Patent Description:
Radiation therapy (or "radiotherapy") can be used to treat cancers or other ailments in mammalian (e.g., human and animal) tissue. One such radiotherapy technique is provided using a linear accelerator (also referred to as "linac"), whereby a tumor is irradiated by high-energy particles (e.g., electrons, protons, ions, high-energy photons, and the like). The placement and dose of the radiation beam can be accurately controlled to ensure the tumor receives the prescribed radiation, and the placement of the beam should be such as to minimize damage to the surrounding healthy tissue, often called the organ(s) at risk (OARs). A physician prescribes a predefined amount of radiation dose to the tumor and surrounding organs similar to a prescription for medicine. Generally, ionizing radiation in the form of a collimated beam is directed from an external radiation source toward a patient.

A specified or selectable beam energy can be used, such as for delivering a diagnostic energy level range or a therapeutic energy level range. Modulation of a radiation beam can be provided by one or more attenuators or collimators, such as a multi-leaf collimator (MLC). The intensity and shape of the radiation beam can be adjusted by collimation to avoid damaging healthy tissue (e.g., OARs) adjacent to the targeted tissue by conforming the projected beam to a profile of the targeted tissue.

Treatment planning is a process involving determination of specific radiotherapy parameters for implementing a treatment goal under the constraints. Examples of the radiotherapy parameters include radiation beam angles, radiation intensity level at each angle, etc. The radiation dose can be calculated using a software model. The outcome of the treatment planning process is a radiotherapy treatment plan, hereinafter also referred to as a treatment plan or simply a plan. The treatment plan can be developed well before radiotherapy is delivered, such as using one or more medical imaging techniques, such as images from X-rays, computed tomography (CT), magnetic resonance (MR), positron emission tomography (PET), single-photon emission computed tomography (SPECT), or ultrasound. A health care provider may use images of patient anatomy to identify a target tumor and the OARs near the tumor, delineate the target tumor that is to receive prescribed radiation dose, and similarly delineate nearby tissue such as organs at risk of damage from the radiation treatment. The delineation can be done manually, or by using an automated tool that assists in identifying or delineating the target tumor and OARs. A radiation therapy treatment plan can then be created using an optimization technique based on clinical and dosimetry objectives and constraints (e.g., the maximum, minimum, and fraction of dose of radiation to a fraction of the tumor volume, and like measures for the critical organs).

For example, document <CIT> discloses a radiotherapy planning method wherein a phantom is irradiated with the initial planned dose distribution at the planned gantry angles. The error between the planned and the real dose is taken into consideration for the final plan.

MR-linac is a radiation treatment system that combines linac radiotherapy with diagnostic-level magnetic resonance imaging (MRI). The MR-linac can enable in-room MRI for anatomic and physiological treatment adaptation and response monitoring, and has a potential to reduce treatment margins with real-time visualization and target tracking. Tumors and surrounding tissue can be precisely located, their movement tracked, and treatment adapted in real time in response to changes in tumor position, shape, biology and spatial relationship to critical organs at the time of treatment.

The treatment planning procedure may include using a three-dimensional (3D) image of the patient to identify a target region (e.g., the tumor) and to identify critical organs near the tumor. Creation of a treatment plan can be a time-consuming process where a planner tries to comply with various treatment objectives or constraints (e.g., dose volume histogram (DVH), overlap volume histogram (OVH)), taking into account their individual importance (e.g., weighting) in order to produce a treatment plan that is clinically acceptable. The treatment plan is comprised of numerical parameters that specify the direction, cross-sectional shape, and intensity of each radiation beam. Once created, the treatment plan can be executed by positioning the patient in the treatment machine and delivering the prescribed radiation therapy directed by the optimized plan parameters. The radiation therapy treatment plan can include dose "fractioning," whereby a sequence of radiation treatments is provided over a predetermined period of time (e.g., <NUM>-<NUM> daily fractions), with each treatment including a specified fraction of a total prescribed dose. However, during treatment, the position of the patient and the position of the target tumor in relation to the treatment machine (e.g., linac) is very important in order to ensure the target tumor and not healthy tissue is irradiated.

The treatment planning system (TPS) can use a beam model (e.g., a software model) to determine a treatment plan, including one or more treatment parameters. A beam model can include parameters that describe, among other things, the energy distribution of radiation emitted from the radiation machine (e.g., a linac). The beam model parameter values can vary from one radiation machine to another, even radiation machines of the same model from the same manufacturer, at least because in each radiation machine there can be small differences, such as influence or energy provided by the radiation machine. Mechanical differences (e.g., mechanical dimensions or material properties) or differences in component values (e.g., electronic circuit component values) between the radiation machines can also contribute to the differences in beam model parameter values between different radiation machines.

In certain approaches, after the radiation machine is installed, and final tuning is performed, a customer can perform measurements using a phantom that simulates patient tissue. The phantom can include a tank of water with a moveable dosimeter inside the tank of water. A beam modeler can then perform beam modeling using the measurements to determine the beam model parameter values for the radiation machine corresponding to the measurements.

Determining optimal beam model parameter values is an important part of treatment planning. The present inventors have recognized that, among other factors, gantry angle can have an impact on the radiation dose calculation, thereby affecting the radiation treatment plan such as generated using a beam model. A gantry is a structure in a radiotherapy machine (e.g., a linac) that holds all the beam-generating components of a linac, including a radiation source, a magnetron, a waveguide, and a MLC, and radiation detectors, among others. The gantry can move (e.g., rotate) the radiation source around a patient. A gantry angle is the angle between the vertical plane and the plane containing the diagnostic or therapeutic beam and the detector array.

A radiotherapy system (e.g., an MR-linac) may include a magnet used for generating a magnetic field for diagnostic imaging (e.g., MRI) or for deciding a shape of a therapeutic beam (e.g., a photon beam). The magnet contains coils that need to be maintained at a low temperature for a desired superconducting state. Cooling of the magnet is achieved by using a cryogen (e.g., liquid helium) stored in chambers of a cryostat. The gantry can be positioned around the cryostat. Conventional beam modeling and dose calculation are based on an assumption of uniformity of the cryogen irrespective of the gantry angle. However, the present inventors have recognized that at least in some imaging and radiotherapy machines, the cryogen in the path of the beam can be non-uniform at different gantry angles. The non-uniformity can be due to cryostat inhomogeneities and/or variations in cryogen level. As such, conventional beam models may introduce errors in dose calculation when the radiation beam is delivered at different angles. Additionally, the thickness of the metal shells that are used to construct the imaging system (e.g., MRI) may vary at different gantry angles. This may introduce variation in the amount of radiation getting through the metal. Dose variation at different gantry angles as discussed above, if not accounted for, may affect radiation treatment efficacy.

The present document discusses methods and systems for determining a radiotherapy treatment plan based at least on information about gantry angle-indexed dose (GAID) variation. An exemplary system can include an interface configured to receive a beam model for use in a radiation machine, and a processor configured to determine, for the radiation machine, information about GAID variation which is represented by a plurality of radiation doses at different gantry angles. The processor can determine a radiation treatment plan for the patient using the beam model and the GAID variation information. Incorporating the information of GAID variation into the beam modeling process as discussed herein can provide more reliable dose calculation (e.g., using GAID variation to modify a pre-calculated radiation dose for a patient), and more accurate machine-specific treatment plan for the patient. The radiation machines can be commissioned more efficiently, and improved patient workflows and improved patient outcomes can be achieved.

The invention pertains to a computer-implemented method for determining a treatment plan for delivering radiotherapy to a patient via a radiation machine. The method comprises steps of: providing a beam model for use in the radiation machine; determining, for the radiation machine, a gantry angle-indexed dose, GAID, variation representing a plurality of radiation doses at different gantry angles; and determining a radiation treatment plan for the patient using the beam model and the determined GAID variation.

The method includes determining the GAID variation that can include: delivering a constant radiation beam to a phantom at different gantry angles; and calculating a dose at each of one or more locations in the phantom corresponding to each of the different gantry angles.

The invention also pertains to a system as defined in claim <NUM>, and a machine-readable storage medium as defined in claim <NUM>.

Further embodiments of the invention are defined in the dependent claims.

The above is intended to provide an overview of subject matter of the present patent application.

In the drawings, which are not necessarily drawn to scale, like numerals describe substantially similar components throughout the several views. Like numerals having different letter suffixes represent different instances of substantially similar components. The drawings illustrate generally, by way of example but not by way of limitation, various embodiments discussed in the present document.

In the following detailed description, reference is made to the accompanying drawings which form a part hereof, and which is shown by way of illustration-specific embodiments in which the present disclosure may be practiced. These embodiments, which are also referred to herein as "examples," are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that the embodiments may be combined, or that other embodiments may be utilized and that structural, logical and electrical changes may be made without departing from the scope of the present disclosure. The invention is defined in the claims. Other embodiments or examples are not a part of the invention. Radiotherapy treatment delivery methods, in particular, are not a part of the invention.

<FIG> illustrates an exemplary radiotherapy system <NUM> for providing radiation therapy to a patient. The radiotherapy system <NUM> includes a data processing device <NUM>. The data processing device <NUM> may be connected to a network <NUM>. The network <NUM> may be connected to the Internet <NUM>. The network <NUM> can connect the data processing device <NUM> with one or more of a database <NUM>, a hospital database <NUM>, an oncology information system (OIS) <NUM>, a radiation therapy device <NUM>, an image acquisition device <NUM>, a display device <NUM>, and a user interface <NUM>. The data processing device <NUM> can be configured to generate radiation therapy treatment plans <NUM> to be used by the radiation therapy device <NUM>.

The data processing device <NUM> may include a memory device <NUM>, a processor <NUM>, and a communication interface <NUM>. The memory device <NUM> may store computer-executable instructions, such as an operating system <NUM>, a radiation therapy treatment plan <NUM> (e.g., original treatment plans, adapted treatment plans and the like), software programs <NUM>. and any other computer-executable instructions to be executed by the processor <NUM> The memory device <NUM> may additionally store data, including medical images <NUM>, patient data <NUM>, and other data required to create and implement a radiation therapy treatment plan <NUM>. The software programs <NUM> may include radiotherapy treatment plan software implementing algorithms of artificial intelligence, deep learning, neural networks, among others. In an example, the software programs <NUM> can convert medical images of one format (e.g.. MRI) to another format (e.g., CT) by producing synthetic images, such as pseudo-CT images. For instance, the software programs <NUM> may include image processing programs to train a predictive model for converting a medical image from the medical images <NUM> in one modality (e.g., an MRI image) into a synthetic image of a different modality (e.g., a pseudo CT image); alternatively, the trained predictive model may convert a CT image into an MRI image. In another example, the software programs <NUM> may register the patient image (e.g.. a CT image or an MR image) with that patient's dose distribution (also represented as an image) so that corresponding image voxels and dose voxels are associated appropriately by the network. In yet another example, the software programs <NUM>,<NUM> may substitute functions of the patient images such as signed distance functions or processed versions of the images that emphasize some aspect of the image information. Such functions might emphasize edges or differences in voxel textures, or any other structural aspect useful to neural network learning. The software programs <NUM> may substitute functions of the dose distribution that emphasize some aspect of the dose information. Such functions might emphasize steep gradients around the target or any other structural aspect useful to neural network learning.

In an example, the software programs <NUM> may generate projection images for a set of two-dimensional (2D) and/or 3D CT or MR images depicting an anatomy (e. g, one or more targets and one or more OARs) representing different views of the anatomy from a first gantry angle of the radiotherapy equipment. For example, the software programs <NUM> may process the set of CT or MR images and create a stack of projection images depicting different views of the anatomy depicted in the CT or MR images from various perspectives of the gantry of the radiotherapy equipment. In particular, one projection image may represent a view of the anatomy from <NUM> degrees of the gantry, a second projection image may represent a view of the anatomy from <NUM> degrees of the gantry, and a third projection image may represent a view of the anatomy from <NUM> degrees of the gantry. The degrees may be a position of the MLC relative to a particular axis of the anatomy depicted in the CT or MR images. The axis may remain the same for each of the different degrees that are measured.

In an example, the software programs <NUM> may generate graphical aperture image representations of MLC leaf positions at various gantry angles. These graphical aperture images are also referred to as aperture images. In particular, the software programs <NUM> may receive a set of control points that are used to control a radiotherapy device to produce a radiotherapy beam. The control points may represent the beam intensity, gantry angle relative to the patient position, and the leaf positions of the MLC, among other machine parameters. Based on these control points, a graphical image may be generated to graphically represent the beam shape and intensity that is output by the MLC at each particular gantry angle. The software programs <NUM> may align each graphical image of the aperture at a particular gantry angle with the corresponding projection image at that angle that was generated. The images are aligned and scaled with the projections such that each projection image pixel is aligned with the corresponding aperture image pixel.

In an example, the software programs <NUM> can include a treatment planning software for generating or estimating a graphical aperture image representation of MLC leaf positions at a given gantry angle for a projection image of the anatomy representing the view of the anatomy from the given gantry angle. The software programs <NUM> may further include a beam model to compute machine parameters or control points for a given type of machine to output a radiation beam from the MLC that achieves the same or similar estimated graphical aperture image representation of the MLC leaf positions. Namely, the treatment planning software may output an image representing an estimated image of the beam shape and intensity for a given gantry angle and for a given projection image of the gantry at that angle, and the function may compute the control points for a given radiotherapy device to achieve that beam shape and intensity.

In some examples, the treatment planning software in the software programs <NUM> may receive information of cryostat variation <NUM>, also referred to as gantry angle-indexed dose (GAID) variation. The GAID variation can be added to the beam model or modify the computed dose. As discussed above, the present inventors have recognized that the cryogen amount in the path of a beam passing through a cryostat of a radiotherapy system can be non-uniform and vary with gantry angles, at least partially due to cryostat inhomogeneities and/or variations in cryogen level. The resulting dose calculation can also vary at different gantry angles. The software programs <NUM> may include a software program that, when executed by a machine, causes the machine to generate GAID variation, such as in a form of a matrix of radiation doses at different gantry angles. The GAID variation may be represented textually or graphically. Depending on how the GAID variation is measured (e.g., the number and distribution of spatial locations where the doses are measured at different gantry angles), the GAID variation can be represented by a dose array (for a single point in the radiation field), a dose profile (for multiple point along a line of interest in the radiation field), or a dose map (for multiple points across a surface of interest in the radiation field), at different gantry angles, examples of which are discussed below with reference to <FIG>.

The GAID variation, once generated, can be stored in the memory <NUM>, the database <NUM>, or the hospital database <NUM>. The treatment planning software in the software programs <NUM> may generate a treatment plan using a beam model and the generated GAID variation. In an example, the treatment planning software may use the generated GAID variation to modify a calculated radiation dose for a patient, and the beam model can generate a treatment plan using the modified radiation dose. In an example, the treatment planning software may use a machine learning method (e.g., a convoluted neural network, or a recurrent neural network, among other deep learning algorithms) to determine a treatment plan, based on the GAID variation, among other information.

In addition to the memory <NUM> storing the software programs <NUM>, it is contemplated that software programs <NUM> may be stored on a removable computer medium, such as a hard drive, a computer disk, a CD-ROM, a DVD, a HD. a Blu-Ray DVD, USB flash drive, a SD card, a memory stick, or any other suitable medium; and the software programs <NUM> when downloaded to data processing device <NUM> may be executed by data processor <NUM>.

The data processor <NUM> may be communicatively coupled to the memory <NUM>, and the processor <NUM> may be configured to execute computer executable instructions stored therein. The processor <NUM> may send or receive medical images <NUM> to the memory <NUM> For example, the processor <NUM> may receive medical images <NUM> from the image acquisition device <NUM> via the communication interface <NUM> and network <NUM> to be stored in memory <NUM>. The processor <NUM> may also send medical images <NUM> stored in memory <NUM> via the communication interface <NUM> to the network <NUM> be stored in the database <NUM> or the hospital database <NUM>.

The data processor <NUM> may utilize software programs <NUM> (e.g. a treatment planning software), along with the medical images <NUM> and patient data <NUM>. to create the radiation therapy treatment plan <NUM>. Medical images <NUM> may include information such as imaging data associated with a patient anatomical region, organ, or volume of interest segmentation data. Patient data <NUM> may include information such as (<NUM>) functional organ modeling data (e.g.. serial versus parallel organs, appropriate dose response models, etc. ); (<NUM>) radiation dosage data (e.g., DVH information): or (<NUM>) other clinical information about the patient and treatment (e.g., other surgeries, chemotherapy, previous radiotherapy, etc.).

In an example, the data processor <NUM> includes a dose engine that can be used to determine the GAID variation, e g. dose metrics or dose statistics at each of a plurality of gantry angles. Various algorithms may be used to calculate the dose. In an example, the dose engine may use Monte Carlo algorithm (implemented as a software package stored in the software programs <NUM>) to calculate the dose metrics or dose statistics. The processor <NUM> can execute the treatment planning software to modulate or update the beam model stored in the software programs <NUM> using the GAID variation or cryostat variation <NUM>. The modulated or updated beam model can later be used to create a radiation therapy treatment plan <NUM> for a patient, such as by the processor <NUM> executing the treatment planning software.

In some examples, the processor <NUM> may utilize software programs <NUM> to generate intermediate data such as updated parameters to be used, for example, by a machine learning model, such as a neural network model; or generate intermediate 2D or 3D images, which may then subsequently be stored in memory <NUM>. The processor <NUM> may subsequently then transmit the executable radiation therapy treatment plan <NUM> via the communication interface <NUM> to the network <NUM> to the radiation therapy device <NUM>. where the radiation therapy plan will be used to treat a patient with radiation In addition, the processor <NUM> may execute software programs <NUM> to implement functions such as image conversion, image segmentation, deep learning, neural networks, and artificial intelligence. For instance, the processor <NUM> may execute software programs <NUM> that train or contour a medical image; such software programs <NUM> when executed may train a boundary detector or utilize a shape dictionary.

The processor <NUM> may be a processing device, include one or more general-purpose processing devices such as a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), or the like. More particularly, the processor <NUM> may be a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction Word (VLIW) microprocessor, a processor implementing other instruction sets, or processors implementing a combination of instruction sets. The processor <NUM> may also be implemented by one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), a System on a Chip (SoC), or the like As would be appreciated by those skilled in the art, in some embodiments, the processor <NUM> may be a special-purpose processor, rather than a general-purpose processor. The processor <NUM> may include one or more known processing devices, such as a microprocessor from the Pentium™, Core™, Xeon™, or Itanium® family manufactured by Intel™, the Turion™, Athlon™, Sempron™, Opteron™, FX™, Phenom™ family manufactured by AMD™, or any of various processors manufactured by Sun Microsystems The processor <NUM> may also include graphical processing units such as a GPU from the GeForce®, Quadro®, Tesla® family manufactured by Nvidia™, GMA. Iris™ family manufactured by Intel™, or the Radeon™ family manufactured by AMD™. The processor <NUM> may also include accelerated processing units such as the Xeon Phi™ family manufactured by Intel™. The disclosed embodiments are not limited to any type of processor(s) otherwise configured to meet the computing demands of analyzing, maintaining, generating, and/or providing large amounts of data or manipulating such data to perform the methods disclosed herein. In addition, the term "processor" may include more than one processor (for example, a multi-core design or a plurality of processors each having a multi-core design). The processor <NUM> can execute sequences of computer program instructions, stored in memory <NUM>, to perform various operations, processes, methods that will be explained in greater detail below.

The memory device <NUM> can store medical images <NUM>. In some embodiments, the medical images <NUM> may include one or more MR images (e. g , 2D MRI. 3D MRI, 2D streaming MRI, four-dimensional (4D) MRI, 4D volumetric MRI, 4D cine MRI, etc.). functional MR images (e.g., fMRI, DCE-MRI, diffusion MRI), CT images (e.g., 2D CT, cone beam CT, 3D CT, 4D CT), ultrasound images (e.g., 2D ultrasound, 3D ultrasound. 4D ultrasound), one or more projection images representing views of an anatomy depicted in the MRI, synthetic CT (pseudo-CT), and/or CT images at different angles of a gantry relative to a patient axis, PET images, X-ray images, fluoroscopic images, radiotherapy portal images, SPECT images, computer generated synthetic images (e.g., pseudo-CT images), aperture images, graphical aperture image representations of MLC leaf positions at different gantry angles, and the like. Further, the medical images <NUM> may also include medical image data, for instance, training images, and ground truth images, contoured images, and dose images. In an embodiment, the medical images <NUM> may be received from the image acquisition device <NUM>. Accordingly, image acquisition device <NUM> may include an MRI imaging device, a CT imaging device, a PET imaging device, an ultrasound imaging device, a fluoroscopic device, a SPECT imaging device, an integrated linac and MRI imaging device, or other medical imaging devices for obtaining the medical images of the patient. The medical images <NUM> may be received and stored in any type of data or any type of format that the data processing device <NUM> may use to perform operations consistent with the disclosed embodiments.

The memory device <NUM> may be a non-transitory computer-readable medium, such as a read-only memory (ROM), a phase-change random access memory (PRAM), a static random access memory (SRAM), a flash memory, a random access memory (RAM), a dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM), an electrically erasable programmable read-only memory (EEPROM), a static memory (e.g., flash memory, flash disk, static random access memory) as well as other types of random access memories, a cache, a register, a CD-ROM, a DVD or other optical storage, a cassette tape, other magnetic storage device, or any other non-transitory medium that may be used to store information including image, data, or computer executable instructions (e.g., stored in any format) capable of being accessed by the processor <NUM>, or any other type of computer device The computer program instructions can be accessed by the processor <NUM>, read from the ROM, or any other suitable memory location, and loaded into the RAM for execution by the processor <NUM>. For example, the memory <NUM> may store one or more software applications. Software applications stored in the memory <NUM> may include, for example, an operating system <NUM> for common computer systems as well as for software-controlled devices. Further, the memory <NUM> may store an entire software application, or only a part of a software application, that are executable by the processor For example, the memory device <NUM> may store one or more radiation therapy treatment plans <NUM>.

The data processing device <NUM> can communicate with the network <NUM> via the communication interface <NUM>, which can be communicatively coupled to the processor <NUM> and the memory <NUM>. The communication interface <NUM> may provide communication connections between the data processing device <NUM> and radiotherapy system <NUM> components (e.g.. permitting the exchange of data with external devices). For instance, the communication interface <NUM> may in some embodiments have appropriate interfacing circuitry to connect to the user interface <NUM>, which may be a hardware keyboard, a keypad, or a touch screen through which a user may input information into radiotherapy system <NUM>.

Communication interface <NUM> may include, for example, a network adaptor, a cable connector, a serial connector, a USB connector, a parallel connector, a high-speed data transmission adaptor (e.g.. such as fiber, USB <NUM>, thunderbolt, and the like), a wireless network adaptor (e.g., such as a WiFi adaptor), a telecommunication adaptor (e. g , <NUM>, <NUM>/LTE and the like), and the like. Communication interface <NUM> may include one or more digital and/or analog communication devices that permit data processing device <NUM> to communicate with other machines and devices, such as remotely located components, via the network <NUM>.

The network <NUM> may provide the functionality of a local area network (LAN), a wireless network, a cloud computing environment (e.g., software as a service, platform as a service, infrastructure as a service, etc.), a client-server, a wide area network (WAN), and the like. For example, network <NUM> may be a LAN or a WAN that may include other systems S1 (<NUM>), S2 (<NUM>), and S3 (<NUM>). Systems S1, S2, and S3 may be identical to data processing device <NUM> or may be different systems. In some embodiments, one or more of systems in network <NUM> may form a distributed computing simulation environment that collaboratively performs the embodiments described herein In some embodiments, one or more systems S1, S2, and S3 may include a CT scanner that obtains CT images (e.g., medical images <NUM>). In addition, network <NUM> may be connected to Internet <NUM> to communicate with servers and clients that reside remotely on the internet.

Therefore, network <NUM> can allow data transmission between the data processing device <NUM> and a number of various other systems and devices, such as the OIS <NUM>, the radiation therapy device <NUM>, and the image acquisition device <NUM>. Further, data generated by the OIS <NUM> and/or the image acquisition device <NUM> may be stored in the memory <NUM>, the database <NUM>, and/or the hospital database <NUM>. The data may be transmitted/received via network <NUM>. through communication interface <NUM> in order to be accessed by the processor <NUM>, as required.

The data processing device <NUM> may communicate with database <NUM> through network <NUM> to send/receive a plurality of various types of data stored on database <NUM>. For example, the database <NUM> may store machine data associated with a radiation therapy device <NUM>. image acquisition device <NUM>, or other machines relevant to radiotherapy. The machine data information may include control points, such as radiation beam size, arc placement, beam on and off time duration, machine parameters, segments, MLC configuration, gantry speed, MRI pulse sequence, and the like. The database <NUM> may be a storage device and may be equipped with appropriate database administration software programs One skilled in the art would appreciate that database <NUM> may include a plurality of devices located either in a central or a distributed manner.

In some embodiments, the database <NUM> may include a processor-readable storage medium (not shown). While the processor-readable storage medium in an embodiment may be a single medium, the term "processor-readable storage medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of computer executable instructions or data. The term "processor-readable storage medium" shall also be taken to include any medium that is capable of storing or encoding a set of instructions for execution by a processor and that cause the processor to perform any one or more of the methodologies of the present disclosure. The term "processor readable storage medium" shall accordingly be taken to include, but not be limited to, solid-state memories, optical and magnetic media. For example, the processor readable storage medium can be one or more volatile, non-transitory, or non-volatile tangible computer-readable media.

The data processor <NUM> may communicate with the database <NUM> to read images into the memory <NUM>, or store images from the memory <NUM> to the database <NUM>. For example, the database <NUM> may be configured to store a plurality of images (e.g.. 3D MRI, 4D MRI, 2D MRI slice images, CT images, 2D Fluoroscopy images, X-ray images, raw data from MR scans or CT scans, Digital Imaging and Communications in Medicine (DICOM) data, projection images, graphical aperture images, etc.) that the database <NUM> received from image acquisition device <NUM>. Database <NUM> may store data to be used by the data processor <NUM> when executing software program <NUM>, or when creating radiation therapy treatment plans <NUM>. Database <NUM> may store the data produced by the trained machine learning model, such as a neural network including the network parameters constituting the model learned by the network and the resulting predicted data. The data processing device <NUM> may receive the imaging data, such as a medical image <NUM> (e. g, 2D MRI slice images, CT images, 2D Fluoroscopy images. X-ray images, 3DMR images. 4D MR images, projection images, graphical aperture images, etc.) either from the database <NUM>. the radiation therapy device <NUM> (e.g., an MR-linac), and or the image acquisition device <NUM> to generate a treatment plan <NUM>.

In an embodiment, the radiotherapy system <NUM> can include an image acquisition device <NUM> that can acquire medical images (e.g., MR images. 3D MRI, 2D streaming MRI, 4D volumetric MRI, CT images, cone-Beam CT, PET images, functional MR images (e.g., fMRI, DCE-MRI and diffusion MRI), X-ray images, fluoroscopic image, ultrasound images, radiotherapy portal images, SPECT images, and the like) of the patient. Image acquisition device <NUM> may, for example, be an MRI imaging device, a CT imaging device, a PET imaging device, an ultrasound device, a fluoroscopic device, a SPECT imaging device, or any other suitable medical imaging device for obtaining one or more medical images of the patient. Images acquired by the image acquisition device <NUM> can be stored within database <NUM> as either imaging data and/or test data. By way of example, the images acquired by the image acquisition device <NUM> can be also stored by the data processing device <NUM>, as medical image <NUM> in memory <NUM>.

In an embodiment, for example, the image acquisition device <NUM> may be integrated with the radiation therapy device <NUM> as a single apparatus. For example, a MR imaging device can be combined with a linear accelerator to form a system referred to as an "MR-linac. " Such an MR-linac can be used, for example, to determine a location of a target organ or a target tumor in the patient, so as to direct radiation therapy accurately according to the radiation therapy treatment plan <NUM> to a predetermined target.

The image acquisition device <NUM> can be configured to acquire one or more images of the patient's anatomy for a region of interest (e.g.. a target organ, a target tumor, or both). Each image, typically a 2D image or slice, can include one or more parameters (e.g., a 2D slice thickness, an orientation, and a location, etc.). In an embodiment, the image acquisition device <NUM> can acquire a 2D slice in any orientation. For example, an orientation of the 2D slice can include a sagittal orientation, a coronal orientation, or an axial orientation The processor <NUM> can adjust one or more parameters, such as the thickness and/or orientation of the 2D slice, to include the target organ and/or target tumor. In an embodiment, 2D slices can be determined from information such as a 3D MRI volume. Such 2D slices can be acquired by the image acquisition device <NUM> in "real-time" while a patient is undergoing radiation therapy treatment, for example, when using the radiation therapy device <NUM>, with "real-time" meaning acquiring the data in at least milliseconds or less.

The data processing device <NUM> may generate and store radiation therapy treatment plans <NUM> for one or more patients. The radiation therapy treatment plans <NUM> may provide information about a particular radiation dose to be applied to each patient. The radiation therapy treatment plans <NUM> may also include other radiotherapy information, such as control points including beam angles, gantry angles, beam intensity, dose-histogram-volume information, number of radiation beams to be used during therapy, dose per beam, and the like.

The data processor <NUM> may generate the radiation therapy treatment plan <NUM> by using software programs <NUM> such as treatment planning software (e.g., Monaco®, manufactured by Elekta AB of Sweden). In order to generate the radiation therapy treatment plans <NUM>. the data processor <NUM> may communicate with the image acquisition device <NUM> (e.g., a CT device, an MRI device, a PET device, an X-ray device, an ultrasound device, etc.) to access images of the patient and to delineate a target, such as a tumor. In some embodiments, the delineation of one or more OARs, such as healthy tissue surrounding the tumor or in close proximity to the tumor may be required. Therefore, segmentation of the OAR may be performed when the OAR is close to the target tumor. In addition, if the target tumor is close to the OAR (e.g., prostate in near proximity to the bladder and rectum), then by segmenting the OAR from the tumor, the radiotherapy system <NUM> may study the dose distribution not only in the target but also in the OAR.

In order to delineate a target organ or a target tumor from the OAR, medical images, such as MR images, CT images. PET images, fMR images, X-ray images, ultrasound images, radiotherapy portal images, SPECT images, and the like, of the patient undergoing radiotherapy may be obtained non-invasively by the image acquisition device <NUM> to reveal the internal structure of a body part. Based on the information from the medical images, a 3D structure of the relevant anatomical portion may be obtained In addition, during a treatment planning process, many parameters may be taken into consideration to achieve a balance between efficient treatment of the target tumor (e.g., such that the target tumor receives enough radiation dose for an effective therapy) and low irradiation of the OAR(s) (e.g., the OAR(s) receives as low a radiation dose as possible). Other parameters that may be considered include the location of the target organ and the target tumor, the location of the OAR, and the movement of the target in relation to the OAR. For example, the 3D structure may be obtained by contouring the target or contouring the OAR within each 2D layer or slice of an MRI or CT image and combining the contour of each 2D layer or slice. The contour may be generated manually (e.g., by a physician, dosimetrist, or health care worker using a program such as Monaco® manufactured by Elekta AB of Stockholm, Sweden) or automatically (e.g.. using a program such as the Atlas-based auto-segmentation software. ABAS™, manufactured by Elekta AB of Stockholm, Sweden). In certain embodiments, the 3D structure of a target tumor or an OAR may be generated automatically by the treatment planning software.

After the target tumor and the OAR(s) have been located and delineated, a dosimetrist, physician, or healthcare worker may determine a dose of radiation to be applied to the target tumor, as well as any maximum amounts of dose that may be received by the OAR proximate to the tumor (e.g., left and right parotid, optic nerves, eyes, lens, inner ears, spinal cord, brain stem, and the like). After the radiation dose is determined for each anatomical structure (e.g., target tumor. OAR), a process known as inverse planning may be performed to determine one or more treatment plan parameters that would achieve the desired radiation dose distribution Examples of treatment plan parameters include volume delineation parameters (e.g., which define target volumes, contour sensitive structures, etc.), margins around the target tumor and OARs, beam angle selection, collimator settings, and beam-on times During the inverse-planning process, the physician may define dose constraint parameters that set bounds on how much radiation an OAR may receive (e.g., defining full dose to the tumor target and zero dose to any OAR; defining <NUM>% of dose to the target tumor: defining that the spinal cord, brain stem, and optic structures receive ≤ 45Gy, ≤ 55Gy and < 54Gy, respectively). The result of inverse planning may constitute a radiation therapy treatment plan <NUM> that may be stored in memory <NUM> or database <NUM>. Some of these treatment parameters may be correlated. For example, tuning one parameter (e.g., weights for different objectives, such as increasing the dose to the target tumor) in an attempt to change the treatment plan may affect at least one other parameter, which in turn may result in the development of a different treatment plan. Thus, the data processing device <NUM> can generate a tailored radiation therapy treatment plan <NUM> having these parameters in order for the radiation therapy device <NUM> to provide radiotherapy treatment to the patient.

In addition, the radiotherapy system <NUM> may include a display device <NUM> and a user interface <NUM>. The display device <NUM> may include one or more display screens that display medical images, interface information, treatment planning parameters (e.g., projection images, graphical aperture images, contours, dosages, beam angles, etc) treatment plans, a target, localizing a target and/or tracking a target, or any related information to the user The user interface <NUM> may be a keyboard, a keypad, a touch screen or any type of device that a user may input information to radiotherapy system <NUM>. Alternatively, the display device <NUM> and the user interface <NUM> may be integrated into a device such as a tablet computer (e. g , Apple iPad®, Lenovo Thinkpad®, Samsung Galaxy ®, etc.).

Furthermore, any and all components of the radiotherapy system <NUM> may be implemented as a virtual machine (e.g., VMWare, Hyper-V, and the like). For instance, a virtual machine can be software that functions as hardware. Therefore, a virtual machine can include at least one or more virtual processors, one or more virtual memories, and one or more virtual communication interfaces that together function as hardware. For example, the data processing device <NUM>, the OIS <NUM>, the image acquisition device <NUM> could be implemented as a virtual machine. Given the processing power, memory, and computational capability available, the entire radiotherapy system <NUM> could be implemented as a virtual machine.

<FIG> illustrates an exemplary radiation therapy device <NUM> that may include a radiation source (e.g., an X-ray source or a linac), a couch <NUM>, an imaging detector <NUM>. and a radiation therapy output <NUM>. The radiation therapy device <NUM> may be configured to emit a radiation beam <NUM> to provide therapy to a patient. The radiation therapy output <NUM> can include one or more attenuators or collimators, such as an MLC. A patient can be positioned in a region <NUM> and supported by the couch <NUM> to receive a radiation therapy dose, according to a radiation therapy treatment plan The radiation therapy output <NUM> can be mounted or attached to a gantry <NUM> or other mechanical support. One or more chassis motors (not shown) may rotate the gantry <NUM> and the radiation therapy output <NUM> around the couch <NUM> when the couch <NUM> is inserted into the treatment area. In an embodiment, the gantry <NUM> may be continuously rotatable around the couch <NUM> when the couch <NUM> is inserted into the treatment area. In another embodiment, the gantry <NUM> may rotate to a predetermined position when the couch <NUM> is inserted into the treatment area. For example, the gantry <NUM> can be configured to rotate the therapy output <NUM> around an axis ("A"). Both the couch <NUM> and the radiation therapy output <NUM> can be independently moveable to other positions around the patient, such as moveable in transverse direction ("T"), moveable in a lateral direction ("L"), or as rotation about one or more other axes, such as rotation about a transverse axis (indicated as "R"). A controller communicatively connected to one or more actuators (not shown) may control the couch <NUM> movements or rotations in order to properly position the patient in or out of the radiation beam <NUM> according to a radiation therapy treatment plan. Both the couch <NUM> and the gantry <NUM> are independently moveable from one another in multiple degrees of freedom, which allows the patient to be positioned such that the radiation beam <NUM> can target the tumor. The MLC may be integrated with the gantry <NUM> to deliver the radiation beam <NUM> of a certain shape.

The coordinate system (including axes A, T, and L) shown in <FIG> can have an origin located at an isocenter <NUM>. The isocenter can be defined as a location where the central axis of the radiation beam <NUM> intersects the origin of a coordinate axis, such as to deliver a prescribed radiation dose to a location on or within a patient. Alternatively, the isocenter <NUM> can be defined as a location where the central axis of the radiation beam <NUM> intersects the patient for various rotational positions of the radiation therapy output <NUM> as positioned by the gantry <NUM> around the axis A. As discussed herein, the gantry angle corresponds to the position of gantry <NUM> relative to axis A, although any other axis or combination of axes can be referenced and used to determine the gantry angle.

The gantry <NUM> may have an attached imaging detector <NUM> that is preferably opposite the radiation therapy output <NUM>. In an embodiment, the imaging detector <NUM> can be located within a field of the therapy beam <NUM>. The imaging detector <NUM> can maintain alignment with the therapy beam <NUM>. The imaging detector <NUM> can rotate about the rotational axis as the gantry <NUM> rotates. In an embodiment, the imaging detector <NUM> can be a flat panel detector (e.g., a direct detector or a scintillator detector). In this manner, the imaging detector <NUM> can be used to monitor the therapy beam <NUM> or the imaging detector <NUM> can be used for imaging the patient's anatomy, such as portal imaging. The control circuitry of radiotherapy device <NUM> may be integrated within system <NUM> or remote from it.

In an illustrative embodiment, one or more of the couch <NUM>. the therapy output <NUM>, or the gantry <NUM> can be automatically positioned, and the therapy output <NUM> can establish the therapy beam <NUM> according to a specified dose for a particular therapy delivery instance. A sequence of therapy deliveries can be specified according to a radiation therapy treatment plan, such as using one or more different orientations or locations of the gantry <NUM>, the couch <NUM>, or the therapy output <NUM>. The therapy deliveries can occur sequentially, but can intersect in a desired therapy locus on or within the patient, such as at the isocenter <NUM>. A prescribed dose of radiation therapy can thereby be delivered to the therapy locus while damage to tissue near the therapy locus can be reduced or avoided.

<FIG> illustrates an exemplary radiotherapy system <NUM> that combines a radiation system (e. g, a linac) and a CT imaging system. The radiation therapy device <NUM> can include an MLC (not shown). The CT imaging system can include an imaging X-ray source <NUM>, such as providing X-ray energy in a kiloelectron-Volt (keV) energy range. The imaging X-ray source <NUM> can provide a fan-shaped and/or a conical beam <NUM> directed to an imaging detector <NUM>, such as a flat panel detector. The radiation therapy device <NUM> can be similar to the system described in relation to <FIG>, such as including a radiation therapy output <NUM>, a gantry <NUM>, a couch <NUM>, and another imaging detector <NUM> (such as a flat panel detector). The X-ray source <NUM> can provide a comparatively-lower-energy X-ray diagnostic beam, for imaging.

As illustrated in <FIG>, the radiation therapy output <NUM> and the X-ray source <NUM> can be mounted on the same rotating gantry <NUM>, rotationally-separated from each other by <NUM> degrees. In some examples, two or more X-ray sources can be mounted along the circumference of the gantry <NUM>, such that each has its own detector arrangement to provide multiple angles of diagnostic imaging concurrently. Similarly, multiple radiation therapy outputs <NUM> can be provided.

<FIG> illustrates an exemplary radiotherapy system <NUM> that combines a radiation system (e g. , a linac) and a MR imaging system, also referred to as an MR-linac system. The system <NUM> may include a couch <NUM>, an image acquisition device <NUM>. and a radiation delivery device <NUM>. The system <NUM> can deliver radiation therapy to a patient in accordance with a radiotherapy treatment plan, such as the treatment plan <NUM> created and stored in the memory <NUM>. In some embodiments, the image acquisition device <NUM> may correspond to the image acquisition device <NUM> in <FIG> that may acquire images of a first modality (e.g., an MRI image) or destination images of a second modality (e.g., an CT image).

The couch <NUM> may support a patient during a treatment session. In some implementations, the couch <NUM> may move along a horizontal translation axis (labelled "I"), such that the couch <NUM> can move the patient resting on the couch <NUM> into and/or out of the system <NUM>. The couch <NUM> may also rotate around a central vertical axis of rotation, transverse to the translation axis To allow such movement or rotation, the couch <NUM> may have motors (not shown) enabling the couch to move in various directions and to rotate along various axes. A controller (not shown) may control these movements or rotations in order to properly position the patient according to a treatment plan.

In some embodiments, the image acquisition device <NUM> may include an MRI machine used to acquire 2D or 3D MR images of the patient before, during, and/or after a treatment session The image acquisition device <NUM> may include a magnet <NUM> for generating a primary magnetic field for magnetic resonance imaging. The magnetic field lines generated by operation of the magnet <NUM> may run substantially parallel to the central translation axis "I". The magnet <NUM> may include one or more coils with an axis that runs parallel to the translation axis "I". In some embodiments, the one or more coils in magnet <NUM> may be spaced such that a central window <NUM> of magnet <NUM> is free of coils. In other embodiments, the coils in magnet <NUM> may be thin enough or of a reduced density such that they are substantially transparent to radiation of the wavelength generated by radiotherapy device <NUM>. In some embodiments, the image acquisition device <NUM> may also include one or more shielding coils, which may generate a magnetic field outside the magnet <NUM> of approximately equal magnitude and opposite polarity in order to cancel or reduce any magnetic field outside of the magnet <NUM>. As described below, a radiation source <NUM> of radiotherapy device <NUM> may be positioned in the region where the magnetic field is cancelled, at least to a first order, or reduced.

The image acquisition device <NUM> may also include two gradient coils <NUM> and <NUM>, which may generate a gradient magnetic field that is superposed on the primary magnetic field. The coils <NUM> and <NUM> may generate a gradient in the resultant magnetic field that allows spatial encoding of the protons so that their position can be determined. The gradient coils <NUM> and <NUM> may be positioned around a common central axis with the magnet <NUM> and may be displaced along that central axis. The displacement may create a gap, or window, between the coils <NUM> and <NUM>. In embodiments where the magnet <NUM> includes a central window <NUM> between the coils, the two windows may be aligned with each other.

The gantry of the radiation therapy system (e.g., the gantry <NUM>), along with the attached beam generating components, can be positioned around a cryostat <NUM>. In an example, the linac can rotate circumferentially about the imaging system and deliver a beam through the cryostat <NUM>. The cryostat <NUM> can support and position the magnet <NUM><NUM> with precision, and reduce the thermal heat loads applied to the magnet <NUM> and the coils thereof (e g. , the coils <NUM> and <NUM>). The cryostat <NUM> consists of shells present in the central window <NUM>. These shells have cylindrical rotational symmetry around the longitudinal axis ("I-I" axis as shown). In an example, at least some shells can be metallic sheets made of various metals or alloys. In another example, at least some shells can be made of fiber glass or dry air. One of the shells can be cryogen (e.g., liquid helium). The cryogen (e.g., liquid helium) and keep the magnet coils <NUM> and <NUM> at a low temperature, such that a desired superconducting state can be achieved. If the cryogen level drops, then a vertical "AP" beam (gantry angle of <NUM>) can pass through less cryogen than a similar beam at a non-zero gantry angle. This breaks the symmetry of the cryostat Beams at gantry values around zero are affected The symmetry of the cryostat model is also broken by imperfections (thickness variations) in the metallic sheets that are used to build the cryostat, welds, and possibly alignment imperfections. Such effects could affect beams at any gantry angle, resulting in GAID variation The software programs <NUM>, when used together with a radiation therapy system such as the system <NUM>, may generate cryostat variation represented by a plurality of gantry-angle indexed radiation doses, and use the generated cryostat variation in radiotherapy planning.

In some embodiments, the image acquisition device <NUM> may be an imaging device other than an MRI, such as an X-ray, a CT, a CBCT, a spiral CT, a PET, a SPECT, an optical tomography, a fluorescence imaging, ultrasound imaging, radiotherapy portal imaging device, or the like. As would be recognized by one of ordinary skill in the art, the above description of image acquisition device <NUM> concerns certain embodiments and is not intended to be limiting.

The radiotherapy device <NUM> may include the radiation source <NUM> (e.g.. an X-ray source or a linac) and a collimator such as an MLC <NUM> A collimator is a beam-limiting device that can help to shape the beam of radiation emerging from the machine and can limit the maximum field size of a beam The MLC <NUM> can be used for shaping, directing, or modulating an intensity of a radiation therapy beam to the specified target locus within the patient. The radiotherapy device <NUM> may be mounted on a chassis <NUM>. One or more chassis motors (not shown) may rotate chassis <NUM> around the couch <NUM> when the couch <NUM> is inserted into the treatment area. In an embodiment, chassis <NUM> may be continuously rotatable around the couch <NUM>, when the couch <NUM> is inserted into the treatment area. The chassis <NUM> may also have an attached radiation detector (not shown), preferably located opposite to radiation source <NUM> and with the rotational axis of chassis <NUM> positioned between radiation source <NUM> and the detector. Further, device <NUM> may include control circuitry (not shown) used to control, for example, one or more of the couch <NUM>, image acquisition device <NUM>. and radiotherapy device <NUM>. The control circuitry of radiotherapy device <NUM> may be integrated within system <NUM> or remote from it.

During a radiotherapy treatment session, a patient may be positioned on the couch <NUM>. System <NUM> may then move the couch <NUM> into the treatment area defined by magnetic <NUM> and coils <NUM>, <NUM>. and chassis <NUM>. Control circuitry may then control the radiation source <NUM>, MLC <NUM>, and the chassis motor(s) to deliver radiation to the patient through the window between coils <NUM> and <NUM> according to a radiotherapy treatment plan.

The radiation therapy output configurations illustrated in <FIG> and <FIG>, such as the configurations where a radiation therapy output can be rotated around a central axis (e.g., an axis "A"), are for the purpose of illustration and not limitation. Other radiation therapy output configurations can be used. For example, a radiation therapy output can be mounted to a robotic arm or manipulator having multiple degrees of freedom. In yet another embodiment, the therapy output can be fixed, such as located in a region laterally separated from the patient, and a platform supporting the patient can be used to align a radiation therapy isocenter with a specified target locus within the patient.

<FIG> illustrate an exemplary test setup for measuring a gantry angle-indexed dose (GAID) variation. The GAID variation represents a correspondence between a plurality of gantry angles and the corresponding radiation dose measurements. The GAID variation can be presented in a form of a two-dimensional data array or a matrix. The GAID variation can be used to generate a treatment plan, such as by the processor <NUM>. In an example, the GAID variation can be used to modify a dose calculation generated by a dose engine, and a beam model can be applied to the modified dose calculation to generate a radiation treatment plan. By way of example, <FIG> illustrates dose measurement at a first gantry angle θ1 of approximately zero, and <FIG> illustrates dose measurement at a second gantry angle θ2 different than θ1, such as approximately <NUM> degrees in an example. A radiotherapy machine <NUM>, such as a linac machine, can generate and deliver a constant radiation beam <NUM> along a central axis of the beam. The beam can be delivered at a specific gantry angle, as indicated by a gantry angle indicator <NUM>. The radiation beam can be delivered to a phantom, such as water phantom <NUM> in a water tank positioned on the couch <NUM>. perpendicular to the central axis of the beam at zero gantry angle. A dose detector <NUM> can be positioned at a pre-determined location, such as at a specific depth from the surface of a water phantom <NUM>. When the gantry angle is changed to θ2, as illustrated in <FIG>, the central axis of the radiation beam <NUM> is no longer perpendicular to the surface of the water phantom <NUM>.

The dose detector <NUM> can include an ionization chamber, such as a Farmer chamber, which can be used for absolute dosimetry in high-energy photon, electron and proton beams A gas-filled ionization chamber has circuitry to measure charge from the number of ion pairs created within a gas caused by incident radiation A voltage potential is applied between an anode electrode and a cathode electrode inside the gas-filled chamber to create an electric field. When gas between the electrodes is ionized by incident ionizing radiation, ion-pairs are created and the resultant positive ions and dissociated electrons move to the electrodes of the opposite polarity under the influence of the electric field. The resulting ionization current can then be measured by an electrometer circuit. Each ion pair deposits or removes a small electric charge to or from an electrode, such that the accumulated charge is proportional to the number of ion pairs created, and hence the radiation dose. This continual generation of charge produces an ionization current, which is a measure of the total ionizing dose entering the chamber.

The dose detector <NUM> can measure radiation dose at different gantry angles when the radiation beam is delivered at different gantry angles between <NUM> and <NUM> degrees, or within a range between <NUM> and <NUM> degrees. In an example, the plurality of gantry angles can be uniformly sampled at a specific step size, such as every one degree, every <NUM> degrees, or every <NUM> degrees. A dose engine, which can be a part of the data processor <NUM>, can calculate one or more dose metrics or dose statistics using a dose calculation algorithm, such as Monte Carlo algorithm. Examples of the dose measurement can include a maximum dose, a minimum dose, a dose range, a coverage region (e.g., contour of coverage), a 3D dose distribution, a dose volume histogram (DVH), or an overlap volume histogram (OVH), among others. Other dose metrics or statistics can include percent depth dose (PDD) or percentile radial dose (PRD), among other scatter data.

In an example, point measurements of a dose metric can be made. The point measurement refer to measurement at a predetermined location in the phantom. The resultant GAID variation can be represented as the dose metric values of a particular point that vary with gantry angles. In another example, profile measurements of a dose metric can be made at each of a plurality of gantry angles. The dose measurements are performed in multiple points along a line of interest. A detector can detect radiation dose at consecutive points along the line of interest. Alternatively, an array with multiple detectors (e.g., arrange linearly along the line of interest) may be used to simultaneously measure radiation doses at different locations along the line of interest. The resultant GAID variation can be represented by a dose profile including calculated doses at all the testing points along the line of interest that vary with gantry angles. In yet another example, image measurements of a dose metric can be made at each of a plurality of gantry angles. An image measurement refers to a planar dose measured at a specified planar surface, or a cylindrical surface, in a water phantom. In an example, the doses are multiple locations on the specified surface (with a specified spatial resolution) can be tested sequentially or concurrently. The resultant GAID variation can be represented as a dose map including dose values of all the testing points across the plane or surface of interest that vary with gantry angles.

The dose metric measurements (obtained from point measurements, profile measurements, or 2D image measurements) can be converted to a relative dose metrics by normalizing the dose metric values at a particular gantry value to the corresponding dose metric value at a reference gantry value. In an example, the relative dose metric value at a particular gantry angle can be expressed as a percentage of the dose metric value at the reference gantry value.

<FIG> is a flowchart illustrating an exemplary method <NUM> of generating a treatment plan using a beam model and gantry angle-indexed dose (GAID) variation. The method <NUM> may be embodied in computer-readable instructions for execution by one or more processors such that the operations of the method <NUM> may be performed in part or in whole by the functional components of the data processing device <NUM>; accordingly, the method <NUM> is described below by way of example with reference thereto. However, in other embodiments, at least some of the operations of the method <NUM> may be deployed on various other hardware configurations The method <NUM> is therefore not intended to be limited to the data processing device <NUM> and can be implemented in whole, or in part, by any other component. Some or all of the operations of method <NUM> can be in parallel, out of order, or entirely omitted.

At <NUM>, a beam model used by a radiation machine, such as the radiation therapy device <NUM> or <NUM>, can be provided to a radiation treatment planning system (TPS) in a radiotherapy system. The beam model can be a software package, such as one that is stored in the software programs <NUM> of the system <NUM>, and can compute machine parameters or control points for a given type of radiotherapy machine. The beam model can include a number of model parameters, such as a size of a radiation source, a position of a radiation source, or an energy spectrum of a radiation source, among other parameters.

a gantry angle-indexed dose (GAID) variation can be determined for the radiation machine that uses the beam model provided at step <NUM>. The GAID variation, also referred to as cryostat variation, represents variation of radiation doses at different gantry angles. The GAID variation can be attributed to, among other factors, non-uniform cryogen in the path of the beam in a cryostat of a radiotherapy system when the radiation beam is delivered at different angles. To determine GAID variation. in an example, a constant radiation beam can be delivered to a phantom (e.g.. water phantom) at different gantry angles between <NUM> and <NUM> degrees, or within a range between <NUM> and <NUM> degrees. In an example, the plurality of gantry angles can be uniformly sampled at a specific step size, such as every one degree, every <NUM> degrees, or every <NUM> degrees.

Doses at one or more locations in the phantom corresponding to each of the different gantry angles can then be calculated, such as using a dose detector. A dose engine can calculate one or more dose metrics or dose statistics. Various algorithms may be used to calculate the dose In an example, the dose engine may use Monte Carlo algorithm (implemented as a software package stored in the software programs <NUM>) to calculate the dose metrics or dose statistics. Examples of the dose metrics or statistics can include a percent depth dose profile. a radial dose profile. a dose-volume histogram, an overlap volume histogram or a three-dimensional dose distribution, among others.

The GAID variation can be measured for one or more point locations in the phantom. <FIG> illustrates and exemplary setup for determining the GAID variation. In an example. dose measurement can be performed at a predetermined point location in the phantom at each of the different gantry angles, and the GAID variation can be represented by a two-dimensional dose array. In another example, dose calculation can be performed at multiple point locations linearly arranged in the phantom at multiple different gantry angles, and the GAID variation can be represented by a dose profile. In yet another example, dose calculation can be performed at multiple point locations across a planar surface or cylindrical surface in the phantom at different gantry angles, and the GAID variation can be represented by a dose map.

At <NUM>, the GAID variation can be used to modify or correct a calculated dose for the patient. In an example. a cylindrical cryostat correction map can be created based on the GAID variation, and introduced in the beam model to modulate the influence of the incoming beams and thus account for GAID variation such as due to cryostat inhomogeneities and/or cryogen level variations. For a Monte Carlo based dose calculation algorithm. the incoming particle weights can be modified as they pass through the cryostat correction map, based on the correction value at the intersection point between the particle trajectory and the cryostat correction map.

At <NUM>, a radiation therapy treatment plan can be generated by applying a beam model to the modified dose. A radiation treatment can be delivered to the patient in accordance with the determined radiation treatment plan.

<FIG> illustrates a block diagram of an embodiment of a machine <NUM> on which one or more of the methods as discussed herein can be implemented. In one or more embodiments, one or more items of the data processing device <NUM> can be implemented by the machine <NUM>. In alternative embodiments. the machine <NUM> operates as a standalone device or may be connected (e.g., networked) to other machines. In one or more embodiments, the data processing device <NUM> can include one or more of the items of the machine <NUM>. In a networked deployment, the machine <NUM> may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB). a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term "machine" shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

The example machine <NUM> includes processing circuitry <NUM> (e.g., a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit, circuitry, such as one or more transistors, resistors, capacitors, inductors. diodes, logic gates, multiplexers, buffers, modulators, demodulators, radios (e.g., transmit or receive radios or transceivers), sensors <NUM> (e.g., a transducer that converts one form of energy (e.g., light, heat, electrical, mechanical, or other energy) to another form of energy), or the like, or a combination thereof), a main memory <NUM> and a static memory <NUM>, which communicate with each other via a bus <NUM>. The machine <NUM> (e.g., computer system) may further include a video display unit <NUM> (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The machine <NUM> also includes an alphanumeric input device <NUM> (e.g.. a keyboard), a user interface (UI) navigation device <NUM> (e.g., a mouse), a disk drive or mass storage unit <NUM>, a signal generation device <NUM> (e.g., a speaker) and a network interface device <NUM>.

The disk drive unit <NUM> includes a machine-readable medium <NUM> on which is stored one or more sets of instructions and data structures (e.g., software) <NUM> embodying or utilized by any one or more of the methodologies or functions described herein. The instructions <NUM> may also reside, completely or at least partially, within the main memory <NUM> and/or within the processor <NUM> during execution thereof by the machine <NUM>, the main memory <NUM> and the processor <NUM> also constituting machine-readable media.

The machine <NUM> as illustrated includes an output controller <NUM>. The output controller <NUM> manages data flow to/from the machine <NUM>. The output controller <NUM> is sometimes called a device controller, with software that directly interacts with the output controller <NUM> being called a device driver.

While the machine-readable medium <NUM> is shown in an embodiment to be a single medium, the term "machine-readable medium" may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more instructions or data structures. The term "machine-readable medium" shall also be taken to include any tangible medium that is capable of storing, encoding or carrying instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present invention, or that is capable of storing, encoding or carrying data structures utilized by or associated with such instructions. The term "machine-readable medium" shall accordingly be taken to include, but not be limited to, solid-state memories. and optical and magnetic media. Specific examples of machine-readable media include non-volatile memory, including by way of example semiconductor memory devices, e.g., Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.

The instructions <NUM> may further be transmitted or received over a communications network <NUM> using a transmission medium. The instructions <NUM> may be transmitted using the network interface device <NUM> and any one of a number of well-known transfer protocols (e.g., HTTP). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet mobile telephone networks, Plain Old Telephone (POTS) networks, and wireless data networks (e.g., WiFi and WiMax networks). The term "transmission medium" shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such software.

As used herein, "communicatively coupled between" means that the entities on either of the coupling must communicate through an item therebetween and that those entities cannot communicate with each other without communicating through the item.

In this document, the terms "a," "an," "the," and "said" are used when introducing elements of aspects of the disclosure or in the embodiments thereof, as is common in patent documents, to include one or more than one or more of the elements, independent of any other instances or usages of "at least one" or "one or more.

In the appended aspects, the terms "including" and "in which" are used as the plain-English equivalents of the respective terms "comprising" and "wherein. " Also, in the following aspects, the terms "comprising," "including," and "having" are intended to be open-ended to mean that there may be additional elements other than the listed elements, such that after such a term (e.g., comprising, including, having) in a aspect are still deemed to fall within the scope of that aspect. Moreover, in the following aspects, the terms "first," "second," and "third," and so forth, are used merely as labels, and are not intended to impose numerical requirements on their objects.

Embodiments of the disclosure may be implemented with computer-executable instructions. The computer-executable instructions (e.g., software code) may be organized into one or more computer-executable components or modules. Other embodiments of the disclosure may include different computer-executable instructions or components having more or less functionality than illustrated and described herein.

Method examples (e.g., operations and functions) described herein can be machine or computer-implemented at least in part (e.g., implemented as software code or instructions). An implementation of such methods can include software code, such as microcode, assembly language code, a higher-level language code, or the like (e.g., "source code"). Such software code can include computer readable instructions for performing various methods (e.g., "object" or "executable code"). The software code may form portions of computer program products. Software implementations of the embodiments described herein may be provided via an article of manufacture with the code or instructions stored thereon, or via a method of operating a communication interface to send data via a communication interface (e.g., wirelessly, over the internet, via satellite communications, and the like).

Further, the software code may be tangibly stored on one or more volatile or non-volatile computer-readable storage media during execution or at other times. These computer-readable storage media may include any mechanism that stores information in a form accessible by a machine (e.g., computing device, electronic system, and the like), such as, but are not limited to, floppy disks, hard disks, removable magnetic disks, any form of magnetic disk storage media, CD-ROMS, magnetic-optical disks, removable optical disks (e.g., compact disks and digital video disks), flash memory devices, magnetic cassettes, memory cards or sticks (e.g., secure digital cards), RAMs (e.g., CMOS RAM and the like), recordable/non-recordable media (e.g., read only memories (ROMs)), EPROMS, EEPROMS, or any type of media suitable for storing electronic instructions, and the like. Such computer readable storage medium coupled to a computer system bus to be accessible by the processor and other parts of the OIS.

In an embodiment, the computer-readable storage medium may have encoded a data structure for a treatment planning, wherein the treatment plan may be adaptive. The data structure for the computer-readable storage medium may be at least one of a Digital Imaging and Communications in Medicine (DICOM) format, an extended DICOM format, a XML format, and the like. DICOM is an international communications standard that defines the format used to transfer medical image-related data between various types of medical equipment. DICOM RT refers to the communication standards that are specific to radiation therapy.

In various embodiments of the disclosure, the method of creating a component or module can be implemented in software, hardware, or a combination thereof. The methods provided by various embodiments of the present disclosure, for example, can be implemented in software by using standard programming languages such as, for example, C, C++, Java, Python, and the like; and combinations thereof. As used herein, the terms "software" and "firmware" are interchangeable, and include any computer program stored in memory for execution by a computer.

Claim 1:
A computer-implemented method for determining a treatment plan for delivering radiotherapy to a patient via a radiation machine, the method comprising:
providing a beam model for use in the radiation machine;
determining, for the radiation machine, a gantry angle-indexed dose, GAID, variation representing a plurality of radiation doses at different gantry angles; and
determining a radiation treatment plan for the patient using the beam model and the determined GAID variation, wherein determining the GAID variation includes:
delivering a constant radiation beam to a phantom at different gantry angles; and
calculating a dose at each of one or more locations in the phantom corresponding to each of the different gantry angles.