other programmable data processing apparatus such that the instructions, when executed on the computer or other programmable device, provide steps for implementing the functions specified in one or more of the flowchart blocks, thereby causing a series of operational steps to be performed on the computer or other programmable device to create a computer-implemented process.

[0022] Thus, the blocks in the block diagrams and flowchart diagrams support combinations of means for performing the specified functions, combinations of steps for performing the specified functions, and program instruction means for performing the specified functions. It will also be understood that each block of the block diagrams and flowchart diagrams, and combinations of blocks in the block diagrams and / or flowchart diagrams, can be implemented by a special-purpose hardware-based computer system that performs the specified functions or steps, or a combination of special-purpose hardware and computer instructions.

[0023] TTFields, also referred to herein as alternating electric fields, have been established as an anti-mitotic cancer treatment because they disrupt proper microtubule polymerization during metaphase, ultimately disrupting cells during telophase and cytokinesis. Their effectiveness increases with increasing field strength, and the optimal frequency depends on the cancer cell line; the highest inhibition of glioma cell growth induced by TTFields was observed at 200 kHz. For cancer treatment, non-invasive devices have been developed using capacitively coupled transducers placed directly on the skin near the tumor, for example, for patients with glioblastoma multiforme (GBM), the most common primary malignant brain tumor in humans.

[0024] Because the effects of TTFields are directional, with cells dividing parallel to the field being more affected than cells dividing in other directions, and cells divide in all directions, TTFields are typically applied through two pairs of transducer arrays that generate perpendicular electric fields within the tumor being treated. More specifically, one pair of transducer arrays may be positioned on the left-right (LR) side of the tumor, and the other pair of transducer arrays may be positioned on the anterior-posterior (AP) side of the tumor. Cycling the electric field between these two directions (i.e., LR and AP) ensures that the widest range of cell orientations is targeted. Other positions of the transducer arrays are contemplated besides perpendicular electric fields. In one embodiment, asymmetric positioning of three transducer arrays is contemplated, where one pair of three transducer arrays may apply an alternating electric field, then another pair of three transducer arrays may apply the same, and then the remaining pair of three transducer arrays may apply the same.

[0025] In vivo and in vitro studies have shown that increasing the intensity of the electric field increases the effectiveness of TTFields therapy. Therefore, optimizing the array placement on the patient's scalp to increase intensity in affected areas of the brain is standard practice for the Optune system. Optimizing the array placement may be performed by "rules of thumb" (e.g., placing the array on the scalp as close as possible to the tumor), measurements describing the patient's head geometry, tumor dimensions, and / or tumor location. The measurements used as input may be derived from image data. Image data is intended to include any type of visual data, such as, for example, single-photon emission computed tomography (SPECT) image data, X-ray computed tomography (X-ray CT) data, magnetic resonance imaging (MRI) data, positron emission tomography (PET) data, data that can be captured by optical instruments (e.g., photographic cameras, charge-coupled device (CCD) cameras, infrared cameras, etc.), and the like. In some implementations, the image data may include 3D data (e.g., point cloud data) obtained from or generated by a 3D scanner. Optimization relies on an understanding of how the electric field is distributed as a function of array position, e.g., within the head, and in some aspects may take into account variations in the distribution of electrical properties within the heads of different patients. The transducer array placement position can be optimized to treat any part of the patient / subject's body (e.g., head, torso, etc.).

[0026] Optimized transducer array placement locations may be determined and recommended to a patient / subject, for example, when the patient / subject attempts to place one or more transducer arrays on / on any part of the patient / subject's body (e.g., head, torso, etc.). For example, a transducer array placement guidance / assistance tool may be used to compare, in real time, image data (e.g., one or more images, videos, representations / avatars, etc.) of a part of the patient / subject's body (e.g., head, torso, etc.) showing the placement of one or more transducer arrays on the patient / subject's surface (skin), with a transducer array layout map that includes optimized and / or recommended regions for the placement of one or more transducer arrays on the patient / subject's surface (skin). The transducer array placement guidance / assistance tool may be used to guide / instruct the patient / subject on where / how to place and / or move the transducer array for optimal TTFields treatment.

[0027] FIG. 1 illustrates an exemplary apparatus 100 for electrotherapy treatment. Generally, apparatus 100 may be a portable, battery- or mains-powered device that creates alternating electric fields within the body using a non-invasive surface transducer array. Apparatus 100 may include an electric field generator 102 and one or more transducer arrays 104. Apparatus 100 may be configured to generate Tumor Treating Electric Fields (TTFields) (e.g., 150 kHz) via field generator 102 and apply the TTFields to a region of the body through one or more transducer arrays 104. Field generator 102 may be a battery- and / or mains-powered device. In one embodiment, one or more transducer arrays 104 are uniformly shaped. In one embodiment, one or more transducer arrays 104 are not uniformly shaped.

[0028] 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.

[0029] The signal generator 108 may generate one or more electrical signals in the form of a waveform or pulse train. The signal generator 108 may be configured to generate alternating voltage waveforms (e.g., TTFields) at frequencies within a range of about 50 KHz to about 500 KHz (preferably about 100 KHz to about 300 KHz). These voltages are such that the electric field strength within the tissue to be treated is within a range of about 0.1 V / cm to about 10 V / cm.

[0030] One or more outputs 114 of the electric field generator 102 may be coupled to one or more conductive leads 112, one end of which is attached to the signal generator 108. The opposite ends of the conductive leads 112 are connected to one or more transducer arrays 104 that are activated by an electrical signal (e.g., a waveform). The conductive leads 112 may comprise standard insulated conductors with flexible metal shielding and may be grounded to prevent the electric field generated by the conductive leads 112 from spreading. The one or more outputs 114 may be operated sequentially. Output parameters of the signal generator 108 may include, for example, the strength of the electric field, the wave frequency (e.g., a treatment frequency), and the maximum allowable temperature of the one or more transducer arrays 104. The output parameters may be set and / or determined by the control software 110 in conjunction with the processor 106. After determining the desired (e.g., optimal) treatment frequency, the control software 110 causes the processor 106 to send control signals to the signal generator 108, causing the signal generator 108 to output the desired treatment frequency to the one or more transducer arrays 104.

[0031] The one or more transducer arrays 104 may be configured in various shapes and positions to generate electric fields of desired configurations, directions, and strengths in the target volume to focus the treatment. The one or more transducer arrays 104 may be configured to apply two perpendicular electric field directions through the volume of interest.

[0032] The one or more transducer 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 include, 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 that they do not come into direct contact with the skin because they are separated from the skin by a layer of conductive hydrogel (not shown) (similar to that found on electrocardiogram pads).

[0033] In an alternative embodiment, the transducer array 104 may include only one single electrode element 106. In one example, the single electrode element is a flexible organic material or a flexible organic composite material positioned on a substrate. In another example, the transducer array 104 may include a flexible organic material or a flexible organic composite material without a substrate.

[0034] The electrodes 116, hydrogel, and flexible circuit board 118 may be attached to a hypoallergenic medical bandage 120 to hold the one or more transducer arrays 104 in place on the body and in continuous direct contact with the skin. Each transducer array 104 may include one or more thermistors (not shown) (accuracy ±1°C), e.g., eight thermistors, to measure the skin temperature beneath the transducer array 104. The thermistors may be configured to measure the skin temperature periodically, e.g., every second. The thermistors may be read by the control software 110 while TTFields are not being delivered to avoid interference with the temperature measurement.

[0035] If the measured temperature falls below a preset maximum temperature (Tmax), e.g., 38.5-40.0°C ± 0.3°C, between two subsequent measurements, the control software 110 may increase the current until it reaches a maximum therapeutic current (e.g., 4 amps peak-to-peak). If the temperature reaches Tmax + 0.3°C and continues to rise, the control software 110 may decrease the current. If the temperature rises to 41°C, the control software 110 may stop TTFields therapy and an overheating alarm may be triggered.

[0036] The one or more transducer arrays 104 may vary in size and include various numbers of electrodes 116 based on the patient's body size and / or different treatments. For example, in the context of a patient's chest, the small transducer arrays may each include 13 electrodes, and the large transducer arrays may each include 20 electrodes, with the electrodes interconnected in series within each array. For example, in the context of a patient's head, as shown in FIG. 2, the transducer arrays may each include 9 electrodes, with the electrodes interconnected in series within each array.

[0037] The status and monitored parameters of the device 100 may be stored in a memory (not shown) and transferred 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, therapy on, alarms, and low battery.

[0038] 3A and 3B illustrate an example application of the device 100. Transducer arrays 104a and 104b are shown incorporated into hypoallergenic medical bandages 120a and 120b, respectively. The hypoallergenic medical bandages 120a and 120b are attached to a skin surface 302. A tumor 304 is located beneath the skin surface 302 and bone tissue 306, and is located within brain tissue 308. An electric field generator 102 causes the transducer arrays 104a and 104b to generate an alternating electric field 310 within the brain tissue 308 that disrupts the rapid cell division exhibited by cancer cells in the tumor 304. The alternating electric field 310 has been shown to halt tumor cell growth and / or destroy tumor cells in non-clinical experiments. The use of alternating electric fields 310 takes advantage of the special properties, geometry, and division rate of cancer cells that make them susceptible to the effects of the alternating electric field 310. The alternating electric field 310 changes its polarity at intermediate frequencies (on the order of 100-300 kHz). The frequency used for a particular treatment can be specific to the cell type being treated (e.g., 150 kHz for MPM). The alternating electric field 310 has been shown to disrupt mitotic spindle microtubule polymers and result in dielectrophoretic rearrangement of intracellular macromolecules and organelles during cytokinesis. These processes trigger physical disruption of the cell membrane and programmed cell death (apoptosis).

[0039] Because the effect of the alternating electric field 310 is directional, with cells dividing parallel to the field being more affected than cells dividing in other directions, and cells divide in all directions, the alternating electric field 310 can be applied through two pairs of transducer arrays 104 to generate a perpendicular electric field within the tumor being treated. More specifically, one pair of transducer arrays 104 can be positioned on the left-right (LR) side of the tumor, and the other pair of transducer arrays 104 can be positioned on the anterior-posterior (AP) side of the tumor. Cycling the alternating electric field between these two directions (e.g., LR and AP) ensures that the maximum range of cell orientations is targeted. In one embodiment, the alternating electric field 310 can be applied according to a symmetrical setup of the transducer arrays 104 (e.g., four total transducer arrays 104, two matched pairs). In another embodiment, the alternating electric field 310 can be applied according to an asymmetrical setup of the transducer arrays 104 (e.g., three total transducer arrays 104). An asymmetric setup of the transducer arrays 104 may use two of the three transducer arrays 104 to apply the alternating electric field 310, then switch to another two of the three transducer arrays 104 to apply the alternating electric field 310, and so on.

[0040] In vivo and in vitro studies have shown that increasing the strength of the electric field increases the effectiveness of TTFields therapy. The described methods, systems, and devices are configured to optimize array placement on a patient's scalp to increase intensity in affected regions of the brain.

[0041] As shown in Figure 4A, the transducer array 104 may be mounted on the patient's head. As shown in Figure 4B, the transducer array 104 may be mounted on the patient's abdomen. As shown in Figure 5A, the transducer array 104 may be mounted on the patient's torso. As shown in Figure 5B, the transducer array 104 may be mounted on the patient's pelvic region. Mounting of the transducer array 104 on other parts of the patient's body (e.g., arms, legs, etc.) is also specifically contemplated.

[0042] 6 is a block diagram illustrating a non-limiting example of a system 600 including a patient support system 602. The patient support system 602 may comprise one or more computers configured to operate and / or store an electric field generator (EFG) configuration application 606, a patient modeling application 608, and / or image data 610. The patient support system 602 may comprise, for example, a computing device. The patient support system 602 may include, for example, a laptop computer, a desktop computer, a mobile phone (e.g., a smartphone), a tablet, and the like.

[0043] The patient modeling application 608 may be configured to generate a three-dimensional model (e.g., a patient model) of a portion of a patient's body according to the image data 610. The image data 610 may include any type of visual data, such as, for example, single-photon emission computed tomography (SPECT) image data, X-ray computed tomography (X-ray CT) data, magnetic resonance imaging (MRI) data, positron emission tomography (PET) data, data that may be captured by an optical instrument (e.g., a photographic camera, a charge-coupled device (CCD) camera, an infrared camera, etc.), and the like. In some implementations, the image data may include 3D data (e.g., point cloud data) obtained from or generated by a 3D scanner. The patient modeling application 608 may also be configured to generate a three-dimensional array ray-ray map based on the patient model and one or more electric field simulations.

[0044] To properly optimize array placement on a portion of a patient's body, image data 610, such as MRI image data, may be analyzed by a patient modeling application 608 to identify regions of interest, including tumors. In the context of a patient's head, a modeling framework based on an anatomical head model using finite element method (FEM) simulations may be used to characterize how electric fields behave and distribute within the human head. These simulations generate a realistic head model based on magnetic resonance imaging (MRI) measurements and distinguish tissue types within the head, such as the skull, white matter, gray matter, and cerebrospinal fluid (CSF). Each tissue type may be assigned dielectric properties in terms of specific conductivity and permittivity, and simulations may be performed in which different transducer array configurations are applied to the surface of the model to understand how an externally applied electric field at a preset frequency distributes throughout any portion of the patient's body, such as the brain. Results from these simulations, employing a paired array configuration, constant current, and a preset frequency of 200 kHz, demonstrated that the electric field distribution is relatively nonuniform throughout the brain, and that field strengths exceeding 1 V / cm are generated within most tissue compartments, except for the CSF. These results are obtained assuming a total current with a peak-to-peak value of 1800 milliamperes (mA) at the transducer array-scalp interface. This threshold of electric field strength is sufficient to arrest cell proliferation in glioblastoma cell lines. In addition, by manipulating the paired transducer array configuration, it is possible to achieve nearly three times the electric field strength to specific brain regions, as shown in Figure 7. Figure 7 shows the electric field magnitude and distribution (in V / cm) shown in coronal images from a finite element method simulation model. This simulation employs a left-right paired transducer array configuration.

[0045] In one embodiment, the patient modeling application 608 can be configured to determine a desired (e.g., optimal) transducer array layout for a patient based on the location and extent of the tumor. For example, initial morphometric head size measurements can be determined from a T1 sequence of a brain MRI using axial and coronal images. Post-contrast axial and coronal MRI slices can be selected to show the maximum diameter of the enhancing lesion. Employing measurements of head size and distance from predetermined fiducial markers to the tumor margin, various permutations and combinations of paired array layouts can be evaluated to generate a configuration that applies the greatest field strength to the tumor site. As shown in FIG. 8A, the output can be a three-dimensional array layout map 800. The three-dimensional array layout map 800 can be used by the patient and / or caregiver in positioning and configuring arrays on the scalp during the normal course of TTFields therapy, as shown in FIG. 8B.

[0046] In one embodiment, the patient modeling application 608 can be configured to determine a three-dimensional array layout map for the patient. MRI measurements of the portion of the patient that is to receive the transducer array can be determined. For example, the MRI measurements can be received via a standard Digital Imaging and Communications in Medicine (DICOM) viewer. The MRI measurement determination can be performed automatically, e.g., using artificial intelligence techniques, or manually, e.g., by a physician.

[0047] Manual MRI measurement determination may include receiving and / or providing MRI data via a DICOM viewer. The MRI data may include a scan of a portion of a patient containing a tumor. For example, in the context of a patient's head, the MRI data may include a head scan containing one or more of a right frontotemporal tumor, a right parietotemporal tumor, a left frontotemporal tumor, a left parieto-occipital tumor, and / or a multifocal midline tumor. Figures 9A, 9B, 9C, and 9D illustrate example MRI data showing a scan of a patient's head. Figure 9A shows an axial T1 sequence slice including an apical-most image, including the orbit, used to measure head size. Figure 9B shows a coronal T1 sequence slice selecting an image at the level of the ear canal, used to measure head size. Figure 9C shows a post-contrast T1 axial image showing the maximum enhancing tumor diameter, used to measure tumor location. Figure 9D shows a post-contrast T1 coronal image showing the maximum enhancing tumor diameter, used to measure tumor location. MRI measurements may begin from fiducial markers at the lateral edge of the scalp and extend tangentially from a right, anterior, superior origin. Morphometric head size may be estimated from an axial T1 MRI sequence selecting the most apical image that still included the orbits (or the image directly above the superior edge of the orbits).

[0048] In one embodiment, the MRI measurements may include, for example, one or more of head size measurements and / or tumor measurements. In one embodiment, one or more MRI measurements may be rounded to the nearest millimeter and provided to a transducer array mounting module (e.g., software) for analysis. The MRI measurements may then be used to generate a three-dimensional array layout map (e.g., three-dimensional array layout map 800).

[0049] The MRI measurements may include one or more head size measurements, such as maximum anterior-posterior (AP) head size, starting from the outer edge of the scalp, maximum width of the head perpendicular to the AP measurement, i.e., lateral distance from right to left, and / or distance from the rightmost edge of the scalp to the anatomical midline.

[0050] The MRI measurements may include one or more head size measurements, such as coronal head size measurements. Coronal head size measurements may be acquired with a T1 MRI sequence that selects an image at the level of the ear canal (FIG. 9B). The coronal head size measurements may include one or more of a vertical measurement from the vertex of the scalp to an orthogonal line delineating the inferior border of the temporal lobes, maximum left-right temporal width, and / or the distance from the rightmost edge of the scalp to the anatomical midline.

[0051] The MRI measurements may include one or more tumor measurements, such as tumor location measurements. Tumor location measurements may be performed first on an axial image showing the maximum enhancing tumor diameter (FIG. 9C) using a T1 post-contrast MRI sequence. The tumor location measurements may include one or more of: maximum AP head size excluding the nose; maximum left-right lateral diameter measured perpendicular to the AP distance; distance from the right edge of the scalp to the anatomical midline; distance from the right edge of the scalp to the nearest tumor edge measured parallel to the left-right lateral distance and perpendicular to the AP measurement; distance from the right edge of the scalp to the farthest tumor edge measured parallel to the left-right lateral distance and perpendicular to the AP measurement; distance from the forehead to the nearest tumor edge measured parallel to the AP measurement; and / or distance from the forehead to the farthest tumor edge measured parallel to the AP measurement.

[0052] The one or more tumor measurements may include coronal tumor measurements. Coronal tumor measurements may include identifying a post-contrast T1 MRI slice characterized by the maximum diameter of tumor enhancement (FIG. 9D). Coronal tumor measurements may include one or more of the following: maximum distance from the vertex of the scalp to the inferior border of the cerebrum. In anterior slices, this is bounded by a horizontal line drawn at the inferior border of the frontal or temporal lobe; posteriorly, it extends to the lowest level of the visible tentorium, i.e., maximum left-right lateral head width; distance from the right edge of the scalp to the anatomical midline; distance from the right edge of the scalp to the nearest tumor edge measured parallel to the right-left lateral distance; distance from the right edge of the scalp to the farthest tumor edge measured parallel to the right-left lateral distance; distance from the vertex to the nearest tumor edge measured parallel to the superior vertex to the inferior cerebral line; and / or distance from the vertex to the farthest tumor edge measured parallel to the inferior cerebral line.

[0053] Other MRI measurements may be used, especially when the tumor is located in another part of the patient's body.

[0054] The MRI measurements may be used by the patient modeling application 608 to generate a patient model. The patient model may then be used to determine a three-dimensional array layout map (e.g., three-dimensional array layout map 800). Continuing with the example of a tumor in a patient's head, a healthy head model may be generated to serve as a deformable template from which a patient model can be created. When creating the patient model, the tumor may be segmented from the patient's MRI data (e.g., one or more MRI measurements). Segmenting the MRI data identifies tissue types within each voxel, and electrical properties may be assigned to each tissue type based on empirical data. Table 1 shows standard electrical properties of tissues that may be used in simulations. The region of the tumor in the patient MRI data may be masked, and a non-rigid registration algorithm may be used to register the remaining regions of the patient's head onto a 3D discrete image representing a deformable template of the healthy head model. This process produces a non-rigid transformation that maps the healthy portion of the patient's head into template space, as well as an inverse transformation that maps the template into patient space. This inverse transformation is applied to the 3D deformable template to generate an approximation of the patient's head in the absence of the tumor. Finally, the tumor (called the region of interest (ROI)) is implanted back into the deformed template to generate a complete patient model, which may be a digital representation in three-dimensional space of a part of the patient's body, including internal structures such as tissues, organs, and tumors.

[0055] [Table 1]

[0056] The application of TTFields can then be simulated by a patient modeling application 608 using the patient model. Simulated field distributions, dosimetry, and simulation-based analysis are described in U.S. Patent Application Publication No. 20190117956 and Ballo et al., "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," International Journal of Radiation Oncology, Biology, Physics, 2019, 104(5), pp. 1106-1113.

[0057] To ensure systematic positioning of the transducer array relative to the tumor location, a reference coordinate system can be defined. For example, the transverse plane can be first defined by conventional LR and anterior-posterior (AP) positioning of the transducer array. The left-right direction can be defined as the x-axis, the AP direction as the y-axis, and the craniocaudal direction, which is normal to the xy plane, as the z-axis.

[0058] After defining the coordinate system, the transducer arrays can be virtually placed on a patient model with its center and longitudinal axis on the xy plane. Pairs of transducer arrays can be systematically rotated from 0 to 180 degrees around the z-axis of the head model, i.e., in the xy plane, thereby covering the entire circumference of the head (by symmetry). The rotation interval can be, for example, 15 degrees, corresponding to a translation of about 2 cm, giving a total of 12 different positions within the 180-degree range. Other rotation intervals are also contemplated. Electric field distribution calculations can be performed for the position of each transducer array relative to the tumor coordinates.

[0059] The electric field distribution in the patient model can be determined by the patient modeling application 608 using a finite element (FE) approximation of the electric potential. Generally, quantities defining a time-varying electromagnetic field are given by complex Maxwell's equations. However, in biological tissue, at the low to mid-frequency range of TTFields (f = 200 kHz), the wavelength of the electromagnetic wave is much larger than the head size, and the permittivity ε is negligibly small compared to the real-valued electrical conductivity σ, i.e., where ω = 2πf is the angular frequency. This means that electromagnetic wave propagation effects and capacitive effects in tissue are negligible, and therefore the scalar electric potential can be well approximated by the static Laplace equation ∇·(σ∇φ) = 0 under appropriate boundary conditions at the electrodes and skin. Therefore, complex impedances are treated as resistive (i.e., reactance is negligible), and therefore, the current flowing in volume conductors is primarily free (ohmic) current. FE approximations to Laplace's equation can be calculated using software such as SimNIBS software (simnibs.org). The calculations were based on the Galerkin method, and the residuals of the conjugate gradient solver were required to be <1E-9. Dirichlet boundary conditions were used, and the potential was set to a fixed (arbitrarily chosen) value at each set of electrode arrays. The electric field (vector) was calculated as the numerical gradient of the electric potential, and the current density (vector field) could be calculated from the electric field using Ohm's law. The electric field values, potential difference and current density, were linearly rescaled to a peak-to-peak total amplitude of 1.8 A for each array pair and calculated as the (numerical) surface integral of the normal current density component over all triangular surface elements on the active electrode disk. The TTFields "dose" could be calculated as the intensity (L2 norm) of the electric field vector. The modeled current could be assumed to be supplied by two separate, sequentially activated current sources, each connected to a pair of 3 × 3 transducer arrays. In the simulation, the left and rear arrays could be defined as sources, and the right and front arrays as corresponding sinks, respectively. However, since TTFields employ an alternating electric field, this choice is arbitrary and does not affect the results.

[0060] The average strength of the electric field generated by a transducer array placed at multiple locations on the patient may be determined by the patient modeling application 608 for one or more tissue types. In one embodiment, the transducer array location corresponding to the highest average electric field strength in the tumor tissue type may be selected as the desired (e.g., optimal) transducer array location for the patient. For example, a method for determining an optimal transducer array layout may include determining a region of interest (ROI) within a 3D model of a portion of the subject's body. Based on the center of the ROI, a plane that intersects the portion of the subject's body may be determined, the plane including multiple pairs of locations along the contour of the plane. The method may include adjusting one or more of the multiple pairs of locations based on anatomical constraints to generate a corrected plane. The anatomical constraints may be based on anatomical features of the portion of the subject's body. For example, a first electric field generated by a first transducer array may be simulated at a first position, a second electric field generated by a second transducer array may be simulated at a second position opposite the first position, and a simulated electric field distribution may be determined based on the first electric field and the second electric field. In some cases, a third electric field generated by the first transducer array may be simulated at a third position, and a fourth electric field generated by the second transducer array may be simulated at a fourth position opposite the third position, and a simulated electric field distribution may be determined based on the third electric field and the fourth electric field. The method may include determining a simulated electric field distribution for each pair of positions among the plurality of pairs of positions on the corrected plane, and determining a dose metric for each pair of positions among the plurality of pairs of positions based on the simulated electric field distribution. One or more sets of pairs of positions among the plurality of pairs of positions that satisfy the angular constraints between the pairs of transducer arrays may be determined. For example, the angular constraints may be and / or may indicate orthogonal angles between pairs of transducer arrays.The angular constraint may be, for example, a range of angles between pairs of transducer arrays and / or may indicate a range of angles. Based on one or more sets of pairs of locations that satisfy the dose metric and the angular constraint, one or more candidate transducer array layouts are mapped. A simulated orientation or a simulated position for at least one transducer array at at least one location of the one or more candidate transducer array layout maps may be adjusted. A final transducer array layout map may be determined based on adjusting the simulated orientation or the simulated position for the at least one transducer array.

[0061] The patient model may be modified, for example, based on the final transducer array layout map to include an indication of the desired transducer array location. The resulting patient model including the indication of the desired transducer array location may be referred to as a three-dimensional array layout map (e.g., three-dimensional array layout map 800). Thus, the three-dimensional array layout map may include a digital representation in three-dimensional space of a portion of the patient's body, an indication of a tumor location, location instructions for placement of one or more transducer arrays, combinations thereof, and the like.

[0062] In one embodiment, a three-dimensional transducer array layout map with one or more recommended transducer placement locations may be generated and provided to the patient in digital and / or physical format. The patient and / or the patient's caregiver may use the three-dimensional transducer array layout map to apply one or more transducer arrays to relevant parts of the patient's body (e.g., head, torso, etc.).

[0063] In another embodiment, an augmented reality assistance tool may use the three-dimensional array layout map to assist the patient and / or patient's caregiver in applying one or more transducer arrays to relevant portions of the patient's body (e.g., head, torso, etc.). For example, a transducer array placement location, such as an optimized transducer array placement location, may be determined, and a representation of a transducer array patch, disk, and / or the like may be presented on the surface of the patient / subject virtual model based on the determined location. For example, the augmented reality assistance tool may be used to instruct a user (e.g., patient, patient caregiver, etc.) to capture an image (e.g., image, video, etc.) of a portion of the patient / subject's body (e.g., head, torso, etc.) for transducer array placement. Registration of the image (e.g., image, video, etc.) to the virtual patient model may be performed, for example, in real time. After registration, representations of the transducer array patches, discs, additional landmarks, and / or the like may be virtually displayed (e.g., overlaid using augmented reality, etc.) on the image and / or patient model to allow the transducer array to be placed with high precision (in an optimized position) on the patient's surface (skin).

[0064] In some cases, the transducer array placement guidance / assistance tool may guide / assist a patient / subject in positioning the transducer array on the patient / subject. For example, when a patient / subject is placing one or more transducer arrays on / on any part of their body (e.g., head, torso, etc.), if the one or more transducer arrays are not properly placed in a position / at a location that optimizes TTFields therapy / treatment, a three-dimensional array layout map may be used to recommend the correct movement and / or placement for the one or more transducer arrays.

[0065] In some cases, a virtual reality-assisted tool may be used to generate a 3D model with optimized transducer array placement positions and / or to guide / assist a patient / subject in placing one or more arrays at the optimized transducer array placement positions. In one example, the virtual reality-assisted tool may be a virtual reality headset, virtual reality goggles, etc. For example, a three-dimensional transducer array layout map may be provided to the patient through the virtual reality-assisted tool. Furthermore, the virtual reality-assisted tool may be used to provide feedback to the patient or caregiver regarding whether one or more transducer arrays are properly placed at / in the optimized positions.

[0066] The described method allows points in two-dimensional (2D) image data indicative of actual transducer array placement relative to a patient / subject's body to be transformed into points in three-dimensional (3D) space. The two-dimensional (2D) image data may include images captured by a user device (e.g., a smartphone, a mobile device, a computing device, etc.) depicting the actual transducer array placement relative to the patient / subject's body. The 3D points / coordinates indicative of the actual transducer array placement relative to the patient / subject's body may be transformed into and / or registered to 3D medical image coordinates, such as MRI coordinates, based on medical image data associated with the patient / subject. The actual transducer array placement may then be compared with one or more recommended transducer array placements previously determined from the medical image data to determine whether the actual transducer array placement corresponds to the one or more recommended transducer array placements.

[0067] For example, a patient / subject may use a user device (e.g., a smartphone, mobile device, computing device, etc.) to capture multiple images from different vantage points and / or viewpoints of a portion of the patient / subject's body on which one or more transducer arrays are placed for TTFields therapy / treatment. The multiple images may capture the placement locations of the one or more transducer arrays. Object recognition and / or the like may be used to analyze the multiple images and determine the placement locations of the one or more transducer arrays. For example, object recognition and / or the like may be used to determine / detect one or more landmarks (e.g., anatomical landmarks, artificial landmarks, etc.) from the multiple images. The one or more landmarks may be used to determine the placement locations for the one or more transducer arrays.

[0068] In some cases, a portion of a patient / subject's body may have one or more regions, such as the patient's back of the head, that lack landmarks that can be determined / detected by object recognition and used to determine a mounting location for one or more transducer arrays. Machine learning may be used to predict and / or estimate a mounting location for one or more transducer arrays, for example, in scenarios where one or more portions of the one or more transducer arrays are not present and / or represented in multiple images. For example, a machine learning model may be trained to estimate the overall shape, configuration, and / or mounting location of a transducer array when only one or more portions of the transducer array are present and / or represented in multiple images. The estimated shape, configuration, and / or mounting location of the one or more transducer arrays may be combined with the mounting location of the one or more transducer arrays determined from object recognition to determine the overall shape, configuration, and / or mounting location of the one or more transducer arrays. The machine learning model may assign estimated points / coordinates to the estimated shape, configuration, and / or mounting location of the one or more transducer arrays.

[0069] Three-dimensional (3D) points (e.g., coordinates) representing and / or associated with the mounting position (and / or shape, configuration, etc.) for one or more transducer arrays may then be determined / generated. The 3D points (e.g., coordinates) may be converted to 3D coordinates and / or used to determine three-dimensional coordinates within an anatomical coordinate system (e.g., a patient coordinate system), such as 3D coordinates used in medical images incorporating anatomical planes (e.g., sagittal, coronal, transverse, etc.) (e.g., magnetic resonance imaging (MRI), X-ray computed tomography (X-ray CT) images, single-photon emission computed tomography (SPECT) images, positron emission tomography (PET) images, etc.). For example, the 3D points (e.g., coordinates) may be converted to 3D coordinates associated with one or more medical images associated with a patient / subject.

[0070] The placement / location of one or more transducer arrays, as determined and / or indicated by 3D coordinates associated with the anatomical coordinate system, may be compared to optimized transducer array placement locations indicated by the 3D transducer array layout map. The optimized transducer array placement locations may be based on one or more TTFields treatment / therapy simulations performed based on one or more medical images associated with the patient / subject. The optimized transducer array placement locations may be recommended to the patient / subject, for example, to promote optimal effects of TTFields therapy / treatment. For example, the placement / location of one or more transducer arrays may be displayed (e.g., superimposed, overlaid, etc.) with the optimized (e.g., recommended, etc.) transducer array placement locations. In some cases, the placement / location of one or more transducer arrays may be displayed (e.g., superimposed, overlaid, etc.) with a representation of a transducer array patch, disk, and / or the like at the optimized (e.g., recommended, etc.) transducer array placement location.

[0071] In another embodiment, the placement / location of one or more transducer arrays may be compared and displayed (e.g., superimposed, overlaid, etc.) with one or more recommended transducer array placement locations. In one example, the one or more transducer placements and the one or more recommended transducer placement locations may be displayed with an actual image and / or realistic depiction of the patient / subject and / or a portion of the patient / subject's body. In another example, the one or more transducer placements and the one or more recommended transducer placement locations may be displayed with a surrogate image (e.g., an avatar, etc.) of the patient / subject and / or a portion of the patient / subject's body.

[0072] In one embodiment, the placement / position of one or more transducer arrays may not match one or more recommended transducer array placement positions. For example, based on comparing 3D coordinates associated with anatomical coordinates with the optimized transducer array placement positions indicated by the 3D transducer array layout map, a variance of at least one of the one or more placement positions for the one or more transducer arrays from at least one of the one or more recommended transducer placement positions may be determined. To resolve the variance, any movement (e.g., corrective movement, etc.) of the placement / position of the one or more transducer arrays that causes the placement / position of the one or more transducer arrays to match the one or more recommended transducer placement positions may be sent to the patient / subject, for example, as a notification. The notification may be a visual notification, an audible notification, a text notification, and / or the like.

[0073] 10 is an exemplary system for inductive transducer placement for TTFields. In some cases, the components of system 1000 may be implemented as a single device and / or the like. In some cases, the components of system 1000 may be implemented as separate devices / components that collectively communicate with each other. In one aspect, some or all steps of any described method may be performed on and / or via components of system 1000.

[0074] The system 1000 may include a user device 1020. The user device 1020 may be an electronic device, such as a smartphone, mobile device, computing device, and / or the like, capable of communicating with the patient support module 1001. The user device 1020 may include an imaging module 1021. The imaging module 1021 may include one or more image capture devices, such as one or more video cameras, that determine / capture a first set of image data (e.g., video data, static / still images, dynamic / interactive images, etc.) corresponding to the real world for the system 1000. In one example, the user device 1020 may be used to determine one or more recommended transducer placement locations. In some cases, the system 1000 may include multiple user devices (e.g., a second user device 1026) with imaging modules that share and / or exchange data / information, such as image data. The imaging module 1021 may capture image data that provides a real-time, real-world representation of a user (e.g., a patient, subject, etc.), such as a real-time, real-world representation of the user and / or a portion of the user's body (e.g., head, torso, etc.). For example, the imaging module 1021 may be used to capture / film a video image of a portion of the user's body (related to the location) where TTFields therapy is to be administered via one or more transducer arrays.

[0075] The user device 1020 may include an interface module 1022. The interface module 1022 may provide a user with an interface for interacting with the user device 1020 and / or the patient support module 1001. The interface module 1022 may include one or more input devices / interfaces, such as a keyboard, a pointing device (e.g., a computer mouse, a remote control), a microphone, a joystick, a scanner, a tactile-sensing and / or tactile input device, and / or the like.

[0076] The interface module 1022 may comprise one or more interfaces for presenting and / or receiving information from a user, such as user feedback. The interface module 1022 may include any software, hardware, and / or interfaces used to provide communication between a user and one or more of the user device 1020, the patient support module 1001, and / or any other components of the system 1000. The interface module 1022 may include one or more audio devices (e.g., stereo, speaker, microphone, etc.) for capturing / obtaining and communicating audio information, such as audio information captured / obtained from and / or communicated to a user. The interface module 1022 may include a graphical user interface (GUI), a web browser (e.g., Internet Explorer®, Mozilla Firefox®, Google Chrome®, Safari®, etc.), applications / APIs. The interface module 1022 may request and / or query various files from local and / or remote sources, such as the patient support module 1001.

[0077] The interface module 1022 may transmit / send data to local or remote devices / components of the system 1000, such as the patient support module 1001. The user device 1020 may include a communications module 1023. The communications module 1023 may enable the user device 1020 to communicate with components of the system 1000, such as the patient support module 1001 and / or another user device, via wired and / or wireless communications technologies. For example, the communications module 1023 may utilize any suitable wired communications technology, such as Ethernet, coaxial cable, fiber optics, and / or the like. The communications module 1023 may utilize any suitable long-range communications technology, such as Wi-Fi (IEEE 802.11), BLUETOOTH, cellular, satellite, infrared, and / or the like. The communications module 1023 may utilize any suitable short-range communications technology, such as BLUETOOTH, near field communication, infrared, and the like.

[0078] The interface module 1022 may include one or more displays (e.g., monitors, head-up displays, head-mounted displays, liquid crystal displays, organic light-emitting diode displays, active-matrix organic light-emitting diode displays, stereo displays, virtual reality displays, etc.) for displaying / presenting information to a user (e.g., a patient, a subject, etc.), such as augmented reality and / or virtual images, mirror images, superimposed images, and / or the like. For example, the interface module 1022 may display a representation of the user and / or a portion of the user's body (e.g., head, torso, etc.) based on a first set of image data captured by the imaging module 1021. In some cases, the representation of the user and / or a portion of the user's body (e.g., head, torso, etc.) may be an actual (e.g., mirror image) representation of the user and / or a portion of the user's body (e.g., head, torso, etc.). In some cases, the representation of the user and / or a portion of the user's body may depict the user and / or a portion of the user's body from different perspectives, angles / positions, fields of view, and / or the like. In some cases, the representation of the user and / or the user's body part may include an actual (e.g., mirror image) representation of the user and / or the user's body part, as well as a representation of the user and / or the user's body part from different viewpoints, angles / positions, fields of view, and / or the like, such as a split-view representation of the user and / or the user's body part. In some cases, the representation of the user and / or the user's body part may include a general / replica representation of the user and / or the user's body part, such as a general image, a duplicate image, a wireframe / stick image, a virtual image (e.g., an avatar, etc.), and / or the like.To generate and / or display a generic / replica representation of the user and / or a portion of the user's body, such as a generic image, a replica image, a wireframe / stick image, a virtual image (e.g., an avatar, etc.), and / or the like, the user device may transmit a first set of image data (e.g., video data, static / still images, dynamic / interactive images, etc.) associated with the portion of the user's body (e.g., head, torso, etc.) captured by the imaging module 1021 to the patient support module 1001. In some instances, one or more user devices may transmit image data (e.g., compiled image data, image data taken from one or more perspectives, etc.) associated with the portion of the user's body (e.g., head, torso, etc.) to the patient support module 1001.

[0079] The patient support module 1001 may use image data (and / or compiled image data) from the user device 1020 to determine a patient model associated with the user and determine transducer array placement positions, such as optimized transducer array placement positions, on the patient model, where the transducer array (or associated equipment such as a patch, disk, array mounting support, and / or the like) may be represented as one or more images superimposed / overlaid with the image data.

[0080] The system 1000 may include a second user device 1026. The second user device 1026 may be a different user device from the user device 1020 or the same user device as the user device 1020. The second user device 1026 may be used to determine the actual placement of one or more transducers. The user device 1026 may be an electronic device, such as a smartphone, a mobile device, a computing device, a virtual reality assistive tool, and / or the like, that can communicate with the patient support module 1001. The second user device 1026 may include an interface module 1028. The interface module 1028 may provide a user with an interface for interacting with the second user device 1026 and / or the patient support module 1001. The interface module 1028 may have a similar structure and / or similar functionality to the interface module 1022.

[0081] The interface module 1028 may transmit / send data to local or remote devices / components of the system 1000, such as the patient support module 1001. The second user device 1026 may include a communications module 1029. The communications module 1029 may enable the second user device 1026 to communicate with components of the system 1000, such as the patient support module 1001 and / or another user device, via wired and / or wireless communications technologies. The communications module 1029 may have a similar structure and / or similar functionality to the communications module 1023.

[0082] The second user device 1026 may include an imaging module 1027. The imaging module 1027 may include one or more image capture devices, such as one or more cameras, that determine / capture a second set of image data (e.g., static / still images, dynamic / interactive images, video, etc.). The imaging module 1027 may capture image data that provides a real-time and / or real-world representation of the user (e.g., patient, subject, etc.), such as a real-time and / or real-world representation of the user and / or a portion of the user's body (e.g., head, torso, etc.). For example, the imaging module 1027 may be used to capture / film images and / or video of a portion of the user's body (related to the location) where TTFields therapy is to be administered via one or more transducer arrays.

[0083] To generate and / or display a representation of the user and / or a portion of the user's body, the second user device 1026 may transmit image data (e.g., video data, static / still images, dynamic / interactive images, etc.) associated with the portion of the user's body (e.g., head, torso, etc.) captured by the imaging module 1027 to the patient support module 1001. The second set of image data may include multiple images taken from multiple vantage points, viewpoints, and / or the like associated with the portion of the user's body.

[0084] The image data may include data indicating and / or determined from one or more tracking points / landmarks, such as anatomical landmarks and / or visual / artificial landmarks. For example, anatomical landmarks may include body locations (e.g., head, bones / ligaments, joints, etc.) and / or facial expression points (e.g., eyes, nose, eyebrows, etc.). Visual / artificial landmarks may include one or more indicators (e.g., stickers, marks / removable tattoos, objects, etc.) placed at one or more locations / positions on the user and / or parts of the user's body.

[0085] The patient support module 1001 may include a processor 1008. The processor 1008 may be a hardware device for executing software, particularly stored in memory 1010. The processor 1008 may be any custom or commercially available processor, a central processing unit (CPU), a coprocessor among multiple processors associated with the patient support module 1001, a semiconductor-based microprocessor (in the form of a microchip or chipset), or generally any device for executing software instructions. When the patient support module 1001 is operating, the processor 1008 may be configured to execute software stored in the memory 1010, communicate data to and from the memory 1010, and generally control the operation of the patient support module 1001 in accordance with the software.

[0086] The I / O interface 1012 may be used to receive user input from and / or provide system output to one or more devices or components, such as the user device 1020 and / or the second user device 1026. User input may be provided, for example, via a keyboard, a mouse, a data / information communication interface, and / or the like. The I / O interface 1012 may include, for example, a serial port, a parallel port, a Small Computer System Interface (SCSI), an IR interface, an RF interface, and / or a Universal Serial Bus (USB) interface.

[0087] The network interface 1014 may be used to transmit 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 token ring adapter, a wireless network adapter (e.g., WiFi), or any other suitable network interface device. The network interface 1014 may include address, control, and / or data connections to enable appropriate communications.

[0088] The memory 1010 (memory system) may include any one or combination of volatile memory elements (e.g., random access memory (RAM, such as DRAM, SRAM, SDRAM)) and non-volatile memory elements (e.g., ROM, hard drive, tape, CD-ROM, DVD-ROM, etc.). Additionally, the memory 1010 may incorporate electronic, magnetic, optical, and / or other types of storage media. In some cases, the memory system 1010 may have a distributed architecture in which various components are located remotely from each other but may be accessed by the processor 1008.

[0089] The memory 1010 may include one or more software programs, each of which includes an ordered listing of executable instructions for implementing logical functions. For example, the memory 1010 may include an EFG configuration application 606, a patient modeling application 608, image data 610, and a suitable operating system (O / S) 1018. The operating system 1018 essentially controls the execution of other computer programs and provides scheduling, input / output control, file and data management, memory management, and communication control and related services.

[0090] The patient support module 1001 may include an image processing module 1016. The image processing module 1016 may process image data from the user device 1020 and the second user device 1026. In some cases, the image processing module 1016 may use artificial intelligence and / or machine learning, such as image recognition, to identify the user and / or parts of the user's body (e.g., head, torso, full body, etc.). In some cases, the image processing module 1016 may use one or more object tracking algorithms and / or the like to determine / detect the location of various tracking points on the user. For example, the tracking points may include body locations (e.g., head, bones / ligaments, joints, etc.) and / or facial expression points (e.g., eyes, nose, eyebrows, etc.). The locations of the various tracking points may be provided to the avatar mapping and rendering module 1025. The avatar mapping and rendering module 1025 may use one or more mapping algorithms to map the user's tracked points to an avatar (e.g., a generic image, a replica image, a wireframe / stick image, a virtual image, etc.). Mapping the user's tracked points to an avatar may allow one or more captured images (e.g., image data) of the user to be represented by the avatar. The patient support module 1001 (avatar mapping and rendering module 1025) may transmit the avatar (e.g., data / information indicative of the avatar, etc.) to the user device 1020 and / or the second user device 1026 for display.

[0091] In some cases, to assist the user in placing the transducer array, the image processing module 1016 may use facial recognition in conjunction with the image data to identify the user. The image processing module 1016 may use object recognition in conjunction with the image data to identify the user (e.g., identify identifying marks / scars on the user, etc.) and / or parts of the user's body represented by the image data (e.g., head, torso, full body, etc.). In some cases, the image processing module 1016 may use object recognition in conjunction with the image data to determine "sensitive areas," such as scar areas, blemish areas, genitalia, and / or the like. The image processing module 1016 may modify the image to obscure, block out, and / or similarly manipulate "sensitive areas," such as when the image data is displayed.

[0092] In some cases, the image processing module 1016 may determine one or more landmarks from the image data. For example, the image processing module 1016 may be used to determine / detect anatomical landmarks from the image data. In one example, the image processing module 1016 may determine one or more landmarks indicated by image data received from the user device 1020 and determine one or more landmarks indicated by image data received from the second user device 1026. Furthermore, the image processing module 1016 may determine that one or more landmarks indicated by the image data received from the user device 1020 correspond to one or more landmarks indicated by the image data received from the second user device 1026. The image processing module 1016 may use artificial intelligence and / or machine learning, such as image / object recognition, to identify one or more landmarks (e.g., anatomical landmarks, artificial landmarks, etc.) depicted by one or more images of a plurality of images included with the image data. In some cases, the image processing module 1016 may use one or more object identification and / or tracking algorithms to determine / detect the location of one or more landmarks. In some cases, the image processing module 1016 may use object recognition in conjunction with the image data to determine "sensitive areas," such as areas of scarring, blemishes, genitalia, and / or the like. The image processing module 1016 may modify the image to obscure, occlude, and / or similarly manipulate the "sensitive areas," such as when the image data is displayed.

[0093] The image processing module 1016 may be used to determine / detect objects depicted by the image data, such as the actual (e.g., real-time) placement of one or more transducer arrays on a user and / or parts of the user's body.

[0094] In some cases, a portion of the user's body may have one or more areas, such as the back of the user's head, that lack landmarks that can be determined / detected by object recognition and used to determine a mounting location for one or more transducer arrays. The image processing module 1016 may use machine learning to predict and / or estimate a mounting location for one or more transducer arrays, for example, in scenarios where one or more portions of the one or more transducer arrays are not present and / or not represented in the multiple images. The image processing module 1016 may include a trained machine learning model that can estimate / predict the overall shape, configuration, and / or mounting of the transducer array when only one or more portions of the transducer array are present and / or represented in the multiple images. The estimated shape, configuration, and / or mounting location of the one or more transducer arrays may be combined with the mounting location of the one or more transducer arrays determined from object recognition to determine the overall shape, configuration, and / or mounting of the one or more transducer arrays. The image processing module 1016 may assign the estimated points / coordinates to an estimated shape, configuration, and / or mounting position of one or more transducer arrays.

[0095] The image processing module 1016 may use the estimated shape, configuration, mounting position of the one or more transducer arrays, and / or one or more landmarks as reference points for coordinate axes relative to a coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, world coordinates, etc.). For example, the one or more landmarks may define a location in space (translation values) that can be used with a transformation and / or projection matrix to determine a 3D point representing the one or more landmarks in 3D space. A 4x4 matrix may be used to represent a coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, etc.) and to transform the 3D point from a coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, world coordinates, etc.) related to the second user device 1026 to a coordinate system (e.g., a 3D coordinate, etc.) related to the medical image data. For example, the 3D point (e.g., coordinate) may be transformed into and / or associated with 3D coordinates of and / or associated with one or more medical images. The one or more medical images may be received from the user device 1020.

[0096] Information / data identifying the user and / or parts of the user's body may be transmitted along with the image data to the patient support module 1001 (image processing module 1016). After the user is identified, the image processing module 1016 may access / obtain a patient model associated with the user, such as a patient model created by the patient modeling application 608.

[0097] The patient support module 1001 may include an image registration module 1017. Image registration may register image data to a three-dimensional transducer array map (e.g., a patient model combined with a final transducer array layout map) generated / output by the patient modeling application 608. For example, in some cases, the image registration module 1017 may determine a relationship between a user coordinate system, such as a coordinate system based on a vantage point of the user and / or user device 1020 (e.g., a vantage point of the imaging module 1021), a coordinate system of an object (e.g., a user) to which one or more transducer arrays are to be applied, and a coordinate system for the three-dimensional transducer array map. The image registration module 1017 may align, fix, and / or stabilize the three-dimensional transducer array map with a center of view associated with the vantage point of the user and / or user device 1020 and an image of the object to which one or more transducer arrays are to be applied based on the principal axis relationship between the respective coordinate systems. In some cases, the image registration module 1017 may register the image data to the three-dimensional transducer array map by associating landmarks included with the image data with landmarks shown on the three-dimensional transducer array map. The landmarks may include physical markers such as the user's nose, mouth, ears, arms, and / or the like. The landmarks may be determined by the image processing module 1016 based on, for example, object recognition and / or the like, and provided to the image registration module 1017 for image registration. The image registration module 1017 may register the image data to the three-dimensional transducer array map based on an affine transformation method and / or a surface analysis method in which one or more surface matching algorithms are applied to the image data and the rigid surfaces of one or more objects identified in the three-dimensional transducer array map.For example, a collection of points (e.g., a point cloud, etc.) may be extracted from a contour in the image data, and a collection of points (e.g., a point cloud, etc.) may be extracted from a contour in the three-dimensional transducer array map. An iterative nearest neighbor algorithm and / or a correspondence matching algorithm may be applied to both collections of points. The image registration module 1017 may register the image data to the three-dimensional transducer array map based on any method and / or technique.

[0098] In some cases, the three-dimensional transducer array map may include and / or be associated with geometric and / or dimensional information (e.g., shape, size, etc.) for one or more transducer arrays (and / or transducer array supporting devices such as patches, disks, and / or the like) to be placed at positions (optimized positions) on the user based on the three-dimensional transducer array map. The registered image data (e.g., video images registered to the three-dimensional transducer array map, etc.) and the geometric and / or dimensional information (e.g., shape, size, etc.) for the one or more transducer arrays (and / or transducer array supporting devices such as patches, disks, and / or the like) may be provided to a graphics rendering module 1019, which generates a graphic guide along with the registered image data. The graphic guide may include a representation of one or more transducer arrays (and / or transducer array supporting devices such as patches, disks, and / or the like) shown at positions (e.g., optimized positions) on the user based on the three-dimensional transducer array map.

[0099] The registered image data and associated graphic guides may be provided to the image rendering module 1024. The image rendering module 1024 may use the registered image data and associated graphic guides to generate composite data. The composite data may include a three-dimensional transducer array map (and associated graphic guides) combined (e.g., superimposed, overlaid, etc.) with the image data. In another example, the combined data may include actual placement / locations of one or more transducer arrays as determined and / or indicated by three-dimensional coordinates associated with an anatomical coordinate system, as well as optimized (e.g., recommended, etc.) transducer array placement positions indicated by the 3D transducer array layout map. The second user device 1026 may cause display of the composite data (in real time), for example, via the interface module 1028. For example, the placement / locations of one or more transducer arrays may be displayed (e.g., superimposed, overlaid, etc.) together with the optimized (e.g., recommended, etc.) transducer array placement positions. In some cases, the arrangement / position at which one or more transducer arrays are placed may be displayed (e.g., superimposed, overlaid, etc.) along with a representation of the transducer array patch, disk, and / or the like at an optimized (e.g., recommended, etc.) transducer array placement position.

[0100] Additionally, image registration module 1017 may register 3D coordinates associated with the anatomical coordinate system (e.g., 3D points transformed from the image data) to the 3D transducer array layout map. For example, image registration module 1017 may determine coordinates of various landmarks indicated by the image data that has been transformed to the anatomical coordinate system. Image registration module 1017 may determine coordinates of one or more landmarks indicated by the 3D transducer array layout map and / or coordinates of one or more transducer arrays indicated by the 3D transducer array layout map. Image registration module 1017 may determine that the transformed coordinates of various landmarks indicated by the image data (e.g., transformed 3D points from the image data) correspond to coordinates of one or more landmarks and / or transducer arrays indicated by the 3D transducer array layout map.

[0101] In some cases, the image registration module 1017 may determine a relationship between the anatomical coordinate system (e.g., the transformed 3D points from the image data) and a coordinate system for the 3D transducer array layout map. The image registration module 1017 may align, fix, and / or stabilize the 3D transducer array layout map with respect to the anatomical coordinate system (e.g., the transformed 3D points from the image data) based on a center of view associated with a vantage point / or viewpoint image included with the image data and a principal axis relationship between the respective coordinate systems. In some cases, the image registration module 1017 may register the 3D coordinates associated with the anatomical coordinate system (e.g., the transformed 3D points from the image data) to the 3D transducer array layout map based on an affine transformation method and / or a surface analysis method in which one or more surface matching algorithms are applied to rigid surfaces of one or more objects identified in the image data and the 3D transducer array layout map. For example, a collection of points (e.g., a point cloud, etc.) may be extracted from a contour in the image data, and a collection of points (e.g., a point cloud, etc.) may be extracted from a contour in the 3D transducer array layout map. An iterative nearest neighbor algorithm and / or a correspondence matching algorithm may be applied to both collections of points. The image registration module 1017 may register 3D coordinates associated with an anatomical coordinate system (e.g., 3D points transformed from the image data) to the 3D transducer array layout map based on any method and / or technique.

[0102] For example, in some cases, the patient support module 1001 (e.g., the image processing module 1016, the image registration module 1017, etc.) may determine one or more landmarks indicated by the medical image data associated with the user. A projection matrix may be used to determine a 2D representation of the one or more landmarks indicated by the medical image data. The patient support module 1001 may determine, for example, using object recognition, one or more landmarks indicated by the first image data received from the user device 1020 and one or more landmarks indicated by the second image data received from the second user device 1026. The patient support module 1001 may determine that the 2D representations of the one or more landmarks indicated by the first image data correspond to one or more landmarks indicated by the second image data. The patient support module 1001 may determine a representation of the one or more landmarks indicated by the image data received from the second user device 1026 in three-dimensional (3D) space based on the correspondence between the 2D representations of the one or more landmarks indicated by the first image data and the one or more landmarks indicated by the second image data. Representations of one or more landmarks indicated by the second image data received from the second user device 1026 in three-dimensional (3D) space may then be associated with and / or registered to a 3D transducer array layout map including recommended placement positions for the transducer array.

[0103] As described, an avatar may be a generic / replica representation of a user and / or a part of the user's body, such as a generic image, a replica image, a wireframe / stick image, a virtual image, and / or the like. For example, the user device 1020 via the interface module 1022 and / or the second user device 1026 via, for example, the interface module 1028, may display the avatar. In some cases, the avatar may be displayed as a static (e.g., non-moving) image representing the user and / or a part of the user's body. In some cases, the user's tracked points may be mapped to the avatar, and one or more kinetic algorithms may be used to cause the avatar to mirror, represent, generalize, and / or perform similar operations on the user based on the image data.

[0104] FIG. 11A illustrates exemplary image data (e.g., video) captured by a user device. A video image 1100 of an area of interest (e.g., the user's head) for transducer array placement on a user may be captured by one or more cameras and displayed to the user via the user device, e.g., in real time. For example, in some instances, the video image 1100 may include image data captured by different cameras (imaging modules) associated with each of one or more user devices. FIG. 11B shows an exemplary avatar 1101 that may be used for assisted transducer array placement generated from the video image 1100. The avatar 1101 may be displayed as a static (e.g., non-moving) avatar representing the user and / or a portion of the user's body. For example, the avatar 1101 represents the user's head as depicted by the video image 1100. In some cases, the user's tracked points may be mapped to an avatar, and one or more kinetic algorithms may be used to cause the avatar to mirror, represent, generalize, and / or perform similar operations on the user based on the image data, such as movements associated with transducer array placement and / or the like.

[0105] FIG. 12A shows exemplary image data (e.g., video) that may be used for assisted transducer array placement. A video image 1200 of a region (e.g., a user's head) of interest for transducer array placement on a user (e.g., the user's head) may be captured by one or more cameras and displayed to the user via a user device, e.g., in real time. FIG. 12B shows an exemplary three-dimensional transducer array map 1201 that may be used for assisted transducer array placement. The three-dimensional transducer array map may include one or more graphic guides. The graphic guides may indicate the placement of an object associated with TTFields treatment to be placed / positioned on the user. For example, graphic guide 1203 may be an outline of a transducer array patch placed in a predetermined location (optimized position) on the three-dimensional transducer array map 1201 for effective TTFields treatment. Graphic guides 1204 and 1205 may indicate the placement of transducers to be placed on the user for effective TTFields treatment.

[0106] 12C shows an example of composite data 1206 presented with actual images and / or realistic depictions of a patient / subject and / or a portion of the patient / subject's body. The composite data 1206 may be displayed to a user via a user device, for example, in real time, to assist the user with transducer array placement. In one example, the composite data includes one or more transducer placement locations overlaid on one or more recommended transducer placement locations. In a more specific example, the composite data includes a three-dimensional (3D) model showing the one or more transducer placement locations and the one or more recommended transducer placement locations.

[0107] 12D shows another example of composite data 1207 presented on a surrogate image (e.g., an avatar) of a patient / subject and / or a portion of the patient / subject's body. The composite data 1207 may be displayed to a user (e.g., via a second user device 1026) in real time, for example, to assist the user with transducer array placement. The composite data 1207 may include a three-dimensional transducer array map 1201 superimposed / overlaid on an avatar 1101.

[0108] Object recognition and tracking (e.g., performed by image processing module 1016, etc.) may be used to identify objects in the image data represented by the graphical guide, such as transducer arrays, transducer array patches, and / or transducer array mounting components (e.g., disks, tapes, etc.), and / or the like. For example, object recognition and tracking may be used to track the movements of a user when placing (or attempting to place) an object represented by the graphical guide on a part of the user's body. In some cases, audible (voice) instructions (e.g., via interface module 1028, etc.) may be provided to the user to guide the user's movements when placing (or attempting to place) an object represented by the graphical guide on a part of the user's body. In FIG. 12D , in some cases, the movements of avatar 1101 may mirror the movements of the user. For example, movements made by the user when placing a transducer array in one or more positions may be mirrored by avatar 1101. In some cases, the avatar 1101 and / or composite data 1207 may remain entirely static (non-moving), with only one or more portions of the composite data 1207, such as the depicted transducer array and / or graphic guide, mirroring / representing the user's movements, such as the movement of the transducer array as the transducer array is placed in one or more positions.

[0109] Feedback and / or confirmation may be provided to the user via second user device 1026 to indicate the placement of the object represented by the graphical guide on (the skin surface of) the user. For example, the placement (or attempted placement) of the transducer array patch on the location on the user indicated by graphical guide 1203 and / or the placement (or attempted placement) of the transducer on the location on the user indicated by graphical guides 1204 and 1205 may cause instructions to be given to the user. In some cases, the graphical guide may be color-coded to indicate the placement of the object represented by the graphical guide on the user. For example, the graphic guide may be represented in yellow. If the object represented by the graphical guide is properly placed, the graphic guide may transition to green, and if the object is not properly placed, the graphic guide may transition to red. In some cases, an audible indicator / notification may be provided to the user to indicate proper and / or improper placement of the object represented by the graphical guide.

[0110] The proper and / or improper placement of an object represented by the graphic guide may be based on one or more tolerance thresholds. In some cases, an object represented by the graphic guide placed on the user at a position indicated by the graphic guide may be determined to be within or out of a target metric range for the position indicated by the graphic guide, for example, by object recognition and correlation of a coordinate system (e.g., the user's coordinate system, a coordinate system relative to a three-dimensional transducer array map, etc.). In some cases, one or more sensing components, such as an accelerometer, gyroscope, tactile sensor, global positioning sensor, and / or the like, configured with the object represented by the graphic guide (e.g., a transducer array patch, etc.), may be used to provide data / information that can be used to determine the placement / position of the object relative to the graphic guide. The placement / position of the object relative to the graphic guide may be compared to one or more placement / position thresholds, thereby determining the proper and / or improper placement of the object.

[0111] 13A-13D show an example for inductive transducer placement for TTFields. FIG. 13A shows an example system 1300 for determining and / or capturing image data that can be used for inductive transducer array placement. The second user device 1026 may capture multiple images of the user 1301, such as images of the user's head and / or any other part of the user's body where TTFields treatment is to be administered. The transducer arrays may be placed at different locations on the user 1301. For example, transducer arrays 1302 and 1303 may be placed on the user's 1301's head.

[0112] To determine whether the transducer arrays 1302 and 1303 are positioned to promote optimal effectiveness of TTFields treatment, the second user device 1026 may capture multiple images of the user 1301 depicting where the transducer arrays 1302 and 1303 are positioned relative to the user 1301. The multiple images may be taken for multiple vantage points, viewpoints, and / or the like. For example, the second user device 1026 may capture images from positions 1304, 1305, 1306, and 1307.

[0113] As described, image data associated with and / or indicative of a plurality of images may include data / information extracted from and / or associated with the plurality of images (e.g., features, data indicative of one or more recognized objects, coordinate data / information, etc.). For example, the image data may include data indicative of one or more landmarks and / or tracking points, such as anatomical landmarks and / or visual / artificial landmarks. Anatomical landmarks may include body locations (e.g., head, bones / ligaments, joints, etc.) and / or facial expression points (e.g., eyes, nose, eyebrows, etc.). For example, anatomical landmark 1308 may include the root of the user's 1301 nose, and anatomical landmark 1309 may include the user's 1301 ear hair. Visual / artificial landmarks may include one or more indicators (e.g., stickers, marks / removable tattoos, objects, etc.) placed at one or more locations / positions on the user and / or a portion of the user's body. For example, the landmark 1310 may include an indicator (e.g., a sticker, mark / removable tattoo, object, etc.) placed on the transducer array 1302 so that the transducer array 1302 can be determined / identified from the image data.

[0114] The one or more landmarks may be used as reference points for coordinate axes for a coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, etc.) for the second user device 1026. The coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, etc.) for the user device 1026 may be used to generate and / or determine 3D points and / or coordinates that may be associated with additional image data associated with the user 1301, such as medical image data. The medical image data may include a volumetric and / or three-dimensional (3D) representation of the user 1301 and / or a portion of the user's 1301's body (e.g., head, etc.) that is used to determine a transducer array layout map. The medical image data may include magnetic resonance imaging (MRI) data, X-ray computed tomography (X-ray CT) data, single photon emission computed tomography (SPECT) image data, positron emission tomography (PET) data, and / or the like, associated with the user 1301.

[0115] To associate 3D points derived from the image data associated with the user with one or more medical images associated with the user, the second user device 1026 may generate and / or determine data / information associated with the image data, such as a device identifier, a user identifier, user information, and / or the like. The device identifier, user identifier, user information, and / or the like may be transmitted along with the image data to the patient support module 1001 and used to determine / identify additional image data associated with the user 1301, such as medical image data. 3D points indicative of one or more resting positions for one or more transducer arrays, derived from the image data associated with the user, may be transmitted from the user device 1026 to the patient support module 1001. The 3D points indicative of one or more resting positions for one or more transducer arrays may be associated with the medical image data. In some cases, the image data and / or data / information associated with the image data may be transmitted to the patient support module 1001. The patient support module 1001 may determine 3D points indicative of one or more resting positions for one or more transducer arrays and associate the 3D points with the medical image data.

[0116] In one example, one or more landmarks from the image data may be used as reference points for coordinate axes of a coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, etc.) for the user device 1026. The coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, etc.) for the user device 1026 may be used to generate and / or determine 3D points and / or coordinates. The image processing module 1016 may use the shape, configuration, mounting position, and / or one or more landmarks of one or more transducer arrays as reference points for coordinate axes for a coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, world coordinates, etc.) for the second user device 1026.

[0117] One or more landmarks represented in 3D space may represent and / or be associated with actual mounting positions for one or more transducer arrays (e.g., transducer arrays 1302 and 1303, etc.), which may be compared to optimized transducer array mounting positions indicated by the 3D transducer array layout map.

[0118] The patient support module 1001 may use data / information associated with the image data (e.g., device identifier, user identifier, user information, coordinate data / information, etc.) to determine a transducer array layout map including optimized transducer array placement positions associated with the user. The optimized transducer array placement positions may be determined from one or more TTFields treatment / therapy simulations performed based on one or more medical images associated with the user. The optimized transducer array placement positions may be recommended to the patient / subject, for example, to promote optimal effectiveness of the TTFields treatment / therapy. For example, the actual placement / position of one or more transducer arrays may be displayed (e.g., superimposed, overlaid, etc.) along with the optimized (e.g., recommended, etc.) transducer array placement positions.

[0119] 13B shows an example representation 1320 of image data used to guide transducer array placement. The image data determined / captured by the second user device 1026 may be represented as a static (e.g., non-moving) or dynamic image of the user 1301 of FIG. 13A and / or a portion of the user's 1301 body. For example, an avatar 1321 may represent the user 1301. To alleviate any privacy concerns and / or user objections associated with communicating image data depicting "sensitive areas," such as scarred areas, blemishes, genitalia, and / or the like, the user 1301 may be represented by the avatar 1321. As shown, various landmarks (e.g., landmark 1310, anatomical landmark 1309, etc.), as well as the transducer arrays 1302 and 1303, are represented in the representation 1320.

[0120] 13C and 13D show exemplary representations of surface-based registration. Image processing module 1016 may use image data of user 1301 depicting a portion of the user's body, such as the head, to determine a plurality of points 1331 (e.g., a data set, etc.) indicative of the facial skin surface of user 1301. Surface 1332 represents the skin surface extracted from medical image data associated with user 1301. FIG. 13C shows the initial positions of points 1331, for example, as determined by image processing module 1316. FIG. 13D shows points 1331 after they have been registered to surface 1332, for example, by image registration module 1017. Registration may be performed, for example, using an iterative nearest neighbor algorithm and / or the like.

[0121] The patient support module 1001 may determine that the actual placement / location of one or more transducer arrays does not match the optimized (e.g., recommended, etc.) transducer array placement locations. For example, based on comparing the 3D coordinates associated with the anatomical coordinates with the optimized transducer array placement locations indicated by the 3D transducer array layout map, the patient support module 1001 may determine a variance of at least one of the one or more placement locations for the one or more transducer arrays from at least one of the optimized (e.g., recommended, etc.) transducer array placement locations.

[0122] 14A-14C show an example for resolving / compensating for variance. FIG. 14A is an example of a visual notification 1430 that may be used to guide transducer array placement. The placement / location where the transducer array electrodes will be placed on the user and the optimized (e.g., recommended, etc.) transducer array placement location may be displayed as a colored mesh on a volumetric representation 1400 of the user and / or a portion of the user's body determined from medical imaging data (e.g., MRI data, etc.) associated with the user (e.g., user 1301). The placement / location where the transducer array electrodes will be placed may be represented by a gray circle 1401, and the optimized (e.g., recommended, etc.) transducer array placement location may be represented by a black circle 1402. The notification may visually instruct the user to lower and pull the transducer array forward when placed on the surface of the skin so that the placement / position of the transducer array electrodes matches the optimized (e.g., recommended, etc.) transducer array placement position.

[0123] 14B is an example of a visual notification 1431 that may be used to guide transducer array placement. The placement / position of the transducer array electrodes on the user and the optimized (e.g., recommended, etc.) transducer array placement position may be displayed on a volumetric representation 1400 of the user and / or a portion of the user's body determined from medical imaging data (e.g., MRI data, etc.) associated with the user (e.g., user 1301, etc.). The placement / position of the transducer array electrodes may be represented by a gray circle 1401, and the movement of the transducer array required to cause the placement / position of the transducer array electrodes to match the optimized (e.g., recommended, etc.) transducer array placement position may be indicated by one or more directional arrows, such as arrow 1403. The arrow 1403 may visually instruct the user to lower and pull the transducer array forward when placing it on the surface of the skin so that the placement / position of the transducer array electrodes matches the optimized (e.g., recommended, etc.) transducer array placement position.

[0124] 14C is an example of a notification 1432 that may be used to guide transducer array placement. The required transducer array movement to cause the placement / position of the transducer array electrodes to match an optimized (e.g., recommended, etc.) transducer array placement position may be indicated by a text notification 1432. The notification 1432 may inform / instruct the user that the placement / position of the transducer array electrodes should be moved in one or more directions. For example, the text notification 1432 may include instructions related to the transducer array (e.g., TA2) indicating "shift 2 cm toward the base and 1 cm toward the face." In some instances, the notification 1432 may include additional data / text encouraging the user to follow the instructions included with the notification 1432 that presents / explains a benefit, such as "moving the transducer array 2 cm forward is expected to improve treatment by 10%."

[0125] 15 is a flowchart of an exemplary method 1500 for guiding transducer array placement. At 1510, a user device (e.g., a smartphone, mobile device, computing device) may capture multiple images from different vantage points and / or viewpoints of a portion of a patient / subject's body onto which one or more transducer arrays are placed for TTFields therapy / treatment. The multiple images may capture the placement positions of the one or more transducer arrays.

[0126] Points and / or coordinates associated with a coordinate system (e.g., a 2D coordinate system, a 3D coordinate system, etc.) for multiple images captured by a user device may be converted into 3D points and / or coordinates (if they are not already 3D points and / or coordinates). A transformation / projection matrix may be used to convert points / coordinates in a 2D coordinate system for multiple images captured by a user device into 3D points / coordinates. For example, object recognition and / or the like may be used to determine / identify one or more anatomical landmarks represented by the multiple images. Points and / or coordinates associated with one or more anatomical landmarks may be converted into 3D points / coordinates. In some cases, one or more transducer arrays may be used as one or more landmarks and / or may include one or more artificial landmarks. For example, one or more transducer arrays may include one or more design attributes (e.g., grooves, depressions, ridges, etc.) that can be used as one or more landmarks (artificial landmarks). Points and / or coordinates associated with one or more landmarks associated with one or more transducer arrays may be converted into 3D points / coordinates. In some cases, the images may include one or more additional artificial landmarks, such as stickers and / or removable tattoos placed on the user, and the points and / or coordinates associated with the one or more artificial landmarks may be converted into 3D points / coordinates.

[0127] Data / information indicating 3D points / coordinates associated with one or more anatomical landmarks derived from a coordinate system for multiple images captured by the user device may be transmitted to a computing device and / or patient support system for analysis, such as the patient support module 1001.

[0128] Identification information (e.g., device identifier, user identifier, user information, etc.) included with the data / information indicating 3D points / coordinates associated with one or more transducer arrays and / or one or more landmarks may also be transmitted to a computing device and / or system (e.g., patient support module 1001).

[0129] At 1520, the computing device and / or patient support system may use the identification information to determine medical image data, such as MRI data, associated with the patient / subject. The MRI data is being used for TTFields therapy / treatment planning for the patient / subject. The MRI data may include a volumetric representation of a body part of the patient / subject. The MRI data may include 3D coordinates. Object recognition and / or the like may be used to determine anatomical landmarks in the MRI data that correspond to anatomical landmarks from the multiple images. 3D points and / or coordinates associated with anatomical landmarks in the MRI data that correspond to anatomical landmarks from the multiple images may be determined.

[0130] A point-based registration of anatomical landmarks from the multiple images with corresponding anatomical landmarks in the MRI data may be performed at 1530. Any method may be used to register 3D points and / or coordinates associated with anatomical landmarks from the multiple images to 3D points and / or coordinates associated with anatomical landmarks in the MRI.

[0131] At 1540, after registering the 3D points and / or coordinates associated with anatomical landmarks from the multiple images to the 3D points and / or coordinates associated with anatomical landmarks in the MRI, all coordinates associated with the coordinate system for the multiple images captured by the user device may be converted to coordinates of the MRI data. As such, any objects contained within the multiple images, such as one or more transducer arrays, may be represented with a volumetric representation of a portion of the patient / subject's body. Coordinates indicating the placement / location at which the one or more transducer arrays are placed may be used to represent the one or more transducer arrays with a volumetric representation of the portion of the patient / subject's body. Coordinates indicating an optimized (e.g., recommended, etc.) transducer array placement location determined from a previous analysis of the MRI data may be used to represent the optimized (e.g., recommended, etc.) transducer array placement location with a volumetric representation of the portion of the patient / subject's body.

[0132] At 1550, the placement / position at which the one or more transducer arrays will be placed may be compared to an optimized (e.g., recommended, etc.) transducer array placement position. For example, the placement / position at which the one or more transducer arrays will be placed may be displayed (e.g., superimposed, overlaid, etc.) with the optimized (e.g., recommended, etc.) transducer array placement position. In some cases, the placement / position at which the one or more transducer arrays will be placed may be displayed (e.g., superimposed, overlaid, etc.) with a representation of a transducer array patch, disk, and / or the like at the optimized (e.g., recommended, etc.) transducer array placement position.

[0133] FIG. 16 is a flowchart illustrating another example of guided transducer array placement for TTFields. At 1620, image data is determined to determine a transducer array map. At 1620, image data (e.g., video data, static / still images, dynamic / interactive images, etc.) associated with a body part of a subject is determined. The subject (user) may use one or more cameras to capture video images of a body part of the subject, such as video images of the subject's head, torso, and / or the like. In some cases, method 1600 may include determining an avatar based on the image data. The avatar may be a representation of the subject's body or one or more of the subject's body parts. In some cases, the avatar may be a static representation of the subject's body or one or more of the subject's body parts. In some cases, the avatar may be one or more dynamic (e.g., moving, mirrored, etc.) representations of the subject or the subject's body parts.

[0134] At 1630, the image data is registered to a three-dimensional (3D) model of a portion of the subject's body, which may include one or more locations indicated by the transducer array map. In some cases, registering the image data to the 3D model may cause a corresponding portion of an avatar representing the image data to be registered to the 3D model.

[0135] At 1640, generating the composite data includes the image data and one or more representations of a transducer array associated with the one or more locations indicated by the transducer array map. In some cases, the composite data may include an avatar and one or more representations of a transducer array associated with the one or more locations indicated by the transducer array map.

[0136] The composite data may include one or more representations of a transducer array associated with one or more locations indicated by the transducer array map overlaid on a video image (or avatar), such as a video image of a portion of the subject's body. In some cases, method 1600 may include causing a display of the composite data.

[0137] In some cases, method 1600 may include determining that the positions of the one or more transducer arrays and the one or more locations indicated by the transducer array map satisfy a tolerance threshold. Determining that the positions of the one or more transducer arrays and the one or more locations indicated by the transducer array map satisfy a tolerance threshold may be based on one or more of object recognition or object tracking. In some cases, method 1600 may include, based on the tolerance threshold condition being met, sending a notification indicating that the positions of the one or more transducer arrays and the one or more locations indicated by the transducer array map are aligned (e.g., the tolerance threshold condition is met) and / or that the one or more transducer arrays are correctly (e.g., accurately, effectively, etc.) placed on the subject. The notification may be an audible notification (e.g., a beep, chirp, or other sound) and / or a visual notification (e.g., displayed on a display along with the composite data, etc.). In some cases, method 1600 may include causing a color change of one or more representations of the transducer array based on the tolerance threshold condition being met. The color change may indicate that the positions of one or more transducer arrays are aligned with one or more positions indicated by the transducer array map (e.g., that an acceptance threshold condition is met, etc.) and / or that one or more transducer arrays are correctly (e.g., accurately, effectively, etc.) placed on the subject.

[0138] 17 is a flowchart illustrating another example of inductive transducer array placement. At 1710, a three-dimensional (3D) model of a portion of a subject's body is determined. At 1720, a transducer array map is determined based on the 3D model, and the transducer array map indicates one or more locations on the 3D model. At 1730, an image of the subject's body portion is received. The subject (user) may use one or more cameras to capture images (e.g., video images, static / still images, dynamic / interactive images, etc.) of the subject's body portion, such as images of the subject's head, torso, and / or the like.

[0139] At 1740, it is determined that the image corresponds to a 3D model. In some cases, object recognition and / or facial recognition may be used to identify a subject from the image. The identified subject may be associated with a predetermined 3D model. In some cases, determining that the image corresponds to a 3D model may include determining one or more visual landmarks associated with the image, determining one or more visual landmarks associated with the 3D model, and determining that the one or more visual landmarks associated with the image correspond to one or more visual landmarks associated with the 3D model. Determining that the one or more visual landmarks associated with the image correspond to one or more visual landmarks associated with the 3D model may include determining that each visual landmark of the one or more visual landmarks associated with the image and a respective visual landmark of the one or more visual landmarks associated with the 3D model meets a correlation threshold.

[0140] At 1750, based on determining that the image corresponds to the 3D model, a composite image is generated that includes the image, the 3D model, and one or more images of the transducer array associated with the one or more locations. In some cases, method 1600 may include causing display of the composite image.

[0141] 18 is a flowchart illustrating another example of guided transducer array placement. At 1810, two-dimensional (2D) image data associated with a body part of a subject is received, the 2D image data indicating one or more placement positions for one or more transducer arrays. Receiving the 2D image data may include receiving the 2D image data from a user device (e.g., a smart device, a mobile device, an image capture device, a second user device 1026, etc.). The 2D image data may include and / or be derived from multiple images, each image of the multiple images associated with a different vantage point on the body part of the subject. The one or more placement positions for the one or more transducer arrays may include one or more actual and / or real-time placement positions for the one or more transducer arrays. In some cases, the image data may include an avatar associated with the body part of the subject.

[0142] At 1820, representations of one or more mounting positions for one or more transducer arrays in three-dimensional (3D) space are determined based on the 2D image data. Determining the representations of one or more mounting positions for one or more transducer arrays in 3D space may include determining one or more landmarks indicated by the 2D image data, determining representations of the one or more landmarks indicated by the 2D image data in 3D space, determining one or more landmarks indicated by the 3D image data, and determining that the representations of the one or more landmarks indicated by the 2D image data in 3D space correspond to the one or more landmarks indicated by the 3D image data. The one or more landmarks indicated by the 2D image data and the one or more landmarks indicated by the 3D image data may include one or more of anatomical landmarks or artificial landmarks. The artificial landmarks may include one or more of stickers, removable tattoos, or design attributes of the one or more transducer arrays.

[0143] Determining a representation of one or more placement positions for one or more transducer arrays in 3D space may include determining a plurality of coordinates indicated by 2D image data, where the plurality of coordinates represent a surface associated with a portion of the subject's body; determining a representation of the surface in 3D space based on the plurality of coordinates; and determining that the representation of the surface in 3D space corresponds to the surface indicated by the 3D image data.

[0144] Determining a representation of one or more mounting positions for one or more transducer arrays in 3D space may include determining one or more landmarks indicated by the 3D image data, determining a 2D representation of the one or more landmarks indicated by the 3D image data, determining one or more landmarks indicated by the 2D image data, determining that the 2D representations of the one or more landmarks indicated by the 3D image data correspond to the one or more landmarks indicated by the 2D image data, and determining a representation of one or more mounting positions for one or more transducer arrays in three-dimensional (3D) space based on a correspondence between the 2D representations of the one or more landmarks indicated by the 3D image data and the one or more landmarks indicated by the 2D image data. Determining a representation of one or more mounting positions for one or more transducer arrays in 3D space may include applying a projection matrix to one or more 2D coordinates associated with the one or more mounting positions for the one or more transducer arrays. Determining a 2D representation of one or more landmarks indicated by the 3D image data may include applying a projection matrix to one or more 3D coordinates associated with the one or more landmarks indicated by the 3D image data.

[0145] At 1830, the representation of the one or more mounting positions for the one or more transducer arrays in 3D space is compared with one or more recommended mounting positions for the one or more transducer arrays indicated by the 3D image data. Comparing the representation of the one or more mounting positions for the one or more transducer arrays in 3D space with the one or more recommended mounting positions for the one or more transducer arrays indicated by the 3D image data may include displaying the representation of the one or more mounting positions for the one or more transducer arrays in 3D space overlaid with the one or more recommended mounting positions for the one or more transducer arrays indicated by the 3D image data.

[0146] At 1840, a variance of at least one of the one or more mounting positions for the one or more transducer arrays from at least one of the one or more recommended mounting positions for the one or more transducer arrays is determined based on a comparison of the representation of the one or more mounting positions for the one or more transducer arrays in 3D space with the one or more recommended mounting positions for the one or more transducer arrays indicated by the 3D image data. In some cases, method 1800 may include sending a notification based on the variance. The notification may include one or more instructions for correcting the variance. Correcting the variance may include associating new coordinates associated with the one or more mounting positions for the one or more transducer arrays in 3D space with coordinates associated with the one or more recommended mounting positions for the one or more transducer arrays indicated by the 3D image data based on coordinates associated with the one or more mounting positions for the one or more transducer arrays in 3D space.

[0147] 19 is a flowchart illustrating another example of guided transducer array placement. At 1910, first image data is determined based on one or more images associated with a body portion of a subject, the one or more images indicating one or more transducer array placement locations. At 1920, second image data associated with the body portion of the subject is determined, the second image data including one or more recommended transducer array placement locations.

[0148] The first image data is registered to the second image data at 1930. Registering the first image data to the second image data may include determining one or more visual landmarks indicated by the first image data, determining one or more visual landmarks indicated by the second image data, and determining that the one or more visual landmarks indicated by the first image data correspond to the one or more visual landmarks indicated by the second image data.

[0149] Determining that the one or more visual landmarks associated with the first image data correspond to one or more visual landmarks associated with the second image data includes determining that each visual landmark of the one or more visual landmarks associated with the first image data and a respective visual landmark of the one or more visual landmarks associated with the second image data satisfy a correlation threshold.

[0150] At 1940, composite data is generated that includes one or more transducer array placement locations and one or more recommended transducer array placement locations. The composite data may include a three-dimensional (3D) model showing the one or more transducer array placement locations and the one or more recommended transducer array placement locations. The composite data may include one or more transducer array placement locations overlaid on the one or more recommended transducer array placement locations. In some cases, method 1900 may include displaying the composite data.

[0151] 20 is a flowchart illustrating another example of guided transducer array placement. At 2010, two-dimensional (2D) image data associated with a body portion of a subject is received, the 2D image data indicating one or more placement positions for one or more transducer arrays. Receiving the 2D image data may include receiving the 2D image data from a user device (e.g., a smart device, a mobile device, an image capture device, the user device 1020, the second user device 1026, etc.). The 2D image data may include and / or be derived from multiple images, each image of the multiple images associated with a different vantage point on the body portion of the subject. The one or more placement positions for the one or more transducer arrays may include one or more actual and / or real-time placement positions for the one or more transducer arrays. In some cases, the image data may include an avatar associated with the body portion of the subject.

[0152] At 2020, one or more three-dimensional (3D) coordinates representing one or more mounting positions relative to one or more transducer arrays are determined based on the 2D image data. Determining the one or more three-dimensional (3D) coordinates may include applying a transformation / projection matrix to one or more points / coordinates associated with the 2D image data.

[0153] At 2030, a representation of one or more mounting positions for the one or more transducer arrays in 3D space is determined based on the registered 3D coordinates and the 3D image data. At 2040, the representation of the one or more mounting positions for the one or more transducer arrays in 3D space is compared to one or more recommended mounting positions for the one or more transducer arrays represented in 3D space. At 2050, a variance of at least one of the one or more mounting positions for the one or more transducer arrays from at least one of the one or more recommended mounting positions for the one or more transducer arrays is determined based on the comparison of the one or more mounting positions for the one or more transducer arrays in 3D space to the one or more recommended mounting positions for the one or more transducer arrays represented in 3D space.

[0154] 21 is a flowchart illustrating an example of generating variance data. At 2110, a variance between at least one of one or more mounting positions for one or more transducer arrays on a portion of a subject's body indicated by two-dimensional (2D) image data from at least one of one or more recommended mounting positions for one or more transducer arrays indicated by three-dimensional (3D) image data is determined.

[0155] At 2120, dispersion data is generated, the dispersion data indicating the dispersion. In some cases, the dispersion data may include a 3D representation of the subject's body part, the 3D representation including one or more mounting positions for the one or more transducer arrays in 3D space overlaid with one or more recommended mounting positions for the one or more transducer arrays. In some cases, the dispersion data may include one or more images of the subject's body part, the images indicating one or more mounting positions for the one or more transducer arrays and one or more recommended mounting positions for the one or more transducer arrays. In some cases, the dispersion data may include real-time video data overlaid with a representation of the one or more recommended mounting positions for the one or more transducer arrays. The dispersion data may include one or more instructions for correcting the dispersion. At 2130, the dispersion data is transmitted to a user device. The user device may display the dispersion data.

[0156] Exemplary Embodiment 1. An apparatus for assisting in transducer placement on a subject's body to apply tumor treating fields, the apparatus comprising one or more processors and a memory, the memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to: determine first image data based on one or more images associated with a portion of the subject's body, the first image data including one or more transducer placement locations; determine second image data based on the one or more images, the second image data including one or more recommended transducer placement locations; register the first image data to the second image data; and generate composite data including the one or more transducer placement locations and the one or more recommended transducer placement locations.

[0157] Exemplary Embodiment 2. The device of Exemplary Embodiment 1, wherein the processor-executable instructions, when executed by the one or more processors, further cause the device to display the composite data.

[0158] Exemplary Embodiment 3. The apparatus described in Exemplary Embodiment 1, wherein the processor-executable instructions that, when executed by one or more processors, cause the apparatus to register the first image data to the second image data further cause the apparatus to determine one or more visual landmarks indicated by the first image data, determine one or more visual landmarks indicated by the second image data, and determine that the one or more visual landmarks indicated by the first image data correspond to one or more visual landmarks indicated by the second image data.

[0159] Exemplary Embodiment 4. The apparatus of Exemplary Embodiment 1, wherein the composite data includes a three-dimensional (3D) model illustrating one or more transducer placement locations and one or more recommended transducer placement locations, and the composite data includes a variance of at least one of the one or more transducer placement locations from at least one of the one or more recommended transducer placement locations illustrated in the 3D model.

[0160] Exemplary Embodiment 5. The apparatus of exemplary embodiment 4, wherein the processor-executable instructions, when executed by the one or more processors, further cause the apparatus to send a notification of the variance to the user device, the notification including one or more instructions for correcting the variance.

[0161] While the present invention has been disclosed with reference to certain embodiments, numerous modifications, alterations, and variations to the described embodiments are possible without departing from the sphere and scope of the invention, as defined in the appended claims. Accordingly, the present invention should not be limited to the described embodiments, but is intended to have the full scope defined by the language of the following claims and equivalents thereof. [Explanation of symbols]

[0162] 100 devices 102 Electric Field Generator 104 Transducer Array 104a Transducer Array 104b Transducer Array 106 processors 108 Signal Generator 110 Control Software 112 Conductive Lead 114 Output 116 Electrode 118 Flexible circuit board 120 Hypoallergenic Medical Bandages 120a, 120b Hypoallergenic medical adhesive bandages 302 Skin surface 304 Tumor 306 Bone tissue 308 Brain Tissue 310 Alternating Electric Field 600 System 602 Patient Support System 606 Electric Field Generator (EFG) Configuration Applications 608 Patient Modeling Applications 610 Image Data 800 Three-dimensional Array Layout Map 1000 systems 1001 Patient Support Module 1008 processor 1010 memory 1014 Network Interface 1016 Image Processing Module 1017 Image Registration Module 1018 Operating System (O / S) 1019 Graphics Rendering Module 1020 User Devices 1021 Imaging module 1022 Interface Module 1023 Communication Module 1025 Avatar Mapping and Rendering Module 1026 Second User Device 1027 Imaging Module 1028 Interface Module 1029 Communication Module 1100 video images 1101 Avatar 1200 video images 1201 Three-dimensional transducer array map 1203 Graphic Guide 1204, 1205 Graphic Guide 1206 Composite Data 1207 Composite Data 1300 System 1301 users 1302, 1303 Transducer array 1304, 1305, 1306, 1307 positions 1308 Anatomical Landmarks 1309 Anatomical Landmarks 1310 Landmark 1316 Image Processing Module 1320 expression 1321 Avatar 1331 points 1332 Surface 1400 Volumetric Representation 1401 Gray Circle 1402 Black Circle 1403 Arrow 1430 Visual Notifications 1431 Visual Notifications 1432 notifications 1500 ways 1600 methods 1800 methods 1900 method

Claims

1. 1. A method for assisting in transducer placement on a body of a subject for applying a tumor treating electric field, comprising: determining first image data based on one or more images associated with a portion of a subject's body, the first image data including one or more transducer placement locations; determining second image data based on the one or more images, the second image data including one or more recommended transducer placement locations; registering the first image data to the second image data; generating composite data comprising the one or more transducer placement locations and the one or more recommended transducer array placement locations.

2. The method of claim 1 , wherein the composite data includes the one or more transducer placement positions overlaid on the one or more recommended transducer placement positions.

3. The method of claim 1 , wherein the composite data includes a three-dimensional (3D) model illustrating the one or more transducer placement locations and the one or more recommended transducer placement locations.

4. The method of claim 3 , further comprising displaying the composite data including the 3D model showing the one or more transducer placement locations and the one or more recommended transducer placement locations on a user device.

5. The method of claim 1 , wherein the one or more images include a plurality of videos, a plurality of images, an avatar, or a combination thereof.

6. The step of registering the first image data to the second image data includes: determining one or more visual landmarks indicated by the first image data; determining one or more visual landmarks indicated by the second image data; and determining that the one or more visual landmarks indicated by the first image data correspond to the one or more visual landmarks indicated by the second image data.

7. The method of claim 6 , wherein the one or more landmarks include at least one of an anatomical landmark or an artificial landmark.

8. The method of claim 7 , wherein the artificial landmark comprises at least one of a sticker, a removable tattoo, or a design attribute of the one or more transducers.

9. The method of claim 1 , further comprising determining and outputting a variance of at least one of the one or more transducer placement locations from at least one of the one or more recommended transducer placement locations based on the composite data.

10. The method of claim 9 , further comprising sending a notification to a user device regarding the dispersion, the notification including one or more instructions for correcting the dispersion.

11. The method of claim 1 , wherein the one or more transducer placement positions indicated by the first image data include one or more real-time placement positions for one or more transducers.

12. 1. A method for assisting in transducer placement on a body of a subject for applying a tumor treating electric field, comprising: generating a three-dimensional (3D) model of the portion of the subject's body based on the first image data, the 3D model including one or more suggested transducer placement locations; receiving second image data of the portion of the subject's body; determining a representation of the one or more placement positions relative to one or more transducers in three-dimensional (3D) space based on the second image data; comparing the representation of the one or more placement positions for the one or more transducers with the presentation of the one or more recommended transducer placement positions; and determining and outputting a variance of at least one of the one or more recommended transducer placement positions for the one or more transducers from at least one of the one or more recommended transducer placement positions based on the comparison result.

13. The method of claim 12 , further comprising generating composite data including the one or more mounting positions for the one or more transducers and the one or more recommended transducer mounting positions.

14. The method of claim 13 , wherein the composite data includes the one or more transducer placement positions overlaid on the one or more recommended transducer placement positions.

15. The method of claim 13 , wherein the composite data includes the variance of at least one of the one or more mounting positions for the one or more transducers from at least one of the one or more recommended transducer mounting positions.

16. The method of claim 15 , further comprising displaying the composite data including the variance on a user device.

17. 17. The method of claim 16, wherein the display includes at least one visual instruction to correct the variance of at least one of the one or more mounting positions for the one or more transducers from at least one of the one or more recommended transducer mounting positions.

18. The method of claim 12 , wherein the first image data is received from a first user device and the second image data is received from a second user device.

19. The method of claim 12 , wherein the one or more mounting positions for the one or more transducers indicated by the first image data include one or more real-time mounting positions for the one or more transducers.

20. determining one or more visual landmarks indicated by the first image data; determining one or more visual landmarks indicated by the second image data; and determining that the one or more visual landmarks indicated by the first image data correspond to the one or more visual landmarks indicated by the second image data.

21. 1. A method for identifying placement of a transducer array on a body of a subject and generating a tumor treating electric field within the body of the subject, comprising: receiving image data of the subject's body and the transducer array to generate a tumor treating electric field within the subject's body; displaying an image having a representation of the subject, a representation of the transducer array, and a representation of a desired position of the transducer array, the displayed image being based on the received image data; and providing a visual indication in the displayed image when it is determined that the transducer array should be placed at the desired location.

22. the image data of the subject's body includes one or more landmarks on the subject's body; The method comprises:

22. The method of claim 21, further comprising determining a location within the displayed image relative to the representation of the desired position of the transducer array based on the one or more landmarks on the subject's body.

23. 22. The method of claim 21, wherein the representation of the subject's body in the displayed image is an image of the subject's body or an avatar of the subject's body.

24. 22. The method of claim 21, wherein the transducer array is determined to be located at the desired location when the transducer array is located within a threshold of the desired location of the transducer array.

25. 22. The method of claim 21, further comprising providing instructions within the displayed image to guide movement of the transducer array to the desired position.

Images