System and non-transitory computer-readable medium for real-time adjustment of radiation therapy treatment for a patient

Abstract

A technique for adjusting a radiotherapy treatment of a patient in real time is provided. The technique includes: retrieving a reference plan including a three-dimensional (3D) volume representation of information of the patient and a plurality of radiotherapy beam delivery zones; identifying, for a first beam delivery zone of the plurality of radiotherapy beam delivery zones, a first portion of the 3D volume representation of information, the first portion including a volume portion of a target irradiated by the first beam delivery zone; accessing a deformation model representing deformation of the patient during radiotherapy treatment segmentation; deforming the first portion of the 3D volume representation of information based on the deformation model; and updating one or more parameters of a radiotherapy treatment device based on the deformed first portion of the 3D volume representation of information.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of priority to U.S. Application Serial No. 62 / 869,344, filed on July 1, 2019, which is hereby incorporated by reference in its entirety. Technical Field

[0003] The present disclosure relates generally to radiation therapy or radiotherapy. More particularly, the present disclosure relates to systems and methods for adjusting parameters of a radiotherapy device during radiotherapy treatment. Background Art

[0004] Radiotherapy is used to treat cancer and other diseases in mammalian (e.g., human and animal) tissues. Radiotherapy includes radiotherapy based on linear particle accelerators (LINAC) and circular particle accelerators (e.g., cyclotrons, synchrotrons, and synchrocyclotrons). The direction and shape of the radiation beam should be accurately controlled to ensure that the target tumor receives the prescribed radiation, and the arrangement of the beam should minimize the damage to surrounding healthy tissues, including particularly sensitive organs commonly referred to as organs at risk (OARs). Treatment planning can be used to control radiation beam parameters, and the radiotherapy device achieves treatment by delivering a spatially varying dose distribution to the patient according to the treatment plan. Summary of the invention

[0005] In some embodiments, a computer-implemented method, a transient or non-transitory computer-readable medium, and a system including a memory and a processor are provided for real-time adjustment of radiotherapy treatment of a patient, the computer-implemented method, the transient or non-transitory computer-readable medium, and the system performing operations including: retrieving a reference plan by a processor circuit, the reference plan including a three-dimensional (3D) volume representation of information of the patient and multiple radiotherapy beam delivery segments; identifying by the processor circuit a first portion of the 3D volume representation of the information for a first beam delivery segment among the multiple radiotherapy beam delivery segments, the first portion including a volume portion of a target irradiated by the first beam delivery segment; accessing by the processor circuit a deformation model representing deformation of the patient during radiotherapy treatment segmentation; deforming by the processor circuit the first portion of the 3D volume representation of the information based on the deformation model; and updating by the processor circuit one or more parameters of the radiotherapy treatment device based on the deformed first portion of the 3D volume representation of the information.

[0006] In some implementations, the reference plan includes a delineation of one or more target volumes and / or one or more organs at risk (OARs), and wherein the 3D volume representation of the information includes a plurality of two-dimensional image slices of the patient or a 3D volume representation of the patient.

[0007] In some implementations, the operations include generating a deformation model based on a description of the patient captured prior to or during a radiotherapy treatment fractionation, the description based on one or more image capture modalities.

[0008] In some implementations, the operations include generating a first 3D cut-out of the patient by projecting an opening of the collimator at the first beam delivery section relative to the source location; and identifying the first portion based on the first 3D cut-out of the patient.

[0009] In some implementations, the operation includes generating a second 3D cut-out of the patient by projecting an opening of the collimator relative to a source position at a second radiotherapy beam delivery segment among a plurality of radiotherapy beam delivery segments; and a second portion of the 3D volume representation of identification information for the second radiotherapy beam delivery segment based on the second 3D cut-out of the patient.

[0010] In some implementations, the volumetric portion in the first portion includes a portion of a target to be irradiated and an organ at risk, and the operation also includes: identifying a first group of voxels in the first portion corresponding to the target to be irradiated; identifying a second group of voxels in the first portion corresponding to the organ at risk; deforming the first group of voxels and deforming the second group of voxels based on a deformation model, respectively; and changing a shape of a beam delivered during a first radiotherapy beam delivery segment based on the deformed first group of voxels and the deformed second group of voxels.

[0011] In some implementations, the operations include identifying a second portion of the 3D volume representation of the information, the second portion including a portion of the volume outside of the region irradiated in the first beam delivery section.

[0012] In some implementations, the operations include deforming the first portion and the second portion, respectively, based on the deformation model; and updating one or more parameters of the radiation therapy treatment device based on the deformed first portion and the deformed second portion.

[0013] In some implementations, deforming the first portion includes applying a geometric transformation defined by the deformation model to the first portion.

[0014] In some implementations, one or more parameters of a radiation therapy treatment device are updated based on treatment objectives defined by a reference plan, wherein at least one of the treatment objectives penalizes exposure of voxels belonging to organs at risk (OARs) to prevent adjustment of the one or more parameters that results in an increased dose to the OARs.

[0015] In some implementations, the operation comprising updating one or more parameters comprises adjusting positions of multi-leaf collimator leaves and clips to fit a contour of an object depicted in the volumetric portion.

[0016] In some implementations, the operations include: identifying a second portion of a 3D volume representation of information for a second radiotherapy beam delivery segment among a plurality of radiotherapy beam delivery segments, the second portion comprising a second volume portion of a target irradiated by the second beam delivery segment; deforming the second portion of the 3D volume representation of the information based on a deformation model; and updating one or more parameters of a radiotherapy treatment device based on the deformed second portion of the 3D volume representation of the information.

[0017] In some implementations, the operations include combining the first portion and the second portion into a combined portion of the 3D volume representation of the information, wherein the deformation and the updating are performed on the combined portion of the 3D volume representation of the information.

[0018] The above summary is intended to provide an overview of the subject matter of this patent application. It is not intended to provide an exclusive or exhaustive explanation of the subject matter of the present invention. Specific embodiments are included to provide additional information about this patent application. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In the drawings, which are not necessarily drawn to scale, similar reference numerals describe substantially similar components throughout the several views. Similar reference numerals with different letter suffixes represent different instances of substantially similar components. The drawings generally illustrate various embodiments discussed in this document as examples and not as limitations.

[0020] Figure 1 An exemplary radiation therapy system suitable for performing geometry-based radiation therapy treatments is shown according to some examples.

[0021] Figure 2 An exemplary image-guided radiation therapy apparatus according to some examples of the present disclosure is shown.

[0022] Figure 3 Exemplary radiation therapy treatment image deformations according to some examples of the present disclosure are shown.

[0023] Figure 4 and Figure 5 A flow chart illustrating exemplary operations for performing a geometry-based radiation therapy treatment according to some examples of the present disclosure is shown. DETAILED DESCRIPTION

[0024] The present disclosure includes various techniques for adjusting radiotherapy device parameters (also referred to as "control points") in real time by taking into account individual subject motion of one or more subjects to improve and enhance radiotherapy treatment. Technical benefits include reduced exposure of normal tissue to radiation and more efficient treatment delivery. The disclosed techniques may be applicable to a variety of medical treatment and diagnostic settings or radiotherapy treatment devices and apparatuses.

[0025] Due to the risk of severe damage and late effects, the dose to vital organs and healthy tissues in radiotherapy treatment should be minimized. However, treatment planning is usually performed based on one or several image sets of the patient (e.g., a snapshot in time of the patient) before the patient's first treatment session. The treatment plan is then delivered in several segments most often over a time span of several days to weeks. The treatment plan consists of several beam segments of different weights - cumulative dosing - that are delivered at discrete or continuous gantry angles using different multi-leaf collimators and clip settings that shape the fluence of the segment. For charged particles, it is the cumulative dosing of each point and the speed of the scanning magnet that can be changed. During treatment, the patient will be approximately stationary, ignoring any internal organ movement or shape changes during the segmentation and changes between the segments, such as weight loss or tumor volume reduction. In order to compensate for these differences, a margin is applied to the target volume to ensure coverage and therefore ensure local control of the tumor. In particular, in order to compensate for these differences, a margin around the area to be irradiated by the radiotherapy beam is applied to increase the radiation exposure in a given segment (e.g., increase the size of the beam shape). While such an approach increases the likelihood of irradiating the tumor with a prescribed dose in a given segment, this approach may have the negative consequence of overexposing the OAR and surrounding normal tissue to radiation.

[0026] The position and shape of sensitive organs (called OARs) in the tumor and surrounding tissue are not static, but are affected by external forces such as gravity and internal movements such as breathing, heartbeat, defecation, etc., and may therefore move and change shape during each fractionation of the treatment. In addition, the tumor and OAR may move between fractions due to, for example, bladder filling or patient weight loss, and in addition, the volume of the tumor may decrease between treatment fractions as a result of the treatment. Therefore, there may be a difference between the planned dose to both the target and the OAR and the actual delivered dose. One way to minimize this difference is to actively track the target movement and possibly the OAR, and adjust the current beam segment accordingly during delivery. The purpose of tracking is to dynamically adjust the current segment (and possible subsequent segments) to achieve the expected dose distribution calculated for a static patient. Tracking has the potential to reduce margins, thereby reducing the dose to surrounding normal tissues and OARs. For simple, well-defined, rigid patient deformations, such as translation and rotation, it is quite simple to adjust a given segment to achieve a dose distribution similar to the reference dose. However, in general, patient deformations are not rigid, and it is therefore much more difficult to reproduce the dose distribution.

[0027] Existing methods adjust beam delivery segments during radiotherapy by taking into account the movement of the entire target volume as a whole. That is, existing methods determine new segment parameters based on the projection of the entire deformed target. In this way, existing methods still end up over- or under-delivering radiation to the tumor and / or exceeding the dose allowed by the OAR. In order to optimize the delivery of radiotherapy doses to the target (e.g., a tumor) or reduce the amount of radiation delivered to the OAR, the disclosed technology performs modifications to the parameters of the radiotherapy device by taking into account the motion and deformation of the portion of the object (e.g., a region of interest, such as an OAR and / or a target) visible in the field of view of the beam and / or the motion and deformation of the portion of the object that is not visible in the field of view of the beam. That is, the disclosed techniques modify radiotherapy treatment device parameters (e.g., control points) based only on a stack of 2D images of a target volume intersecting a given segment (e.g., based on radiotherapy beam delivery parameters or control points for a given segment in segmentation), such as a stack of 2D images in the field of view of the beam (from which a 3D representation can be reconstructed) and the movement of the object, target (e.g., tumor) to be irradiated and / or OARs in the stack of 2D images under consideration. In this way, the disclosed techniques reduce the amount of radiation to which the OARs are exposed and increase the amount of radiation delivered to the tumor in a given segment.

[0028] In some embodiments, in order to perform real-time adjustments to radiotherapy device parameters based on patient geometry, the disclosed technology retrieves, by a processor circuit, a reference plan including three-dimensional (3D) image information of the patient and a plurality of radiotherapy beam delivery zones. The disclosed embodiment identifies, by the processor circuit, a first portion of the 3D image information for a first beam delivery zone among the plurality of radiotherapy beam delivery zones, the first portion including a volumetric portion of a target irradiated by the first beam delivery zone. The disclosed embodiment accesses, by the processor circuit, a deformation model (e.g., a motion model representing patient motion) during radiotherapy treatment segmentation and deforms, by the processor circuit, the first portion of the 3D image information based on the motion model. The disclosed embodiment updates, by the processor circuit, one or more parameters of the radiotherapy treatment device based on the deformed first portion of the 3D image information.

[0029] In particular, the disclosed technology provides a process for tracking that uses a patient deformation model and a reference geometry of a patient's region of interest at each moment during treatment. In this process, a subvolume of a target and / or OAR is determined by the intersection of a reference segment (e.g., beam delivery segment parameters or control points specifying the position of MLC blades and clips, bed position, and / or other radiotherapy device parameters) with the reference geometry, and then the current segment (e.g., one or more radiotherapy device parameters) is dynamically adjusted according to the current patient deformation model. In some cases, the intersection of the reference segment and the reference geometry is located in the isocenter plane of the radiotherapy device. As input, the process receives an optimized treatment plan, referred to as a reference plan, and a geometric transformation (e.g., a patient deformation or motion model) that describes the current deformation of the patient compared to the reference geometry at each moment. The optimized or initial reference plan is calculated before the first treatment segmentation, but the reference plan can then be updated for each segmentation at some time between segments (thereby generating a daily plan) or at longer intervals. The plan can include a delineation of the target volume (e.g., tumor) and OARs, and the patient anatomy deformation updates can be provided by a displacement vector field.

[0030] Figure 1 An exemplary radiotherapy system 100 is shown that is suitable for performing radiotherapy planning processing operations using one or more of the methods discussed herein. These radiotherapy planning processing operations are performed to enable the radiotherapy system 100 to provide radiotherapy to a patient based on captured medical imaging data and treatment dose calculations or specific aspects of radiotherapy machine configuration parameters. In particular, the following processing operations can be implemented as part of a geometry-based radiotherapy treatment workflow 130 implemented by the treatment processing logic 120. However, it should be understood that many variations and use cases of the following treatment processing logic 120 can be provided, including data validation, visualization, and other medical evaluation and diagnostic settings.

[0031] The radiation therapy system 100 includes a radiation therapy processing computing system 110 that hosts a treatment processing logic 120. The radiation therapy processing computing system 110 can be connected to a network (not shown), and such a network can be connected to the Internet. For example, the network can connect the radiation therapy processing computing system 110 with one or more medical information sources (e.g., a radiology information system (RIS), a medical record system (e.g., an electronic medical record (EMR) / electronic health record (EHR) system), an oncology information system (OIS)), one or more image data sources 150, an image acquisition device 170 (e.g., an imaging modality), a treatment device 180 (e.g., a radiation therapy device, also referred to herein as a radiation therapy device), and a treatment data source 160. As an example, the radiotherapy treatment computing system 110 can be configured to monitor the current patient geometry in real time within a given segmentation by executing instructions or data from the treatment processing logic 120 to calculate a dose delivery to the subject (e.g., based on one or more MR images), and to modify parameters of the radiotherapy device for subsequent doses delivered in the same segmentation based on a comparison of the calculated dose delivery with the expected dose delivery specified in the treatment plan. In particular, the radiotherapy treatment computing system 110 can be configured to monitor the current patient geometry to update and / or create a patient deformation model (e.g., a patient motion model) that will be used to deform one or more portions of the 3D volume for a given beam delivery zone of the radiotherapy treatment plan. Once these portions are deformed, the radiotherapy treatment computing system 110 can update one or more control points of the radiotherapy device to adapt to the beam delivery zone (e.g., change the shape of the beam delivered in the one or more zones).

[0032] The radiotherapy treatment computing system 110 may include a processing circuit 112, a memory 114, a storage device 116, and other hardware and software operable features such as a user interface 142, a communication interface (not shown), etc. The storage device 116 may store transient or non-transient computer executable instructions, such as an operating system, a radiotherapy treatment plan (e.g., training data, treatment planning strategies, patient motion models, patient deformation models, beam delivery segment information, 3D and / or 2D image information of the patient and device adjustment parameters, etc.), a software program (e.g., image processing software, image or anatomical visualization software, etc.), and any other computer executable instructions executed by the processing circuit 112.

[0033] In an example, the processing circuit 112 may include a processing device, such as 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 processing circuit 112 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 implementing other instruction sets, or a processor implementing a combination of instruction sets. The processing circuit 112 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.

[0034] As will be appreciated by those skilled in the art, in some examples, processing circuitry 112 may be a special purpose processor rather than a general purpose processor. Processing circuitry 112 may include one or more known processing devices, such as those provided by Intel. TM Pentium TM 、Core TM , Xeon TM or series of microprocessors, produced by AMD TM Made by Turion TM , Athlon TM 、Sempron TM 、Opteron TM FX TM 、Phenom TM Processing circuit 112 may also include a graphics processing unit, such as a graphics processing unit manufactured by Nvidia TM Manufactured series of GPUs, from Intel TM GMA, Iris TM Series or by AMD TM Made by Radeon TM The processing circuit 112 may also include an accelerated processing unit such as an Intel TM Xeon Phi manufactured TMseries. 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 physical (circuit-based) processor or software-based processor, such as a multi-core design or multiple processors each having a multi-core design. The processing circuit 112 can execute a sequence of transient or non-transient computer program instructions stored in the memory 114 and accessed from the storage device 116 to perform various operations, processes, methods that will be described in more detail below. It should be understood that any component in the system 100 can be implemented separately and operated as a stand-alone device, and can be coupled to any other component in the system 100 to perform the techniques described in the present disclosure.

[0035] The memory 114 may include read-only memory (ROM), phase-change random access memory (PRAM), static random access memory (SRAM), flash memory, random access memory (RAM), dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM), electrically erasable programmable read-only memory (EEPROM), static memory (e.g., flash memory, flash disk, static random access memory), and other types of random access memory, cache memory, registers, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage device, cassette tape, other magnetic storage device, or any other non-transitory medium that can be used to store information including images, training data, ML technique parameters, device adaptation functions, data, or transient or non-transitory computer executable instructions (e.g., stored in any format) that can be accessed by the processor system 112 or any other type of computer device. For example, computer program instructions can be accessed by the processing circuit 112, can be read from ROM or any other suitable memory location, and can be loaded into RAM for execution by the processing circuit 112.

[0036] The storage device 116 may constitute a drive unit including a transitory or non-transitory machine-readable medium on which is stored one or more transitory or non-transitory instruction sets and data structures (e.g., software) implemented or utilized by any one or more of the methods or functions described herein (including, in various examples, the treatment processing logic 120 and the user interface 142). During execution of the instructions by the radiation therapy treatment computing system 110, the instructions may also reside in whole or at least in part within the memory 114 and / or within the processing circuit 112, wherein the memory 114 and the processing circuit 112 also constitute transitory or non-transitory machine-readable media.

[0037] The memory 114 and the storage device 116 may constitute a non-transitory computer-readable medium. For example, the memory 114 and the storage device 116 may store or load transient or non-transitory instructions for one or more software applications on a computer-readable medium. Software applications stored or loaded using the memory 114 and the storage device 116 may include, for example, operating systems for general-purpose computer systems and software-controlled devices. The radiotherapy treatment computing system 110 may also operate various software programs including software codes for implementing the treatment treatment logic 120 and the user interface 142. In addition, the memory 114 and the storage device 116 may store or load the entire software application, a portion of the software application, or code or data associated with the software application, which can be executed by the processing circuit 112. In other examples, the memory 114 and the storage device 116 may store, load, and manipulate one or more radiotherapy treatment plans, imaging data, segmentation data, treatment visualization, histograms, or measurement results, etc. It is contemplated that the software program may be stored not only on storage device 116 and memory 114, but also on removable computer media such as a hard drive, a computer disk, a CD-ROM, a DVD, a Blu-ray DVD, a USB flash drive, an SD card, a memory stick, or any other suitable media; such software programs may also be transmitted or received over a network.

[0038] Although not depicted, the radiotherapy treatment computing system 110 may include a communication interface, a network interface card, and a communication circuit. Example communication interfaces 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., an IEEE 802.11 / Wi-Fi adapter), a telecommunications adapter (e.g., communicating with 3G, 4G / LTE, and 5G networks, etc.), etc. Such a communication interface may include one or more digital and / or analog communication devices, one or more digital and / or analog communication devices allowing the machine to communicate with other machines and devices, such as remotely located components, via a network. The network may 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 may be a LAN or WAN that may include other systems (including additional image processing computing systems or image-based components associated with medical imaging or radiotherapy operations).

[0039] In an example, the radiation therapy treatment computing system 110 may obtain image data 152 from an image data source 150 (e.g., CT and / or MR images) to be hosted on the storage device 116 and the memory 114. In another example, the software program may replace the functionality of the patient image, such as a signed distance function or a processed version of the image that emphasizes some aspects of the image information.

[0040] In an example, the radiation therapy treatment computing system 110 may obtain image data 152 from or transmit image data 152 to the image data source 150. In other examples, the treatment data source 160 receives or updates planning data 162 as a result of radiation therapy device parameter adjustments or zone adaptations generated by the geometry-based radiation therapy treatment workflow 130; the image data source 150 may also provide or host the image data 152 for use in the geometry-based radiation therapy treatment workflow 130.

[0041] The processing circuitry 112 may be communicatively coupled to the memory 114 and the storage device 116, and the processing circuitry 112 may be configured to execute computer-executable instructions stored thereon from the memory 114 or the storage device 116. The processing circuitry 112 may execute the instructions to cause a medical image from the image data 152 to be received or obtained in the memory 114 and processed using the treatment processing logic 120.

[0042] In addition, the processing circuit 112 can utilize a software program to generate intermediate data, such as updated parameters to be used by, for example, a neural network model, a machine learning model, a geometry-based radiation therapy treatment workflow 130, or other aspects involved in the generation of device parameter adjustments or segment adaptations as discussed herein. Moreover, using the techniques further discussed herein, such a software program can utilize the treatment processing logic 120 to implement the geometry-based radiation therapy treatment workflow 130 to generate updated radiation therapy parameters to provide to the treatment data source 160 to modify the dose delivered to the target within a given fractionation and / or for presentation on the output device 146. The processing circuit 112 can then transmit the updated radiation therapy parameters to the treatment device 180 via the communication interface and network, where the updated parameters will be used to treat the patient with radiation via the treatment device 180, consistent with the results of the workflow 130. Other outputs and uses of the software program and workflow 130 can occur in conjunction with the use of the radiation therapy treatment computing system 110. Radiotherapy parameters (also called control points) can include MLC positions and settings for each segment or portion of a given treatment fraction, gantry angle, radiation dose (e.g., the amount of monitoring units (MU)), radiotherapy beam direction, radiation beam size, arc placement, beam switch duration, machine parameters, gantry speed, MRI pulse sequence, any combination thereof, and the like.

[0043] In an example, the image data 152 may include one or more MR 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, 2D cone beam CT, 3D CT, 3D CBCT, 4D CT, 4DCBCT), ultrasound images (e.g., 2D ultrasound, 3D ultrasound, 4D ultrasound), positron emission tomography (PET) images, X-ray images, fluoroscopic images, radiotherapy field images, single photon emission computed tomography (SPECT) images, computer-generated synthetic images (e.g., pseudo CT images), etc. In addition, the image data 152 may also include or be associated with medical image processing data such as training images and ground truth images, contour images, and dose images. In other examples, equivalent representations of anatomical regions may be represented in non-image formats (e.g., coordinates, mappings, etc.).

[0044] In an example, image data 152 may be received from an image acquisition device 170 and may be stored in one or more of an image data source 150 (e.g., a Picture Archiving and Communication System (PACS), a Vendor Neutral Archive (VNA), a medical record or information system, a data warehouse, etc.). Thus, the image acquisition device 170 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, a CBCT imaging device, or other medical imaging device for obtaining medical images of a patient. The image data 152 may be received and stored in any data type or any format type (e.g., in a Digital Imaging and Communications in Medicine (DICOM) format) that the image acquisition device 170 and the radiation therapy treatment computing system 110 may use to perform operations consistent with the disclosed embodiments. Furthermore, in some examples, the models discussed herein may be trained to process the original image data format or a derivative thereof.

[0045] In an example, the image acquisition device 170 can be integrated with the treatment device 180 into a single device (e.g., an MRI device combined with a linear accelerator, also referred to as an "MRI-Linac"). For example, such an MRI-Linac can be used to determine the location of a target within a patient's body, thereby accurately guiding the radiation beam to the predetermined target according to the radiotherapy treatment plan. For example, a radiotherapy treatment plan can provide information about the specific radiation dose to be applied to each patient. The radiotherapy treatment plan may also include other radiotherapy information and radiotherapy device parameters, such as beam angles, dose-volume histogram information, the number of radiation beams to be used during treatment, the dose per beam, etc. MRI-Linac can be used to calculate, generate and / or update a patient deformation model to deform an image portion of a 3D or 2D image of the patient corresponding to a given beam delivery segment.

[0046] The radiotherapy treatment computing system 110 can communicate with an external database via a network to send / receive multiple various types of data related to image processing and radiotherapy operations. For example, the external database may include machine data (including device constraints) that provides information associated with the treatment device 180, the image acquisition device 170, or other machines related to radiotherapy or medical procedures. The machine data information may include radiation beam size, arc placement, beam switch duration, machine parameters, sections, MLC configurations, gantry speeds, MRI pulse sequences, and the like. The external database may be a storage device and may be equipped with an appropriate database management software program. In addition, such a database or data source may include multiple devices or systems located in a central or distributed manner.

[0047] The radiation therapy treatment computing system 110 can collect and obtain data via a network and communicate with other systems using one or more communication interfaces, which are communicatively coupled to the processing circuit 112 and the memory 114. For example, the communication interface can provide a communication connection between the radiation therapy treatment computing system 110 and the radiation therapy system components (e.g., allowing data to be exchanged with external devices). For example, in some examples, the communication interface can have appropriate interface circuits with the output device 146 or the input device 148 to connect to the user interface 142, which can be a hardware keyboard, keypad, or touch screen through which a user can enter information into the radiation therapy system.

[0048] As an example, the output device 146 may include a display device that outputs a representation of the user interface 142 as well as one or more aspects, visualizations, or representations of a medical image, a treatment plan, and the status of training, generation, validation, or implementation of such a plan. The output device 146 may include one or more display screens that display a medical image, interface information, treatment planning parameters (e.g., contours, doses, beam angles, labels, mappings, etc.), a treatment plan, image portions identified and deformed for a given treatment segment, targets, positioning targets, and / or tracking targets, or any information relevant to a user. The input device 148 connected to the user interface 142 may be a keyboard, a keypad, a touch screen, or any type of device that a user can use to input information to the radiation therapy system 100. Alternatively, the output device 146, the input device 148, and the features of the user interface 142 may be integrated into a device such as a smart phone or tablet computer (e.g., an Apple Lenovo Samsung etc.) in a single device.

[0049] In addition, any and all components of the radiotherapy system 100 can be implemented as virtual machines (e.g., via VMWare, Hyper-V, and similar virtualization platforms) or stand-alone devices. For example, a virtual machine can be software used as hardware. Thus, 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 are collectively used as hardware. For example, the radiotherapy treatment computing system 110, the image data source 150, or similar components can be implemented as virtual machines or implemented within a cloud-based virtualization environment.

[0050] The image acquisition device 170 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, which is typically a 2D image or slice, can include one or more parameters (e.g., 2D slice thickness, orientation, and position, etc.). In an example, the image acquisition device 170 can acquire 2D slices of any orientation. For example, the orientation of the 2D slice can include a sagittal orientation, a coronal orientation, or an axial orientation. The processing circuit 112 can adjust one or more parameters such as the thickness and / or orientation of the 2D slice to include the target organ and / or the target tumor. In an example, the 2D slice can be determined based on information such as a 3D CBCT or CT or MRI volume. When the patient is undergoing radiotherapy treatment, such as when using the treatment device 180, such 2D slices can be acquired by the image acquisition device 170 in "near real time" (wherein, as known in the art, "near real time" means acquiring data without a lag (or with minimal lag) between image acquisition and treatment). In an example, a stack of one or more 2D slices may be used to generate a 3D volume representation of a region of interest.

[0051] Figure 2 An exemplary image-guided radiotherapy device 202 is shown, which includes a radiation source, such as an x-ray source or a linear accelerator, a bed 216, an imaging detector 214, and a radiotherapy output 204. The radiotherapy device 202 can be configured to emit a radiotherapy beam 208 to provide treatment to a patient. The radiotherapy output 204 can include one or more attenuators or collimators, such as a multi-leaf collimator (MLC).

[0052] As an example, a patient can be positioned in an area 212 supported by a treatment couch 216 to receive a radiation therapy dose in accordance with a radiation therapy treatment plan. The radiation therapy output 204 can be mounted or attached to a gantry 206 or other mechanical support. When the couch 216 is inserted into the treatment area, one or more chassis motors (not shown) can rotate the gantry 206 and the radiation therapy output 204 around the couch 216. In an example, the gantry 206 can continuously rotate around the couch 216 when the couch 216 is inserted into the treatment area. In another example, the gantry 206 can rotate to a predetermined position when the couch 216 is inserted into the treatment area. For example, the gantry 206 can be configured to rotate the treatment output 204 around an axis ("A"). Both the couch 216 and the radiation therapy output 204 can be independently moved to other positions around the patient, for example, movable in a transverse direction ("T"), movable in a lateral direction ("L"), or rotated about one or more other axes, such as about a transverse axis (shown as "R"). A controller communicatively connected to one or more actuators (not shown) can control the movement or rotation of the couch 216 to appropriately position the patient in or out of the radiation therapy beam 208 according to the radiation therapy treatment plan. Both the couch 216 and the gantry 206 can be moved independently of each other in multiple degrees of freedom, which allows the patient to be positioned so that the radiation therapy beam 208 can be precisely aimed at the tumor.

[0053] The coordinate system (including axes A, T, and L) can have an origin located at an isocenter 210. The isocenter 210 can be defined as the location at which the central axis of the radiotherapy beam 208 intersects the origin of the coordinate axes, such as to deliver a prescribed radiation dose to a location on a patient or a location within the body. Alternatively, the isocenter 210 can be defined as the location at which the central axis of the radiotherapy beam 208 intersects the patient for various rotational positions of the radiotherapy output 204 positioned by the gantry 206 about the axis A.

[0054] The gantry 206 may also have an attached imaging detector 214. The imaging detector 214 is preferably positioned opposite the radiation source (output 204), and in an example, the imaging detector 214 may be located within the field of the radiotherapy beam 208. The imaging detector 214 may preferably be mounted on the gantry 206 opposite the radiotherapy output 204, for example to maintain alignment with the radiotherapy beam 208. As the gantry 206 rotates, the imaging detector 214 rotates about the rotation axis. In an example, the imaging detector 214 may be a flat panel detector (e.g., a direct detector or a scintillator detector). In this way, the imaging detector 214 may be used to monitor the treatment beam 208, or the imaging detector 214 may be used to image the patient's anatomical structure, such as portal imaging. The control circuitry of the radiotherapy device 202 may be integrated within the radiotherapy system 100 or remote from the radiotherapy system 100.

[0055] In the illustrative example, one or more of the couch 216, the treatment output 204, or the gantry 206 can be automatically positioned, and the treatment output 204 can establish the radiotherapy beam 208 according to the specified dose for a particular treatment delivery instance. The sequence of treatment deliveries can be specified according to the radiotherapy treatment plan, for example, using one or more different orientations or positions of the gantry 206, the couch 216, or the radiotherapy output 204. The treatment deliveries can occur sequentially, but can intersect at a desired treatment site on or within the patient, such as at the isocenter 210. Thus, a prescribed cumulative dose of radiotherapy can be delivered to the treatment site while reducing or avoiding damage to tissue near the treatment site.

[0056] therefore, Figure 2 In particular, an example of a radiotherapy device 202 is shown that is operable to provide radiotherapy treatment to a patient in accordance with or in accordance with a radiotherapy treatment plan and parameters of the device adjusted within a given fractionation, having a configuration in which a radiotherapy output can rotate about a central axis (e.g., axis "A"). Other radiotherapy output configurations can be used. For example, the radiotherapy output can be mounted to a robotic arm or manipulator having multiple degrees of freedom. In another example, the treatment output can be fixed, such as located in an area laterally separated from the patient, and a platform supporting the patient can be used to align the radiotherapy isocenter with a specified target site in the patient's body. In another example, the radiotherapy device can be a combination of a linear accelerator and an image acquisition device. In some examples, 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., as will be recognized by a person of ordinary skill in the art.

[0057] Return to reference Figure 1, the geometry-based radiotherapy workflow includes a patient deformation process 132, a reference patient anatomy process 134, an image portion identification and deformation process 136, and a radiotherapy device parameter adaptation process 140. In an implementation, the processing implemented by the reference patient anatomy process 134, the image portion identification and deformation process 136, and the radiotherapy device parameter adaptation process 140 can be performed in real time during a given treatment fractionation (e.g., when each beam delivery segment begins or ends) and / or before or after the patient undergoes a given treatment fractionation.

[0058] In an example, a radiotherapy treatment plan for a given patient is obtained with reference to the patient anatomy process 134. A radiotherapy treatment plan can be generated by a clinician to deliver radiotherapy during one or more radiotherapy treatment fractionations. The radiotherapy treatment plan includes image information of the patient representing the OAR and the target to be irradiated. The image information can be a collection of 2D or 3D MR or CT images. The radiotherapy treatment plan also includes multiple radiotherapy beam delivery segments. Each beam delivery segment defines a set of radiotherapy device control points used throughout the radiotherapy treatment fractionation. In particular, one beam delivery segment defines a first set of control points used during a first time point or time interval of the treatment fractionation, and a second beam delivery segment defines a second set of control points used during a second time point or time interval of the treatment fractionation, the second time point or time interval being after, before and / or adjacent to the first time point. Multiple beam delivery segments define beam delivery parameters used throughout the treatment fractionation. The radiotherapy treatment plan also includes a depiction of one or more target volumes and / or one or more OARs.

[0059] In an example, a patient deformation process 132 generates, obtains, and / or updates a patient deformation model. The patient deformation model represents an estimated or predicted movement of a patient and / or a region of a patient during an upcoming, real-time, and / or past treatment segmentation. In an embodiment, the patient deformation model is generated based on at least one of one or more descriptions of the patient captured before or during a radiotherapy treatment segmentation. The one or more descriptions may be generated based on one or more magnetic resonance (MR) images, one or more computed tomography (CT) images, one or more cone beam computed tomography (CBCT) images, surface scans, or radio beacons. The patient deformation model may represent actual and / or estimated (predicted) patient movement at specific times or time intervals during a treatment segmentation and / or throughout a treatment segmentation. The patient deformation model may be provided as one or more displacement vectors.

[0060] In an example, the image portion recognition and deformation process 136 obtains control points for a given zone defined by a radiotherapy treatment plan. The image portion recognition and deformation process 136 processes the 3D or 2D image information in the reference treatment plan to identify a given portion of the 3D or 2D image information that intersects the given zone. In particular, the image portion recognition and deformation process 136 identifies a portion of the 3D or 2D image information that is within the field of view of the beam for a particular beam delivery zone in the beam delivery zones. The image portion recognition and deformation process 136 can identify one or more other portions for each additional zone in the treatment plan in the same manner.

[0061] In some embodiments, for each segment of the reference plan, all or part of the target volume will be irradiated. The image portion identification and deformation process 136 defines the identified portion as an elementary tracking volume (ETV) for a given segment, which is determined by the intersection of the three-dimensional target volume information (e.g., the moving target volume) and the three-dimensional cut-out of the patient, which is created by projecting the collimator opening of the segment relative to the source position throughout the patient volume. In particular, the portion identified in the reference patient image information includes the portion of the moving target volume that is irradiated by the current segment. The image portion identification and deformation process 136 can calculate or identify the portion of the patient volume that is irradiated or within the view of the beam by tracing the path of each pixel in the virtual screen from the imaginary eye (MLC view or beam view) and calculating the color of the objects visible through it. Any other tomographic reconstruction technique can be used to generate a projection image from the view of the MLC beam of the anatomical structure depicted in the 3D image of the patient for a given beam delivery segment.

[0062] In this way, the image portion recognition and deformation process 136 tracks or processes only the portion of the moving target volume that is within the collimator opening. The dose to the ETV is recreated for the purpose of ensuring target coverage. Given a voxelized representation of the patient, a selected set of voxels belonging to the ETV can be formally described by {v∈P:M*v∈S}, where P is the number of voxels belonging to the ETV. where M is the homogeneous transformation matrix that projects the point relative to the radiation source onto the isocenter plane, and S is the isocenter projection of the collimator opening of the segment that belongs to the isocenter plane. A set of points in . In this way, a tracking volume is created for each beam segment of the reference plan. In particular, the image portion recognition and deformation process 136 can identify the following portion of the patient image: the portion is within the field of view of the beam during a given segment and only includes the area within the portion corresponding to the tumor (or target to be irradiated). Other areas (e.g., OARs) that are also within the field of view of the beam within the identified portion can be excluded. In some embodiments, the image portion recognition and deformation process 136 can identify a first portion and a second portion for a given segment. The first portion may include an area of ​​the image portion within the field of view of the beam that only includes the target, and the second portion may include an area of ​​the image portion within the field of view of the beam that only includes the OAR. In this way, the movement of the OAR and the tumor (or target) at each segment can be tracked and represented separately. In some embodiments, the identified portion includes all or part of the target to be irradiated during the treatment segment and all or part of the OAR within or outside the field of view of the beam during the treatment segment.

[0063] In some embodiments, in addition to the ETV, the image portion identification and deformation process 136 tracks or identifies one or more additional volumes within the volume representation based on the 3D or 2D reference patient image. The additional image portions created may include tracked volumes that are in addition to the ETV, such as those in the volume representation based on the 2D or 3D reference patient image that are not in the image representation by the patient. voxels within the boundaries of the defined segment. The goal corresponding to the volume is to minimize excess in the target voxels. In particular, the image portion identification and deformation process 136 can identify, for a given segment, a first portion of the reference patient image that is within the field of view of the beam and a second portion of the reference patient image that is not within the field of view of the beam (e.g., the second portion can be a portion of the reference patient image that is within the field of view of the beam in the second segment within the treatment segmentation).

[0064] As another example, the image portion recognition and deformation process 136 includes the OAR in the tracking volume for each beam segment of the reference plan. The image portion recognition and deformation process 136 can track the portion of the OAR inside the beam segment, such as {v∈O:M*V∈S} and the complement of the volume Both, O is OAR Similarly, healthy tissue structures may be introduced in the tracking volume, which may also include both portions of the volume that intersect the current segment and portions that do not intersect the current segment. Adding these volumes to the tracking volume will force planning goals related to excess of these structures during tracking to be met for each beam segment. As described herein, a volume intersects a segment when the control points of the segment define a radiotherapy beam that irradiates a given portion (but not all) of an object depicted or included in a 2D or 3D patient reference image.

[0065] For example, the image portion identification and deformation process 136 may generate a first 3D cut-out of the patient by projecting an opening of the collimator at a first radiotherapy beam delivery zone relative to the source position. The image portion identification and deformation process 136 identifies a first portion of the reference patient imaging information within the field of view of the beam for a given zone based on the 3D cut-out of the patient. The image portion identification and deformation process 136 may generate a second 3D cut-out of the patient by projecting an opening of the collimator at a second radiotherapy beam delivery zone in the plurality of radiotherapy beam delivery zones relative to the source position. The image portion identification and deformation process 136 may identify a second portion of the 3D image information within the field of view of the beam during the second zone based on the second 3D cut-out of the patient.

[0066] In some embodiments, the image portion identification and deformation process 136 obtains a patient deformation model from the patient deformation process 132. The image portion identification and deformation process 136 deforms or adjusts the position or orientation of the identified image portion based on the patient deformation model (e.g., the following image portions of the reference image: within the field of view of the beam, outside the field of view of the beam during a given segment, only including the tumor within the field of view of the beam during a given segment, only including the OAR within the field of view of the beam during a given segment, including a portion of the OAR and a portion of the tumor within or outside the field of view of the beam during a given segment, and / or any combination thereof). The image portion identification and deformation process 136 performs such deformation and / or adjustment in real time during treatment fractionation, after radiotherapy treatment fractionation, and / or before radiotherapy treatment fractionation. In embodiments, the image portion identification and deformation process 136 performs such deformation and / or adjustment by applying a geometric transformation to the image portion at a given time or segment of a radiotherapy fractionation.

[0067] Figure 3 illustrative radiotherapy treatment image deformations according to some examples of the present disclosure are shown. Figure 3 As shown, the image portion recognition and deformation process 136 obtains a reference segment 310 that delivers radiation to a portion of a patient volume specified in a radiation therapy treatment plan for the patient. In particular, the image portion recognition and deformation process 136 obtains control points for a given segment and also obtains corresponding 2D or 3D image information from the treatment plan. The image portion recognition and deformation process 136 projects a view of a collimator or MLC using the control points to identify a portion of a volume representation based on the 2D or 3D image information that is within the view of the collimator or MLC during a given segment. This portion of the patient volume is irradiated during the delivery of the reference segment 310. Figure 3 A reference segment 310 and a projection of the 3D volume onto a 2D plane are shown.

[0068] For each reference segment 310, one or more regions (tracking volumes) are identified by the image portion identification and deformation process 136. For example, the image portion identification and deformation process 136 identifies a first region 320 that includes only a target or tumor in the reference segment 310. The first region 320 is drawn to include a portion 312 of the target in the reference segment 310 that is viewed in 3D from the collimator in the reference segment 310 below the OAR. In particular, the image portion identification and deformation process 136 identifies a first group of voxels in the reference segment 310 that correspond to the target to be irradiated. The image portion identification and deformation process 136 identifies a second region 322 that includes only a portion of the OAR in the reference segment 310. In particular, the image portion identification and deformation process 136 identifies a second group of voxels in the reference segment 310 that correspond to the OAR within the field of view of the beam and / or outside the field of view of the beam. In an embodiment, the image portion identification and deformation process 136 can identify a third region (not shown) that includes both the OAR and the tumor or target in the reference segment 310 and / or as part of another reference segment that is supplementary to the reference segment 310 and / or is not within the field of view of the beam.

[0069] Once the tracking volume is identified, the image portion identification and deformation process 136 obtains a patient deformation model. Using the patient deformation model, the image portion identification and deformation process 136 deforms each tracking volume separately and independently (e.g., adjusts the shape, size, position and / or orientation). For example, the image portion identification and deformation process 136 deforms the first group of voxels and the second group of voxels separately based on the deformation model. In this way, for example, the image portion identification and deformation process 136 deforms the region of the reference segment 310 that includes only the target or tumor separately and independently from the region of the reference segment 310 that includes only the OAR. The image portion identification and deformation process 136 generates a deformed tracking volume 330 that represents the adjustment made to the portion of the patient volume included in the tracking volume. In some embodiments, the image portion identification and deformation process 136 combines the first region 320 and the second region 322 into a single deformed tracking volume 330. In some cases, when setting the blades of the MLC, the first region 320 that includes only the tumor is considered separately from the second region 322 that includes only the OAR. In some embodiments, the image portion recognition and deformation process 136 stores deformed versions of the first region 320 and the second region 322 as separate images. In particular, as an example, as shown, based on the deformation model, the image portion recognition and deformation process 136 determines that the targets included in the first region 320 are rotated 20 degrees clockwise relative to their positions in the reference segment 310. In addition, based on the deformation model, the image portion recognition and deformation process 136 determines that the OARs in the second region 322 are rotated 10 degrees counterclockwise. The image portion recognition and deformation process 136 generates a deformed tracking volume 330 that includes or takes into account these deformations of the first region and the second region 322. In a similar manner, any other tracking volumes or regions identified for the current segment and / or one or more subsequent segments or previous segments (adjacent or non-adjacent) can be similarly deformed based on the deformation model. In some embodiments, the image portion recognition and deformation process 136 repeats the process of generating a deformed tracking volume 330 one or more times for each segment in the treatment plan for a given treatment segmentation. In some embodiments, the image portion identification and deformation process 136 is performed once for a given segment to define an image portion, and deformation of the image portion is performed more than once for a set of remaining segments.

[0070] Return to reference Figure 1 , the radiotherapy device parameter adaptation process 140 calculates new control points or updates control points for a given segment based on the deformed identified portion (e.g., the deformed tracking volume 330) provided by the image portion recognition and deformation process 136. In particular, the radiotherapy device parameter adaptation process 140 changes the shape of the beam delivered during the beam segment for which the first set of voxels and the second set of voxels ( Figure 3) (e.g., a first group of voxels in the reference segment 310 corresponding to the target to be irradiated and a second group of voxels in the reference segment 310 corresponding to OARs within the field of view of the beam and / or outside the field of view of the beam) calculate or determine the deformation. As an example, the radiotherapy device parameter adaptation process 140 calculates or updates one or more parameters of the radiotherapy treatment device based on the treatment objectives defined by the reference plan, wherein at least one of the treatment objectives penalizes exposure of voxels belonging to organs at risk (OARs) to prevent adjustment of one or more parameters that results in an increased dose to the OARs. In some embodiments, the radiotherapy device parameter adaptation process 140 updates one or more parameters (e.g., adjusts the position of multi-leaf collimator leaves and clips) to adapt the contours of an object (e.g., a target or tumor) depicted in the volumetric portion of the reference image for a given segment. In particular, the radiotherapy device parameter adaptation process 140 identifies a beam segment in the treatment plan that corresponds to the identified portion of the deformation.

[0071] That is, the radiotherapy device parameter adaptation process 140 determines which beam segment is used to identify the portion within the field of view of the beam during the beam segment. The radiotherapy device parameter adaptation process 140 then obtains the control points (e.g., radiotherapy device parameters) specified by the identified beam segment. Once the control points are obtained, the radiotherapy device parameter adaptation process 140 adjusts one or more control points based on the deformation (e.g., change in shape, orientation, and / or position) of the portion depicting the object (e.g., OAR and / or tumor). In an embodiment, the control points are adjusted to increase, decrease, or change the shape of the radiotherapy beam delivered during the identified segment to increase or decrease the amount of radiation exposed to the target and / or OAR.

[0072] In an embodiment, based on a deformed tracking volume (e.g., including an identified portion of an object that was within the field of view of the beam during the segment), a new segment (e.g., new control points) is determined by geometrically attempting to recreate the intent of the reference segment. Depending on which purpose of the reference plan is considered most important, the updated segment can be created in several different ways. Due to the limited resolution of both the projected MLC leaves and the projections themselves, which may be the case in voxelization, which should be accommodated, the updated positions of the MLC leaves and clips can be adapted to the deformed projection of the tracking volume in some way, such as adapting the middle position of the leaves to the contour of the object in the deformed portion and / or considering the distance of the reference plan's leaves / clips to the projection contour when setting the new position. For example, the radiotherapy device parameter adaptation process 140 can obtain treatment plan parameters for the identified segment that specify the distance between leaf and / or clip projections (e.g., the distance between the edge of the radiation beam to the OAR or a portion of the OAR). The radiotherapy device parameter adaptation process 140 recalculates the segment to generate a new beam shape for the deformed portion, which includes the portion of the OAR at a new position relative to the OAR position in the treatment plan parameters of the segment. When generating a new beam shape, the radiotherapy device parameter adaptation process 140 may maintain a specified distance between the edge of the radiation beam and the newly located portion of the OAR to be the same distance as in the treatment plan.

[0073] In an embodiment, the positions of the clips and leaves of the MLC are adjusted to the contours of the projected contours to ensure target (tumor) coverage. If an OAR has been included when creating a tracking volume for a given segment, the radiotherapy device parameter adaptation process 140 can generate new segment parameters or control points by penalizing the exposure of voxels belonging to the OAR, which ensures that the OAR dose objectives specified in the treatment plan are not violated when setting new leaf positions. For example, the radiotherapy device parameter adaptation process 140 can reduce the size or shape of the beam used for the segment in a manner that reduces the radiation exposure of the OAR.

[0074] As an example, the radiotherapy device parameter adaptation process 140 optimizes the MLC leaf positions based on the identified portion of the deformation. In particular, the positioning of the leaves and clips can be algorithmically determined by some criteria such as the maximum or average position of the target position contour depicted in the deformed image portion. A slightly more complex approach is to decide the leaf positions through optimization including trade-offs between different objectives and / or using a machine learning model. An example of an optimization process for leaf positioning is provided below, where the ETV and the supplemental ETV are used as tracking volumes. The function to be minimized (assuming that the radiotherapy device parameter adaptation process 140 only penalizes underdosing of the ETV and overdosing of the supplemental ETV) is defined as: min-w1n ETV，j +w2n cETV，j , n ETV，j, n cETV，j ≥0. Satisfied The weight of n ETV，j , n cETV，j is the number of voxels in leaf pair j that belong to the ETV and the supplementary ETV in the new segment. The number of voxels in each leaf pair j is determined by:

[0075]

[0076] Among them, ρ j (x) is the density of a given tracking volume along the axis parallel to the blade, a j and b j is the position of the blade, for example a quantity that should be determined in the optimization. In an embodiment, this optimization is inherently non-convex and can only be solved approximately.

[0077] In increasingly advanced scenarios, cumulative dose may be included in the positioning of the MLC leaves and clips, generating dosimetric tracking instead of or in addition to geometric tracking. The above optimization may then be updated to include the dose and dose density to be delivered in the segment instead of or in addition to voxels and voxel density. In an embodiment, the dose previously delivered to all structures may be taken into account when updating the current segment parameters. If the patient deformation is large, the radiotherapy device parameter adaptation process 140 may split the ETV into two or more parts after the deformation. If the dose is accumulated, this information may be used to construct new segments to compensate for underdosing during or after treatment. And conversely, if certain areas have received more dose than planned, segments or portions of segments may be removed during treatment to compensate for this effect.

[0078] In some embodiments, a first portion of a patient image in a treatment plan corresponds to a portion of a volume within a region to be irradiated during a first segment of a treatment segmentation. For example, the treatment processing logic 120 identifies a first portion of a volume representation from a stack of 2D or 3D reference images of the patient, the first portion including a target to be irradiated during a first segment of a treatment segmentation (e.g., a target within the field of view of the beam) (e.g., the first portion may include only the target and may exclude other regions that are also within the field of view of the beam during a second segment). A second portion of the patient image is identified, the second portion including a portion of a volume outside the region to be irradiated. The second portion may be from the same beam delivery segment and / or from another different beam delivery segment. For example, the treatment processing logic 120 identifies a second portion of a volume representation based on a 2D or 3D reference image of the patient, the second portion not including a target to be irradiated (e.g., a target within the field of view of the beam) but including an OAR outside the field of view of the beam (e.g., an OAR visible through the beam or within the view of the collimator during a subsequent or previous segment and / or an OAR not visible through the beam during the first segment). For example, the treatment processing logic 120 identifies a second portion of a 2D or 3D reference image of the patient, the second portion including a portion of a target to be irradiated (e.g., a target within the field of view of the beam) that is outside the field of view of the beam during a first segment, but within the field of view of the beam during a second segment. The first portion and the second portion are deformed separately based on a patient deformation model. After the first portion and the second portion are deformed, the radiotherapy device parameter adaptation process 140 updates the beam delivery segment (e.g., parameters of the current segment, the previous segment, and / or the subsequent segment) based on the deformed versions of the first portion and the second portion.

[0079] In some embodiments, a first portion of a patient image in a treatment plan corresponds to a volumetric portion within a region that includes a target to be irradiated during a first segment of a treatment segmentation. For example, the treatment processing logic 120 identifies a first portion of a volumetric representation of a 2D or 3D reference image of the patient that includes a target to be irradiated during a first segment of a treatment segmentation (e.g., a target within a field of view of a beam) (e.g., the first portion may include only the target and may exclude other regions that are also within the field of view of the beam during a second segment). A second portion of the patient image is identified that includes a volumetric portion of a target to be irradiated during a second segment (the second segment may be adjacent to or not adjacent to the first segment). For example, the treatment processing logic 120 identifies a second portion of a volumetric representation of a 2D or 3D reference image of the patient that includes a target to be irradiated during a second segment of a treatment segmentation (e.g., a target within a field of view of a beam) (e.g., the second portion may include only the target and may exclude other regions that are also within the field of view of the beam during the second segment). The first portion and the second portion are deformed separately based on a patient deformation model. After the first portion and the second portion are deformed, the radiation therapy device parameter adaptation process 140 updates the beam delivery sectors (eg, parameters of the current sector, previous sectors, and / or subsequent sectors) based on the deformed versions of the first portion and the second portion.

[0080] Figure 4 4 is a flow chart illustrating example operations of the treatment processing logic 120 in performing the process 400 according to an example implementation. The process 400 may be implemented in computer-readable instructions executed by one or more processors, such that the operations of the process 400 may be performed in part or in whole by functional components of the treatment processing logic 120; therefore, the process 400 is described below by way of example with reference thereto. However, in other implementations, at least some of the operations of the process 400 may be deployed on various other hardware configurations. Therefore, the process 400 is not intended to be limited to the treatment processing logic 120 and may be implemented in whole or in part by any other components. Some or all of the operations of the process 400 may be performed in parallel, out of order, or omitted entirely.

[0081] At operation 410 , the treatment processing logic 120 retrieves a reference plan that includes a three-dimensional (3D) volume representation based on image information of the patient and a plurality of radiotherapy beam delivery zones.

[0082] At operation 420 , the treatment processing logic 120 identifies, for a first beam delivery zone of the plurality of radiotherapy beam delivery zones, a first portion of the 3D image information that includes a volumetric portion of a target irradiated by the first beam delivery zone.

[0083] At operation 430 , the treatment processing logic 120 accesses a deformation model representing patient motion during the radiation therapy treatment fractionation.

[0084] At operation 440 , the therapy processing logic 120 deforms the first portion of the 3D image information based on the deformation model.

[0085] At operation 450 , the treatment processing logic 120 updates one or more parameters of the radiation therapy treatment device based on the deformed first portion of the 3D image information.

[0086] Figure 5 5 is a flow chart illustrating example operations of the treatment processing logic 120 in performing the process 500 according to an example embodiment. The process 500 may be implemented in computer-readable instructions executed by one or more processors, such that the operations of the process 500 may be performed in part or in whole by functional components of the treatment processing logic 120; therefore, the process 500 is described below by way of example with reference thereto. However, in other embodiments, at least some of the operations of the process 500 may be deployed on various other hardware configurations. Therefore, the process 500 is not intended to be limited to the treatment processing logic 120 and may be implemented in whole or in part by any other components. Some or all of the operations of the process 500 may be performed in parallel, out of order, or omitted entirely.

[0087] At operation 510 , the treatment processing logic 120 obtains one or more images of a patient.

[0088] At operation 520 , the treatment processing logic 120 renders the acquired one or more images of the patient.

[0089] At operation 530 , the treatment processing logic 120 generates a reference radiation therapy treatment plan using the depicted images, the reference radiation therapy treatment plan including a plurality of beam delivery zones.

[0090] At operation 540 , the treatment processing logic 120 identifies, for each beam delivery zone, one or more portions of the image in the reference radiation therapy treatment plan, the one or more portions including the area to be irradiated in the given zone.

[0091] At operation 550 , the treatment processing logic 120 obtains a patient deformation model for a given pair of control points in a reference radiation therapy treatment plan.

[0092] At operation 560 , the therapy processing logic 120 deforms the identified one or more portions of the image based on the patient deformation model.

[0093] At operation 570 , the treatment processing logic 120 uses the deformed portion of the image to calculate one or more new parameters for a given pair of control points in the radiotherapy beam delivery zone.

[0094] At operation 580, the treatment processing logic 120 determines whether there are additional control points to process, and if so, proceeds to operation 550 to calculate new parameters for the additional control points by deforming the image portion.

[0095] As previously discussed, each electronic computing system or device can implement one or more of the methods or functional operations discussed herein. In one or more embodiments, the radiotherapy treatment computing system 110 can be configured, adapted or used to control or operate the image-guided radiotherapy device 202, perform or implement the operations of process 400 and process 500, or perform any one or more of the other methods discussed herein. In various embodiments, such an electronic computing system or device operates as a standalone device or can be connected (e.g., networked) to other machines. For example, such a computing system or device can operate as a server or client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The features of the computing system or device can be implemented by a personal computer (PC), a tablet PC, a personal digital assistant (PDA), a cellular phone, a web device, or any machine capable of executing instructions (sequentially or otherwise) specifying actions to be taken by the machine.

[0096] As also indicated above, the functionality discussed above may be implemented by instructions, logic, or other information stored on a machine-readable medium. Although a machine-readable medium may have been described in various examples with reference to a single medium, the term "machine-readable medium" may include a single medium or multiple media (e.g., a centralized or distributed database and / or associated cache memories and servers) storing one or more transient or non-transient instructions or data structures. The term "machine-readable medium" should also be considered to include any tangible medium that is capable of storing, encoding, or carrying transient or non-transient instructions for execution by a machine and causing the machine to perform any one or more of the methods of the subject matter of the present invention, or any tangible medium that is capable of storing, encoding, or carrying data structures utilized by or associated with such instructions.

[0097] The above detailed description includes reference to the accompanying drawings, which form a part of the detailed description. The accompanying drawings show the specific embodiments in which the subject matter of the present invention can be practiced by way of explanation rather than by way of limitation. These embodiments are also referred to as "examples" in this article. Such examples may include elements other than those shown or described. However, the present disclosure also contemplates examples that only provide those elements shown or described. In addition, the present disclosure also contemplates 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 in this article.

[0098] All publications, patents, and patent documents cited in this document are incorporated herein by reference in their entirety, as if individually incorporated by reference. If there is an inconsistent usage between this document and those documents incorporated by reference, the usage in the incorporated reference should be considered supplementary to that of this document; for conflicting inconsistencies, the usage in this document controls.

[0099] In this document, the terms "a," "an," "the," and "said" are used when introducing elements of various aspects of the present subject matter or elements in embodiments thereof to include one or more than one or more of the elements as is common in patent documents, independent of any other instances or uses of "at least one" or "one or more." In this document, unless otherwise indicated, the term "or" is used to refer to a non-exclusive or such that "A or B" includes "including A but not B," "including B but not A," and "A and B."

[0100] In the following claims, the terms "including" and "in which" are used as the plain-English equivalents of the respective terms "comprising" and "wherein." Further, in the following claims, the terms "comprising," "including," and "having" are intended to be open-ended, to mean that there may be additional elements in addition to the listed elements, such that anything following such a term in a claim (e.g., comprising, including, having) is still considered to fall within the scope of the claim. Moreover, in the following claims, the terms "first," "second," and "third," etc. are used merely as labels, and are not intended to impose numerical requirements on their objects.

[0101] The subject matter of the present invention also relates to a computing system suitable for, configured to, or operated to perform the operations 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 (e.g., instruction, code, etc.) stored in a computer. Unless otherwise specified, the order of implementation or execution of the operations in the embodiments of the present invention shown and described herein is not necessary. That is, unless otherwise specified, operations may be performed in any order, and embodiments of the present invention may include additional or fewer operations compared to the operations disclosed herein. For example, it is contemplated that it is within the scope of the aspects of the subject matter of the present invention to implement or perform a specific operation before, simultaneously with, or after another operation, another operation.

[0102] In view of the above, it will be seen that the several objects of the inventive subject matter are achieved and other beneficial results are obtained. Having described aspects of the inventive subject matter in detail, it will be apparent that modifications and variations are possible without departing from the scope of aspects of the inventive subject matter as defined in the appended claims. As various changes may be made in the above-described constructions, products and methods without departing from the scope of aspects of the inventive subject matter, it is intended that all matter contained in the above description and shown in the accompanying drawings shall be interpreted as illustrative and not in a limiting sense.

[0103] The examples described herein may be implemented in various embodiments. For example, one embodiment includes a computing device including processing hardware (e.g., a processor or other processing circuit) and memory hardware (e.g., a storage device or volatile memory) including instructions implemented thereon, such that the instructions, when executed by the processing hardware, cause the computing device to implement, execute, or coordinate electronic operations for these techniques and system configurations. Another embodiment discussed herein includes a computer program product, which may be implemented, for example, by a machine-readable medium or other storage device, that provides transient or non-transient instructions for implementing, executing, or coordinating electronic operations for these techniques and system configurations. Another embodiment discussed herein includes a method that is capable of operating on the processing hardware of a computing device to implement, execute, or coordinate electronic operations for these techniques and system configurations.

[0104] In other embodiments, the logic, commands, or transient or non-transient instructions that implement various aspects of the above-described electronic operations may be provided in a distributed or centralized computing system, including any number of form factors for computing systems such as desktop or notebook personal computers, mobile devices such as tablet computers, netbooks and smart phones, client and server-hosted machine instances, etc. Another embodiment discussed herein includes incorporating the techniques discussed herein into other forms, including other forms of programmed logic, hardware configurations, or dedicated components or modules, including devices having corresponding means for performing the functions of such techniques. The corresponding algorithms for implementing the functions of such techniques may include sequences of some or all of the above-described electronic operations or other aspects depicted in the accompanying drawings and the following detailed description.

[0105] 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. In addition, without departing from the scope of the present disclosure, many modifications can be made to adapt specific situations or materials to the teachings of the present disclosure. Although the size, type, and example parameters, functions, and implementations of the materials described herein are intended to limit the parameters of the subject matter of the present invention, they are by no means restrictive embodiments, but exemplary embodiments. After reviewing the above description, many other embodiments will be apparent to those skilled in the art. Therefore, the scope of the subject matter of the present invention should be determined with reference to the full range of equivalents given by the attached claims and such claims.

[0106] In addition, in the above detailed description, various features can be combined together to simplify the present disclosure. This should not be interpreted as meaning that: unclaimed disclosed features are essential to any claim. Instead, the subject matter of the present invention may lie in less than all the features of a particular disclosed embodiment. Therefore, the attached claims are thus incorporated into the detailed description, wherein each claim itself independently serves as a separate embodiment. The scope of the subject matter of the present invention should be determined with reference to the attached claims and the full range of equivalents given to such claims.

Claims

1. A non-transitory computer readable medium comprising non-transitory computer readable instructions for adjusting a radiation therapy treatment of a patient in real time, the computer readable instructions comprising instructions for performing operations comprising: retrieving a reference plan comprising a three-dimensional (3D) volume representation of information of the patient and a plurality of radiotherapy beam delivery zones; identifying, for a first radiation therapy beam delivery zone of the plurality of radiation therapy beam delivery zones, a first portion of the 3D volume representation of the information, the first portion comprising a volumetric portion of a target irradiated by the first radiation therapy beam delivery zone; accessing a deformation model representing deformation of a patient during radiotherapy treatment fractionation; deforming the first portion of the 3D volumetric representation of the information based on the deformation model; as well as updating one or more parameters of the radiotherapy treatment device based on the deformed first portion of the 3D volumetric representation of the information, Wherein, the volume portion in the first part includes a portion of the target to be irradiated and an organ at risk, and the operation further includes: identifying a first group of voxels in the first portion corresponding to the target to be irradiated; identifying a second group of voxels in the first portion corresponding to the organ at risk; deforming the first set of voxels and deforming the second set of voxels respectively based on the deformation model; and A shape of a beam delivered during the first radiotherapy beam delivery section is changed based on the deformed first set of voxels and the deformed second set of voxels.

2. The non-transitory computer readable medium of claim 1, wherein: The reference plan comprises a delineation of one or more target volumes and / or one or more organs at risk (OARs), and wherein the 3D volume representation of the information comprises a plurality of two-dimensional image slices of the patient or a 3D volume representation of the patient.

3. The non-transitory computer readable medium according to claim 1 or 2, wherein: The operations further include generating the deformation model based on a description of the patient captured prior to or during the radiotherapy treatment fractionation, the description being based on one or more image capture modalities.

4. The non-transitory computer readable medium according to claim 1 or 2, wherein: The operations also include: generating a first 3D cut-out of the patient by projecting an opening of a collimator at the first radiotherapy beam delivery section relative to a source position; and The first portion is identified based on the first 3D cut-out of the patient.

5. The non-transitory computer readable medium of claim 4, wherein: The operations also include: generating a second 3D cut-out of the patient by projecting the opening of the collimator at a second one of the plurality of radiotherapy beam delivery sectors relative to the source position; and A second portion of the 3D volume representation of the information is identified for the second radiotherapy beam delivery zone based on the second 3D cut-out of the patient.

6. The non-transitory computer readable medium according to claim 1 or 2, wherein: The operations also include identifying a second portion of the 3D volume representation of the information, the second portion comprising a portion of the volume outside of a region irradiated in the first radiotherapy beam delivery zone.

7. The non-transitory computer readable medium of claim 6, wherein: The operations also include: deforming the first portion and the second portion respectively based on the deformation model; and The one or more parameters of the radiation therapy treatment device are updated based on the deformed first portion and the deformed second portion.

8. The non-transitory computer readable medium according to claim 1 or 2, wherein: Deforming the first portion includes applying a geometric transformation defined by the deformation model to the first portion.

9. The non-transitory computer readable medium according to claim 1 or 2, wherein: The one or more parameters of the radiotherapy treatment device are updated based on treatment objectives defined by the reference plan, wherein at least one of the treatment objectives penalizes exposure of voxels belonging to organs at risk (OARs) to prevent adjustments of the one or more parameters that result in increased dose to the OARs.

10. The non-transitory computer readable medium according to claim 1 or 2, wherein: Updating the one or more parameters includes adjusting positions of multi-leaf collimator leaves and clips to fit a contour of an object depicted in the volumetric portion.

11. The non-transitory computer readable medium according to claim 1 or 2, wherein: The operations also include: identifying, for a second radiation therapy beam delivery zone of the plurality of radiation therapy beam delivery zones, a second portion of the 3D volume representation of the information, the second portion comprising a second volumetric portion of the target irradiated by the second radiation therapy beam delivery zone; deforming the second portion of the 3D volumetric representation of the information based on the deformation model; and One or more parameters of the radiation therapy treatment device are updated based on a second portion of the deformed 3D volumetric representation of the information.

12. The non-transitory computer readable medium of claim 11, wherein: The operations further include combining the first portion and the second portion into a combined portion of the 3D volumetric representation of the information, wherein the deforming and the updating are performed on the combined portion of the 3D volumetric representation of the information.

13. A system for real-time adjustment of radiation therapy treatment for a patient, the system comprising: One or more processors for performing operations comprising: retrieving a reference plan comprising a three-dimensional (3D) volume representation of information of the patient and a plurality of radiotherapy beam delivery zones; identifying, for a first radiation therapy beam delivery zone of the plurality of radiation therapy beam delivery zones, a first portion of the 3D volume representation of the information, the first portion comprising a volumetric portion of a target irradiated by the first radiation therapy beam delivery zone; accessing a deformation model representing deformation of a patient during radiotherapy treatment fractionation; deforming the first portion of the 3D volumetric representation of the information based on the deformation model; and updating one or more parameters of the radiotherapy treatment device based on the deformed first portion of the 3D volumetric representation of the information, Wherein, the volume portion in the first part includes a portion of the target to be irradiated and an organ at risk, and the operation further includes: identifying a first group of voxels in the first portion corresponding to the target to be irradiated; identifying a second group of voxels in the first portion corresponding to the organ at risk; deforming the first set of voxels and deforming the second set of voxels respectively based on the deformation model; and A shape of a beam delivered during the first radiotherapy beam delivery section is changed based on the deformed first set of voxels and the deformed second set of voxels.

14. The system according to claim 13, wherein: The reference plan comprises a delineation of one or more target volumes and / or one or more organs at risk (OARs), and wherein the 3D volume representation of the information comprises a plurality of two-dimensional image slices of the patient or a 3D volume representation of the patient.

15. The system according to claim 13 or 14, wherein: The operations further include generating the deformation model based on a description of the patient captured prior to or during the radiotherapy treatment fractionation, the description being based on one or more image capture modalities.

16. The system according to claim 13 or 14, wherein: The operations also include: generating a first 3D cut-out of the patient by projecting an opening of a collimator at the first radiotherapy beam delivery section relative to a source position; and The first portion is identified based on the first 3D cut-out of the patient.

17. The system of claim 16, wherein: The operations also include: generating a second 3D cut-out of the patient by projecting the opening of the collimator at a second one of the plurality of radiotherapy beam delivery sectors relative to the source position; and A second portion of the 3D volume representation of the information is identified for the second radiotherapy beam delivery zone based on the second 3D cut-out of the patient.

18. The system according to claim 13 or 14, wherein: The operations also include identifying a second portion of the 3D volume representation of the information, the second portion comprising a portion of the volume outside of a region irradiated in the first radiotherapy beam delivery zone.

19. The system of claim 18, wherein: The operations also include: deforming the first portion and the second portion respectively based on the deformation model; and The one or more parameters of the radiation therapy treatment device are updated based on the deformed first portion and the deformed second portion.

20. The system according to claim 13 or 14, wherein: Deforming the first portion includes applying a geometric transformation defined by the deformation model to the first portion.

21. The system according to claim 13 or 14, wherein: The one or more parameters of the radiotherapy treatment device are updated based on treatment objectives defined by the reference plan, wherein at least one of the treatment objectives penalizes exposure of voxels belonging to organs at risk (OARs) to prevent adjustments of the one or more parameters that result in increased dose to the OARs.

22. The system according to claim 13 or 14, wherein: Updating the one or more parameters includes adjusting positions of multi-leaf collimator leaves and clips to fit a contour of an object depicted in the volumetric portion.

23. The system according to claim 13 or 14, wherein: The operations also include: identifying, for a second radiation therapy beam delivery zone of the plurality of radiation therapy beam delivery zones, a second portion of the 3D volume representation of the information, the second portion comprising a second volumetric portion of the target irradiated by the second radiation therapy beam delivery zone; deforming the second portion of the 3D volumetric representation of the information based on the deformation model; and One or more parameters of the radiation therapy treatment device are updated based on a second portion of the deformed 3D volumetric representation of the information.

24. The system of claim 23, wherein: The operations further include combining the first portion and the second portion into a combined portion of the 3D volumetric representation of the information, wherein the deforming and the updating are performed on the combined portion of the 3D volumetric representation of the information.

Images