Phantoms for adaptive radiation therapy

Abstract

The present invention relates to a method of verifying a radiotherapy treatment session. A deformable radiotherapy phantom may be produced using an additive manufacturing process based on medical images of a patient. The deformable phantom may include a dosimeter for measuring radiation dose distribution. Smart materials may allow deformation in response to an applied stimulus. The phantom may be used, among other things, to verify radiation dose distortion, radiotherapy treatment planning, determine a patient's maximum acceptable deformation, verify cumulative accuracy of dose distortion and deformable image registration, and the like.

Description

[0001] This application is a divisional application of the Chinese invention patent application with application number 201980029382.1, application date April 23, 2019, and invention name “Phantom for Adaptive Radiation Therapy”. Technical Field

[0002] The present disclosure relates generally to radiation therapy. More specifically, but not by way of limitation, the present disclosure relates to the use of phantoms for quality assurance testing in radiation therapy. Background Art

[0003] Radiation therapy, also known as radiotherapy, is used to treat tumors and other diseases in mammalian (e.g., human and animal) tissues. In a radiotherapy treatment session, a high-energy beam is applied from an external source toward the patient to produce a collimated radiation beam directed to a target site of the patient. The target can be an area of ​​the patient's body containing a diseased organ or tumor to be exposed to and treated by the radiation beam. The placement and dose of the radiation beam must be accurately controlled to ensure that the target receives the radiation dose prescribed by the physician for the patient. The beam should be arranged so that it minimizes damage to surrounding healthy tissue, commonly referred to as organs at risk (OARs).

[0004] One way to improve the accuracy of beam placement is by acquiring one or more medical images of the patient in the intended treatment position. Such images are called planning images. Planning images are acquired before a radiation therapy session, and typically many days before the treatment session.

[0005] The physician can use the planning images to identify and outline the target and OAR. Outlining can be performed manually, semi-automatically, or automatically. Create a treatment outline, which is usually called a planning target volume (PTV), which includes the target outline plus sufficient margins to take into account microscopic lesions and treatment uncertainties. The radiation dose is prescribed by the physician, and a radiotherapy treatment plan is created that optimally delivers the prescribed dose to the PTV while minimizing the dose to OARs and other normal tissues. The treatment plan can be generated manually by the physician, or it can be automatically generated using optimization techniques. Optimization techniques can be based on clinical and dosimetry indicators and constraints (e.g., maximum, minimum, and average radiation doses to tumors and OARs).

[0006] Treatment courses are developed to deliver a prescribed dose in multiple fractions, with each fraction delivered in a different treatment session. For example, 30 to 40 fractions are typical, but five or even one fraction may be used. These fractions are usually delivered once or in some cases twice per weekday. In some cases, the radiation therapy plan may change throughout the course of treatment to focus more dose in certain areas.

[0007] In each fraction, the patient is placed on a patient support attachment (often called a "treatment couch") of the radiotherapy apparatus and repositioned as closely as possible to the patient's position in the planning image. This is a difficult task to perform accurately in practice because the patient is not a rigid object and the patient's anatomy can move. The fraction-to-fraction movement is often referred to as the inter-fraction movement, while the movement that occurs during the fraction itself is often referred to as the intra-fraction movement.

[0008] Image-guided radiation therapy (IGRT) attempts to address the problem of inter-fraction motion. IGRT involves acquiring one or more medical images of the patient shortly before radiation therapy (commonly referred to as "daily images") and using these images to identify and compensate for inter-fraction motion. In contrast to planning images, which can be acquired on any diagnostic scanner, IGRT images are acquired directly in the treatment room with the patient in the treatment position. To compensate for inter-fraction motion, the IGRT images are compared to the planning images to quantify changes that have occurred in the patient's anatomy since the planning images were generated. For example, the planning images and IGRT images can be analyzed to calculate an overall shift and / or rotation that maps the planning image to the IGRT image. Once the shift and / or rotation has been calculated, the position of the patient support attachment can be adjusted accordingly so that the position of the patient during the treatment session more closely matches the position of the patient when the planning images were acquired.

[0009] Adaptive radiation therapy is another technique that aims to address the problem of inter-fraction motion. Like IGRT, adaptive radiation therapy involves acquiring one or more medical images of the patient shortly before a radiation therapy treatment fraction and using these images to identify and compensate for inter-fraction motion. In adaptive radiation therapy, planning images and images taken shortly before a treatment fraction can be analyzed to generate a deformation vector field (DVF). A DVF is a matrix whose elements are vectors and in which each vector defines a geometric transformation that maps a voxel in the planning image to a corresponding voxel in an image taken shortly before the treatment fraction. The DVF can be used to transform the spatial distribution of the radiation dose specified by the treatment plan in order to compensate for changes in the patient's anatomy that have occurred since the planning images were acquired.

[0010] Shifting the dose distribution in this way may result in the target receiving less than the prescribed dose of drug and / or the OAR being exposed to higher radiation levels than the physician intended. Therefore, there is a need to verify that the shifted dose distribution is clinically effective and safe. Summary of the invention

[0011] A deformable radiotherapy phantom can be produced using an additive manufacturing process based on medical images of a patient. The deformable phantom can include a dosimeter for measuring radiation dose distribution. Smart materials can allow deformation in response to applied stimuli. In particular, the phantom can be used to verify radiation dose distortion, radiotherapy treatment planning, determine the maximum acceptable deformation of a patient, verify the cumulative accuracy of dose distortion and deformable image registration, etc.

[0012] Additional advantages of the disclosure will be set forth in part in the detailed description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.

[0013] 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 of the invention, as claimed. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings, which constitute a part of this specification, illustrate some embodiments and, together with the description, serve to explain the principles of the disclosure.

[0015] Figure 1A , Figure 1B and Figure 1C They are plan view, front view, and side view of the patient's area of ​​interest, respectively.

[0016] Figure 2A It is used for simulation Figures 1A to 1C Perspective view of the phantom of the area of ​​interest shown in .

[0017] Figure 2B It shows that the dose meter is Figure 2A Schematic diagram of the arrangement within the phantom.

[0018] Figure 3 An example of a validation or quality assurance testing method that may use a phantom is shown.

[0019] Figure 4 An example of a method of validating a dose mapping algorithm is shown.

[0020] Figure 5 An example of another authentication method is shown.

[0021] Figure 6A block diagram of an embodiment of an apparatus or machine is shown on which one or more of the methods discussed herein may be implemented, such as for verifying dose distortion, deformable image registration, etc., such as described herein.

[0022] Figure 7 An example of a radiation therapy system is shown.

[0023] Figure 8 An example of a radiation therapy system is shown that can include a radiation therapy output configured to provide a therapy beam. DETAILED DESCRIPTION

[0024] Exemplary embodiments are described with reference to the accompanying drawings. In the drawings, the leftmost one or more digits of a reference number represent the figure in which the reference number appears for the first time. Where convenient, the same reference numerals are used in all drawings to refer to the same or similar parts. Although examples and features of the disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the spirit and scope of the disclosed embodiments. In addition, the words "comprise", "have", "contain", and "include" and other similar forms are meant to be equivalent in meaning and open-ended, because an item or items after any of these words are not meant to be a complete list of such items or items, or are not meant to be limited to the listed one or more items. It should also be noted that, as used herein and in the appended claims, the singular forms "one", "an", and "the" include plural references unless the context clearly indicates otherwise.

[0025] Exemplary embodiments generally relate to the use of phantoms for quality assurance in adaptive radiation therapy. As explained in more detail below, a phantom is manufactured using medical images of a patient, thereby resulting in a phantom that closely reflects the anatomy of a specific patient to be treated by radiation therapy. Multiple dosimeters can be set within the phantom, allowing the radiation dose to be measured at multiple points within the internal volume of the phantom, which in turn enables prediction of the spatial distribution of the dose that the patient will receive. In some embodiments, the phantom is deformable so as to enable simulation of the effects of patient motion on the dose distribution. Multiple such phantoms can be manufactured, each phantom being manufactured using a different medical image of the patient. The dose distribution received by each phantom can be compared in order to verify, for example, a treatment plan for adaptive radiation therapy or a deformable image registration algorithm that is used to generate a deformation vector field for adaptive radiation therapy.

[0026] In the field of radiation therapy, a "phantom" is an object used as a substitute for a patient's body or a part of a patient's body. Phantoms are often used to test radiation therapy treatment plans. For example, a radiation beam can be applied to the phantom according to the treatment plan, and the radiation passing through the phantom can be measured by a detector positioned relative to the beam. The radiation dose received by the phantom can be inferred from the detector measurements. The clinical efficacy and safety of the treatment plan can be determined by comparing the prescribed dose (that is, the dose that the treatment plan intends to deliver) with the dose actually received by the phantom. Therefore, phantoms allow treatment plans to be tested without exposing the patient to radiation.

[0027] A phantom according to the present disclosure will now be described with reference to FIGS. 1 and 2 . Figure 1A , Figure 1B and Figure 1C is a schematic diagram of a patient's region of interest 100 depicted in three mutually orthogonal directions. More specifically, Figure 1A is a plan view of the region of interest 100, Figure 1B is a front view of the region of interest 100, and Figure 1C 1 is a side view of a region of interest 100. The region of interest 100 includes an organ at risk (OAR) 104 and a target 104. It will be understood that FIG. 1 is a very simplified representation of the region of interest and is intended for purposes of explanation only. In practice, the OAR 102 and the target 104 may have highly irregular shapes. Furthermore, in practice, the region of interest 100 may have multiple OARs, other non-target areas, and / or multiple targets.

[0028] According to the present disclosure, a phantom of the region of interest 100 is manufactured using a medical image of the patient. A medical image is a three-dimensional image (also called a volumetric image) composed of a plurality of elements called voxels. Each voxel represents the intensity of the image at a specific point in three-dimensional space. The medical image may be acquired using any suitable imaging modality, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), ultrasound, or single photon emission computed tomography (SPECT). Alternatively, the medical image may be generated by fusing images acquired using two or more different imaging modalities. The medical image used to manufacture the phantom may be an image that has already been acquired for the purpose of radiotherapy itself. For example, a planning image or a daily image may be used to manufacture the phantom. This may avoid the need to acquire images solely for the purpose of manufacturing the phantom.

[0029] The medical image is divided into a target region and at least one non-target region. Segmentation generally refers to the process of assigning labels to voxels in an image to indicate what these voxels represent. Thus, the target region includes a plurality of voxels that are marked as targets 104 to be treated by exposure to radiation. Each non-target region includes a plurality of voxels that are marked as things other than the target 104. For example, a non-target region may include voxels that are marked as organs 102 at risk. A medical image may include one or more organs at risk. As another example, a non-target region may include voxels that are marked as background voxels, i.e., voxels that do not represent the patient's body. The medical image may have been manually segmented (e.g., by a physician, dosimeter, or health care worker) or automatically segmented (e.g., using a program such as ABAS, an automatic segmentation software based on Atlas manufactured by Elekta AB of Stockholm, Sweden).

[0030] The phantom may be manufactured by an additive manufacturing process, such as based on a medical image of a region of interest of the patient. The region of interest may include a target region and a non-target region. The first portion and the second portion of the phantom may each have a corresponding shape defined by the shapes of the target region and the non-target region in the medical image, respectively.

[0031] After imaging, an additive manufacturing process can then be used to create a three-dimensional phantom that simulates the anatomical structures in the three-dimensional medical image. As used herein, the term "additive manufacturing" refers to the process of manufacturing an object in a layer-by-layer manner. According to the American Society for Testing and Materials (ASTM), there are currently seven types of additive manufacturing processes: binder jetting; direct energy deposition; material extrusion, also known as fused deposition modeling; material jetting; powder bed melting; lamination; and photopolymerization. Any suitable one or more of these types of additive manufacturing processes, or any other suitable type of additive manufacturing process that may exist in the future, can be used to manufacture a phantom. In addition, any suitable software tool can be used to convert a three-dimensional medical image into instructions and / or data that can be used by an additive manufacturing device to produce a phantom that replicates the anatomical structures in the medical image.

[0032] Figure 2A It is used for simulation Figures 1A to 1C A perspective view of a phantom 200 of the region of interest shown in FIG. Figure 2AAs can be seen, the phantom 200 is a three-dimensional physical object that represents the anatomical structure of the region of interest. The phantom includes a portion 202 that represents the OAR 102 and a portion 204 that represents the target 104. It will be appreciated that FIG. 2 is a very simplified representation of the phantom 200 and that, in reality, the phantom has a more complex shape that reflects the patient's anatomical structure. In addition, the phantom 200 may include more than Figure 2A More parts are shown in the figure.

[0033] The phantom 200 includes one or more materials having radiation absorption properties similar to or identical to the radiation absorption properties of the materials of the anatomical structures in the region of interest 100. For example, a portion 202 of the phantom 200 may include a material having a density similar to the density of an organ (such as the prostate, bladder, brain, etc.), while a portion 204 of the phantom 200 may include a material having a density similar to the density of a tumor. The phantom 200 can thus be used to predict the radiation dose that will be absorbed by the corresponding anatomical structure of the patient during radiation therapy. The constituent materials of the phantom 200 can be selected based on their radiation absorption properties and their suitability for compatibility with a particular additive manufacturing process. A variety of materials can be combined in order to manufacture a phantom 200 that has desired radiation absorption properties and can be manufactured by a given additive manufacturing process. For example, the portions 202, 204 can be manufactured by forming a hollow polymer shell using additive manufacturing and then filling the shell with a material having a density similar to the density of the corresponding anatomical structures 102, 104.

[0034] In some embodiments, the phantom 200 may be deformable. Deformation of the phantom 200 allows for simulation of movement of the OAR 102 and / or target 104. Possible causes of movement of the OAR 102 and / or target 104 that may be simulated by deformation of the phantom 200 include, for example: physiological processes such as breathing, emptying of the bladder and / or bowels, filling of the bladder and bowels; weight loss or weight gain of the patient; growth of the target 104 due to disease progression; and shrinkage of the target 104 due to successful radiation therapy. By using one or more deformable materials (such as elastomeric materials) to make the phantom and applying forces to the phantom to cause movement of the portions 202, 204, the phantom 200 may be deformed in a manner that accurately reflects actual movement of the OAR 102 and / or target 104. One or both of the portions 202, 204 may be deformable.

[0035] In some embodiments, deformation of the phantom 200 can be achieved by manufacturing the phantom using one or more smart materials. A smart material is a material that exhibits a predictable and controllable change in shape when exposed to an external stimulus. For example, there are smart materials that change shape when exposed to a stimulus such as humidity, temperature, light, electric fields, or magnetic fields. In addition, there are some so-called "4D printing" materials that are smart materials that can be used in additive manufacturing processes. The characteristics of the smart material and / or the stimulus applied thereto (e.g., amplitude, frequency, etc.) can be selected to cause the phantom 200 to deform in a manner that simulates the movement of the OAR 102 and / or the target 104. One or both of the portions 202, 204 can include a smart material.

[0036] The phantom 200 includes a plurality of radiation dosimeters. The dosimeters may be located within the phantom 200. More specifically, the plurality of dosimeters may be distributed throughout the interior volume of the phantom 200. This may allow the radiation dose to be measured at some points in space, thereby allowing the spatial distribution of the dose received by the phantom 200 to be determined. This in turn allows the phantom 200 to be used to accurately predict the dose that will be received by the OARs 102 and the targets 104 during radiation therapy. The dosimeters may also be located on the outer surface of the phantom 200. The dosimeter may include any suitable device capable of measuring radiation dose. For example, the dosimeter may include an electronic dosimeter, such as a metal oxide semiconductor field effect transistor (MOSFET) dosimeter. Alternatively or additionally, the dosimeter may include a thermo-optical dosimeter (TLD), or a chemical substance whose properties (e.g., color) change when exposed to radiation.

[0037] Figure 2B is an example of a dosimeter 206 in Figure 2A Schematic diagram of the arrangement within the phantom 200. Figure 2B Portions 202 and 204 are shown in cross-section to enable the spatial distribution of dosimeters 206 to be seen. Figure 2B As shown in FIG. 1 , a plurality of dosimeters 206 are distributed throughout the interior volume of each portion 202, 204 of the phantom 200. The dosimeters 206 may be evenly distributed throughout the interior volume of the phantom 200. For example, Figure 2B, the dosimeters 206 are located at the nodes of the three-dimensional grid shown by the dashed lines. However, the dosimeters 206 need not be evenly distributed throughout the interior volume of the phantom 200. For example, a greater number of dosimeters 206 per unit volume may be used in areas where it is desired to measure dose with higher spatial resolution (near the boundaries of the OAR 102 and the target 104), and a smaller number of dosimeters 206 per unit volume may be used elsewhere. As another example, deformation of the phantom 200 may result in an uneven distribution of dosimeters. The dosimeters 206 may be automatically positioned in the phantom 200 during the additive manufacturing process, or may be added to the phantom after the additive manufacturing process is completed.

[0038] The phantoms described above can be used for various quality assurance tests. In the field of radiation therapy, quality assurance (QA) generally refers to the process of ensuring that the patient receives the prescribed radiation dose.

[0039] Figure 3 An example of a quality assurance testing method 300 in which a phantom may be used is shown. At 302, a phantom based on a medical image of a region of interest (ROI) of a patient may be manufactured or obtained. The ROI may include target areas and non-target areas to be treated by radiotherapy, such as may include organs at risk (OARs) to be avoided for radiotherapy treatment. The phantom may be produced by 3D printing or other additive manufacturing processes such as those described herein. The phantom may be deformed in a manner such as to resemble a portion of a patient to be subjected to radiotherapy treatment, which may involve positioning or repositioning the patient on a radiation therapy couch or other movement or deformation of the patient such as via breathing, etc. In an example, the phantom may include a plurality of radiation dosimeters included or distributed therein.

[0040] At 304, the phantom may be deformed, for example, to simulate a deformation of at least one or both of a target region or a non-target region of the patient. The deformation may include applying a physical force to the phantom to cause the phantom to deform, such as by compression, stretching, twisting, or otherwise, in a manner similar to an expected, predicted, or measured deformation of a corresponding region of the patient. In an example, the phantom may include a "smart" material that exhibits a shape change when exposed to an external stimulus, in which case deforming the phantom may include applying the external stimulus to the smart material.

[0041] At 306, a distorted radiation dose may be calculated, such as by applying a geometric transformation to a prescribed radiation dose. The prescribed radiation dose may define an expected spatial distribution of radiation to be delivered to the patient's ROI. The prescribed radiation dose may be included as part of a treatment plan for the patient, such as may be created, such as may include using Monte Carlo dose calculation techniques in the Monaco Treatment Planning System (TPS) available from Elekta AB of Sweden. The expected spatial distribution of radiation of the prescribed radiation dose may be transformed in geometric form.

[0042] In an example, the geometric transformation may optionally include applying a deformation matrix that may be generated by: (1) acquiring an image of the phantom before deforming the phantom; (2) acquiring an image of the deformed phantom; and (3) calculating the geometric transformation based on the image of the undeformed phantom and the image of the deformed phantom.

[0043] For example, the image of the undeformed phantom and the image of the deformed phantom may each include a plurality of voxels, and computing the geometric transformation may include performing a deformable image registration to compute a deformation vector field matrix that maps each voxel in the image of the phantom to a corresponding voxel in the image of the undeformed phantom.

[0044] At 308, such as may include using a Monte Carlo dose calculation technique applied to generate a distorted radiation dose, for example, such as using the Monaco Treatment Planning System (TPS) available from Elekta AB of Sweden to generate, create a radiation therapy treatment plan for configuring a radiation therapy device to deliver a distorted radiation dose.

[0045] At 310, measurements of radiation dose distribution received by the deformed phantom may be obtained, such as when delivering radiation to the deformed phantom by operating a radiotherapy device according to a radiotherapy treatment plan. Such measurements may be obtained using a plurality of dosimeters included or distributed in the deformed phantom.

[0046] At 312, the radiation therapy treatment plan can be verified by comparing the measured radiation dose distribution to the prescribed radiation dose. This can include: calculating a similarity or difference metric between the measured radiation dose distribution and the prescribed radiation dose distribution; and confirming the treatment plan when the similarity between the measured radiation dose distribution and the prescribed radiation dose distribution exceeds a specified similarity sufficiency value, or when the difference between the measured radiation dose distribution and the prescribed radiation dose distribution is less than a specified difference sufficiency value. Additionally or alternatively, one or more other metrics can be used to verify the radiation therapy treatment plan, for example, if the aggregate or other radiation exposure of one or more organs at risk (OARs) exceeds a maximum acceptable value.

[0047] Optionally, acts 304 to 312 may be repeated with different deformations applied to the deformable phantom, such as at 304. By verifying at 312 using the different deformations applied at 304, a maximum acceptable deformation of at least one of the target region or the non-target region for which the radiation therapy treatment plan is effective may be determined at 314. For example, when the recurring deformations are gradually increased at 304, a similarity metric between the measured radiation dose and the prescribed radiation dose may eventually drop below a specified acceptable similarity limit, or a difference metric may eventually exceed a specified acceptable difference limit, when the deformation is increased beyond a certain value, such that a previous (acceptable) deformation in the series of repetitively increasing deformations may be considered a maximum acceptable deformation.

[0048] Figure 4An example of a method 400 for validating a dose mapping algorithm is shown. At 402, a first medical image representing an ROI of a patient may be accessed, such as by accessing a medical imaging database, including voxel data obtained using an imaging modality, through an image processing circuit system. At 404, a second medical image may be generated using the first medical image, such as by applying a first deformation vector field to the first medical image to generate the second medical image. At 405A, a first phantom may be obtained, provided, or generated (e.g., such as may include using 3D printing or other additive manufacturing processes), such as based on the first medical image. At 405B, a (deformed) second phantom may be obtained, provided, or generated (e.g., such as may include using 3D printing or other additive manufacturing processes), such as based on the (deformed) second medical image. At 406, a radiation dose distribution received by at least one phantom may be measured, such as in response to radiation delivered to the phantom by, such as operating a radiotherapy device according to a radiotherapy treatment plan. In an example, the at least one phantom may include a first phantom and a second phantom. In an example, at least one phantom, such as one having a plurality of dosimeters included or distributed therein, may be manufactured using 3D printing or other additive processes. At 408, a distorted radiation dose may be calculated using an image processing circuit system, such as by applying a first deformation vector field to a measured radiation dose distribution using a dose warping or mapping technique to be verified. At 410, the accuracy or other properties of the dose warping or mapping technique to be verified may be verified by comparing the calculated dose distribution with a measured radiation dose distribution on the same phantom. This may include calculating a voxel-by-voxel or aggregate composite similarity or difference metric between them, and comparing the similarity or difference metric to a corresponding threshold value to determine whether the metric falls within an acceptable range to verify the accuracy of the dose warping or mapping technique. Additionally or alternatively, a combination of voxel-by-voxel and composite verification may be used, for example, if the difference or error metric of any voxel falls outside a corresponding first acceptable range, or if the composite difference or error metric falls outside a corresponding second acceptable range, the dose warping or mapping technique may be considered invalid. Additionally or alternatively, a more complex set of validation rules may be applied, for example, the statistical measures may be calculated differently for different density regions where a distorted radiation dose distribution is being measured or calculated.For example, such density information may be obtained from medical image data.

[0049] Figure 5 An example of another method 500 for optionally verifying the cumulative accuracy of dose distortion and deformable image registration is shown. Figure 4 Steps 402 to 410 are performed as described.

[0050] At 512, optionally, a second deformation vector field can be generated, such as by performing deformable image registration on the first medical image and the second medical image. The image registration can include mapping individual voxels (eg, each individual voxel) in the first medical image to corresponding voxels in the second medical image.

[0051] At 514 , optionally, a distorted radiation dose distribution may be calculated, such as by applying the second deformation vector field generated at 410 .

[0052] At 516, optionally, a verification of the cumulative accuracy of the calculated warped radiation dose distribution calculated at 414 and the deformable image registration of the first medical image and the second medical image used to generate the second deformation vector field can be performed. The verification can compare the measured radiation dose distribution of 406 with the calculated warped radiation dose calculated at 414 using the second deformation vector field based on the deformable image registration. As explained elsewhere herein, the verification can include calculating a voxel-by-voxel or aggregate composite similarity or difference metric therebetween, and comparing the similarity or difference metric to a corresponding threshold value to determine whether the metric falls within an acceptable range to verify the accuracy of the dose warping or mapping technique. Additionally or alternatively, a combination of voxel-by-voxel and composite verification can be used, for example, if the difference or error metric of any voxel falls outside a corresponding first acceptable range, or if the composite difference or error metric falls outside a corresponding second acceptable range, the dose warping or mapping technique can be considered invalid. Additionally or alternatively, a more complex set of validation rules may be applied, for example, the statistical measures may be calculated differently for different density regions where a distorted radiation dose distribution is being measured or calculated.For example, such density information may be obtained from medical image data.

[0053] Figure 6A block diagram of an embodiment of a device or machine 1000 on which one or more methods discussed herein can be implemented is shown. One or more items of the image processing circuit system described herein can be implemented by machine 1000. Machine 1000 can operate as a standalone device, or can be connected (e.g., networked) to other machines. The image processing circuit system may include one or more items of machine 1000. In a networked deployment, machine 1000 can operate as a server or client machine in a server-client network environment, or as a peer machine in a peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet computer, a set-top box (STB), a personal digital assistant (PDA), a cellular phone, a Web device, a network router, a switch or a bridge, or any machine capable of (sequentially or otherwise) executing instructions that specify the actions to be performed by the machine. In addition, although only a single machine is shown, the term "machine" should also be understood to include any combination of machines that individually or collectively execute a set (or multiple sets) of instructions to perform any one or more methods discussed herein.

[0054] The example machine 1000 may include: processing circuitry 1002 (e.g., a central processing unit (CPU); a graphics processing unit (GPU); an application specific integrated circuit, circuitry such as one or more transistors, resistors, capacitors, inductors, diodes, logic gates, multiplexers, buffers, modulators, demodulators, radios (e.g., transmitting or receiving radios or transceivers), sensors 1021 (e.g., transducers that convert one form of energy (e.g., light, heat, electricity, mechanical or other energy) into another form of energy), etc., or a combination thereof), a main memory 1004 and a static memory 1006, which communicate with each other via a bus 1008. Datums or data associated with the described methods may be stored in such memory or retrieved from such memory and initialized or updated as desired to perform the methods described herein. The machine 1000 (e.g., a computer system) may also include a video display unit 1010 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The machine 1000 may also include an alphanumeric input device 1012 (e.g., a keyboard), a user interface (UI) navigation device 1014 (e.g., a mouse), a disk drive or mass storage unit 1016, a signal generating device 1018 (e.g., a speaker), and a network interface device 1020.

[0055] The disk drive unit 1016 may include a machine-readable medium 1022 on which is stored one or more sets of instructions and data structures (e.g., software) 1024 that are implemented or utilized by any one or more of the methods or functions described herein. During execution of the instructions 1024 by the machine 1000, the instructions 1024 may also reside, in whole or in part, within the main memory 1004 and / or within the processor 1002, which also constitute machine-readable media.

[0056] The illustrated machine 1000 may include an output controller 1028. The output controller 1028 manages the flow of data to and from the machine 1000. The output controller 1028 may sometimes be referred to as a device controller, which has software that interacts directly with the output controller 1028 (referred to as a device driver).

[0057] Although the machine-readable medium 1022 is shown as a single medium in the embodiments, the term "machine-readable medium" may include a single medium or multiple media (e.g., a centralized or distributed database, and / or associated caches and servers) storing one or more instructions or data structures. The term "machine-readable medium" should also be considered to include tangible media that can store, encode, or carry instructions executed by a machine and cause the machine to perform any one or more methods of the present invention, or that can store, encode, or carry data structures used by or associated with such instructions. Therefore, the term "machine-readable medium" should be considered to include, but is not limited to, solid-state memory and optical and magnetic media. Specific examples of machine-readable media include: non-volatile memory, including, by way of example, semiconductor storage devices, such as erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices; magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

[0058] Instructions 1024 may also be sent or received over a communication network 1026 using a transmission medium. Instructions 1024 may be sent using a network interface device 1020 and any of a number of well-known transmission protocols (e.g., HTTP). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet, a mobile telephone network, a plain old telephone (POTS) network, and wireless data networks (e.g., WiFi and WiMax networks). The term "transmission medium" shall be taken to include any intangible medium that is capable of storing, encoding, or carrying instructions for execution by a machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such software.

[0059] Figure 7 An exemplary radiation therapy system 100 for providing radiation therapy to a patient, to a portion of a patient, or to a "phantom" that may include a target object representing the patient or a portion of a patient is shown. The radiation therapy system 7100 includes an image processing device 7112. The image processing device 7112 may be connected to a network 7120. The network 7120 may be connected to the Internet 7122. The network 7120 may connect the image processing device 7112 with one or more of: a database 7124, a hospital database 7126, an oncology information system (OIS) 7128, a radiation therapy device 7130, an image acquisition device 7132, a display device 7134, and a user interface 7136. The image processing device 7112 may be configured to generate a radiation therapy treatment plan 7142 to be used by the radiation therapy device 7130.

[0060] The image processing device 7112 may include a memory device 7116, a processor 7114, and a communication interface 7118. The memory device 7116 may store computer executable instructions such as an operating system 7143, a radiation therapy treatment plan 7142 (e.g., an original treatment plan, a modified treatment plan, etc.), a software program 7144 (e.g., artificial intelligence, deep learning, a neural network, radiation therapy treatment planning software), and any other computer executable instructions to be executed by the processor 7114. In one embodiment, the software program 7144 may convert a medical image in one format (e.g., MRI) to another format (e.g., CT) by generating a synthetic image, such as a pseudo CT image. For example, the software program 7144 may include an image processing program to train a prediction model for converting a medical image 7146 (e.g., an MRI image) in one manner to a synthetic image (e.g., a pseudo CT image) in a different manner; alternatively, the trained prediction model may convert a CT image to an MRI image. In another embodiment, the software program 7144 can align a patient image (e.g., a CT image or an MR image) with a dose distribution (also represented as an image) for the patient so that corresponding image voxels and dose voxels are appropriately associated by the network. In yet another embodiment, the software program 7144 can replace functionality of the patient image, such as a signed distance function or a processed version of the image that emphasizes particular aspects of the image information. Such functionality may emphasize edges or differences in voxel texture or any other structural aspects useful for neural network learning. In another embodiment, the software program 7144 can replace functionality of a dose distribution that emphasizes some aspects of the dose information. Such functionality may emphasize steep gradients around a target or any other structural aspects useful for neural network learning. The memory device 7116 can store data, including medical images 7146, patient data 7145, and other data required to create and implement the radiation therapy treatment plan 7142.

[0061] In addition to the memory 4116 storing the software program 7144, it is also expected that the software program 7144 can be stored on a removable computer medium such as a hard drive, a computer disk, a CD-ROM, a DVD, an HD, a Blu-ray DVD, a USB flash drive, an SD card, a memory stick, or any other suitable medium; and when downloaded to the image processing device 7112, the software program 7144 can be executed by the image processor 7114.

[0062] The processor 7114 may be communicatively coupled to the memory device 116, and the processor 7114 may be configured to execute computer executable instructions stored thereon. The processor 7114 may send a medical image 7146 to the memory 7116 or receive a medical image 7146 from the memory 7116. For example, the processor 7114 may receive a medical image 7146 from the image acquisition device 7132 via the communication interface 7118 and the network 7120 to store the medical image 7146 in the memory 7116. The processor 7114 may also send the medical image 7146 stored in the memory 7116 to the network 7120 via the communication interface 7118 to store the medical image 7146 in the database 7124 or the hospital database 7126.

[0063] In addition, the processor 7114 can create a radiation therapy treatment plan 7142 using a software program 7144 (e.g., treatment planning software) along with medical images 7146 and patient data 7145. The medical images 7146 can include information such as imaging data associated with patient anatomical regions, organs, or volume of interest segmentation data. The patient data 7145 can include information such as: (1) functional organ modeling data (e.g., serial versus parallel organs, appropriate dose response models, etc.); (2) radiation dose data (e.g., dose-volume histogram (DVH) information); or (3) other clinical information about the patient and treatment process (e.g., other surgeries, chemotherapy, previous radiation therapy, etc.).

[0064] In addition, the processor 7114 can utilize a software program to generate intermediate data, such as, for example, updated parameters to be used by a neural network model; or the processor 7114 can utilize a software program to generate an intermediate 2D image or 3D image, which can then be stored in the memory 7116. The processor 7114 can then transmit the executable radiation therapy treatment plan 7142 to the network 7120 and then to the radiation therapy device 7130 via the communication interface 7118, where the radiation therapy plan will be used to treat the patient with radiation. In addition, the processor 7114 can execute a software program 7144 to implement functions such as image conversion, image segmentation, deep learning, neural networks, and artificial intelligence. For example, the processor 7114 can execute a software program 7144 that trains medical images or outlines medical images; such software 7144, when executed, can train a boundary detector or utilize a shape dictionary.

[0065] The processor 7114 may be a processing device including one or more general-purpose processing devices such as a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), etc. More specifically, the processor 7114 may be a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor that implements other instruction sets, or a processor that implements a combination of instruction sets. The processor 7114 may also be implemented by one or more special-purpose processing devices such as an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), a system on a chip (SoC), etc. As will be appreciated by those skilled in the art, in some embodiments, the processor 7114 may be a special-purpose processor rather than a general-purpose processor. The processor 7114 may include one or more known processing devices, such as those from Intel. TM Pentium manufactured TM 、Core TM , Xeon TM or series of microprocessors; from AMD TM Made by Turion TM , Athlon TM 、Sempron TM 、Opteron TM FX TM 、Phenom TMseries of microprocessors; or any of a variety of processors manufactured by Sun Microsystems. Processor 7114 may also include a graphics processing unit, such as a graphics processing unit from Nvidia TM Manufactured series of GPUs; by Intel TM GMA, Iris TM series GPU; or by AMD TM Made by Radeon TM Processor 7114 may also include an accelerated processing unit, such as an Intel TM Xeon Phi manufactured TM The disclosed embodiments are not limited to any type of processor that is otherwise configured to meet the computational requirements of identifying, analyzing, maintaining, generating, and / or providing large amounts of data or manipulating such data to perform the methods disclosed herein. In addition, the term "processor" may include more than one processor, for example, a multi-core design or multiple processors each having a multi-core design. The processor 7114 can execute sequences of computer program instructions stored in the memory 7116 to perform various operations, processes, and methods that will be described in more detail below.

[0066] The memory device 7116 may store medical images 7146. In some embodiments, the medical images 7146 may include one or more MRI images (e.g., 2D MRI, 3D MRI, 2D flow MRI, 4D MRI, 4D volume MRI, 4D imaging MRI, etc.), functional MRI images (e.g., fMRI, DCE-MRI, diffusion MRI), computed tomography (CT) images (e.g., 2D CT, cone beam CT, 3D CT, 4D CT), ultrasound images (e.g., 2D ultrasound, 3D ultrasound, 4D ultrasound), positron emission tomography (PET) images, X-ray images, fluoroscopic images, radiotherapy portal images, single photon emission computed tomography (SPECT) images, computer-generated synthetic images (e.g., pseudo CT images), etc. In addition, the medical images 146 may also include medical image data, such as training images, ground truth images, contour images, and dose images. In an embodiment, the medical images 7146 may be received from the image acquisition device 7132. Thus, the image acquisition device 7132 may include an MRI imaging device, a CT imaging device, a PET imaging device, an ultrasound imaging device, a fluoroscope device, a SPECT imaging device, an integrated linear accelerator and MRI imaging device, or other medical imaging devices for obtaining medical images of a patient. The medical images 7146 may be received and stored in any type of data or in any type of format that the image processing device 7112 may use to perform operations consistent with the disclosed embodiments. The memory device 7116 may be a non-transitory computer-readable medium, such as a read-only memory (ROM), a phase-change random access memory (PRAM), a static random access memory (SRAM), a flash memory, a random access memory (RAM), a dynamic random access memory (DRAM) such as a synchronous DRAM (SDRAM), an electrically erasable programmable read-only memory (EEPROM), a static memory (e.g., a flash memory, a flash disk, a static random access memory), and other types of random access memory, a cache memory, a register, a compact disk read-only memory (CD-ROM), a digital versatile disk (DVD) or other optical storage device, a cassette, other magnetic storage devices, or any other non-transitory medium that can be used to store information (e.g., stored in any format) including images, data, or computer executable instructions that can be accessed by the processor 7114 or any other type of computer device. The computer program instructions can be accessed by the processor 7114, read from the ROM or any other suitable memory location, and loaded into the RAM for execution by the processor 7114. For example, the memory 7116 may store one or more software applications.The software applications stored in the memory 7116 may include, for example, an operating system 7143 for common computer systems and for software-controlled devices. In addition, the memory 7116 may store an entire software application or only a portion of a software application that can be executed by the processor 7114. For example, the memory device 7116 may store one or more radiation therapy treatment plans 7142.

[0067] The image processing device 7112 can communicate with the network 7120 via a communication interface 7118, which can be communicatively coupled to the processor 7114 and the memory 7116. The communication interface 7118 can provide a communication connection between the image processing device 7112 and the components of the radiation therapy system 7100 (e.g., allowing data to be exchanged with external devices). For example, in some embodiments, the communication interface 7118 can have appropriate interface circuitry to connect to a user interface 7136, which can be a hardware keyboard, keypad, or touch screen, through which a user can input information into the radiation therapy system 7100.

[0068] The communication interface 7118 may include, for example, a network adapter, a cable connector, a serial connector, a USB connector, a parallel connector, a high-speed data transmission adapter (e.g., optical fiber, USB 3.0, thunderbolt, etc.), a wireless network adapter (e.g., a WiFi adapter), a telecommunication adapter (e.g., 3G, 4G / LTE, etc.), etc. The communication interface 7118 may include one or more digital and / or analog communication devices that allow the image processing device 7112 to communicate with other machines and devices, such as remotely located components, via the network 7120.

[0069] The network 7120 can provide the functionality of a local area network (LAN), a wireless network, a cloud computing environment (e.g., software as a service, platform as a service, infrastructure as a service, etc.), a client-server, a wide area network (WAN), etc. For example, the network 120 can be a LAN or a WAN, which can include other systems S1 (138), S2 (140), and S3 (141). The systems S1, S2, and S3 can be the same as the image processing device 7112, or can be different systems. In some embodiments, one or more of the systems in the network 120 can form a distributed computing / simulation environment that collaboratively performs the embodiments described herein. In some embodiments, one or more of the systems S1, S2, and S3 can include a CT scanner that obtains a CT image (e.g., a medical image 7146). In addition, the network 7120 can be connected to the Internet 7122 to communicate with servers and clients remotely residing on the Internet.

[0070] Thus, the network 7120 may allow data transfer between the image processing device 7112 and a variety of other systems and devices, such as the OIS 7128, the radiotherapy device 7130, and the image acquisition device 7132. In addition, data generated by the OIS 7128 and / or the image acquisition device 7132 may be stored in the memory 7116, the database 7124, and / or the hospital database 7126. Data may be sent / received via the network 7120 through the communication interface 7118 for access by the processor 7114, as desired.

[0071] The image processing device 7112 can communicate with the database 7124 through the network 7120 to send / receive various types of data stored on the database 8124. For example, the database 8124 may include machine data as information associated with the radiation therapy device 8130, the image acquisition device 8132, or other machines related to radiation therapy. The machine data information may include radiation beam size, arc placement, beam on and off duration, machine parameters, segments, multi-leaf collimator (MLC) configuration, gantry speed, MRI pulse sequence, etc. The database 8124 may be a storage device and may be equipped with an appropriate database management software program. Those skilled in the art will appreciate that the database 8124 may include multiple devices located in a central or distributed manner.

[0072] In some embodiments, the database 7124 may include a processor-readable storage medium (not shown). Although the processor-readable storage medium in the embodiments may be a single medium, the term "processor-readable storage medium" should be considered to include a single medium or multiple media (e.g., a centralized or distributed database and / or associated cache memory and server) storing one or more computer-executable instruction sets or data. The term "processor-readable storage medium" should also be considered to include any medium capable of storing and encoding an instruction set executed by a processor and causing the processor to execute any one or more methods in the present disclosure. Therefore, the term "processor-readable storage medium" should be considered to include, but is not limited to, solid-state memory, optical media, and magnetic media. For example, a processor-readable storage medium may be one or more volatile, non-transient, or non-volatile tangible computer-readable media.

[0073] The image processor 7114 may communicate with the database 7124 to read images into the memory 7116 or store images from the memory 7116 to the database 7124. For example, the database 7124 may be configured to store a plurality of images (e.g., 3D MRI, 4D MRI, 2D MRI slice images, CT images, 2D fluoroscopic images, X-ray images, raw data from MR scans or CT scans, Digital Imaging and Communications in Medicine (DIMCOM) data, etc.) received by the database 7124 from the image acquisition device 7132. The database 7124 may store data to be used by the image processor 7114 when executing the software program 7144 or when creating a radiation therapy treatment plan 7142. The database 7124 may store data generated by a trained neural network, including network parameters constituting a model learned by the network and resulting prediction data. The image processing device 7112 can receive imaging data 7146 (e.g., 2D MRI slice images, CT images, 2D fluoroscopic images, X-ray images, 3D MRI images, 4D MRI images, etc.) from a database 7124, a radiotherapy device 7130 (e.g., MRI-Linac) and / or an image acquisition device 7132 to generate a treatment plan 7142.

[0074] In one embodiment, the radiotherapy system 7100 may include an image acquisition device 7132 that is capable of acquiring medical images of the patient (e.g., magnetic resonance imaging (MRI) images, 3D MRI, 2D flow MRI, 4D volume MRI, computed tomography (CT) images, cone beam CT, positron emission tomography (PET) images, functional MRI images (e.g., fMRI, DCE-MRI, and diffusion MRI), X-ray images, fluoroscopic images, ultrasound images, radiotherapy portal images, single photon emission computed tomography (SPECT) images, etc.). The image acquisition device 7132 may be, for example, an MRI imaging device, a CT imaging device, a PET imaging device, an ultrasound device, a fluoroscopic device, a SPECT imaging device, or any other suitable medical imaging device for obtaining one or more medical images of the patient. The images acquired by the image acquisition device 7132 may be stored in the database 7124 as imaging data and / or test data. As an example, the image acquired by the imaging acquisition device 7132 may also be stored by the image processing device 7112 as medical image data 7146 in the memory 7116 .

[0075] In an embodiment, for example, the image acquisition device 7132 can be integrated with the radiotherapy device 7130 into a single device (e.g., an MRI device combined with a linear accelerator, also referred to as "MRI-Linac"). Such MRI-Linac can be used, for example, to determine the location of a target organ or target tumor in a patient's body so as to accurately guide the radiotherapy to a predetermined target according to the radiotherapy treatment plan 7142.

[0076] The image acquisition device 7132 can be configured to acquire one or more images of the patient's anatomical structure for a region of interest (e.g., a target organ, a target tumor, or both). Each image, typically a 2D image or slice, can include one or more parameters (e.g., 2D slice thickness, orientation, and position, etc.). In an embodiment, the image acquisition device 7132 can acquire 2D slices in any orientation. For example, the orientation of the 2D slice can include a sagittal orientation, a coronal orientation, or an axial orientation. The processor 7114 can adjust one or more parameters such as the thickness and / or orientation of the 2D slice to include the target organ and / or target tumor. In an embodiment, the 2D slice can be determined based on information such as a 3D MRI volume. When the patient is receiving radiotherapy treatment, such as when using the radiotherapy device 7130, such 2D slices can be acquired by the image acquisition device 7132 in "near real time". "Near real time" means acquiring data at least in milliseconds or less.

[0077] The image processing device 7112 can generate and store a radiation therapy treatment plan 7142 for one or more patients. The radiation therapy treatment plan 7142 can provide information about the specific radiation dose to be applied to each patient. The radiation therapy treatment plan 7142 can also include other radiation therapy information, such as beam angles, dose-volume histogram information, the number of radiation beams to be used during therapy, the dose of each beam, etc.

[0078] The image processor 7114 may be used by using a software program 7144 such as treatment planning software (e.g., manufactured by Elekta AB of Stockholm, Sweden). ) to generate a radiation therapy treatment plan 7142. To generate the radiation therapy treatment plan 7142, the image processor 7114 can communicate with an image acquisition device 7132 (e.g., a CT device, an MRI device, a PET device, an X-ray device, an ultrasound device, etc.) to access patient images and depict a target (e.g., a tumor). In some embodiments, it may be necessary to depict one or more organs at risk (OARs), such as healthy tissue surrounding a tumor or immediately adjacent to a tumor. Therefore, segmentation of the OARs can be performed if the OARs are close to the target tumor. In addition, if the target tumor is close to the OARs (e.g., the prostate is close to the bladder and rectum), by segmenting the OARs relative to the tumor, the radiation therapy system 100 can study not only the dose distribution in the target, but also the dose distribution in the OARs.

[0079] In order to depict the target organ or target tumor relative to the OAR, medical images such as MRI images, CT images, PET images, fMRI images, X-ray images, ultrasound images, radiotherapy field images, SPECT images, etc. of patients undergoing radiotherapy can be obtained non-invasively by the image acquisition device 7132 to expose the internal structure of the body part. Based on the information from the medical image, the 3D structure of the relevant anatomical part can be obtained. In addition, during the treatment planning process, multiple parameters can be considered to achieve a balance between effective treatment of the target tumor (e.g., so that the target tumor receives enough radiation dose to achieve effective treatment) and low irradiation of the OAR (e.g., the OAR receives the lowest possible radiation dose). Other parameters that can be considered include the position of the target organ and the target tumor, the position of the OAR, and the movement of the target relative to the OAR. For example, the 3D structure can be obtained by outlining the target or outlining the OAR in each 2D layer or slice of the MRI or CT image and combining the outlines of each 2D layer or slice. The measurement may be performed manually (eg, by a physician, dosimetrist, or medical staff using a program such as MONACO manufactured by Elekta AB of Stockholm, Sweden). TM ) or automatically (e.g., using a program such as the Atlas-based automatic segmentation software ABAS manufactured by Elekta AB of Stockholm, Sweden TM ) Generate contours. In some embodiments, the 3D structure of the target tumor or OAR can be automatically generated by treatment planning software.

[0080] After the target tumor and OAR have been located and delineated, the dosimetrist, physician, or medical staff can determine the radiation dose to be applied to the target tumor and any maximum dose that can be received by the OARs adjacent to the tumor (e.g., left and right parotid glands, optic nerves, eyes, lenses, inner ears, spinal cord, brainstem, etc.). After the radiation dose is determined for each anatomical structure (e.g., target tumor, OAR), a process called inverse planning can be performed to determine one or more treatment planning parameters that will achieve the desired radiation dose distribution. Examples of treatment planning parameters include volume delineation parameters (e.g., which define the target volume, contour-sensitive structures, etc.), margins around the target tumor and OAR, beam angle selection, collimator settings, and beam opening times. During the inverse planning process, the physician can define dose constraint parameters that set limits on how much radiation the OAR can receive (e.g., for tumor targets, define full dose, for any OAR, define zero dose; for target tumors, define 95% of the dose; define spinal cord, brainstem, and optic nerve structures to receive ≤45Gy, ≤55Gy, and <54Gy, respectively). The results of the inverse planning can constitute a radiation therapy treatment plan 7142 that can be stored in the memory 7116 or the database 7124. Some of these treatment parameters can be interrelated. For example, adjusting one parameter to change the treatment plan (e.g., the weighting for different goals, such as increasing the dose to the target tumor) may affect at least one other parameter, which in turn may result in the development of a different treatment plan. Therefore, the image processing device 7112 can generate a customized radiation therapy treatment plan 7142 with these parameters so that the radiation therapy device 7130 provides the radiation therapy treatment to the patient.

[0081] In addition, the radiation therapy system 7100 may include a display device 7134 and a user interface 7136. The display device 7134 may include one or more display screens that display medical images, interface information, treatment plan parameters (e.g., contours, doses, beam angles, etc.), treatment plans, targets, positioning and / or tracking of targets, or any related information to the user. The user interface 7136 may be a keyboard, keypad, touch screen, or any type of device through which a user can input information to the radiation therapy system 7100. Alternatively, the display device 7134 and the user interface 7136 may be integrated into a computer such as a tablet computer (e.g., Apple Lenovo Samsung etc.) device.

[0082] In addition, any and all components of the radiation therapy system 7100 can be implemented as virtual machines (e.g., VMWare, Hyper-V, etc.). For example, a virtual machine can be software that acts as hardware. Therefore, a virtual machine can include at least one or more virtual processors, one or more virtual memories, and one or more virtual communication interfaces that act together as hardware. For example, the image processing device 7112, the OIS 7128, and the image acquisition device 7132 can be implemented as virtual machines. Assuming that processing power, memory, and computing power are available, the entire radiation therapy system 7100 can be implemented as a virtual machine.

[0083] Figure 8 An exemplary radiation therapy device 8202 is shown, which may include a radiation source, such as an x-ray source or a linear accelerator, a treatment couch 8216, an imaging detector 8214, and a radiation therapy output 8204. The radiation therapy device 8202 may be configured to emit a radiation beam 8208 to provide therapy to a patient. The radiation therapy output 8204 may include one or more attenuators or collimators, such as a multi-leaf collimator (MLC).

[0084] exist Figure 8In the embodiment of the present invention, a patient can be positioned in an area 8212 supported by a treatment couch 8216 to receive a radiation therapy dose according to a radiation therapy treatment plan. The radiation therapy output 8204 can be mounted or attached to a gantry 8206 or other mechanical support. When the treatment couch 8216 is inserted into the treatment area, one or more chassis motors (chassis motor) (not shown) can rotate the gantry 8206 and the radiation therapy output 8204 around the treatment couch 8216. In one embodiment, when the treatment couch 8216 is inserted into the treatment area, the gantry 8206 can continuously rotate around the treatment couch 8216. In another embodiment, when the treatment couch 8216 is inserted into the treatment area, the gantry 8206 can rotate to a predetermined position. For example, the gantry 8206 can be configured to rotate the therapy output 8204 around an axis ("A"). Both the treatment couch 8216 and the radiation therapy output 8204 can be independently moved to other locations around the patient, for example, can be moved in a transverse direction ("T"), can be moved in a lateral direction ("L"); or both the treatment couch 8216 and the radiation therapy output 8204 can be rotated about one or more other axes, such as about a transverse axis (denoted as "R"). A controller communicatively connected to one or more actuators (not shown) can control the treatment couch 8216 to move or rotate so as to appropriately position the patient within or outside of the radiation beam 8208 according to the radiation therapy treatment plan. Because both the treatment couch 8216 and the gantry 8206 can move independently of each other in multiple degrees of freedom, this allows the patient to be positioned so that the radiation beam 8208 can accurately target the tumor.

[0085] Figure 8 The coordinate system shown (including axes A, T, and L) can have an origin located at the isocenter 8210. The isocenter can be defined as the location where the central axis of the radiation therapy beam 8208 intersects the origin of the coordinate axes to deliver a prescribed radiation dose to a location on or within the patient. Alternatively, the isocenter 8210 can be defined as the location where the central axis of the radiation therapy beam 8208 intersects the patient for various rotational positions of the radiation therapy output end 8204 positioned by the gantry 8206 about axis A.

[0086] The gantry 8206 may also have an attached imaging detector 8214. The imaging detector 8214 is preferably located opposite the radiation source 8204, and in embodiments, the imaging detector 8214 may be located within the field of the treatment beam 8208.

[0087] The imaging detector 8214 can be preferably mounted on the gantry 8206 opposite the radiation therapy output end 8204 so as to maintain alignment with the treatment beam 8208. As the gantry 8206 rotates, the imaging detector 8214 rotates about the rotation axis. In an embodiment, the imaging detector 8214 can be a flat panel detector (e.g., a direct detector or a scintillator detector). In this way, the imaging detector 8214 can be used to monitor the treatment beam 8208; or the imaging detector 8214 can be used to image the patient's anatomical structure, such as portal imaging. The control circuit system of the radiation therapy device 8202 can be integrated into the system 8100 or remote from the system 8100.

[0088] In an illustrative embodiment, one or more of the treatment couch 8216, therapy output 8204, or gantry 8206 may be automatically positioned, and therapy output 8204 may establish a therapy beam 8208 according to a specified dose for a particular therapy delivery instance. A sequence of therapy deliveries may be specified according to a radiation therapy treatment plan, for example, using one or more different orientations or positions of gantry 8206, treatment couch 8216, or therapy output 8204. The therapy deliveries may occur sequentially, but may be interleaved in desired therapy sites on or within a patient, for example, at an isocenter 8210. A prescribed cumulative dose of radiation therapy may thereby be delivered to the therapy site, while damage to tissue near the therapy site may be reduced or avoided.

[0089] Figure 8 Embodiments of a radiation therapy device configured to provide radiation therapy treatment to a patient are generally shown, including a configuration in which a radiation therapy output can rotate about a central axis (e.g., axis "A"). Other radiation therapy output configurations can be used. For example, the radiation therapy output can be mounted to a robotic arm or manipulator having multiple degrees of freedom. In yet another embodiment, the therapy output can be fixed, such as in an area laterally separated from the patient, and a platform supporting the patient can be used to align the radiation therapy isocenter with a designated target site in the patient's body.

[0090] In another embodiment, the radiotherapy device can be a combination of a linear accelerator and an image acquisition device. As will be appreciated by those of ordinary skill in the art, in some embodiments, the image acquisition device can be an MRI, X-ray, CT, CBCT, spiral CT, PET, SPECT, optical tomography, fluorescence imaging, ultrasound imaging, or a radiotherapy portal imaging device, etc.

[0091] As used herein, "communicatively coupled between" means that entities on either of the couplings must communicate through an item between them, and the entities cannot communicate with each other without communicating through the item.

[0092] The above description includes reference to the accompanying drawings, which form a part of the specific embodiments. The accompanying drawings illustrate the specific embodiments by way of illustration, in which the present invention can be put into practice. These embodiments are also referred to as "examples" in this article. Such examples may include elements other than the elements shown or described. However, the inventors also contemplate examples that only provide those elements shown or described. In addition, the inventors also contemplate examples of any combination or arrangement of those elements (or one or more aspects of those elements) shown or described with respect to a specific example (or one or more aspects of a specific example) or with respect to other examples (or one or more aspects of other examples) shown or described herein.

[0093] In the event of an inconsistent usage between this document and any document incorporated by reference, the usage in this document controls.

[0094] As is common in patent documents, in this document, the terms "a" or "an" are used to include one or more than one, independent of any other instance or usage of "at least one" or "one or more". In this document, unless otherwise stated, the term "or" is used to refer to non-exclusivity, or so that "A or B" includes "A but not B", "B but not A", and "A and B". In this document, the terms "including" and "in which" are used as the plain English equivalents of the corresponding terms "comprising" and "wherein". In addition, in the appended claims, the terms "including" and "comprising" are open-ended, that is, systems, devices, articles, compositions, formulas, or processes that include elements other than the elements listed after such terms in the claims are still considered to fall within the scope of the claim. In addition, in the appended claims, the terms "first", "second", and "third", etc. are used only as labels and are not intended to impose numerical requirements on their objects.

[0095] The method examples described herein may be at least partially machine or computer-implemented. Some examples may include a computer-readable medium or machine-readable medium encoded with instructions, which can be operated to configure an electronic device to perform the method described in the above example. The implementation of such a method may include codes such as microcode, assembly language code, high-level language code, etc. Such a code may include computer-readable instructions for performing various methods. The code may form part of a computer program product. In addition, in an example, for example, during execution or at other times, the code may be tangibly stored on one or more volatile, non-transient or non-volatile tangible computer-readable media. Examples of these tangible computer-readable media may include, but are not limited to, hard disks, removable disks, removable optical disks (e.g., compact disks and digital video disks), cassettes, memory cards or memory sticks, random access memory (RAM), read-only memory (ROM), etc.

[0096] The above description is intended to be illustrative rather than restrictive. For example, the examples described above (or one or more aspects of the examples) can be used in combination with each other. After reviewing the above description, other embodiments may be used by those skilled in the art, for example. The abstract is provided to comply with 37C.FR§1.72(b) to allow readers to quickly determine the nature of the technical disclosure. It should be understood that it will not be used to interpret or limit the scope or meaning of the claims when submitting this document. In addition, in the above specific embodiments, various features can be grouped together to simplify the present disclosure. This should not be interpreted as intending that: for any claim, the disclosed features that are not claimed for protection are necessary. Instead, the subject matter of the invention may be less than all the features of a specific disclosed embodiment. Therefore, the attached claims are incorporated into the specific embodiments as examples or embodiments, wherein each claim itself exists as a separate embodiment, and it is conceivable that such embodiments can be combined with each other in various combinations or arrangements. The scope of the present invention should be determined with reference to the attached claims and the full range of equivalents given by these claims.

[0097] The present disclosure also relates to a system for performing the operations described herein. The system may be specially constructed for the desired purpose, or the system may include a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer-readable storage medium, such as, but not limited to, any type of disk, including a floppy disk, an optical disk, a CD-ROM, a magneto-optical disk, a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic card or an optical card, or any type of medium suitable for storing electronic instructions, each medium being coupled to a computer system bus.

[0098] Unless specifically stated, the order in which the operations in the embodiments shown and described herein are implemented or performed is not required. That is, unless specifically stated, the operations may be performed in any order, and embodiments of the present invention may include more or fewer operations than those disclosed herein. For example, it is contemplated that implementing or performing a specific operation before, simultaneously with, or after another operation is within the scope of the claims.

[0099] The present disclosure can be implemented with computer executable instructions. Computer executable instructions can be organized into one or more computer executable components or modules. Aspects of the present invention can be implemented with such components or modules of any number and organization. For example, aspects of the present invention are not limited to the specific computer executable instructions or specific components or modules shown in the accompanying drawings and described in this article. Other embodiments of the present invention may include different computer executable instructions or components, which have more or less functions than shown and described herein.

[0100] It will be apparent that modifications and variations are possible without departing from the scope of the appended claims. Various changes may be made to the above structures, products and methods without departing from the scope of the claims, and it is intended that all matter contained in the above description and shown in the accompanying drawings shall be interpreted as illustrative rather than limiting.

[0101] In addition, the embodiment of the present invention further includes:

[0102] (1) A method for verifying a radiotherapy treatment plan, comprising:

[0103] making or obtaining a phantom based on a medical image of a region of interest of the patient, the region of interest including a target region and a non-target region to be treated by radiation therapy;

[0104] deforming the phantom to simulate deformation of at least one of the target region or the non-target region;

[0105] determining a maximum deformation of at least one of the target region or the non-target region for which the radiation therapy treatment plan is effective;

[0106] calculating a distorted radiation dose by applying a geometric transformation to a prescribed radiation dose, wherein the prescribed radiation dose defines a spatial distribution of radiation to be delivered to the region of interest;

[0107] generating a radiation therapy treatment plan for configuring a radiation therapy treatment device to deliver the distorted radiation dose;

[0108] measuring the radiation dose distribution received by a deformable phantom when the radiation therapy treatment device is operated according to the radiation therapy treatment plan to deliver radiation to the deformable phantom; and

[0109] Included is validating the radiation therapy treatment plan by comparing the measured radiation dose distribution to the prescribed radiation dose.

[0110] (2) The method of (1), wherein the phantom comprises a smart material that exhibits a shape change when exposed to an external stimulus, and deforming the phantom comprises applying the external stimulus to the smart material.

[0111] (3) The method according to (1), wherein the method further comprises:

[0112] acquiring an image of the phantom prior to deforming the phantom;

[0113] acquiring an image of the deformed phantom; and

[0114] The geometric transformation is calculated based on the image of the phantom and the image of the deformed phantom.

[0115] (4) The method according to (3), wherein the image of the phantom and the image of the deformed phantom each include a plurality of voxels, and wherein calculating the geometric transformation includes:

[0116] Deformable image registration is performed to compute a deformation vector field that maps each voxel in the image of the phantom to a corresponding voxel in the deformed image of the phantom.

[0117] (5) The method according to (1), wherein the phantom is manufactured by an additive manufacturing process.

[0118] (6) The method according to (1), wherein manufacturing the phantom includes placing a plurality of dosimeters within the phantom.

[0119] (7) A method for verifying dose distortion or other dose mapping techniques, comprising:

[0120] accessing a first medical image representing a region of interest of a patient;

[0121] generating a second medical image by applying a first deformation vector field to the first medical image;

[0122] Generate, obtain or provide a first phantom and a second phantom corresponding to the first medical image and the second medical image respectively;

[0123] measuring respective radiation dose distributions received by the first phantom and the second phantom when the radiation therapy treatment device is operated to deliver radiation to the first phantom and the second phantom, respectively;

[0124] including generating a second deformation vector field by performing deformable image registration on the first medical image and the second medical image, the deformable image registration mapping each voxel in the first medical image to a corresponding voxel in the second medical, and including calculating a warped radiation dose by applying the second deformation vector field;

[0125] Using a dose warping or other dose mapping technique to be validated includes calculating the warped radiation dose by applying the first deformation vector field to a first radiation dose distribution measured using the first phantom; and

[0126] The accuracy of the dose distortion or mapping technique is verified by comparing the calculated distorted dose to a second radiation dose distribution measured using the second phantom.

[0127] (8) The method according to (7), wherein at least one of the first phantom and the second phantom is manufactured by an additive manufacturing process.

[0128] (9) The method of (7), wherein manufacturing at least one of the first phantom and the second phantom includes placing a plurality of dosimeters in the first phantom and the second phantom.

[0129] (10) The method according to (7), comprising verifying the cumulative accuracy of the dose distortion and the deformable image registration.

[0130] (11) A method for verifying a radiotherapy treatment session, comprising:

[0131] manufacturing a phantom based on medical images of a region of interest of a patient, the medical images being acquired prior to a radiation therapy treatment session in which radiation is delivered to the patient by operating a radiation therapy device according to a radiation therapy treatment plan;

[0132] determining a maximum deformation of at least one of the target region or the non-target region for which the radiation therapy treatment plan is effective;

[0133] measuring the radiation dose distribution received by the phantom when delivering radiation to the phantom by operating the radiotherapy device according to the radiotherapy treatment plan; and

[0134] Included is validating the radiation therapy treatment session by comparing the measured radiation dose distribution with dose measurements obtained during the radiation therapy treatment.

[0135] (12) The method according to (11), wherein the phantom is manufactured by an additive manufacturing process.

[0136] (13) The phantom of (11), wherein manufacturing the phantom includes positioning a plurality of dosimeters within the phantom.

[0137] (14) A phantom for radiotherapy quality assurance, the phantom comprising:

[0138] Representing the first portion of the patient's target area;

[0139] representing a second portion of the non-target region of the patient; and

[0140] Wherein at least one of the first portion or the second portion comprises a smart material, wherein the smart material exhibits a shape change when exposed to an external stimulus based on at least one of humidity, temperature, light, electric field or magnetic field.

[0141] (15) The phantom according to (14), wherein the phantom is manufactured by an additive manufacturing process.

[0142] (16) A phantom according to (14), wherein the phantom is manufactured by the additive manufacturing process based on a medical image of the patient's area of ​​interest, the area of ​​interest including the target area and the non-target area, so that the first part and the second part of the phantom each have a corresponding shape defined by the shape of the target area and the non-target area in the medical image, respectively.

[0143] (17) The phantom according to (14), wherein the phantom includes a plurality of dosimeters located within the phantom.

Claims

1. A method for verifying a radiotherapy treatment session, comprising: manufacturing a phantom based on medical images of a region of interest of a patient, the region of interest including a target region and a non-target region to be treated by radiotherapy, the medical images being acquired prior to a radiotherapy treatment session in which radiation is delivered to the patient by operating a radiotherapy device according to a radiotherapy treatment plan; determining a maximum deformation of at least one of the target region and the non-target region for which the radiation therapy treatment plan is effective by applying different deformations to the phantom; deforming the phantom to simulate deformation of at least one of the target region or the non-target region; measuring a radiation dose distribution received by the phantom when the radiation therapy device is operated according to the radiation therapy treatment plan to deliver radiation to the phantom; as well as validating the radiation therapy treatment session by operations comprising: comparing the measured radiation dose distribution with dose measurements obtained during the radiation therapy treatment so as not to exceed an acceptable difference limit, Wherein, determining the maximum deformation of at least one of the target area and the non-target area in which the radiotherapy treatment plan is effective by applying different deformations to the phantom includes determining the maximum deformation of at least one of the target area and the non-target area in which the radiotherapy treatment plan is effective by repeating the following actions while applying different deformations to the phantom: deforming the phantom to simulate deformation in at least one of the target area or the non-target area; calculating a distorted radiation dose by applying a geometric transformation to a prescribed radiation dose; generating the radiotherapy treatment plan; measuring the radiation dose distribution received by the deformed phantom; and verifying the radiotherapy treatment plan by comparing the measured radiation dose distribution with the prescribed dose so as not to exceed an acceptable difference limit.

2. The method according to claim 1, wherein: The phantom is manufactured by an additive manufacturing process.

3. The method according to claim 1, wherein: Fabricating the phantom includes positioning a plurality of dosimeters within the phantom.

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