Systems, methods and software for magnetic resonance imaging-guided radiation therapy

Abstract

Systems, methods, and computer software are disclosed that may include receiving a treatment prescription for a patient and retrieving a diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflow (MRgRT&P workflow) associated with the treatment prescription from a workflow library, the diagnosis-based MRgRT&P workflow having a parameter list comprising parameters utilized for MRI-guided radiation therapy. The diagnosis-based MRgRT&P workflow may perform any of the following: imaging with an MRI-guided radiation therapy system utilizing radiation therapy imaging parameters from the parameter list; generating a radiation therapy plan utilizing radiation therapy planning parameters from the parameter list; and / or controlling an MRI-guided radiation therapy system utilizing radiation therapy delivery parameters from the parameter list.

Description

[Technical Field]

[0001] This application claims priority to and the benefit of U.S. Provisional Patent Application No. 63 / 417,921, filed October 20, 2022, entitled "Systems, Methods, and Software for Magnetic Resonance Imaging-Guided Radiation Therapy," which is incorporated by reference. [Background technology]

[0002] Magnetic resonance imaging (MRI) or nuclear magnetic resonance imaging is a non-invasive imaging technique that uses the interaction of radio frequency pulses and a strong magnetic field (varying by weak gradient fields applied across it to specifically encode or decode phase and frequency) with body tissue to obtain projections, spectral signals, and planar or volumetric images from within a patient's body. Magnetic resonance imaging is particularly useful in imaging soft tissues and may be used to diagnose disease. Real-time MRI or cine MRI may be used to diagnose health conditions that require imaging of moving structures within a patient. Real-time MRI may also be used in conjunction with interventional procedures such as radiation therapy or image-guided surgery. Summary of the Invention [Means for solving the problem]

[0003] In one aspect, systems, methods, and computer software are disclosed that may include at least one programmable processor and non-transitory machine-readable medium stored instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising accepting a treatment prescription for a patient and retrieving a diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflow (MRgRT&P workflow) associated with the treatment prescription from a workflow library, the diagnosis-based MRgRT&P workflow having a parameter list comprising parameters utilized for MRI-guided radiation therapy. The diagnosis-based MRgRT&P workflow may include: imaging with an MRI-guided radiation therapy system utilizing radiation therapy imaging parameters from the parameter list; generating a radiation therapy plan utilizing radiation therapy planning parameters from the parameter list; and / or controlling an MRI-guided radiation therapy system utilizing radiation therapy delivery parameters from the parameter list.

[0004] In some variations, the treatment prescription may include disease type, treatment site, stage, total dose, number of fractions, dose per structure per fraction, minimum / maximum / average dose constraints, and / or dose constraints to targets and organs.

[0005] In some variations, obtaining the diagnosis-based MRgRT&P workflow may include comparing the treatment prescription to a stored treatment prescription associated with the stored diagnosis-based MRgRT&P workflow, and returning the stored treatment prescription and the stored diagnosis-based MRgRT&P workflow that matches the treatment prescription.

[0006] In some variations, the radiation therapy imaging parameters may include one or more volumetric imaging parameters, planar imaging parameters, or tissue tracking parameters.

[0007] In some variations, the radiation treatment planning parameters may include one or more of an anatomical identification parameter, an auto-contouring parameter, or a relative electron density parameter.

[0008] In some variations, the radiation therapy delivery parameters may include one or more of beam energy, MLC position, or couch position.

[0009] In some variations, the operations may include providing a workflow editor configured to facilitate correction of the MRgRT&P workflow based on the diagnosis.

[0010] In some variations, the computation may include retrieving additional diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflows (MRgRT&P workflows) associated with the treatment prescription from a workflow library and presenting a number of selectable diagnosis-based MRgRT&P workflows to the user.

[0011] In interrelated aspects, the systems, methods, and computer software may include at least one programmable processor and non-transitory machine-readable medium stored instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising capturing initial parameters for a diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflow (MRgRT&P workflow) associated with a treatment prescription, the capturing comprising recording initial parameters utilized during imaging with an MRI-guided radiation therapy system, utilized during generation of the radiation therapy plan, and utilized during control of the MRI-guided radiation therapy system, creating the diagnosis-based MRgRT&P workflow with the initial parameters, and storing the diagnosis-based MRgRT&P workflow associated with the treatment prescription in a workflow library.

[0012] Implementations of the present subject matter may include, but are not limited to, methods consistent with the description provided herein and articles comprising tangibly embodied machine-readable media operable to cause one or more machines (e.g., computers, etc.) to perform operations that implement one or more of the described features. Similarly, computer systems, which may include one or more processors and one or more memories coupled to the one or more processors, are also contemplated. The memory, which may include a computer-readable storage medium, may include, encode, store, etc., one or more programs that cause the one or more processors to perform one or more of the described operations. A computer-implemented method consistent with one or more implementations of the present subject matter may be performed by one or more data processors in one computing system or multiple computing systems. Such multiple computing systems may be connected and exchange data and / or commands or other instructions, etc., via one or more connections, including, but not limited to, connections over a network (e.g., the Internet, a wireless wide area network, a local area network, a wide area network, a wired network, etc.) via a direct connection between one or more of the multiple computing systems, etc.

[0013] The details of one or more variations of the subject matter described herein are set forth in the accompanying drawings and the following description. Other features and advantages of the subject matter described herein will be apparent from the specification and drawings, and from the claims. While certain features of the presently disclosed subject matter are described for illustrative purposes with respect to particular implementations, it should be readily understood that such features are not intended to be limiting. The claims following this disclosure are intended to define the scope of protected subject matter. [Brief explanation of the drawings]

[0014] The accompanying drawings, which are disclosed in and constitute a part of this specification, illustrate certain aspects of the presently disclosed subject matter and, together with the description, help to explain certain principles associated with the disclosed implementations. [Figure 1]FIG. 1 is a diagram illustrating an exemplary parameter list that may be utilized in magnetic resonance imaging-guided radiation therapy (MRgRT) imaging, planning, or delivery according to certain aspects of the present disclosure. [Figure 2] FIG. 2 is a diagram illustrating the generation and storage of a diagnostic-based magnetic resonance guided radiation therapy and planning (MRgRT&P) workflow according to certain aspects of the present disclosure. [Figure 3] FIG. 3 is a diagram illustrating the use of a diagnostic-based MRgRT&P workflow according to certain aspects of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0015] FIG. 1 illustrates an exemplary parameter list that may be utilized in magnetic resonance-guided radiation therapy (MRgRT) imaging, planning, and / or delivery in accordance with certain aspects of the present disclosure. MRgRT is a highly complex and precise procedure that may involve dozens (or even hundreds) of decisions during the planning and execution of the imaging / planning / treatment workflow. Treatment planning for a patient may involve not only determining a radiation treatment plan but also determining machine parameters (e.g., for the MRI and radiation source) utilized during treatment. This disclosure generally separates such parameters (e.g., parameter list 100) into three sections: imaging parameters 110, planning parameters 130, and delivery parameters 150. However, a particular parameter may be utilized in more than one section. For example, some imaging parameters may be determined as part of imaging performed during the planning procedure and may also be used during imaging in the delivery procedure. Thus, in various embodiments, parameter list 100 may include any combination of the parameters described herein. However, the parameters disclosed herein are not intended to be an exhaustive list, and other parameters utilized in planning, imaging, and irradiation may be included within the scope of this disclosure and should be considered.

[0016] Radiation therapy imaging parameters 110 may include volumetric imaging parameters 112 (shown separately in FIG. 1 but similar or identical to volumetric imaging parameters 132 used in planning). Other parameters may include planar imaging parameters 114 for cine imaging, such as the cine effect for treatment, cine label, cine recording, number of planes, plane orientation (axial, sagittal, coronal, oblique), contrast, frame rate, slice thickness, in-plane analysis, cine origin, cine view, etc. Further parameters may include tissue tracking parameters 116, such as the structure to track in each plane, how to generate tracking boundaries for each tracked structure, including isodose level thresholds (>dose level, or <dose level), boundary structures, or structure margin expansion in each specific direction (+x, -x, +y, -y, +z, -z). Gating parameters for each plane may include soft tissue tracking algorithm (e.g., standard, highly deformed, small and mobile, etc.), percentage area encroachment allowed, percentage confidence value, display settings for patient (e.g., hidden contour-only image and contour), k-space blending on / off, noise removal on / off using noise parameters, motion correction on / off, number of times tracking is turned off between frames (e.g., 0-5), number of times tracking is turned on between frames (e.g., 0-5), etc.

[0017] The radiation treatment planning parameters 130 may include one or more of volumetric imaging parameters 132, image registration parameters 134, anatomical segmentation parameters 136, treatment planning parameters 138, treatment plan dose parameters 140, treatment plan optimization parameters 142, dose display parameters 144, treatment selection parameters 146, etc.

[0018] Volumetric imaging parameters 132 for initial treatment planning and daily setup integration may include, for example, the following parameters: Planned patient orientation can be specified, for example, head-first or feet-first, and prone or supine. Parameters for couch position may be used to set the imaging volume. Parameters for known treatment locations (e.g., tumors) and / or anatomical regions, such as organs at risk, may be used for volume constraints or initial setup (e.g., approximate size of tumor, lungs, heart, etc.). The number of scans and scan contrast (pulse sequence) for each scan may be set, as well as which scans are required for treatment. Parameters for skin masking algorithms or thresholds for skin surface determination (e.g., given intensity values ​​or image gradients, noise floors, etc.) may be used (e.g., to detect and define skin surfaces outside of which volumetric imaging is not required). In some embodiments, imaging parameters determined during pre-treatment imaging may be further used during treatment (e.g., by real-time MRgRT).

[0019] Some embodiments may include volumetric imaging parameters that can be set for each scan. For example, a scan label, scan record, and scan position may be set. A field of view (FOV) may be set. The system may also accept or reject such settings based on a skin mask. For example, if the skin mask is more than 1 cm but less than 2 cm inside, the FOV may be accepted; otherwise, the FOV may be expanded or contracted to add 1 cm of margin if small or 2 cm if large. Parallel imaging configurations may be set, such as parallel imaging along 0, 1, or 2 axes. Scan resolution may be set, such as high resolution for critical features or small dimensions and low resolution in non-critical areas. Other parameters may include planned breath holds, such as acquiring images during inspiration and expiration, or no breath holds if no breath holds are used.

[0020] Image registration parameters 134 may include parameters for secondary image sets defined for deformable image registration to aid in planning, such as defining any X-ray CT scan that produces a relative electron density (RED) map or pre-irradiated doses defined for deformable image registration.

[0021] Anatomical segmentation parameters 136 may include target and OAR definitions for treatment planning, Boolean operators and rules for creating contours, auto-contouring templates, definitions for synthetic CT creation, RED density overrides, color of each target or OAR, display of segmentations as lines, line thickness, and / or water-based paint on / off with percent opacity, etc.

[0022] The treatment planning parameters 138 may include the number of isocenters, the locations of the isocenters, the location of the couch relative to the planning isocenters, the number of beams at each isocenter, the type of each beam (e.g., conformal or intensity modulated radiation therapy (IMRT)), beam aperture generation rules for each conformal beam (e.g., structure and clearance in each beam direction), etc.

[0023] Treatment plan dose parameters 140 include pixel size (e.g., 4 mm x 4 mm or 3 mm or 2 mm), dose grid resolution, IMRT efficiency (e.g., 0.2 to 20), pixel history / cm from Monte Carlo dose calculations, 2 (e.g., 15,000), total segment history with Monte Carlo dose calculations (e.g., 4,800,000), options to use magnetic field in pixel dose calculations or magnetic field in segment dose calculations, etc.

[0024] The treatment plan optimization parameters 142 may include the type of IMRT leaf sequencer (e.g., fixed segments, accuracy goal, or fixed discretization), the maximum leaf sequencer discretization (e.g., 1 to 16), the leaf sequencer accuracy goal (e.g., 0.1 to 0.01), the maximum number of segments, the type of optimization objective function (simple or advanced), etc. For targets and OARs in the advanced objective function, other parameters may include the objective importance, the objective power, increasing or decreasing, etc. For targets and OARs in the simple objective function, other parameters may include the objective high importance, the objective low importance, the objective high power, the objective low power, the threshold dose, etc. For each target or OAR, other parameters may further include constraints such as minimum dose or less, maximum dose or less, average dose or less, average dose, etc. Parameters for the dose histogram constraints for the advanced objective function of each target or OAR may include the volume in percent or cc, the dose or less, etc.

[0025] The dose display parameters 144 may include the number of isodose lines, the dose level of each isodose line, the isodose line display in Gy (gray) or percentage, the color of each isodose line, the thickness of the isodose line, the opacity of the isodose line, dose water paint on or off, the water paint color map, the water paint opacity, the water paint display in Gy or percentage, the minimum water paint value, the maximum water paint value, etc.

[0026] Treatment selection parameters 146 may include adaptive or non-adaptive, adding the approved treatment plan to the fraction delivery calendar, setting subsequent adaptive fractions to become a new online adaptive plan or the original plan, etc.

[0027] In some embodiments, radiation treatment planning parameters that may be utilized to create relative electron density (RED) settings or maps may further include anatomical identification parameters (e.g., adjustment or labeling of structures or compositions within a patient), auto-contouring parameters (e.g., similar to anatomical segmentation parameters 116), relative electron density parameters (e.g., RED values ​​placed on identified anatomical structures), etc.

[0028] The radiation treatment delivery parameters 150 may include one or more of beam energy 152, MLC position 154, or couch position 156. Such radiation treatment delivery parameters may thereby provide the physical configuration of the radiation delivery device (e.g., power supply connected, MLC leaves at a particular location, treatment couch positioned at a particular height / orientation, etc.).

[0029] The present disclosure contemplates automating certain aspects of radiation therapy planning, imaging, and / or treatment. This may be done by utilizing pre-determined parameters for a particular treatment prescription in imaging, planning, and / or treatment procedures for patients with a particular diagnosis. The parameters associated with the treatment prescription may constitute what is described herein as a diagnosis-based MRgRT&P workflow (note that although the acronym does not explicitly include an "I," when this disclosure uses this term, it is understood that imaging parameters may be included in the workflow as described).

[0030] 2 is a simplified diagram illustrating the generation of a diagnosis-based magnetic resonance guided radiation therapy and planning (MRgRT&P) workflow according to certain aspects of the present disclosure. In some embodiments, the diagnosis-based MRgRT&P workflow may be generated through manual data entry of parameters such as those described above. In other embodiments, the diagnosis-based MRgRT&P workflow may be generated in part or entirely through the incorporation of parameters utilized during actual sessions of imaging, planning, and / or treatment (e.g., performed by an expert or experienced clinician).

[0031] In the exemplary procedure 200 of Figure 2, initial parameters for a diagnosis-based MRgRT&P workflow associated with a treatment prescription may be captured at 210. Capture may include recording of initial parameters used during imaging with the MRI-guided radiation therapy system (e.g., any of the imaging parameters 110), during generation of a radiation treatment plan (e.g., any of the planning parameters 130), and / or during control of the MRI-guided radiation therapy system (e.g., any of the delivery parameters 150). In one embodiment, capture may be performed by a system that automatically captures data entry fields, keystrokes, or other manual computer inputs.

[0032] At 220, a diagnosis-based MRgRT&P workflow may be created based on the captured parameters by associating a set of initial parameters 224 with the diagnosis-based MRgRT&P workflow. Any subcombination of the captured initial parameters may be used, for example, including only certain parameters related to planning, imaging, delivery, planning and imaging, planning and delivery, or planning, imaging, and delivery. In a preferred embodiment, the diagnosis-based MRgRT&P workflow includes parameters related to imaging, planning, and treatment, although the present disclosure contemplates diagnosis-based MRgRT&P workflows that potentially include parameters related to only a subset of the above MRgRT operations.

[0033] The present disclosure also contemplates systems and software that provide a workflow editor configured to facilitate diagnostic-based MRgRT&P workflow corrections, which may include utilizing a graphical user interface (GUI) to, for example, change parameter values, modify anatomical contours, update labels, modify treatment goals and constraints, change imaging or radiation therapy machine settings, etc.

[0034] A diagnosis-based MRgRT&P workflow may be associated with a treatment prescription 222. As used herein, the term "treatment prescription" broadly describes a patient's diagnosis and / or the parameters of a particular treatment for the patient. For example, a treatment prescription may include any of the following: disease type (e.g., malignant or benign), treatment site, stage (T, N, M), grade, initial reference target, objective (curative, palliative, etc.), total dose, number of fractions, dose per fraction, dose constraints to the target including target prescription dose range specifications (e.g., the prescription dose (Drx) covers ≥ 95% of the target volume), target hot spot dose tolerance (e.g., ≤ 1% of the target volume is covered by > 107% of Drx), target cold spot dose tolerance (e.g., ≥ 99% of the target volume is covered by 95% of Drx), dose constraints to healthy risk organs for treatment of a given diagnosis (e.g., dose constraints to the bladder, rectum, and thigh in the treatment of prostate cancer), minimum dose constraints to the target, average dose constraints to the target and healthy risk organs, maximum dose constraints to the target and healthy risk organs, etc. Also, as used herein, "dose" may be a physical dose in Gy or a biologically effective dose (BED).

[0035] In some embodiments, there may be different (i.e., multiple) diagnosis-based MRgRT&P workflows for a particular diagnosis. For example, when treating prostate cancer, a diagnosis-based MRgRT&P workflow may provide parameters for treatment with 24 Gy in one fraction, while other diagnosis-based MRgRT&P workflows may treat with, for example, 8 Gy in five fractions or 2 Gy in 39 fractions, such that each of these treatment plans delivers a similar biologically equivalent dose.

[0036] It is also contemplated that there may be different (i.e., multiple) diagnosis-based MRgRT&P workflows for a given treatment prescription. For example, different workflows for the same prescription may include different optimization parameters for the plan (e.g., treatment plan optimization parameters 142, etc.). Different optimization settings may then provide different plans that may result in slightly different doses to the target, organ sparing, etc., and a user may utilize multiple workflows to compare similar plans and select a preferred plan.

[0037] At 230, the diagnosis-based MRgRT&P workflow may be stored in a workflow library associated with the treatment prescription. The workflow library may be any data store and may contain other diagnosis-based MRgRT&P workflows that may be generated for other treatment prescriptions. In other embodiments, the diagnosis-based MRgRT&P workflow may be stored in a database 240 (e.g., a local server or other computer memory) that can be accessed by the workflow library 230 to incorporate any number of diagnosis-based MRgRT&P workflows 220.

[0038] 3 is a diagram illustrating an exemplary use of a diagnosis-based MRgRT&P workflow according to certain aspects of the present disclosure. At 310, procedure 300 may include accepting a patient treatment prescription, such as by a system interpreting entered clinician text or fields, selecting a predefined treatment prescription (e.g., from a list), etc. For example, the treatment prescription may include disease type, treatment site, disease stage, total dose, number of fractions, dose per structure per fraction, minimum / maximum / average dose constraints, and / or dose constraints to targets and organs, etc.

[0039] At 320, a diagnosis-based MRgRT&P workflow 330 associated with a treatment prescription 332 may be retrieved from the workflow library 320. The diagnosis-based MRgRT&P workflow 330 may include a parameter list 334 with parameters utilized for MRI-guided radiation therapy. For example, given the input of a treatment prescription at 310, an appropriate diagnosis-based MRgRT&P workflow may be found in the workflow library 320, for example, by comparing the treatment prescription with a stored treatment prescription associated with the stored diagnosis-based MRgRT&P workflow. The system may then return the stored diagnosis-based MRgRT&P workflow along with the stored treatment prescription that matches the treatment prescription. The parameter list 334 may include parameters that were previously generated and stored during the generation procedure (e.g., as described with reference to FIG. 2).

[0040] In some cases, the system may return multiple different diagnosis-based MRgRT&P workflows to the user for selection. For example, workflows for a particular treatment prescription may include different optimization parameters for planning, and the user may be presented with multiple workflows and utilize / select the one deemed most desirable. Thus, the system may be configured to retrieve additional diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflows (MRgRT&P workflows) associated with the treatment prescription from a workflow library and present the user with multiple selectable diagnosis-based MRgRT&P workflows.

[0041] Although the diagnosis-based MRgRT&P workflow 330 may be utilized for planning, imaging, treatment, etc., some embodiments allow for editing the diagnosis-based MRgRT&P workflow 340 prior to use. For example, various parameters may be modified by a physician or technician based on a patient's specific needs or imaging / planning / delivery system configuration. However, the automatic recall and application of pre-determined parameters in the diagnosis-based MRgRT&P workflow of the present disclosure dramatically reduces such manual requirements.

[0042] The MRgRT&P workflow 330 based on the recalled diagnosis enables the system to subsequently perform any combination of imaging with an MRI-guided radiation therapy system 360 utilizing the radiation therapy imaging parameters in the parameter list 334, generating a radiation therapy plan utilizing the radiation therapy planning parameters in the parameter list 334 (at 350 in FIG. 3), and controlling the MRI-guided radiation therapy system utilizing the radiation therapy delivery parameters in the parameter list 334 (at 370, represented in FIG. 3 by a typical gantry-mounted radiation therapy system inside a split MRI).

[0043] While the above-described embodiments may be used for imaging, planning, and treatment, other embodiments may include those in which the diagnostically-based MRgRT&P workflow 330 is used with any one or two of these stages in a subcombination. In one embodiment, the system is capable of generating a radiation treatment plan using radiation treatment planning parameters in the parameter list 334 and controlling an MRI-guided radiation treatment system using radiation treatment delivery parameters in the parameter list. In another embodiment, the system is capable of imaging with an MRI-guided radiation treatment system using radiation treatment imaging parameters in the parameter list 334 and generating a radiation treatment plan using radiation treatment planning parameters in the parameter list 334. In yet another embodiment, the system is capable of imaging with an MRI-guided radiation treatment system using radiation treatment imaging parameters in the parameter list 334 and controlling an MRI-guided radiation treatment system using radiation treatment delivery parameters in the parameter list 334. In other embodiments, the system may be configured for one of imaging with an MRI-guided radiation treatment system using radiation treatment imaging parameters in the parameter list 334, generating a radiation treatment plan using radiation treatment planning parameters in the parameter list 334, or controlling an MRI-guided radiation treatment system using radiation treatment delivery parameters in the parameter list 334.

[0044] In some implementations, the procedures described herein may further include requesting user confirmation regarding the creation, imaging, and / or control based on parameter list 334. For example, the system may request confirmation of parameters in a diagnostic-based MRgRT&P workflow at various steps throughout the procedure to ensure that the user desires to proceed in a specified manner.

[0045] Hereinafter, further features, characteristics and exemplary technical solutions of the present disclosure will be described in terms of the items that can be selected and claimed in any combination.

[0046] Item 1 is a system comprising at least one programmable processor and non-transitory machine-readable medium stored instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising accepting a treatment prescription for a patient and retrieving from a workflow library a diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflow (MRgRT&P workflow) associated with the treatment prescription, wherein the diagnosis-based MRgRT&P workflow has a parameter list comprising parameters used for MRI-guided radiation therapy, i.e., imaging using an MRI-guided radiation therapy system utilizing radiation therapy imaging parameters from the parameter list, generating a radiation therapy plan utilizing radiation therapy planning parameters from the parameter list, and / or controlling an MRI-guided radiation therapy system utilizing radiation therapy delivery parameters from the parameter list.

[0047] Item 2 is a system as in Item 1 in which the treatment prescription includes disease type, treatment site, stage, total dose, number of fractions, dose per structure per fraction, minimum / maximum / average dose constraints, and / or dose constraints to targets and organs.

[0048] Item 3 is a system such as any one of the preceding items, wherein obtaining a diagnosis-based MRgRT&P workflow comprises comparing the treatment prescription with a stored treatment prescription associated with the stored diagnosis-based MRgRT&P workflow, and returning the stored diagnosis-based MRgRT&P workflow with the stored treatment prescription that matches the treatment prescription.

[0049] Item 4 is a system such as any one of the preceding items, wherein the radiation treatment planning parameters include one or more of an anatomical identification parameter, an auto-contouring parameter, or a relative electron density parameter.

[0050] Item 5 is a system such as any one of the preceding items, wherein the radiation treatment planning parameters include one or more of volumetric imaging parameters, image registration parameters, anatomical fractionation parameters, treatment planning parameters, treatment plan dose calculation parameters, treatment plan optimization parameters, dose display parameters, or treatment selection parameters.

[0051] Item 6 is a system such as any one of the preceding items, wherein the radiation therapy imaging parameters include one or more of volumetric imaging parameters, planar imaging parameters, or tissue tracking parameters.

[0052] Item 7 is a system such as any one of the preceding items, wherein the radiation therapy delivery parameters include one or more of beam energy, MLC position, or couch position.

[0053] Item 8 is a system as in any one of the preceding items, wherein the operation further comprises requesting user confirmation for creating, capturing, and / or controlling based on the parameter list.

[0054] Item 9 is a system as in any one of the preceding items, further comprising providing a workflow editor whose operations are configured to facilitate correction of the MRgRT&P workflow based on the diagnosis.

[0055] Item 10 is a system such as any one of the preceding items, wherein the operations further comprise retrieving from a workflow library additional diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflows (MRgRT&P workflows) associated with the treatment prescription, and presenting to the user a number of selectable diagnosis-based MRgRT&P workflows.

[0056] Item 11 is a system comprising at least one programmable processor; and non-transitory machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising capturing initial parameters for a magnetic resonance imaging-guided radiation therapy and planning workflow (MRgRT&P workflow) based on a diagnosis associated with a treatment prescription, the capturing comprising recording the initial parameters utilized during imaging with an MRI-guided radiation therapy system, utilized during generation of a radiation therapy plan, and utilized during control of the MRI-guided radiation therapy system, creating the diagnosis-based MRgRT&P workflow using the initial parameters, and storing the diagnosis-based MRgRT&P workflow associated with the treatment prescription in a workflow library.

[0057] Item 12 is the system as in item 11, further comprising providing a workflow editor whose operations are configured to facilitate correction of the MRgRT&P workflow based on the diagnosis.

[0058] This disclosure contemplates that the calculations disclosed in the embodiments may be performed in many ways applying the same concepts taught herein, and that such calculations are equivalent to the disclosed embodiments.

[0059] One or more aspects or features of the subject matter described herein may be implemented in digital electronic circuitry, integrated circuits, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), computer hardware, firmware, software, and / or combinations thereof. Various aspects or features may include implementation in one or more computer programs executable and / or interpretable on a programmable system including at least one programmable processor, which may be special purpose or general purpose, coupled to receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device. The programmable system or computing system may include clients and servers. Clients and servers are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0060] These computer programs, which may also be referred to as programs, software, software applications, applications, components, or code, may include machine instructions for a programmable processor and may be implemented in a high-level procedural language, an object-oriented programming language, a functional programming language, a logic programming language, and / or an assembly / machine language. As used herein, the term "machine-readable medium" (or computer-readable medium) refers to any computer program product, apparatus, and / or device used to provide machine instructions and / or data to a programmable processor, such as, for example, magnetic disks, optical disks, memories, and programmable logic devices (PLDs), and includes a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" (or computer-readable signal) refers to any signal used to provide machine instructions and / or data to a programmable processor. A machine-readable medium may store such machine instructions non-transitoryly, such as, for example, a non-transitory solid-state memory or a magnetic hard drive or any equivalent storage medium. The machine-readable medium may alternatively or additionally store such machine instructions in a transitory manner, such as a processor cache or other random access memory associated with one or more physical processor cores.

[0061] To provide for user interaction, one or more aspects or features of the subject matter described herein may be implemented on a computer having a display device, such as a cathode ray tube (CRT), liquid crystal display (LCD), or light emitting diode (LED) monitor, for displaying information to a user, and a keyboard and pointing device, such as a mouse or trackball, by which the user may provide input to the computer. Similarly, other types of devices may be used to provide for user interaction. For example, feedback provided to the user may be in the form of any sensory feedback, such as visual feedback, auditory feedback, or tactile feedback, and input from the user may be received in any form, including, but not limited to, acoustic input, voice input, or tactile input. Other possible input devices include, but are not limited to, touchscreens or other contact-sensitive devices, such as single or multi-point resistive or capacitive trackpads, voice recognition hardware and software, optical scanners, optical pointers, digital image capture devices and associated interpretation software, etc.

[0062] In the above description and in the claims, phrases such as "at least one" or "one or more" may follow a conjunctive list of elements or features. The term "and / or" may also follow a list of more than one element or feature. Unless otherwise expressly or explicitly contradicted by the context, such phrases are intended to mean either of the elements or features on the individual list, or any of the listed elements or features in combination with any of the other listed elements or features. For example, "at least one of A and B," "one or more of A and B," and "A and / or B" are intended to mean "A only, B only, or A and B together," respectively. A similar interpretation is intended for lists containing more than two items. For example, "at least one of A, B, and C," "one or more of A, B, and C," and "A, B, and / or C" are intended to mean "A only, B only, C only, A and B together, A and C together, B and C together, or A, B, and C together," respectively. Use of the term "based on" above and in the claims is intended to mean "based at least in part on," allowing for unrecited features or elements.

[0063] The subject matter described herein may be embodied in systems, apparatus, methods, computer programs, and / or articles in any desired configuration. Any method or logic flow depicted in the accompanying figures and / or described herein does not necessarily require the particular order shown or order for achieving desired results. The implementations set forth in the foregoing description do not represent all implementations consistent with the subject matter described herein. Instead, they are merely some examples consistent with aspects related to the subject matter described. While a few variations have been described in detail above, other modifications or additions are possible. In particular, additional features and / or variations may be provided in addition to those set forth herein. The above-described implementations may be directed to various combinations and subcombinations of the disclosed features and / or combinations and subcombinations of the additional features described above. Furthermore, the above-described advantages are not intended to limit the application of any issued claims to procedures and structures that achieve any or all advantages.

[0064] Additionally, section headings should not limit or characterize the invention(s) presented in any claim(s) that may issue from this disclosure. Moreover, descriptions of technology in the "Background" section should not be construed as admissions that they are prior art to any invention(s) of this disclosure. The "Summary" section should also not be considered as a characterization of the invention(s) set forth in the issued claims. Furthermore, any reference to this disclosure generally or use of the word "invention" in the singular is not intended to imply any limitations on the claims set forth below. Multiple inventions may be set forth by the limitations of the multiple claims issuing from this disclosure, and such claims accordingly define the invention(s) and their equivalents protected thereby.

Claims

1. at least one programmable processor; a non-transitory machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform an operation, the operation comprising: Acceptance of treatment prescriptions for patients; acquiring a diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflow (MRgRT&P workflow) associated with the treatment prescription from a workflow library, the workflow having a parameter list comprising parameters utilized in the MRI-guided radiation therapy; imaging with an MRI-guided radiotherapy system utilizing the radiotherapy imaging parameters of the parameter list; generating a radiation treatment plan utilizing the radiation treatment plan parameters from the parameter list; and controlling an MRI-guided radiation therapy system utilizing the radiation therapy delivery parameters of the parameter list. A system comprising:

2. 10. The system of claim 1, wherein the treatment prescription includes disease type, treatment site, stage, total dose, number of fractions, dose per structure per fraction, minimum / maximum / average dose constraints, and / or dose constraints to targets and organs.

3. The obtaining of the MRgRT&P workflow based on the diagnosis includes: comparing the treatment prescription with a stored treatment prescription associated with a stored diagnosis-based MRgRT&P workflow; and returning an MRgRT&P workflow based on the stored diagnosis along with a stored treatment prescription that matches the treatment prescription.

4. The system of claim 1 , wherein the radiation treatment planning parameters include one or more of an anatomical identification parameter, an auto-contouring parameter, or a relative electron density parameter.

5. 10. The system of claim 1, wherein the radiation treatment planning parameters include one or more of volumetric imaging parameters, image registration parameters, anatomical segmentation parameters, treatment planning parameters, treatment plan dose calculation parameters, treatment plan optimization parameters, dose display parameters, or treatment selection parameters.

6. The system of claim 1 , wherein the radiation therapy imaging parameters include one or more of volumetric imaging parameters, planar imaging parameters, or tissue tracking parameters.

7. The system of claim 1 , wherein the radiation therapy delivery parameters include one or more of beam energy, MLC position, or couch position.

8. The system of claim 1 , wherein the operation further comprises requesting user confirmation regarding the creating, capturing, and / or controlling based on the parameter list.

9. The system of claim 1 , wherein the operations further comprise providing a workflow editor configured to facilitate correction of an MRgRT&P workflow based on the diagnosis.

10. The calculation is retrieving from the workflow library an additional diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflow (MRgRT&P workflow) associated with the treatment prescription; and 10. The system of claim 1, further comprising: presenting a user with an MRgRT&P workflow based on multiple selectable diagnoses.

11. at least one programmable processor; a non-transitory machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform an operation, the operation comprising: capturing initial parameters for a diagnosis-based magnetic resonance imaging-guided radiation therapy and planning workflow (MRgRT&P workflow) associated with a treatment prescription, the capturing comprising a record of initial parameters utilized during imaging with an MRI-guided radiation therapy system, utilized during generation of a radiation treatment plan, and utilized during control of the MRI-guided radiation therapy system; creating an MRgRT&P workflow based on the diagnosis according to the initial parameters; and storing in a workflow library the MRgRT&P workflow based on the diagnosis associated with the treatment prescription. A system comprising:

12. The system of claim 11 , wherein the operations further comprise providing a workflow editor configured to facilitate correction of an MRgRT&P workflow based on the diagnosis.

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