System and method for radiation therapy treatment planning for breath hold

Abstract

A method for generating a radiation therapy treatment plan with breath hold for a subject includes receiving a plurality of free-breathing CT scans of the subject acquired with a CT imaging system, receiving breathing surrogate data for the subject, selecting a reference CT scan from the plurality of free-breathing CT scans, determining a breathing motion model with a breath hold component based on at least the plurality of free-breathing CT scans of the subject, the breathing surrogate data, and the reference CT scan, where the breathing motion model with a breath hold component is associated with the subject, and determining a breath hold position of a target tissue at a predetermined breathing amplitude using the breathing motion model with a breath hold component.

Description

SYSTEM AND METHOD FOR RADIATION THERAPY TREATMENT PLANNING FOR BREATH HOLDCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is based on, claims priority to, and incorporates herein by reference in its entirety U.S. Serial No. 63 / 600,288 filed November 17, 2023, and entitled ‘'System And Method for Breathing Motion Modeling Breath Hold Integration.”BACKGROUND

[0002] Computer Tomography (CT) scanning is the most common imaging modality for radiation therapy (RT) treatment planning. Treatment planning of lung tumors requires measurement of the patient's tumor motion, as well as the tumor shape and size to be able to design and optimize the radiation treatment. However, the measurement and modeling of breathing motion for treatment planning and its associated tumor delineation is one of the most inaccurate and unpredictable processes in radiation therapy.

[0003] 4DCT is a CT imaging process that was developed to measure and characterize breathing motion for radiation therapy treatment planning. For example, 4DCT has been used to provide respiratory amplitude- or phase-gated images for radiation oncology’. Commercial implementations of 4DCT were developed by modifying existing cardiac-gated imaging techniques to respiratory time scales. This proved to be highly sensitive to breathing irregularity', and most lung and many upper abdominal cancer patients breathe irregularly. 4DCT acquires image data at each body location within approximately 8 seconds, a time length selected such that each location is imaged for just over one breath. This provides data throughout at least one breath, or a complete set of breathing phase angles. The central assumption of 4DCT is that the motion during each breath is similar to every other breath. The image reconstruction or sorting, depending on the vendor, will yield artifact-ridden images and ambiguous motion assessments for irregular breathing patients due to (i) the CT acquisition method and (ii) the unrealistic simplifying assumptions of breathing regularity, including breath-to-breath amplitude variations, period differences, and / or breathing drift. Some hardware advances have improved the robustness of 4DCT to breathing irregularity, but these do not go nearly far enough to provide the quality of imaging similar to that employed elsewhere in radiation therapy.

[0004] A workflow has been developed that may be used to replace the 4DCT process with a model-based process. The model-based process can use multiple fast helical CT scans acquired coincidentally with a breathing amplitude surrogate, and can conduct deformableimage registration to measure, for example, tumor and other patient tissue motion. A mathematical equation or algorithm with patient-specific parameters can be used at each tissue location within the patient to describe the motion of that tissue as a function of breathing amplitude. This model-based process or approach may be termed model-based CT (MBCT). MBCT can use one of the CT images as a reference image and a user or operator can request or instruct the system to generate an image at any user-selected breathing amplitude and rate, and the system may deform the reference CT image to the anatomical geometry modeled by the equation.

[0005] While all patients can undergo radiation therapy during free breathing, there are cases where breath hold would benefit the patient's radiation dose distribution. Breath hold techniques have been used extensively, but they suffer from repeatability and consistency issues such that the breath-to-breath reproducibility can lead to greater tumor motion than free-breathing would have. A method to non-invasively determine breath-hold tumor position or the breath hold position of other tissues would be greatly valuable for radiation therapy for patients that can hold their breath.SUMMARY

[0006] In accordance with an embodiment, a method for generating a radiation therapy treatment plan with breath hold for a subject includes receiving a plurality of free-breathing CT scans of the subject acquired with a CT imaging system, receiving breathing surrogate data for the subject, selecting a reference CT scan from the plurality of free-breathing CT scans, determining a breathing motion model with a breath hold component based on at least the plurality of free-breathing CT scans of the subject, the breathing surrogate data, and the reference CT scan, where the breathing motion model with a breath hold component is associated with the subject, and determining a breath hold position of a target tissue at a predetermined breathing amplitude using the breathing motion model with a breath hold component.

[0007] In accordance with another embodiment, a system for generating a radiation therapy treatment plan with breath hold for a subject, includes a processor device and a non-transitory computer readable memory storing instructions executable by the processor device. The instructions, when executed by the processor device cause the system to receive a plurality of free-breathing CT scans of the subject acquired with a CT imaging system, receive breathing surrogate date for the subject, select a reference CT scan from the plurality of free-breathing CT scans, determine a breathing motion model with a breath hold component based on at least the plurality of free-breathing CT scans of the subject, the breathing surrogate data, andthe reference CT scan, where the breathing motion model with a breath hold component is associated with the subject, and determine a breath hold position of a target tissue at a predetermined breathing amplitude using the breathing motion model with a breath hold component.BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The present invention will hereafter be described with reference to the accompanying drawings, wherein like reference numerals denote like elements.

[0009] FIG. 1 A is an illustration of an example of an x-ray computed tomography (CT) system in accordance with an embodiment;

[0010] FIG. IB is a block diagram of the example x-ray system of FIG. 1 A in accordance with an embodiment;

[0011] FIG. 2 is a schematic diagram of an example radiation treatment system in accordance with an embodiment;

[0012] FIG. 3 illustrates a method for generating a radiation therapy treatment plan with breath hold for a subject in accordance with an embodiment;

[0013] FIG. 4 illustrates a method for generating a breathing motion model with a breath hold component in accordance with an embodiment;

[0014] FIG. 5 illustrates an example method for generating a breath hold component for a breathing motion model in accordance with an embodiment; and

[0015] FIG. 6 is a block diagram of an example computer system in accordance with an embodiment.DETAILED DESCRIPTION

[0016] FIGs. 1A and IB show an example of a computed tomography (CT) system 100 that may be used to perform one or more aspects of the methods described herein. The CT system 100 includes a gantry 102, to which at least one x-ray source 104 is coupled. The x-ray source 104 projects an x-ray beam 106, which may be a fan-beam or cone-beam of x-rays, tow ards a detector array 108 on the opposite side of the gantry 102. The detector array 108 includes a number of x-ray detector elements 110. Together, the x-ray detector elements 110 sense the projected x-rays 106 that pass through a subject 112, such as a medical patient or an object undergoing examination, that is positioned in the CT system 100. Each x-ray detector element 110 produces an electrical signal that may represent the intensity of an impinging x-ray beam and, hence, the attenuation of the beam as it passes through the subject 112. In some configurations, each x-ray detector 110 is capable of counting the number of x-ray photons that impinge upon the detector 1 10. During a scan to acquire x-ray projection data, the gantry' 102 and the components mounted thereon rotate about a center of rotation 114 within the CT system 100.

[0017] The CT system 100 also includes an operator workstation 116, which typically includes a display 118; one or more input devices 120, such as a keyboard and mouse; and a computer processor 122. The computer processor 122 may include a commercially available programmable machine running a commercially available operating system. The operator workstation 116 provides the operator interface that enables scanning control parameters to be entered into the CT system 100. In general, the operator workstation 116 is in communication with a data store server 124 and an image reconstruction system 126. By way of example, the operator workstation 116, data store server 124, and image reconstruction system 126 may be connected via a communication system 128, which may include any suitable network connection, whether wired, wireless, or a combination of both. As an example, the communication system 128 may include both proprietary' or dedicated networks, as well as open networks, such as the internet. In some embodiments, a breathing surrogate (not shown), for example, a bellows-based breathing surrogate, may be used to monitor the breathing cycle of the subject 112 and may be in communication with the operator workstation 116. The breathing surrogate may provide breathing surrogate data (e.g., breathing amplitude) to the operator workstation 116.

[0018] The operator workstation 116 is also in communication with a control system 130 that controls operation of the CT system 100. The control system 130 generally includes an x-ray controller 132, a table controller 134, a gantry controller 136, and a data acquisition system (DAS) 138. The x-ray controller 132 provides power and timing signals to the x-ray source 104 and the gantry' controller 136 controls the rotational speed and position of the gantry 102. The table controller 134 controls a table 140 to position the subject 112 in the gantry 102 of the CT system 100.

[0019] The DAS 138 samples data from the detector elements 110 and converts the data to digital signals for subsequent processing. For instance, digitized x-ray data is communicated from the DAS 138 to the data store server 124. The image reconstruction system 126 then retrieves the x-ray data for a scan from the data store server 124 and reconstructs one or more slices (or images) therefrom. The image reconstruction system 126 may include a commercially available computer processor, or may be a highly parallel computer architecture, such as a system that includes multiple-core processors and massively parallel, high-density computing devices. Optionally, image reconstruction can also be performed on the processor 122 in the operator workstation 116. Reconstructedslices (or images) for a scan can then be communicated back to the data store server 124 for storage or to the operator workstation 116 to be displayed to the operator or clinician.

[0020] The CT system 100 may also include one or more networked workstations 142, by way of example, a networked workstation 142 may include a display 144; one or more input devices 146, such as a keyboard or mouse; and a processor 148. The networked workstation 142 may be located within the same facility as the operator workstation 116, or a different faci 1 i ty, such as a different healthcare institution or clinic.

[0021] The networked workstation 142, whether within the same facility or in a different facility as the operator workstation 116, may gain remote access to the data store server 124 and / or the image reconstruction system 126 via the communication system 128. Accordingly, multiple networked workstations 142 may have access to the data store server 124 and / or image reconstruction system 126. In this manner, x-ray data, reconstructed slices (or images), or other data may be exchanged between the data store server 124, the image reconstruction system 126, and the networked workstations 142, such that the data or slices may be remotely processed by a networked workstation 142. This data may be exchanged in any suitable format, such as in accordance with the transmission control protocol (“TCP”), the internet protocol (“IP”), or other known or suitable protocols.

[0022] FIG. 2 is a schematic diagram of an example radiation treatment (or therapy) system in accordance with an embodiment. In some embodiments, the radiation treatment (or therapy) system 200 may be used to perform one or more aspects of the methods described herein. The radiotherapy system 200 may generally include a delivery system 202, an imaging system 204, and a positioning system 206, each in communication with a treatment console 208. The delivery system 202 can be configured to generate and direct radiation to a patient positioned on a treatment table 210, in accordance with a radiation treatment plan, where the treatment table 210 can be movable. The imaging system 204 (e.g., the CT imaging system 100 shown in FIGs. 1A and IB) may be configured to image the patient before, during or after treatment. Although shown in FIG. 2 as a separate system, in some embodiments, the imaging system 204 may be part of, or combined with, the delivery system 202. In some embodiments, the imaging system 204 can be, for example, an x-ray source, a cone-beam CT system, a CT system, a 4DCT system, and the like. The positioning system 206 may be configured to position and orient the treatment table 210. In addition, the positioning system 206 may also be configured to move the patient to the imaging system 204. In some embodiments, the treatment console 208 may be implemented on a computersystem, for example, computer system 600 described below with respect to FIG. 6. In addition, various aspects of the delivery system 202, imaging system 204, and positioning system 206 may be implemented using one or more processors (e.g., as described below with respect to FIG. 6).

[0023] The treatment console 208, or another suitable controller, may be configured to receive a radiation treatment plan from a planning workstation 212. or another location, such as a database 214, server 216, or cloud 218. Thereafter, the treatment console 208 may control the delivery system 202, imaging system 204, and positioning system 206 to execute the radiation treatment plan. During treatment, the delivery system 202 builds radiation dose inside a patient to achieve dose distributions in accordance with the radiation treatment plan. The plan may include, for example, a number of treatment fields having various beam numbers, beam shapes or fluences, beam energies, beam orientations relative to the patient, and durations of exposure. The delivery system 202, for example, a linear accelerator (LINAC), can be moved about the patient on the treatment table 210. In some embodiments, the radiation treatment plan may also be executed using a combination of table 210 and delivery system 202 movements.

[0024] The planning workstation 212 may implement a treatment planning system that can be utilized to generate a radiation treatment plan based on, for example, dosimetric prescriptions and imaging information obtained from a subject 220 (e.g., using imaging system 104), for example, obtained from one or more images (e.g.. CT images or scans) of a region of interest of the subject 120 including a target (e.g., a tumor) that are acquired, for example, before treatment. In some embodiments, generating the treatment plan includes selecting appropriate treatment fields, which can vary in number, duration, shape or fluence, energy and orientation relative to the patient, to optimize patient outcomes. In some embodiments, the planning workstation 212 and treatment planning system may be implemented on a computer system, for example, computer system 600 described below with respect to FIG. 6.

[0025] Breathing motion modeling can be implemented in radiation therapy as a method for addressing, for example, breathing motion for lung and upper abdominal radiation therapy. Existing techniques include obtaining CT scans of the patient during breathing (i.e., free- breathing scans). As mentioned above, commercial implementations are termed 4DCT and can be prone to errors due to irregular breathing. Another approach, termed model-based CT (MBCT). replaces the assumption of temporal regularity' with an assumption of proportionality between breathing motion and real-time acquired breathing surrogates. In some embodiments, MBCT can use both breathing amplitude and rate as real time surrogates,so the process may also be termed 5DCT (3 spatial dimensions, rate, and amplitude). MBCT can use conventional CT scans (for example, fast-helical scans) with simultaneous breathing monitoring (for example, using a breathing surrogate) that is correlated against the breathing motion as measured using the CT scans and technology generally termed deformable image registration. The correlation between the deformation and breathing surrogate can be done using a universal breathing motion model that connects the breathing phase (a general term that in the case of MBCT approach: 1) for lung cancer can refer to the patient’s breathing amplitude and breathing rate and 2) for abdominal motion can refer to the patient’s breathing amplitude) to the tissue motion measurements to create a model that describes the motion at any subsequent breathing state (or phase). The breathing motion model may then be used to create, for example, images used for treatment planning, images used for treatment verification, and the model itself may be used to predict motion characteristics for treatment planning. However, one aspect of treating the lung and upper abdomen that the MBCT breathing motion model has not been designed to do is manage voluntary breath hold. Voluntary breath hold may be used in radiation therapy to freeze breathing, but since patients cannot hold their breath indefinitely, the application is limited. Breath hold reproducibility also challenges clinical implementations, especially deep-inspiration breath hold. There is a need for a quantitative and reproducible breath hold process in radiation therapy to supplement free-breathing methods.

[0026] The present disclosure describes a system and method for generating a radiation therapy treatment plan with breath hold that can include adding breath hold to a free- breathing modeling approach. This allows the benefits of breath hold, namely the temporary freezing of the tumor motion, with the quantitation offered by a free-breathing modeling approach. In some embodiments, the described technique can include adding one or more breath-hold CT scans to free-breathing MBCT scans and adding the resulting images to the deformation registration. In addition, a breathing motion model can be modified to include a breath-hold component that reflects the relaxation of the thorax and abdomen during breath hold and the corresponding shift in tumor and normal tissue positions.

[0027] Accordingly, the disclosed systems and methods for generating a radiation therapy treatment plan for a subject can be configured to integrate (or add) breath hold, for example, voluntary or forced breath hold, to the tools available to radiation therapy (e.g., to perform treatment planning for administering treatment during a breath hold). In some embodiments the disclosed systems and methods may be used for patients or subjects lying supine, which is the vast majority of radiation therapy patients. During the transition from free-breathing tobreath hold, the patient (or subject) will close their mouth and restrict air access through their nose and relax their diaphragm. In response, the abdominal and pelvic contents apply pressure to the diaphragm which, now relaxed, will be pushed superiorly. Given the air cannot escape the lungs, the resulting pressure will be equilibrated by the chest expanding and the chest muscle elasticity providing an increasing counter force until equilibrium is reached. This process should be reproducible as it does not involve the patient influencing their muscles, only relaxing their muscles. Therefore, this process can lead to a reproducible shift of lung tissues, referred to herein as the breath hold component, from the free-breathing motion model. In some embodiments, the existing motion model used in MBCT correlates the breathing amplitude and breathing rate (which is the time derivative of the amplitude), with the tissue positions. The breathing amplitude can itself be related to diaphragm position, so the internal tissue positions can also be modeled against the diaphragm. The MBCT motion model's prediction of the tissue position as a function of the diaphragm position can be in error by the amount that tissue moves during the breath hold, so if that motion of the tissue during breath hold is captured, then it can be used to offset the free-breathing model to predict the breath hold tissue positions. The disclosed systems and methods can be configured to use the tissue morion during breath hold to offset the free-breathing model. In some embodiments, one or more breath hold scans can be added to the CT scan protocol and the breath hold CT scan(s) can be used to determine the breath hold component that can be used in the breathing motion model. In some embodiments, an estimated or population-based breath hold component may be used in the breathing motion model.

[0028] In some aspects, the present disclosure describes a method for the generation of a breathing motion model using: 1) the deformable registration of a plurality of free-breathing CT scans of a subject with a real-time breathing surrogate, and 2) the addition of a model modifying breath hold component that converts a free-breathing model to one that models breath hold, enabling determination of, for example, the lung tissue and / or lung tumor positions from the breathing surrogate during breath hold. In some embodiments, the realtime breathing surrogate can be measured while the plurality of free-breathing CT scans are acquired. In some embodiments, the generated breathing motion model can be configured to predict the position of tissues such as, for example, lung or upper abdominal tissue and / or lung or upper abdominal tumors, during breath hold.

[0029] In some embodiments, the present disclosure describes systems and methods that couple breath hold with MBCT. In some embodiments, the MBCT CT acquisition process (e.g., that can include acquisition of free-breathing CT scans) can be supplemented by one ormore breath-hold CT scans, either voluntary or forced, at either similar or different levels of breath hold. In some embodiments, a breathing motion model can be supplemented by the difference between, for example, the tumor and normal tissue positions for a breath hold scan and the predicted free-breathing tissue (e.g., tumor or normal tissue) positions for the equivalent breathing amplitude as the breath hold scan. This difference can be termed the breath-hold component and reflects the physiologic difference between a breathing patient and one undergoing breath hold. In some embodiments, the breath-hold component may be a single vector field that relates the free-breathing MBCT breathing motion model and the breath-hold position, or a range of vectors that relate the difference at different breath hold amplitudes.

[0030] FIG. 3 illustrates a method for generating a radiation therapy treatment plan with breath hold for a subject in accordance with an embodiment. Although the blocks of the processes of FIG. 3 are illustrated in a particular order, in some embodiments, one or more blocks may be executed in a different order than illustrates in FIG. 3, or may be bypassed.

[0031] In FIG. 3, at block 302, a plurality of free-breathing CT scans of a region of interest of the subject may be received from, for example, a CT system (e.g., CT system 100 shown in FIGs. 1A and IB). Each CT scan (or CT scan dataset) in the plurality' of free-breathing CT scans can include a set of slices acquired during the scan. In some embodiments, the plurality' of free-breathing CT scans may be received in real-time from the CT system (e.g., from the data store server 124 or image reconstructions system 126 of CT system 100 shown in FIG. I B), for example, the CT system 100 may acquire CT data for each CT scan and reconstruct a set of CT slices for each CT scan using know n reconstruction methods. In some embodiments, the plurality of free-breathing CT scans may be received or retrieved from data storage of an imaging system (e.g., data storage of CT system 100 shown in FIGs. 1A-1B) or data storage of other computer systems (e.g., storage device 616 of computer system 600 shown in FIG. 6). In some embodiments, the free-breathing CT scans may be acquired using known free-breathing CT acquisition protocols such as, for example, a fast helical free- breathing CT (FHFBCT) protocol. In some embodiments, the acquired free-breathing CT scans of the subject may be of a region of interest in the subject, for example, the subject’s lungs (e g., a portion of the lungs or the entire lungs) and surrounding tissues, or the upper abdominal region and surrounding tissue. The region of interest can include, for example, a target or target site (e.g., a tumor) and normal or healthy tissue.

[0032] At block 304, breathing surrogate data may be received from, for example, a breathing surrogate. In some embodiments, the surrogate is measured externally. Forexample, an abdominal pneumatic bellows may be used as a real-time breathing surrogate to monitor and record the breathing (e.g., a breathing state or phase) of the subject simultaneously with the acquisition of the free-breathing CT scans and / or one or more breath hold CT scans (discussed further below with respect to block 308). In another example, the breathing surrogate can be created using patient abdomen and / or thorax optical imaging that measures or characterizes the abdominal and / or chest expansion and contraction during breathing. In some embodiments, the breathing surrogate may be obtained or extracted from the image data (e.g., the free-breathing or breath hold CT scans) itself. In some embodiments, the breathing surrogate data includes a breathing amplitude (A). The breathing amplitude A may be derived from the breathing surrogate. In some embodiments, the breathing surrogate data can also include a breathing rate (e.g., a time derivative of the breathing amplitude). The breathing surrogate may be synchronized with the CT scan acquisition so that an amplitude can be assigned to each CT slice in the scan as related to the CT slice acquisition time. In some embodiments, a breathing rate may also be assigned to each slice in a CT scan. In some embodiments, the breathing surrogate data may be received in real time from the breathing surrogate. In some embodiments, the breathing surrogate data may be received from data storage of the breathing surrogate, or data storage of other computer systems (e.g., storage device 616 of computer system 600 shown in FIG. 6).

[0033] At block 306, a reference CT scan may be selected from the plurality of free- breathing CT scans. At block 308. a breathing motion model with a breath hold component can be generated for the subject. In some embodiments, the breathing motion model with the breath hold component can be generated based on, for example, the plurality of free- breathing CT scans, the breathing surrogate data, the reference breathing condition, and, in some embodiments, one or more breath hold CT scans of the subject (as discussed further below with respect to FIG. 5). In some embodiments, the breathing motion model can have independent variables derived from the measured breathing surrogate data rather than time, enabling breathing irregularity to be explicitly included in the measured breathing surrogate rather than the breathing motion model. In some embodiments, a breathing motion model for lungs can include two variables, the plethysmograph-measured tidal volume which allows motion based on lung fdling, and the airflow, which supported hysteresis motion found in breathing motion. The two surrogates can be, therefore, the tidal volume and airflow, v and f respectively. In some embodiments, a bellows-based breathing surrogate (or other known breathing surrogates) can be used to provide measurements that are functionally related to tidal volume and since airflow is the time derivative of tidal volume, the original volume andflow surrogates may be replaced with the bellows-based breathing amplitude and breathing rate, although the original variables v and respectively, may be retained.

[0034] In some embodiments, the breathing motion model can describe the position Xtof a specific voxel of tissue i (e.g., lung tissue including lung tumors). As mentioned above, in some embodiments, the breathing motion model can advantageously include a breath hold component (jq) to offset a free-breathing tissue position to predict the breath hold tissue positions. In some embodiments, the breathing motion model with breath hold component can be given as, for example:where v and / are the breathing amplitude and breathing rate, respectively, XO lis the position of voxel i at zero breathing amplitude and breathing rate, < / andare the patient and voxel specific vectors used to describe the motion as a function of breathing amplitude and breathing rate, respectively, 5( ) is equal to 1 when under breath hold and 0 otherwise, and jq, is the breath hold component. As discussed further below with respect to FIG. 4, the plurality of free-breathing CT scans (each comprised of a set of CT slices) of the subj ect can be the source of data used to determine the parameters XO l, a . and for each voxel. Because the patient continuously breathes during a free-breathing acquisition, in some embodiments, the breathing surrogate values (amplitudes and rates) may be assigned to each of the plurality of free-breathing CT slices using the synchronized breathing surrogate signal (e.g., the breathing surrogate data from block 304). As discussed further below with respect to FIG. 5, in some embodiments, the breath hold component, jq, (e.g., a reproducible shift of tissue(s) (e.g., lung tissues) due to the breath hold) can be determined from one or more breath hold CT scans, or, in some embodiments, the breath hold component, jq, may be an estimated breath hold component or a population-based breath hold component.

[0035] FIG. 4 illustrates a method for generating a breathing motion model with a breath hold component in accordance with an embodiment. Although the blocks of the processes of FIG. 4 are illustrated in a particular order, in some embodiments, one or more blocks may be executed in a different order than illustrates in FIG. 4. or may be bypassed. At block 402, tissue position(s), breathing amplitude(s) and breathing rate(s) can be determined for each free-beathing CT scan of the subject (e.g., each of the plurality of free-breathing CT scans received at block 302 of FIG. 3). For example, a deformable image registration process can be used to determine the tissue position(s) (Xt) in each of the plurality of free-breathing CT scans. As mentioned above, in some embodiments, the breathing surrogate data (e.g., asreceived at block 304 of FIG. 3) can be assigned to each of the plurality of free-breathing CT scans. For example, a breathing amplitude and breathing rate from the breathing surrogate data can be assigned to each slice of each the plurality’ of free-breathing CT scans.

[0036] At block 404, one or more subject specific parameters of the breathing motion model can be determined based on the determined tissue position(s), breathing amplitude(s) and breathing rate(s) for each of the plurality’ of free-breathing CT scans of the subject. For example, referring to Equation 1 above, the parameters XO l.and / ?, can be determined from the tissue position(s) (2Q, breathing amplitude(s) (v), and breathing rate(s) ( / ) for each of the plurality of free-breathing CT scans. For example, in some embodiments, the subject specific parameters (e.g.,o (, a^, and / ?,) can be determined using a fitting algorithm. In some embodiments, when determining the subject specific parameters (e.g., XQ l, at, and J , the breath hold component in Equation 1 can be assumed to be zero.

[0037] At block 406, a breath hold component for the breathing motion model may be determined. In some embodiments, the breath hold component (jq) may be determined using at least one breath hold CT scan of the subject. FIG. 5 illustrates an example method for generating a breath hold component for a breathing motion model in accordance with an embodiment. At block 502, at least one breath hold CT scan of the region of interest of the subject can be received. In some embodiments, the at least one breath hold CT scan may be received from, for example, a CT system (e.g., CT system 100 shown in FIGs. 1A and IB). Each CT scan (or CT scan dataset) in the at least one breath hold CT scan (or image) can include a set of slices acquired during the scan. In some embodiments, the at least one breath hold CT scan may be received in real-time from the CT system (e.g., from the data store server 124 or image reconstructions system 126 of CT system 100 shown in FIG. IB), for example, the CT system 100 may acquire CT data for each CT scan and reconstruct a set of CT slices for each CT scan using known reconstruction methods. In some embodiments, the at least one breath hold CT scan may be received from data storage of an imaging system (e.g., data storage of CT system 100 shown in FIGs. 1 A-1B) or data storage of other computer systems (e.g., storage device 616 of computer system 600 shown in FIG. 6). In some embodiments, the one or more breath hold CT scans may be acquired using known breath hold CT acquisition protocols. In some embodiments, the acquired breath hold CT scans of the subject may be of a region of interest on the subject, for example, the subject's lungs (e g., apportion of the lungs or the entire lungs) and surrounding tissues, or the upperabdominal region and surrounding tissue. In some embodiments, the at least one breath hold CT scan is acquired of the same region of interest as the plurality of free-breathing CT scans.

[0038] At block 504, the reference CT scan selected from the plurality of free-breathing CT scans (e.g., at block 306 of FIG. 3) may be retrieved, for example, from data storage. At block 506, a free-breathing CT scan may be simulated at a predetermined breathing amplitude. In some embodiments, the predetermined breathing amplitude is a breathing amplitude associated with one of the one or more breath hold CT scans. As mentioned above, breathing surrogate data may be acquired with (e g., simultaneously) the breath hold CT scan(s) and a breathing amplitude from the breathing surrogate data can be assigned to each breath hold CT scan. In some embodiments, the breathing motion model, for example, as given by Equation 1. can be used to predict tissue position and simulate the free-breathing CT scan at the predetermined breathing amplitude. It is noted that for a simulated free-breathing CT scan, the breath hold component of the breathing motion model will be zero and the breathing motion model of Equation 1 can become, for example:Equation 2 describes the motion of, for example, a lung (or lung tumor) voxel i subject to respiratory motion in the reference image (e.g., associated with the selected reference breathing condition) as a function of breathing amplitude (v) and breathing rate (f).

[0039] At block 508, the breath hold component ( jq) can be determined by determining the difference in tissue position between the simulated free-breathing CT scan at the predetermined breathing amplitude and the breath hold CT scan associated with the predetermined breathing amplitude (e.g., from the one or more breath hold CT scans). In some embodiments, the difference in tissue position can be determined using a deformable image registration process. In some embodiments, the breath hold component is an integer value. In some embodiments, the breath-hold component may be a single vector field that relates the free-breathing tissue position and the breath-hold tissue position. In some embodiments, the breath hold component may be a range of vectors that relate the difference at different breath hold amplitudes. In some embodiments, if either only one breath hold CT scan is acquired or a single breath hold CT scan is selected from multiple acquired breath holds CT scans at different amplitudes, one breath hold component can be determined and assumed to be a constant for the subject. Accordingly, the determined breath hold component can be used for the beathing motion model for estimating breath hold tissue position (or simulating breath bold CT scans) for any breathing amplitude. In some embodiments, abreath hold component may be determined for a plurality of breathing amplitudes by repeating steps 504-508 using different breath hold CT scans at different amplitudes and simulated free-breathing CT scans and breathing amplitudes. At block 510, the breath hold component or breath hold components (e.g., for different breathing amplitudes) can be stored in a data storage, for example, data storage of CT system 100 shown in FIGs. 1A-1B), data storage of a radiation treatment system or treatment planning system 212 (e.g., database 214 shown in FIG. 2) or data storage of other computer systems (e.g.. storage device 616 of computer system 600 shown in FIG. 6).

[0040] Returning to block 406 of FIG. 4, in some embodiments, the breath hold component may be an estimated breath hold component or a population-based breath hold component and, accordingly, a breath hold CT scan or scans of the subject would not be required. In some embodiments, an estimated breath hold component may be determined using machine learning. In some embodiments, the estimated breath hold component or the population-based breath hold component may be predetermined and, for example, may be received from data storage such as data storage of a computer system (e.g., storage device 616 of computer system 600 shown in FIG. 6). At bock 408. the breathing motion model with breath hold component can be stored in a data storage, for example, data storage of CT system 100 shown in FIGs. 1A-1B), data storage of a radiation treatment system or treatment planning system 212 (e.g.. database 214 shown in FIG. 2), or data storage of other computer systems (e g., storage device 616 of computer system 600 shown in FIG. 6).

[0041] Returning to FIG. 3, at block 310, motion of a target tissue of a subject may be estimated (or the tissue position predicted) using the breathing motion model with a breath hold component, for example, the breathing motion model given by Equation 1 discussed above. In some embodiments, a treatment planning system may use the motion model to estimate the motion and position of a tumor. To determine the motion or position of a tissue, a reference breathing condition can be selected (e.g., v = 0. f= 0). In some embodiments, the reference CT image can be deformed to the reference breathing condition using the determined breathing motion model with breath hold component. To plan treatment during a breath hold, the breathing rate (f) will be zero and the breathing motion model of Equation 1 can become, for example:As discussed above with respect to block 308 and FIGs. 4-5, in some embodiments, the breath hold component, jq, (e.g., a reproducible shift of tissue, for example, lung tissues,from the breath hold) can be determined from one or more breath hold CT scans of the subject, or. in some embodiments, the breath hold component, yh* may be an estimated breath hold component or a population-based breath hold component. To plan treatment during free- breathing, the breath hold componentwill be zero and the breathing motion model may be given, for example, by Equation 2 above.

[0042] At block 312, CT scans can also optionally be generated (or simulated) at predetermined (e.g., selected by a user or operator) breathing phases (or states) using the breathing motion model with a breath hold component. Accordingly, the breathing motion model with breath hold component can be used to simulate a CT scan at any user specified breathing amplitude and breathing rate (for free-breathing scans) or other breathing surrogate description. For example, in some embodiments, the CT scans may be generated by deforming a reference CT scan using the breathing motion model with the breath hold component, for example, as given by Equation 1 above, To generate a breath hold CT scan, the breathing rate (f) will be zero and the breathing motion model of Equation 1 can be given by, for example, Equation 3 above. To generate a free-breathing CT scan, the breath hold component (jq) will be zero and the breathing motion model may be given, for example, by Equation 2 above. In some embodiments, the generated CT scan(s) of the subject may be of, for example, the subject's lungs and surrounding tissues. In some embodiments, the reference CT scan (or image) can be deformed (reshaped) to be consistent with whatever breathing state (or phase) a user or downstream workflow requires.

[0043] At block 314, the estimated motion or predicted tissue position from block 310 may be displayed on a display (e.g., a display 118 of a CT sy stem 100 shown in FIG. IB, a display associated with a radiation treatment system or treatment planning system (e.g., a planning workstation 212 shown in FIG. 2). or a display 618 of a computer system 600 shown in FIG. 6). The estimated motion or predicted tissue position may also be stored in a data storage, for example, data storage of CT system 100 shown in FIGs. 1A-1B), data storage of a radiation treatment system or treatment planning system 212 (e.g., database 214 shown in FIG. 2), or data storage of other computer systems (e.g., storage device 416 of computer system 400 shown in FIG. 4.

[0044] At block 316, the generated (or simulated) CT scans from block 312 may be optionally displayed on a display (e.g., a display 118 of a CT sy stem 100 shown in FIG. IB, a display associated with a radiation treatment system or treatment planning system (e.g. a planning workstation 212 shown in FIG. 2). or a display 618 of a computer system 600shown in FIG. 6). The generated CT scans may also be stored in a data storage, for example, data storage of CT system 100 shown in FIGs. 1 A-1B), data storage of a radiation treatment system or treatment planning system 212 (e.g., database 214 shown in FIG. 2), or data storage of other computer systems (e.g., storage device 616 of computer system 600 shown in FIG. 6). In some embodiments, the CT scans generated at block 312 may be used to determine at least one quantitative lung parameter. In some embodiments, the quantitative lung parameters can include, for example, ventilation measurements (e.g.. local tissue expansion), lung motion measurements and description, breathing dynamics, biomechanical properties, high spatial resolution dynamic ventilation processed, and other structural and functional properties. In some embodiments, the generated CT image may be used to determine the internal lung and tumor motion during the CT session. In some embodiments, the generated CT scans can be used to identify, for example, the location of each piece of the lung and tumor throughout the scans.

[0045] FIG. 6 is a block diagram of an example computer system in accordance with an embodiment. Computer system 600 may be used to implement the systems and methods described herein. In some embodiments, the computer system 600 may be a workstation, a notebook computer, a tablet device, a mobile device, a multimedia device, a network server, a mainframe, one or more controllers, one or more microcontrollers, or any other general- purpose or application-specific computing device. The computer system 600 may operate autonomously or semi-autonomously, or may read executable software instructions from the memory or storage device 616 or a computer-readable medium (e.g., a hard drive, a CD- ROM, flash memory ), or may receive instructions via the input device 620 from a user, or any other source logically connected to a computer or device, such as another networked computer or server. Thus, in some embodiments, the computer system 600 can also include any suitable device for reading computer-readable storage media.

[0046] Data, such as data acquired with an imaging system (e.g., a CT imaging system) may be provided to the computer system 600 from a data storage device 616, and these data are received in a processing unit 602. In some embodiment, the processing unit 602 includes one or more processors. For example, the processing unit 602 may include one or more of a digital signal processor (DSP) 604, a microprocessor unit (MPU) 606, and a graphics processing unit (GPU) 608. The processing unit 602 also includes a data acquisition unit 610 that is configured to electronically receive data to be processed. The DSP 604, MPU 606, GPU 608, and data acquisition unit 610 are all coupled to a communication bus 612. Thecommunication bus 612 may be, for example, a group of wires, or a hardware used for switching data between the peripherals or between any component in the processing unit 602.

[0047] The processing unit 602 may also include a communication port 614 in electronic communication with other devices, which may include a storage device 616, a display 618, and one or more input devices 620. Examples of an input device 620 include, but are not limited to, a keyboard, a mouse, and a touch screen through which a user can provide an input. The storage device 616 may be configured to store data, which may include data such as, for example, acquired data, acquired scans, breathing surrogate data, deformation data, generated CT images, determined tissue positions, etc., whether these data are provided to, or processed by, the processing unit 602. The display 618 may be used to display images and other information, such as CT images, patient health data, and so on.

[0048] The processing unit 602 can also be in electronic communication with a network 622 to transmit and receive data and other information. The communication port 614 can also be coupled to the processing unit 602 through a switched central resource, for example the communication bus 612. The processing unit can also include temporary storage 624 and a display controller 626. The temporary storage 624 is configured to store temporary information. For example, the temporary storage 624 can be a random access memory.

[0049] Computer-executable instructions for radiation therapy treatment planning including generating computed tomography (CT) scans of a subject or estimating motion of a target tissue of a subject using a breathing motion model with a breath hold component according to the above-described methods may be stored on a form of computer readable media. Computer readable media includes volatile and nonvolatile, removable, and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer readable media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), flash memory or other memory technology, compact disk ROM (CD-ROM), digital volatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired instructions and which may be accessed by a system (e.g., a computer), including by internet or other computer network form of access.

[0050] The present technology' has been described in terms of one or more preferred embodiments, and it should be appreciated that many equivalents, alternatives, variations,and modifications, aside from those expressly stated, are possible and within the scope of the invention.

Claims

CLAIMS:

1. A method for generating a radiation therapy treatment plan with breath hold for a subject, the method comprising: receiving a plurality of free-breathing CT scans of the subj ect acquired with a CT imaging system; receiving breathing surrogate data for the subject; selecting a reference CT scan from the plurality of free-breathing CT scans; determining a breathing motion model with a breath hold component based on at least the plurality of free-breathing CT scans of the subject, the breathing surrogate data, and the reference CT scan, wherein the breathing motion model with a breath hold component is associated with the subject; and determining a breath hold position of a target tissue at a predetermined breathing amplitude using the breathing motion model with a breath hold component.

2. The method according to claim 1, further comprising generating one or more breath hold CT scans at predetermined breathing phases using the breathing motion model with the breath hold component.

3. The method according to claim 1, wherein determining a breathing motion model with a breath hold component further comprises: receiving at least one breath hold CT scan of the subject acquired with the CT imaging system; and determining the breath hold component based at least on the at least one breath hold CT scan.

4. The method according to claim 1 , wherein the breath hold component is one of an estimated beath hold component or a population-based breath hold component.

5. The method according to claim 1, where the plurality of free-breathing CT scans includes at least a portion of the subject's lungs.

6. The method according to claim 1, wherein the plurality of free-breathing CT scans include at least a portion of the subject's abdomen.

7. The method according to claim 2, wherein the predetermined breathing phases are selected by a user.

8. The method according to claim 2, wherein generating one or more breath hold CT scans at predetermined breathing phases using the breathing motion model with a breath hold component comprises deforming the reference CT scan using the breathing motion model with a breath hold component.

9. A system for generating a radiation therapy treatment plan with breath hold for a subject, the system comprising: a processor device; and a non-transitory computer readable memory storing instructions executable by the processor device, wherein the instructions, when executed by the processor device cause the system to: receive a plurality of free-breathing CT scans of the subject acquired with a CT imaging system; receive breathing surrogate date for the subject; select a reference CT scan from the plurality' of free-breathing CT scans; determine a breathing motion model with a breath hold component based on at least the plurality of free-breathing CT scans of the subject, the breathing surrogate data, and the reference CT scan, wherein the breathing motion model with a breath hold component is associated with the subject; and determine a breath hold position of a target tissue at a predetermined breathing amplitude using the breathing motion model with a breath hold component.

10. The system according to claim 9, wherein the instructions, when executed by7the processor device, further cause the system to: generate one or more breath hold CT scans at predetermined breathing phases using the breathing motion model with a breath hold component.

11. The system according to claim 9, wherein the instructions, when executed by the processor device, further cause the system to for determining the breathing motion model with a breath hold component:receive at least one breath hold CT scan of the subject acquired with the CT imaging system; and determine the breath hold component based at least on the at least one breath hold CT scan.

12. The system according to claim 9, wherein the breath hold component is one of an estimated beath hold component or a population-based breath hold component.

13. The system according to claim 10, wherein generating one or more breath hold CT scans at predetermined breathing phases using the breathing motion model with a breath hold component comprises deforming the reference CT scan using the breathing motion model with a breath hold component.

14. The system according to claim 9, wherein the plurality of free-breathing CT scans includes at least a portion of the subject's lungs.

15. The system according to claim 9, wherein the plurality of free-breathing CT scans include at least a portion of the subject's abdomen.

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