Motion compensation in cardiac radioablation treatment planning
By generating patient-specific motion models and optimizing treatment plans, the problem of uneven dosage caused by cardiac motion in cardiac radioablation has been solved, achieving more precise treatment and better protective effects.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- VARIAN MEDICAL SYSTEMS INC
- Filing Date
- 2024-11-05
- Publication Date
- 2026-06-12
Smart Images
Figure CN122207084A_ABST
Abstract
Description
Technical Field
[0001] These teachings generally concern motion compensation in cardiac radioablation treatment planning. They also cover the use of energy to treat a patient's heart according to an energy-based treatment plan, and more specifically, the optimization of such a plan. Furthermore, these teachings address motion compensation during cardiac radioablation. Background Technology
[0002] Recurrent sustained monomorphic ventricular tachycardia (VT) is a type of arrhythmia characterized by rapid and regular heartbeats originating from the ventricles of the heart. Ventricular tachycardia is an arrhythmia characterized by rapid and regular heartbeats originating from the ventricles (inferior chambers) of the heart. In ventricular tachycardia, the ventricles beat at a rate faster than normal sinus rhythm and can significantly impair the heart's ability to pump blood effectively. "Monomorphic VT" refers to a specific subtype of ventricular tachycardia in which ventricular contractions during the arrhythmia appear very similar in shape and duration on an electrocardiogram (ECG). Sustained ventricular tachycardia can last for a relatively long time, typically 30 seconds or longer. Sustained ventricular tachycardia can be dangerous to patients.
[0003] Recurrent sustained monomorphic ventricular tachycardia (RPVT) can be caused by a variety of underlying conditions, including scar tissue from a previous heart attack. Treatment for RVT typically involves the use of antiarrhythmic medications, or in some cases, more invasive treatments such as catheter ablation. Unfortunately, not all patients respond to conventional treatments and continue to experience these dangerous episodes.
[0004] Limited ongoing research is considering the use of radiation therapy in patients with ischemic or non-ischemic cardiomyopathy, who have failed antiarrhythmic drug therapy, and who have experienced recurrent ventricular tachycardia after catheter ablation. Early results are encouraging, but many unknowns and challenges remain regarding the use of radiation therapy for this purpose and in this specific location on the body. This therapy is known in existing techniques as cardiac radiation ablation.
[0005] Generally, the use of energy (such as X-rays) to treat cancerous tumors falls within the scope of known existing technological efforts. Unfortunately, the applied energy itself does not distinguish between unwanted material and adjacent tissues, organs, etc., which are desired or even critical for the patient's continued survival. Therefore, energy such as radiation is usually applied in a carefully managed manner to at least attempt to confine the energy to a given target volume. So-called radiation therapy programs are typically used for the aforementioned purposes.
[0006] Radiation therapy plans typically consist of specified values for each of a variety of treatment platform parameters during each of multiple consecutive fields of view. Treatment plans for radiation therapy courses are often automatically generated through a process known as optimization. As used herein, "optimization" will be understood as improving candidate treatment plans, without necessarily ensuring that the result of optimization is actually the best single solution. Such optimization typically involves automatically adjusting one or more physical therapy parameters (often while simultaneously observing one or more corresponding limitations in these aspects), and mathematically calculating the possible corresponding treatment outcomes (such as dose levels) to identify a given set of treatment parameters that represents a good trade-off between the desired treatment outcome and the avoidance of undesirable side effects.
[0007] One challenge in confidently planning and administering radiation therapy to patients is movement within the treatment area. Some parts of the body, such as the heart, body parts associated with respiration, and body parts associated with stomach activity (including peristaltic movements for the purposes of this discussion), are capable of and do move over time. These movements can be rapid or slow, involve short or relatively large distances, and can shift portions of the target area and the protected area to different locations. As a result, underdose or overdose of the target and overdose of the protected area can occur.
[0008] When considering cardiac radioablation, the aforementioned challenges, which are common in the use of radiation therapy to address unwanted tumors, are also present, although the details may vary considerably. Summary of the Invention
[0009] In one aspect, the present invention provides a method for planning cardiac radioablation therapy to facilitate compensation for motion in a specific patient, as defined in claim 1. The compensated motion may be motion predicted to occur during a cardiac radioablation procedure targeting the patient's heart. This method can facilitate compensation for motion that may occur during future planned treatment procedures targeting the patient. Optional features are specified in the dependent claims.
[0010] In another aspect, the present invention provides an apparatus for facilitating compensatory movement during a cardiac radioablation procedure targeting the heart of a particular patient, as defined in claim 13. Optional features are specified in the dependent claims.
[0011] On the other hand, the present invention provides a method for facilitating compensatory motion during cardiac radioablation procedures targeting the heart of a specific patient, the method comprising: by a control circuit: Access multidimensional information specific to a particular patient; Based at least in part on multidimensional information, supplementary boundaries for at least one part of a specific patient can be automatically determined. Attached Figure Description
[0012] The above-mentioned needs for devices and methods for motion compensation (e.g., during cardiac radioablation) are at least partially met through the following detailed description, particularly when studied in conjunction with the accompanying drawings, wherein:
[0013] Figure 1 Including block diagrams configured as in various embodiments according to these teachings;
[0014] Figure 2 This includes diagrams configured as in various embodiments according to these teachings;
[0015] Figure 3 This includes diagrams configured as in various embodiments according to these teachings;
[0016] Figure 4 Including flowcharts of various embodiments configured according to these teachings; and
[0017] Figure 5 This includes flowcharts configured as in various embodiments based on these teachings.
[0018] For simplicity and clarity, the elements in the accompanying drawings are illustrated and not necessarily drawn to scale. For example, the size and / or relative positioning of some elements in the drawings may be exaggerated relative to other elements to aid in understanding the various embodiments of this teaching. Furthermore, common but well-known elements that are useful or necessary in commercially viable embodiments are generally not depicted so that views of these various embodiments of this teaching are not obstructed. Certain actions and / or steps may be described or depicted in a specific order of occurrence, and those skilled in the art will understand that such specificity regarding the order is not actually necessary. The terms and expressions used herein have the ordinary technical meanings that those skilled in the art, as set forth above, would assign to these terms and expressions, unless otherwise set forth herein with different specific meanings. The word “or” as used herein should be interpreted as having a separating construction rather than a connecting construction, unless otherwise specifically indicated. Detailed Implementation
[0019] These teachings address facilitating compensatory motion during cardiac radioablation procedures targeting a specific patient's heart. Generally, according to these various embodiments, control circuitry can access multidimensional information specific to the patient and then, at least in part based on that multidimensional information, automatically determine supplementary boundaries for at least one portion of that specific patient (such as a treatment target comprising a part of the patient's heart and / or one or more organs at risk). The latter may include, for example, determining a margin for the boundaries added to at least one portion of that specific patient. Configured in this way, the control circuitry can then, for example, determine the planned treatment volume based at least in part on that supplementary boundary. These teachings will then allow for optimization of the cardiac radioablation treatment plan for the specific patient, for example, based on various motion dimensions derived at least in part from the aforementioned multidimensional information.
[0020] The aforementioned multidimensional information may include, for example, three Cartesian orientations and a fourth, fifth, or more dimensions, which can refer to any of a variety of patient-centered motion-based references. Examples include, but are not limited to, patient-specific cardiac-based imaging, respiratory-based imaging, and imaging based on periodic gastric motility.
[0021] As an example, multidimensional information can include four- or five-dimensional information specific to a particular patient. In this case, the fourth and fifth dimensions could refer to different patient-centered motion-based references, where at least one of the patient-centered motion-based references includes cardiac-based imaging. Similarly, these teachings would be adapted to the use of six or more dimensions, where, for example, additional dimensions correspond to cardiac-based imaging of other parts of the heart, respiratory-based imaging, and patient-specific imaging based on periodic gastric motility.
[0022] These teachings are highly flexible in practice and will be adapted to any of the various modifications and / or additions.
[0023] As an example of the foregoing aspects, these teachings would be adapted to present the aforementioned motion-based imaging to a user and then provide the user via a user interface with the opportunity to selectively separate the motion of one motion-based imaging (such as, for example, heart-based imaging) from the motion of another motion-based imaging (such as, for example, respiratory-based imaging) to modify the playback.
[0024] As another example of the foregoing aspects, these teachings will be adapted to generate a motion model for a specific patient, at least in part, based on the aforementioned multidimensional information specific to that patient. Such a motion model can then serve as a basis for, for example, evaluating the efficacy of each of several different treatment modalities for that specific patient.
[0025] Through a method, these teachings may optionally support access to patient-specific supplemental multidimensional information during treatment, and then update the aforementioned motion model at least in part based on that supplemental multidimensional information and / or validate the motion model at least in part based on that supplemental multidimensional information.
[0026] As another example of the flexibility of these teachings, by one method, these teachings can optionally be adapted to reconstruct the absorbed dose applied during a cardiac radioablation treatment procedure based at least in part on the aforementioned patient-specific multidimensional information and the aforementioned patient-specific motion model generated based at least in part on the patient-specific multidimensional information.
[0027] This configuration allows for a better understanding of one or more motion patterns specific to a patient and the use of these patterns to generate cardiac radioablation treatment plans, and optionally, corresponding treatments that may produce better overall outcomes for the patient. These better outcomes may include more precise (and / or consistent) dosing to the treatment target and / or more effective protection against radiation from non-target areas.
[0028] These and other benefits will become clearer upon reviewing and studying the following detailed description. Refer now to the accompanying drawings, especially... Figure 1 The first thing to be presented is an illustrative device 100 that is compatible with many of the teachings in these teachings.
[0029] In this particular example, the enabling device 100 includes a control circuit 101. As a “circuit”, the control circuit 101 therefore includes a structure comprising at least one (and typically many) conductive paths (such as paths comprising conductive metals such as copper or silver) that transmit electricity in an ordered manner, and the paths will typically also include corresponding electrical components (both passive components such as resistors and capacitors and active components such as various semiconductor-based devices, as applicable) to allow the circuit to implement the control aspects of these teachings.
[0030] Such control circuitry 101 may include a fixed-purpose hardwired hardware platform (including, but not limited to, application-specific integrated circuits (ASICs) (i.e., integrated circuits designed for a specific purpose rather than intended for general use), field-programmable gate arrays (FPGAs), etc.), or may include a partially or fully programmable hardware platform (including, but not limited to, microcontrollers, microprocessors, etc.). These architectural options for such a configuration are well known and understood in the art and need not be further described herein. The control circuitry 101 is configured (e.g., by using corresponding programming, as will be understood by those skilled in the art) to perform one or more of the steps, actions, and / or functions described herein.
[0031] Control circuitry 101 is operatively coupled to memory 102. Memory 102 may be integrated with control circuitry 101, or may be physically separated ( wholly or partially) from control circuitry 101 as desired. Memory 102 may also be local to control circuitry 101 (where, for example, both share a common circuit board, chassis, power supply, and / or enclosure), or may be partially or completely remote from control circuitry 101 (where, for example, memory 102 is physically located in another facility, metropolitan area, or even country compared to control circuitry 101).
[0032] In addition to information such as image information, patient-specific optimization information, and information about a specific radiotherapy platform as described herein, the memory 102 can be used, for example, to non-transitory store computer instructions that, when executed by the control circuitry 101, cause the control circuitry 101 to behave as described herein. (As used herein, "non-transitory" will be understood as referring to a non-transient state with respect to the stored content (thus excluding when the stored content constitutes only a signal or wave), rather than the volatility of the storage medium itself, and therefore includes both non-volatile memory (such as read-only memory (ROM)) and volatile memory (such as dynamic random access memory (DRAM)).
[0033] Alternatively, the control circuitry 101 may also be operatively coupled to the user interface 103. The user interface 103 may include any of a variety of user input mechanisms (such as, but not limited to, keyboards and keypads, cursor control devices, touch-sensitive displays, voice identification interfaces, gesture identification interfaces, etc.) and / or user output mechanisms (such as, but not limited to, visual displays, audio transducers, printers, etc.) to facilitate receiving information and / or instructions from the user and / or providing information to the user.
[0034] If desired, the control circuitry 101 can also be operatively coupled to a network interface (not shown). With this configuration, the control circuitry 101 can communicate with other components (both internal and external to the device 100) via the network interface. Network interfaces (including both wireless and non-wireless platforms) are well known in the art and will not be specifically described here.
[0035] Through a method, computed tomography apparatus 106 and / or other imaging apparatus 107 (such as positron emission tomography and / or magnetic resonance imaging (including both functional and quantitative methods)) known in the art can derive some or all of any desired patient-related imaging information. Through a method, these teachings will support the generation of treatment-day images (or images at any time prior to treatment) using virtually any imaging modality available on the treatment delivery device, for example, to update and validate motion models. Examples of useful image modalities include, but are not limited to, X-ray projection imaging, X-ray fluoroscopy, cone-beam computed tomography (CBCT), multicolor CBCT, dual-energy CBCT, 4D-CBCT, 5D-CBCT, and even, for example, cardiac-specific imaging and planning tools.
[0036] In this illustrative example, control circuitry 101 is configured to ultimately output an optimized cardiac radioablation treatment plan (such as, for example, an optimized cardiac radioablation plan 113). This cardiac radioablation treatment plan typically includes specified values for each of a variety of treatment platform parameters during each exposure field in a plurality of sequential exposure fields. In this case, the cardiac radioablation treatment plan is generated through an optimization process, examples of which are further provided herein.
[0037] In one manner, control circuitry 101 can be operatively coupled to an energy-based treatment platform 114, which is configured to direct treatment onto a treatment volume 105 comprising at least one portion of the patient's heart (such as, for example, a portion of one or more ventricles) and one or more organs at risk (in accordance with an optimized cardiac radioablation plan 113). Figure 1 Therapeutic energy 112 is delivered to the corresponding patient 104 (represented by the first to Nth organs at risk 108 and 109). These teachings are generally applicable to use with any of a wide variety of energy-based therapeutic platforms / devices. In a typical application setting, the energy-based therapeutic platform 114 will include an energy source such as a radiation source 115, such as ionizing radiation 116.
[0038] The radiation source 115 can be selectively moved along an arcuate path via a gantry (wherein, during treatment application, the path at least partially surrounds the patient). The arcuate path may, as desired, comprise a complete or nearly complete circle. Control circuitry 101 controls the movement of the radiation source 115 along the arcuate path, and can accordingly control when the radiation source 115 begins to move, stops moving, accelerates, decelerates, and / or the speed at which the radiation source 115 moves along the arcuate path.
[0039] As an illustrative example, radiation source 115 may include, for example, an X-ray source based on a radio frequency (RF) linear particle accelerator (a linear accelerator). A linear accelerator is a particle accelerator that greatly increases the kinetic energy of charged subatomic particles or ions by subjecting charged particles to a series of oscillating potentials along a linear beamline. This can be used to generate ionizing radiation (e.g., X-rays) 116 and high-energy electrons.
[0040] A typical energy-based treatment platform 114 may also include one or more support devices 110 (such as a sofa) supporting the patient 104 during treatment, one or more patient immobilization devices 111 (including, but not limited to, structures configured to limit physical offsets associated with the patient’s breathing), a gantry or other movable mechanism that allows selective movement of the radiation source 115, and one or more energy shaping devices (e.g., beamforming devices 117, such as jaws, multi-leaf collimators, etc.) to provide selective energy shaping and / or energy modulation as desired.
[0041] In a typical application setting, this document assumes that the patient support device 110 can be controlled by the control circuitry 101 to selectively move in any direction (i.e., any X, Y, or Z direction, including rotational motion) during an energy-based therapeutic procedure. Since the foregoing components and systems are well known in the art, further details in these aspects will not be elaborated unless relevant to the description.
[0042] refer to Figure 2 and Figure 3 It may be helpful to describe and explain certain terms, acronyms and concepts that may be related to this teaching.
[0043] The patient's gross target volume (GTV) can be determined from patient images, such as computed tomography (CT), positron emission tomography (PET), and / or magnetic resonance imaging (MRI). Alternatively, this GTV can be coupled with boundary information to determine the clinical target volume (CTV). This boundary information can be based on known biological records, for example, of boundary conditions for scar tissue in the ventricles.
[0044] The internal target volume (ITV) can then be based on the clinical target volume incorporating patient internal motion information (e.g., derived from observations of the respiratory system). The planned target volume (PTV) can then be based on the aforementioned internal target volume plus an additional margin or safety / error, for example, based on potential and / or observed setup errors.
[0045] like Figure 3As shown, at reference numeral 301, a planned outer boundary of the organ at risk can be provided for a given organ at risk, taking into account motion information that can influence / determine the volume in which the organ at risk may exist during the treatment course. Reference numeral 302 schematically illustrates the aforementioned boundary / margin for the patient's target volume. The corresponding target volume (TV) is also depicted and will be described in more detail below.
[0046] A method can be used to analyze motion based on multidimensional imaging and patient-specific motion models to... Figure 3 The rightmost section links to the optimized treatment plan. Based on the foregoing, these teachings will support the determination of the individual patient's planned organ-at-risk volume and patient treatment volume, as well as possible plan alternatives that may differ depending on the organ at risk. The drawn prescription and lower isodose line can be one of several plan implementation methods.
[0047] Currently, patients may be selected for cardiac radioablation by a cardiac electrophysiologist based on previous unsuccessful treatment for recurrent persistent monomorphic ventricular tachycardia. The service provider may then collaborate with a radiation oncologist to conduct cardiac examinations, with the radiation oncologist providing support such as computed tomography simulations. The cardiac electrophysiologist can then define the treatment target, and the radiation oncologist can plan the radiotherapy itself. The administration of radiation will typically be performed by one or more radiation oncology technicians.
[0048] Now for reference Figure 4 The following describes a process 400 that can be executed, for example, in conjunction with the application settings described above (and more specifically via the control circuit 101 described above). Generally, this process 400 is used to facilitate the generation of an optimized cardiac radioablation plan 113, thereby facilitating the treatment of a specific patient's heart with therapeutic radiation using a specific radiotherapy platform according to this optimized cardiac radioablation treatment plan, to, for example, ablate scar tissue in the ventricles. More specifically, this process 400 can be used to generally compensate for movement during the therapeutic cardiac radioablation treatment procedure for that specific patient.
[0049] In box 401, procedure 400 provides access to multidimensional information specific to a particular patient. As used herein, the term "multidimensional" will be understood to mean at least three standard Cartesian dimensions plus one or more additional motion-based dimensions. Examples of motion-based dimensions include, but are not limited to, a patient's cardiac-based activity, respiratory-based activity, and / or periodic gastric-based activity.
[0050] As an illustrative example in these respects, this activity may include access to motion-based imaging, which includes one, two, or all three of the following: cardiac-based imaging for the specific patient, respiratory-based imaging for the specific patient, and imaging based on periodic gastric motility for the specific patient. The aforementioned images may share a common image capture mode, or may utilize a variety of different image capture modes, such as computed tomography, positron emission tomography, and / or magnetic resonance imaging, to name just three examples.
[0051] If desired, these teachings will also adapt to viewing the motion of different parts of the heart as distinct dimensions. In this case, there could be two or more motion dimensions, each corresponding to a different part of the patient's heart.
[0052] By an optional method, and as indicated by optional box 402, process 400 will adapt to present some or all of the aforementioned motion-based imaging to a user (e.g., via the aforementioned user interface 103). The displayed images can be still images (including, for example, a single frame of video content) and / or video content. These images may be displayed with or without additional content (such as graphic additions, icons, explanatory or labeled text, etc.) as desired.
[0053] In option 403, these instructions will then be adapted to provide the user (again via the aforementioned user interface 103) with the opportunity to selectively modify the movement of one or more displayed images. The latter may include, for example, allowing the user to select a specific part or area of the displayed image with a cursor, and then manipulate that part / area by, for example, moving the cursor and / or selecting available changes via a submenu.
[0054] One approach to these modifications could be to slow down or stop the displayed patient movement. The modification could also adapt (abruptly or via a smoother transition) to a different dimension of movement. As an example, the modification could include adding respiratory movement with a lower amplitude to reflect the deployment of a compression device in the patient's abdomen to help suppress the amplitude of respiratory movement.
[0055] One approach to this opportunity may include allowing a user to selectively modify the motion of one motion-based image separately from the motion of another displayed (or undisplayed) motion-based image; in other words, modifying one motion-based image does not result in automatic changes to any other currently displayed motion-based images. Using this approach, as an illustrative example, respiratory motion can be modified while cardiac motion is displayed without any concurrent modification.
[0056] Instead of the foregoing or in combination with it, in optional box 404, these teachings will be adapted to generate a motion model for a specific patient, at least in part, based on multidimensional information specific to that patient. (Alternatively, or in combination with this, this process 400 will be adapted to access motion models based on other patient populations, which can then be further modified to include the current specific patient, if desired.) These teachings will be adapted to employ any model from a variety of models, including, for example, any generative model from a variety of generative models. Examples of models / algorithms include, but are not limited to, classical linear models, linear regression, principal component analysis (an unsupervised learning technique), and generative neural networks such as variational autoencoders (whose encoded distribution is typically regularized during training) and generative adversarial networks, etc.
[0057] Assuming the availability of one or more such motion models, in optional box 405, the motion model can be used, at least in part, to evaluate the efficacy of each of several different treatment modalities for a particular patient, based on the motion model(s). For example, one radiotherapy method can be compared with another different radiotherapy method by determining the corresponding efficacy for each method based on the motion model (and / or the intermediate and mean position information mentioned herein), and then comparing these efficacies to identify the method that appears to be most effective.
[0058] In box 406, the process 400 provides the automatic determination, at least in part, of supplementary boundaries for at least one portion of a specific patient based on multidimensional information. The aforementioned portion may be, for example, a therapeutic target or some designated portions thereof, and / or (multiple) organs at risk or some designated portions thereof. (By one method, the aforementioned portion may include portions of the PTV and / or PRV.)
[0059] One method may be used to include a margin, for example, added to at least one part of the established boundary of the particular patient. Such a margin may be calculated and / or otherwise selected to accommodate a specific range of motion that may occur with respect to the aforementioned part of the patient's body.
[0060] By an optional method, and as shown in optional box 407, process 400 will adapt to determine the planned treatment volume, at least in part, based on the aforementioned supplementary boundaries. This concept is described above. Figure 3 The diagram illustrates that a margin, represented as target volume 303, is added to the previously determined planned target volume. These teachings are flexible in practice and will be adapted to use different margin sizes for different parts of the target. For example, the margin can be smaller (or even zero) in directions where the patient's movement is not expected to change during motion, while it can be larger in directions more likely to include a greater range of motion. It should be understood that the same approach can also be used for organs at risk.
[0061] In optional box 408, the process 400 will adapt to optimize a radiation-based treatment plan for a specific patient based on the aforementioned multidimensional patient motion. When the multidimensional information contains information on two or more different types of patient motion, the foregoing may include optimizing the plan based on at least two different motion dimensions derived at least in part from the multidimensional information.
[0062] In optional box 409, process 400 may then optionally provide the application of the resulting optimized cardiac radioablation therapy to a specific patient according to the optimized plan (using, for example, the radiotherapy platform 114 described above).
[0063] In the above description, motion models can be used to help optimize cardiac radioablation treatment plans for specific patients. These insights can also be utilized during or after treatment for that particular patient.
[0064] refer to Figure 5 In optional box 501, the procedure 500 will optionally provide access to supplemental multidimensional information for a specific patient during treatment. As used herein, the reference to “supplemental” will be understood as multidimensional information in addition to the original accessed multidimensional information as described above, and also as a time period that at least partially overlaps with the treatment window. This supplemental multidimensional information may come from the same image source as the original service, but may also rely partially or entirely on alternative sources if desired. The latter may include, for example, the treatment delivery device or onboard imaging capabilities available on the device itself, as previously described.
[0065] This supplementary multidimensional information can then be utilized in any of a variety of ways.
[0066] By means of a method, and as shown in optional box 502, the aforementioned supplementary multidimensional information can be utilized by updating the aforementioned motion model at least in part based on the supplementary multidimensional information.
[0067] By means of another method, and as shown in optional box 503, instead of or in combination with the foregoing, process 500 will provide at least in part the validation of the foregoing motion model based on the supplementary multidimensional information.
[0068] Whether or not supplemental multidimensional information is developed, and by yet another method, in place of or in combination with the foregoing, and as indicated in optional box 504, these teachings will allow the reconstructing of the absorbed dose applied during the treatment course, at least in part based on patient-specific multidimensional information and / or at least in part based on patient-specific motion models generated from patient-specific multidimensional information.
[0069] Further details will now be provided with specific application settings and examples. It should be understood that these teachings are not to be considered as being limited to the specific details of these settings and examples.
[0070] In radiotherapy, many techniques have been applied to account for patient motion. Cardiac radioablation is not yet universally considered a widely established treatment method. Therefore, there is no universally established approach to address target motion in the setup of cardiac radioablation applications. In cardiac radioablation, the treatment target is typically an area of the ventricular wall that is identified prior to treatment planning using anatomical (4DCT, 4D-MRI) and functional (PET) imaging, in addition to cardiology-specific target localization techniques.
[0071] In addition to cardiac and therefore corresponding target motion, there is respiratory motion. These contributing factors typically result in a relatively large amplitude of target motion. The latter is usually compensated for in radiotherapy by adding this amplitude of motion to the total or clinical target volume (GTV, CTV), thus generating the internal target volume (ITV). This amplitude of motion can be, for example, 10 mm. Adding a setting uncertainty (typically 3 mm to 5 mm) to this ITV yields the planned target volume (PTV).
[0072] In such cases, the contribution from target motion is typically significantly greater than the setup uncertainty. Therefore, this increased margin can result in a substantial PTV, as well as a corresponding significant dose contribution to non-target tissues and organs at risk (OARs), since the entire PTV will receive the prescribed treatment dose according to the corresponding plan. This adverse effect of high dose to the OAR can itself lead to a dose reduction in the target to avoid such adverse doses to sensitive tissues. In cardiac radioablation, a single dose of 25 Gy is generally accepted. Limiting the effects of target motion (or reducing the margin from GTV / CTV to PTV) is very helpful in avoiding underdose of the target or overdose of nearby sensitive tissues.
[0073] Treatment volume, or PTV, is typically planned using the internal target volume (ITV) approach to compensate for changes in target shape and position caused by heartbeats at a fixed respiratory level (usually using breath-holding), or by means of respiratory gating to accommodate a specific respiratory phase or amplitude. To extract the ITV, the cardiac motion envelope can be extracted using deformable registration from each phase of a cardiac 4D CT scan to a planning (reference) CT scan. The resulting ITV can comprise the union of CTVs at all phases of the cardiac 4D CT. Finally, the planned target volume (PTV) can be generated by adding a small margin (such as 3 mm to 5 mm margin) to the ITV based on typical patient setup errors. This approach can still result in a relatively large volume, which may jeopardize the dose to nearby organs at risk.
[0074] This teaching addresses such problems related to patient motion. Specifically, it provides tools and methods for general workflows that can utilize individualized models of patients and their corresponding expected motion. Such patient motion models can be constructed from various imaging modalities, such as 4D / 5D CT / CBCT / MR / PET and fluoroscopy, and combinations thereof. Instead of the foregoing or their combinations, this teaching also adapts to employing, for example, the intermediate or average position of a cardiac target, which can be calculated to produce a single 3D image dataset that can be used for treatment planning and patient localization. There are no limitations on whether it is patient-specific or based on data from a population (e.g., statistics representing typical motion).
[0075] During the treatment plan
[0076] Image sequences of 4D / 5D / 6D+ CT / CBCT / MR / PET, or alternatively, resolving both respiration and cardiac motion (in this example), including CTV and other structures of interest, can be loaded into the viewer. These images can be segmented by the user and / or automatically segmented to identify clinical target volume (CTV) and organs at risk, and those features can be registered to all phases of the 4D / 5D CT / CBCT / MR content.
[0077] These instructions will be adapted to play a combined representation of breathing and heart movements. That is, according to these instructions, users can selectively freeze (or slow down) breathing movements to play only heart movements (or at least emphasize the latter), or alternatively, freeze (or slow down) heart movements to play only breathing movements (or at least emphasize the latter).
[0078] If desired, these teachings would support providing a display scale overlaid on the viewer to facilitate manual measurement of displacement. Additional geometric measurement tools could be provided, if desired, to quantify things such as overlap between structures (by volume or percentage) and / or, for example, the distance at the nearest point between two structures.
[0079] One method allows these teachings to be adapted for the automatic assessment of CTV displacement due to cardiac and respiratory movements, as well as the automatic generation of the internal target volume (ITV) or intermediate or average target position. This can include taking into account the deformation field as desired. Another method allows users to play motion information, thus visually verifying CTV motion within the ITV.
[0080] Through a method, these instructions are adapted to a Planned Vital Organ Volume (PRV) margin calculator. Users can choose / select specific structures to display, and these instructions are then adapted for automatic assessment of structural displacement due to cardiac and respiratory movements, and automatic generation of the corresponding PRV. The relevant movements can then be displayed / played for the user to verify that the structural movement is within that PRV.
[0081] Through a methodology, and based on treatment plans and movement models as described herein, these teachings will be adapted to computational probabilistic models to assess the expected success rate of a successful delivery plan and / or the fulfillment of certain specific criteria as desired. The latter can be used, for example, to evaluate various candidate movement mitigation strategies. This may at least partially include assessing the impact of applying one or more of various techniques (such as, but not limited to, breath-holding, respiratory gating, tracking, use of ventilation devices, ECG gating, and / or ICD pacing) on CTV, structural movement, margin, dosing plan, organs at risk, and / or treatment outcomes to identify potentially useful options.
[0082] Treatment Day
[0083] These teachings will support comparisons of motion on simulation days and treatment days. In particular, such comparisons can be used, for example, to validate one or more motion models. This can include, for example, a geometric comparison of expected motion trajectories to determine whether observed treatment-day motion is covered by the motion model. While the term "treatment day" is used, it should be understood that the comparison does not necessarily involve motion on the treatment day. The motion can occur at any time after the simulation time and before the treatment time (e.g., more than a day or more before treatment). In these respects, these teachings can be used to determine whether observed motion can be represented by a normal set of parameters of the patient's motion model, to detect possible overfitting of the model given treatment-day motion, and / or whether the model estimates, for example, a high probability of treatment-day motion.
[0084] As another example in these respects, these teachings will be adapted to the scope of comparison models (i.e., whether the simulation model and the treatment day model can or are expressing / representing the same movement). Although the term "treatment day" is used, it should be understood that the comparison does not necessarily involve models on the treatment day. The model can be any time after the simulation time and before the treatment time (e.g., more than a day or more before treatment).
[0085] If needed or desired, these teachings will support adjustments to the plan based on movement observed on the treatment day. While the term "treatment day" is used, it should be understood that adjustments do not necessarily involve movement on the treatment day. This movement can occur at any time after the simulation time and before the treatment time (e.g., more than a day or more before treatment). This may include, for example, reassessing previously defined requirements. Instead of the foregoing or in combination therewith, ITV, PRV, and various corresponding priorities may be checked, and / or treatment trials may be performed on new data.
[0086] These teachings will also adapt to dose reconstruction using 4D / 5D CBCT and / or multidimensional motion models, such as 5D motion models. This could include, for example, calculating the delivered dose while considering motion and comparing the planned dose with the delivered dose. These teachings will also support applying the scheduled plan to the motion using the updated motion model of the day as part of a trial run. The latter will allow for checking the expected treatment with respect to dose-volume parameters and then deciding whether the scheduled plan can be executed based on the observed motion of the day. If not, online plan adaptation can be triggered to help ensure that the expected treatment for that fraction is achieved. For fractionated treatment, these teachings can be used to facilitate compensation for under-dose / over-dose in future fractions. For single-fraction plans, these teachings can facilitate compensation for under-dose immediately after treatment exposure (i.e., while the patient is still on the patient support platform in the radiotherapy platform and between subsequent arcs). These teachings will also support real-time monitoring of organ-at-risk doses with the option of early treatment cessation (i.e., before the end of the planned treatment course) to protect a given organ-at-risk.
[0087] If desired, these teachings will be used to implement adaptive / dynamic ITV. For example, ITV can be used as an upper limit to define treatment. The corresponding margin can then be dynamically reduced (or increased) based on, for example, the current respiratory pattern. Assuming, for example, the availability of multimodal 2D / 3D / 4D / 5D planning images from the treatment simulation phase, time-series image resolution of respiratory and cardiac motion, (automatic) segmentation of relevant targets and organs at risk, and patient motion models based on planning images (although it should be understood that multiple motion models can be generated, such as a motion model for the heart on one hand and a motion model for respiratory activity on the other), these teachings will be adapted to provide / use multiple cardiac radioablation treatment plans, including treatment strategies such as breath-holding, gating, tracking, ITV approach, plans based on intermediate or average position CT or CBCT, and backup plans in case a particular respiratory control treatment strategy may not be feasible on the treatment day. Several motion mitigation strategies based on the effects of CTV, ITV, PRV, and / or OAR motion and their margins can be used, such as, but not limited to, breath-holding, gating, bundle or bed tracking, ventilation devices, ECG gating, and / or ICD pacing.
[0088] One approach involves presenting the updated motion model for the treatment day (or any time prior to treatment) along with (multiple) original patient motion models to the user to help guide the decision-making process and potential adaptive treatment workflows. Useful examples in these areas include (automatic) registration of previous models and models for the treatment day (or any time prior to treatment) (or multiple motion models in the case of multiple motion models from previous fractions), parallel dynamic visualization of user-selected motion models, and / or one or more mixed views of dynamic motion models, including (if desired) sliders or other user interfaces that allow the user to fade in / out of a given model from the presentation.
[0089] Through one approach, these teachings will facilitate coverage of target and organ-at-risk segmentation using original and / or any adaptive segmentation sets. This can include, for example, using motion model registration to create (automatic) segmentations on new motion models, using automatic segmentation algorithms to create segmentations, and automating (but also user-defined if desired) analysis of centroid (COM) motion differences (e.g., between target and organ-at-risk), surface distances between segments, overlaps between segments (regarding the margin between the OAR / PRV / GTV / CTV / target to PTV used), and expected dose distribution, or any additional clinically valuable metrics (such as, for example, distances between structures to nearest points). These teachings will also be adapted to use AI-guided editing tools to adapt existing target and organ-at-risk segmentations to patient motion models from the treatment day (or any time prior to treatment).
[0090] These teachings will also adapt to enable the coverage of dose distributions on treatment days (or any time prior to treatment) to new (or updated) motion models. In these respects, these teachings will support, for example, the use of motion model registration to deform one or more preprocessed 3D dose distributions onto a motion model on the treatment day (or any time prior to treatment), automated analysis of planned quality metrics and dose-volume thresholds defined for the patient at an early stage, and / or automated analysis of outcome-related measures based on the actual patient-based motion on the treatment plan and treatment day (or any time prior to treatment).
[0091] When a treatment plan has been created using the exercise robust planning techniques described herein, assessing the similarity of exercise components can be meaningful. These teachings can be used to support the analysis of exercise models on the treatment day (or any time prior to treatment) or to analyze potential improvements in robust dosing plans, in terms of exercise robust planning requirements and / or the need to inform users of any deviations.
[0092] A method allows for the updating of a motion model during treatment based on external inputs such as kV images, respiratory signals, patient surface monitoring, and / or ECG. This updated motion model can then be used for real-time dose calculation, which in turn enables dose tracking during treatment.
[0093] For example, the foregoing may include real-time comparisons of patient movement with respect to expected movement, as well as ITV and PRV based on expected movement. If movement changes during treatment, a new dosing plan can be adjusted during flight (or after bundle maintenance) to accommodate movement following changes in anatomy.
[0094] Other examples of these aspects include real-time comparison of planned doses with delivered doses during treatment of target and / or organs at risk, control of adjustable thresholds to initiate bundle maintenance when deviations exceed, for example, user or clinic-acceptable thresholds, compensation for dose deviations in a given fraction by adjusting the plan for subsequent fractions, and / or for single-fraction treatment and during treatment, after bundle maintenance and reanalysis or based on near real-time automated replanning to promote adaptation.
[0095] This motion model can also be used for motion-adaptive therapy delivery beyond beam gating or tracking. Possible ways to consider motion during therapy delivery include, but are not limited to, slowing and / or accelerating therapy delivery based on motion, delivering therapy only at gantry angles where motion is minimal from the beam viewpoint, selecting from pre-calculated plans at least in part based on observed motion, and / or otherwise planning for anticipated motion.
[0096] Those skilled in the art will recognize that various modifications, alterations, and combinations can be made to the above embodiments without departing from the scope of the invention, and such modifications, alterations, and combinations should be considered within the scope of the inventive concept.
Claims
1. A method for planning cardiac radioablation therapy to facilitate exercise compensation in a specific patient, the method comprising: Control circuit: Access to multidimensional information specific to the patient; At least in part based on the multidimensional information, supplementary boundaries for at least one part of the specific patient are automatically determined.
2. The method of claim 1, wherein the supplementary boundary includes a margin of boundary added to the at least one portion of the particular patient.
3. The method according to claim 1 or 2, wherein the at least one portion of the particular patient comprises at least one of the following: The therapeutic target portion of the heart; It endangers organs.
4. The method according to claim 1, 2 or 3, further comprising: The planned treatment volume is determined at least in part based on the supplementary boundary.
5. The method according to any one of claims 1 to 4, wherein the multidimensional information includes motion-based imaging, the motion-based imaging including cardiac-based imaging for the particular patient and at least one of: respiratory-based imaging for the particular patient and periodic gastric motility-based imaging for the particular patient.
6. The method according to claim 5, further comprising: Presenting the motion-based imaging to the user; The user interface provides the user with the opportunity to selectively modify the motion of one motion-based imaging separately from the motion of another motion-based imaging.
7. The method according to any one of claims 1 to 6, further comprising: A motion model for the specific patient is generated, at least in part, based on the multidimensional information specific to the specific patient.
8. The method according to claim 7, further comprising: The efficacy of each of several different treatment modalities for the specific patient is evaluated, at least in part, based on the said motion model.
9. The method according to claim 7 or 8, further comprising: Access supplemental multidimensional information specific to the patient during treatment; The motion model is updated at least in part based on the supplementary multidimensional information.
10. The method according to claim 7 or 8, further comprising: Access supplemental multidimensional information specific to the patient during treatment; The motion model is verified at least in part based on the supplementary multidimensional information.
11. The method according to any one of claims 1 to 10, further comprising: The absorbed dose administered during the cardiac radioablation procedure shall be reconstructed, at least in part, according to at least one of the following: The multidimensional information specific to the patient; as well as A motion model for the specific patient, generated at least in part based on the multidimensional information specific to the specific patient.
12. The method according to any one of claims 1 to 11, further comprising: Based on at least two different motion dimensions derived at least partially from the multidimensional information, the cardiac radioablation treatment plan for the specific patient is optimized.
13. A device for facilitating compensatory motion during a cardiac radioablation procedure targeting the heart of a specific patient, the device comprising: The control circuit is configured and arranged as follows: Access to multidimensional information specific to the patient; At least in part based on the multidimensional information, supplementary boundaries for at least one part of the specific patient are automatically determined.
14. The apparatus of claim 13, wherein the supplemental boundary includes a margin of the boundary added to the at least one portion of the particular patient.
15. The device according to claim 13 or 14, wherein the at least one portion of the particular patient comprises at least one of the following: The therapeutic target portion of the heart; It endangers organs.
16. The apparatus according to claim 13, 14 or 15, wherein the control circuit is configured to: The planned treatment volume is automatically determined, at least in part, based on the supplementary boundary.
17. The apparatus of any one of claims 13 to 16, wherein the multidimensional information includes motion-based imaging, the motion-based imaging including cardiac-based imaging for the particular patient and at least one of: respiratory-based imaging for the particular patient and periodic gastric motility-based imaging for the particular patient.
18. The apparatus of claim 17, wherein the control circuit is further configured to: Present the heart-based imaging and the respiration-based imaging to the user; The user interface provides the user with the opportunity to selectively modify the motion of one motion-based imaging separately from the motion of another motion-based imaging.
19. The apparatus according to any one of claims 13 to 18, wherein the control circuit is further configured to: A motion model for the specific patient is generated, at least in part, based on the multidimensional information specific to the specific patient.
20. The apparatus of claim 19, wherein the control circuit is further configured to: The efficacy of each of several different treatment modalities for the specific patient is evaluated, at least in part, based on the said motion model.
21. The apparatus of claim 19 or 20, wherein the control circuit is configured to: Access supplemental multidimensional information specific to the patient during treatment; The motion model is updated at least in part based on the supplementary multidimensional information.
22. The apparatus of claim 19 or 20, wherein the control circuit is configured to: Access supplemental multidimensional information specific to the patient during treatment; The motion model is verified at least in part based on the supplementary multidimensional information.
23. The apparatus according to any one of claims 13 to 22, wherein the control circuit is configured to: The absorbed dose administered during the cardiac radioablation procedure shall be reconstructed, at least in part, according to at least one of the following: The multidimensional information specific to the patient; and A motion model for the specific patient, generated at least in part based on the multidimensional information specific to the specific patient.
24. The apparatus according to any one of claims 13 to 23, wherein the control circuit is further configured to: Based on at least two different motion dimensions derived at least partially from the multidimensional information, the cardiac radioablation treatment plan for the specific patient is optimized.