Methods and apparatus for improving scatter estimation and correction in imaging

Abstract

Provided is an x-ray imaging device and an associated method for receiving projection data measured from a wide-aperture scan of a wide axial region and a narrow-aperture scan of a narrow axial region within the wide axial region, and for determining an estimated scatter in the wide axial region using an optimized scatter estimation technique. The optimized scatter estimation technique is based on a difference between measured scatter in the narrow axial region and estimated scatter in the narrow axial region. A kernel-based scatter estimation / correction technique can be fitted to minimize the scatter difference in the narrow axial region, and the fitted (optimized) kernel-based scatter estimation / correction is then applied to the wide axial region. The optimization can be performed in the projection data domain or the reconstruction domain. An iterative process is also used.

Description

[0001] Cross - reference to related applications

[0002] This application claims the benefit of the following 11 U.S. Provisional Patent Applications, including: U.S. Provisional Patent Application Serial No. 62 / 773,712, filed November 30, 2018 (Attorney Docket No. 38935 / 04001); U.S. Provisional Patent Application Serial No. 62 / 773,700, filed November 30, 2018 (Attorney Docket No. 38935 / 04002); U.S. Provisional Patent Application Serial No. 62 / 796,831, filed January 25, 2019 (Attorney Docket No. 38935 / 04004); U.S. Provisional Patent Application Serial No. 62 / 800,287, filed February 1, 2019 (Attorney Docket No. 38935 / 04003); U.S. Provisional Patent Application Serial No. 62 / 801,260, filed February 5, 2019 (Attorney Docket No. 38935 / 04006); U.S. Provisional Patent Application Serial No. 62 / 813,335, filed March 4, 2019 (Attorney Docket No. 38935 / 04007); U.S. Provisional Patent Application Serial No. 62 / 821,116, filed March 20, 2019 (Attorney Docket No. 38935 / 04009); U.S. Provisional Patent Application Serial No. 62 / 836,357, filed April 19, 2019 (Attorney Docket No. 38935 / 04016); U.S. Provisional Patent Application Serial No. 62 / 836,352, filed April 19, 2019 (Attorney Docket No. 38935 / 04017); U.S. Provisional Patent Application Serial No. 62 / 843,796, filed May 6, 2019 (Attorney Docket No. 38935 / 04005); and U.S. Provisional Patent Application Serial No. 62 / 878,364, filed July 25, 2019 (Attorney Docket No. 38935 / 04008). This application is also related to ten non-provisional U.S. patent applications filed on the same day, including: non-provisional U.S. patent application titled "MULTIMODAL RADIATION APPARATUS AND METHODS" with Attorney Docket No. 38935 / 04019; non-provisional U.S. patent application titled "APPARATUS AND METHODS FOR SCALABLE FIELD OF VIEW IMAGING USING A MULTI-SOURCE SYSTEM" with Attorney Docket No. 38935 / 04020;Non-provisional U.S. patent application with Attorney Docket No. 38935 / 04011 titled "INTEGRATED HELICAL FAN-BEAM COMPUTED TOMOGRAPHY IN IMAGE-GUIDED RADIATION TREATMENT DEVICE"; non-provisional U.S. patent application with Attorney Docket No. 38935 / 04010 titled "COMPUTED TOMOGRAPHY SYSTEM AND METHOD FOR IMAGE IMPROVEMENT USING PRIOR IMAGE"; non-provisional U.S. patent application with Attorney Docket No. 38935 / 04013 titled "OPTIMIZED SCANNING METHODS AND TOMOGRAPHY SYSTEM USING REGION OF INTEREST DATA"; non-provisional U.S. patent application with Attorney Docket No. 38935 / 04015 titled "HELICAL CONE-BEAM COMPUTED TOMOGRAPHY IMAGING WITH AN OFF-CENTERED DETECTOR"; non-provisional U.S. patent application with Attorney Docket No. 38935 / 04021 titled "MULTI-PASS COMPUTED TOMOGRAPHY SCANS FOR IMPROVED WORKFLOW AND PERFORMANCE"; non-provisional U.S. patent application with Attorney Docket No. 38935 / 04012 titled "METHOD AND APPARATUS FOR SCATTER ESTIMATION IN CONE-BEAM COMPUTED TOMOGRAPHY"; non-provisional U.S. patent application with Attorney Docket No. 38935 / 04014 titled "ASYMMETRIC SCATTER FITTING FOR OPTIMAL PANEL READOUT IN CONE-BEAM COMPUTED TOMOGRAPHY"and non - provisional U.S. patent application Ser. No. 38935 / 04022, entitled "METHOD AND APPARATUS FOR IMAGE RECONSTRUCTION AND CORRECTION USING INTER - FRACTIONAL INFORMATION". The contents of all of the above - mentioned patent applications and patents are hereby incorporated by reference in their entirety. FIELD OF THE INVENTION

[0003] Aspects of the disclosed technology relate to estimating scatter in projection data, and more particularly, to using narrow - aperture scans to estimate scatter in wide - aperture scans during various imaging techniques, including x - ray scans, computed tomography (CT) scans, and cone - beam computed tomography (CBCT) scans. BACKGROUND OF THE INVENTION

[0004] Scatter in cone - beam CT can account for a large portion of the detected photons, especially when anti - scatter grids are not used in wide collimation openings. Scatter has a negative impact on image quality, including contrast and quantitative accuracy. Thus, scatter measurement, estimation, and correction are applicable to cone - beam CT data processing and image reconstruction, including in the context of image - guided radiation therapy (IGRT). IGRT can utilize medical imaging techniques (e.g., CT) to collect images of a patient before, during, and / or after treatment.

[0005] For cone - beam computed tomography (CBCT) using a flat - panel detector, a pair of high - attenuation blades can be used as part of a collimator to form an aperture that limits the axial extent of the x - ray beam irradiating within the patient / detector. A large aperture allows for large axial coverage of the patient during scanning. Thus, if imaging a larger axial extent of the patient is desired, the total scan time can be reduced by using a larger aperture. However, the trade - off is that the amount of scatter also increases with the aperture, while the primary data remains the same. Without scatter correction, the increased scatter will have a negative impact on image quality and quantification.

[0006] Hardware - based scatter reduction includes using anti - scatter grids on the detector panel surface, using very narrow apertures, bow - tie filters, air separation between the patient and the detector, etc. Conventional anti - scatter grids can significantly reduce the amount of x - ray scatter. The main drawback is that the system is more complex and also reduces a large amount of raw data. Using very narrow apertures can significantly reduce scatter (and effectively reduce it to a negligible level), but the axial coverage is so small that the entire scan time becomes impractical.

[0007] Software-based scatter reduction / correction can use physical models to estimate scatter in the acquired data. These methods can model the data acquisition system as well as the process of interaction between x-rays and materials. The former requires a detailed understanding of the main components of the entire imaging chain as well as patient information, which can be obtained through CT planned without scatter correction or the first-pass reconstruction. These methods can be implemented stochastically (e.g., methods based on Monte Carlo simulations) or deterministically (e.g., methods based on the radiative transfer equation). The former is computationally expensive, while the latter is generally considered an unsolved problem in the field. Model-based methods are usually patient-specific and can be more accurate. However, these methods require a large amount of prior information about the data acquisition system and the patient, making the effectiveness of these methods highly dependent on the modeling accuracy. In addition, they also require high computational power and time, resulting in a significant negative impact on the workflow and throughput. Then the estimated scatter is used to correct the data before or during image reconstruction.

[0008] In software-based scatter correction methods, there is kernel-based scatter estimation and correction. In kernel-based methods, the scatter kernel is determined through physical measurements or Monte Carlo simulations assuming the material is a composite material. For example, a typical technique is to measure the scatter kernel with different water layer thicknesses at a given x-ray spectrum and aperture. The aperture projected onto the detector plane can be as large as the axial dimension of the panel. Once the kernels at different water layers are measured / determined, they can be used for scatter correction in patient scans, provided that it is assumed that patient tissue is equivalent to water layers of different thicknesses. The application of the kernel for scatter estimation and correction can include using the kernel for scatter deconvolution in the spatial domain or frequency domain and can be adapted to local variations of the object. For example, the measured scatter data can be considered the convolution result of the primary kernel and the scatter kernel. By using an appropriate kernel established in advance, a deconvolution process can be performed to separate the primary kernel and the scatter kernel.

[0009] Kernel-based scatter estimation / correction is widely used in CBCT due to its simplicity. However, the fundamental challenge of this type of method is that when the patient tissue distribution is highly inhomogeneous, especially in the chest and pelvic regions, the accuracy may deteriorate. In addition, when the aperture is large, the performance of this method also deteriorates based on the scatter enhancement associated with the large aperture. Summary of the Invention

[0010] In one embodiment, an imaging device includes: a rotating imaging source for emitting a radiation beam; a detector positioned to receive the radiation from the imaging source; and a beam shaper configured to adjust the shape of the radiation beam emitted by the imaging source such that the shape of the radiation beam is configured for wide-aperture scanning of a wide axial region and narrow-aperture scanning of a narrow axial region within the wide axial region, wherein an estimated scatter in the wide axial region is based on projection data from the narrow axial region.

[0011] Features described and / or shown with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments, and / or combined with or substituted for features of other embodiments.

[0012] The description of the present invention does not in any way limit the words used in the claims or the scope of the claims or the present invention. The words used in the claims have their full ordinary meaning. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In the drawings, embodiments of the present invention are shown, which are incorporated into and form a part of the specification, and together with the general description of the present invention given above and the detailed description given below are used to illustrate embodiments of the present invention. It should be understood that the element boundaries shown in the figures (e.g., boxes, groups of boxes, or other shapes) represent one embodiment of the boundaries. In some embodiments, one element may be designed as multiple elements, or multiple elements may be designed as one element. In some embodiments, an element shown as an internal component of another element may be implemented as an external component, and vice versa. Additionally, the elements may not be drawn to scale.

[0014] Figure 1 is a perspective view of an exemplary x-ray imaging device according to one aspect of the disclosed technology.

[0015] Figure 2 is a schematic diagram of an x-ray imaging device integrated into an exemplary radiotherapy device according to one aspect of the disclosed technology.

[0016] Figure 3 is a schematic diagram of an exemplary scan design for imaging an axial region of a target object.

[0017] Figure 4 is a flowchart depicting an exemplary method for scatter estimation in the projection data domain using a scan design having a narrow scan region within a wide scan region.

[0018] Figure 5 is a flowchart depicting another exemplary method for scatter estimation in the projection data domain using a scan design having a narrow scan region within a wide scan region.

[0019] Figure 6 is a flowchart depicting an exemplary iterative method for performing scatter estimation in a projection data domain using a scan design with a narrow scan region within a wide scan region.

[0020] Figure 7 is a flowchart depicting an exemplary method for performing scatter correction in a reconstruction domain using a scan design with a narrow scan region within a wide scan region.

[0021] Figure 8 is a flowchart depicting an exemplary iterative method for performing scatter correction in a reconstruction domain using a scan design with a narrow scan region within a wide scan region.

[0022] Figure 9 is a flowchart depicting an exemplary method for determining a narrow scan for a narrow / wide scan design from previous image data.

[0023] Figure 10 is a flowchart depicting an exemplary method for determining a narrow scan for a narrow / wide scan design from wide scan data.

[0024] Figure 11 is a flowchart depicting an exemplary method for using IGRT of a radiotherapy device.

[0025] Figure 12 is a block diagram depicting an exemplary pre-irradiation image-based step.

[0026] Figure 13 is a block diagram depicting exemplary data sources that can be used during imaging or pre-irradiation image-based steps. DETAILED DESCRIPTION

[0027] The following includes definitions of exemplary terms that can be used throughout the disclosure. The singular and plural forms of all terms fall within each meaning.

[0028] As used herein, a "component" can be defined as a part of hardware, a part of software, or a combination thereof. A part of hardware can at least include a processor and a part of a memory, where the memory includes instructions to be executed. A component can be associated with a device.

[0029] As used herein, "logic" synonymous with "circuit" includes, but is not limited to, hardware, firmware, software, and / or combinations of each to perform functions or actions. For example, depending on the desired application or requirements, logic can include a software-controlled microprocessor, discrete logic such as an application-specific integrated circuit (ASIC), or other programmed logic devices and / or controllers. Logic can also be fully embodied as software.

[0030] As used herein, "processor" includes, but is not limited to, one or more of any number of processor systems or stand-alone processors, e.g., microprocessors, microcontrollers, central processing units (CPUs), and digital signal processors (DSPs) in any combination. The processor may be associated with various other circuits that support the operation of the processor, such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), clock, decoder, memory controller, or interrupt controller, etc. These support circuits may be internal or external to the processor or its associated electronic package. The support circuits communicate operably with the processor. The support circuits need not be shown separately from the processor in a block diagram or other figure.

[0031] As used herein, "signal" includes, but is not limited to, one or more electrical signals (including analog or digital signals), one or more computer instructions, bits, or bitstreams, etc.

[0032] As used herein, "software" includes, but is not limited to, one or more computer-readable and / or executable instructions that cause a computer, processor, logic, and / or other electronic device to perform functions, actions, and / or respond in a desired manner. The instructions may be embodied in various forms, such as routines, algorithms, modules, or programs, including separate applications or code from dynamically linked sources or libraries.

[0033] Notwithstanding the foregoing exemplary definitions, Applicant intends the broadest reasonable interpretation consistent with this specification to be applied to these and other terms.

[0034] As discussed in more detail below, embodiments of the disclosed technology relate to estimating scatter in imaging projection data, including during x-ray scans, CT scans, and CBCT scans, using data from a narrow aperture scan within a wider aperture scan to estimate scatter in data from the wider aperture scan. In some embodiments, a radiotherapy delivery device and method may utilize an integrated low-energy radiation source for CT, for use in combination with or as part of IGRT. In particular, for example, a radiotherapy delivery device and method may combine a low-energy collimated radiation source for imaging in a gantry using rotational (e.g., helical or step-and-shoot) image acquisition with a high-energy radiation source for therapeutic treatment.

[0035] Compared with imaging using a high - energy radiation source (e.g., megavoltage (MV)), a low - energy radiation source (e.g., kilovoltage (kV)) can produce higher - quality images. Compared with using MV energy, images generated using kV energy generally have better tissue contrast. High - quality volume imaging may be required for visualization of the target object and organs at risk (OARS), adaptive treatment monitoring, and treatment planning / re - planning. In some embodiments, the kV imaging system can also be used for localization, motion tracking, and / or characterization or correction capabilities.

[0036] The image acquisition method can include or otherwise utilize multiple rotational scans, which can be, for example, continuous scans (e.g., having a helical source trajectory about a central axis and longitudinal movement of the patient support through the gantry aperture), discontinuous circular stop - and - reverse scans with step - by - step longitudinal movement of the patient support, step - and - shoot circular scans, etc.

[0037] According to various embodiments, the imaging device collimates the radiation source, using, for example, a beam former, into a beam including, for example, a cone beam or a fan beam. In one embodiment, the collimated beam can be combined with a gantry that rotates continuously while the patient is moving, thereby producing helical image acquisition.

[0038] In some embodiments, the time associated with increased scan rotation to complete a high - quality volume image can be mitigated by a high gantry rate / speed (e.g., using fast slip - ring rotation, including, for example, up to 10 revolutions per minute (rpm), 20 rpm, 60 rpm or higher), high kV frame rate, and / or sparse data reconstruction techniques to provide kV CT imaging on a radiotherapy delivery platform. Detectors (with various row / slice sizes, configurations, dynamic ranges, etc.), scan pitch, and / or dynamic collimation are additional features in various embodiments, including for selectively exposing portions of the detector and selectively defining an effective read - out region, as discussed in detail below. In particular, image quality can be improved by using an adjustable beam former / collimator on the x - ray (low - energy) imaging radiation source and / or optimizing the read - out range of the detector (by estimating scatter, as described below).

[0039] Imaging devices and methods can provide selective and variable collimation of a radiation beam emitted by a radiation source, including adjusting the shape of the radiation beam to expose less than the entire active area of an associated radiation detector (e.g., a radiation detector positioned to receive radiation from an x-ray radiation source). For example, as the spacing changes during helical scanning, the beam shaper of the imaging device can adjust the shape of the radiation beam. In another example, the beam aperture can be adjusted by the beam shaper for various axial field of view (aFOV) requirements. In particular, the aFOV can be adjusted for scan regions of various axial (longitudinal) lengths, including narrow and wide regions. Also, exposing only the primary area of the detector to direct radiation can cause the shadow area of the detector to receive only scatter. In some embodiments, the scatter measurements in the shadow area of the detector (and in some embodiments, the measurements in the penumbra area) can be used to estimate the scatter in the primary area of the detector that receives the projection data.

[0040] Imaging devices and methods can provide selective and variable detector readout areas and ranges, including adjusting the detector readout range to limit the active area of the detector to improve the readout speed. For example, less than the available shadow area data can be read and used for scatter estimation. Combining selective readout with beam shaping allows for various optimizations of scatter fitting techniques.

[0041] Reference Figure 1 and Figure 2 , shows an imaging device 10 (e.g., an x-ray imaging device). It should be understood that the imaging device 10 can be associated with a radiation therapy device, such as Figure 2associated with and / or integrated into a radiotherapy device that can be used for a variety of applications, including but not limited to IGRT. The imaging device 10 includes a rotatable gantry system, referred to as gantry 12, which is supported by or otherwise housed within a support unit or housing 14. As used herein, a gantry refers to a gantry system that includes one or more gantries (e.g., a ring or C-arm) that are capable of supporting one or more radiation sources and / or associated detectors as they rotate around a target object. For example, in one embodiment, a first radiation source and its associated detector may be mounted to a first gantry of the gantry system, and a second radiation source and its associated detector may be mounted to a second gantry of the gantry system. In another embodiment, more than one radiation source and associated detector may be mounted to the same gantry of the gantry system, including, for example, the case where the gantry system consists of only one gantry. Various combinations of gantries, radiation sources, and radiation detectors can be combined into various gantry system configurations to image and / or treat the same volume within the same device. For example, kV radiation sources and MV radiation sources may be mounted on the same or different gantries of the gantry system and selectively used for imaging and / or treatment as part of an IGRT system. If mounted on different gantries, the radiation sources can rotate independently but still be able to image the same (or nearly the same) volume simultaneously. As described above, the rotatable ring gantry 12 may be capable of 10 rpm or higher. The rotatable gantry 12 defines a gantry aperture 16 through which a patient can move in and through and be positioned for imaging and / or treatment. According to one embodiment, the rotatable gantry 12 is configured as a slip-ring gantry for providing continuous rotation of the imaging radiation source (x-ray) and associated radiation detector while providing sufficient bandwidth for high-quality imaging data received by the detector. The slip-ring gantry can eliminate the need for the gantry to rotate in alternating directions in order to wind and unwind cables carrying power and signals associated with the device. Even when integrated into an IGRT system, this configuration can perform continuous helical computed tomography, including CBCT.

[0042] The patient support 18 is positioned adjacent to the rotatable gantry 12 and is configured to generally support the patient in a horizontal position for longitudinal movement into and within the rotatable gantry 12. The patient support 18 can move the patient, for example, in a direction perpendicular to the plane of rotation of the gantry 12 (along or parallel to the axis of rotation of the gantry 12). The patient support 18 can be operatively coupled to a patient support controller that controls the movement of the patient and the patient support 18. The patient support controller can be synchronized with the rotatable gantry 12 and the radiation source mounted to the rotating gantry for rotation about the longitudinal axis of the patient according to a commanded imaging and / or treatment plan. Once the patient support is located within the aperture 16, it can also be moved up and down and side to side within a limited range to adjust the patient position for optimal treatment. The axes x, y, and z are shown, where, as viewed from the front of the gantry 12, the x-axis is horizontal and points to the right, the y-axis points into the plane of the gantry, and the z-axis is vertical and points to the top. The x, y, and z axes follow the right-hand rule.

[0043] It should be understood that other variations can be employed without departing from the scope of the disclosed technology. For example, the rotatable gantry 12 and the patient support 18 can be controlled such that as the support is controlled to move relative to the rotatable gantry 12 (at a constant or variable speed), the gantry 12 rotates about the patient supported on the patient support in a "back-and-forth" manner (e.g., alternately clockwise and counterclockwise rotation) (as opposed to the continuous manner described above). In another embodiment, in the case of a continuous stepped acquisition circular scan, the movement (stepping) of the patient support 18 in the longitudinal direction alternates with the scan rotation of the rotatable gantry 12 (acquisition) until the desired volume is captured. The apparatus 10 is capable of performing volume-based and planar-based imaging acquisitions. For example, in various embodiments, the apparatus 10 can be used to acquire volume images and / or planar images and perform the associated processing methods described below.

[0044] Relative movement of the radiation source and the patient to generate projection data can be achieved using various other types of radiation sources and / or patient support movement. Discontinuous movement, continuous but variable / non-constant (including linear and non-linear) linear movement, speed, and / or trajectory, etc., of the radiation source and / or patient support, as well as combinations thereof, including in conjunction with the various embodiments of the radiotherapy apparatus 10 described above, can be used.

[0045] As Figure 2As shown, the x-ray imaging device 10 includes an imaging radiation source 30, which is coupled to or otherwise supported by a rotatable gantry 12. The imaging radiation source 30 emits a radiation beam (generally denoted as 32) for generating high-quality images. In this embodiment, the imaging radiation source is an x-ray source 30, which is configured as a kilovolt (kV) source (e.g., a clinical x-ray source with an energy level in the range of approximately 20 kV to approximately 150 kV). In one embodiment, the kV radiation source includes a peak photon energy in kiloelectron volts (keV) of up to 150 keV. The imaging radiation source can be any type of transmission source suitable for imaging. For example, the imaging radiation source can be, for example, an x-ray generating source (including those for CT) or any other means of generating photons with sufficient energy and flux (e.g., a gamma source (e.g., cobalt 57, with an energy peak at 122 keV), an x-ray fluorescence source (e.g., a fluorescence source through Pb k-lines, having two peaks at approximately 70 keV and approximately 82 keV), etc.). For a particular embodiment, the references to x-rays, x-ray imaging, x-ray imaging sources, etc. herein are exemplary. In various other embodiments, other imaging transmission sources can be used interchangeably.

[0046] The x-ray imaging device 10 may also include another radiation source 20, which is coupled to or otherwise supported by the rotatable gantry 12. According to one embodiment, the radiation source 20 is configured as a therapeutic radiation source, e.g., a high-energy radiation source for treating tumors in a patient's body in a region of interest. It should be understood that, without departing from the scope of the disclosed technology, the therapeutic radiation source can be a high-energy x-ray beam (e.g., a megavolt (MV) x-ray beam) and / or a high-energy particle beam (e.g., an electron beam, a proton beam, or a heavy ion (e.g., carbon) beam) or another suitable form of high-energy radiation. In one embodiment, the radiation source 20 includes a peak photon energy in megaelectron volts (MeV) of 1 MeV or greater. In one embodiment, the high-energy x-ray beam has an average energy greater than 0.8 MeV. In another embodiment, the high-energy x-ray beam has an average energy greater than 0.2 MeV. In another embodiment, the high-energy x-ray beam has an average energy greater than 150 keV. Generally, the radiation source 20 has a higher energy level (peak and / or average, etc.) than the imaging radiation source 30.

[0047] In one embodiment, the radiation source 20 is a LINAC that produces therapeutic radiation (e.g., MV), and the imaging system includes a separate imaging radiation source 30 that produces relatively low-intensity and lower-energy imaging radiation (e.g., kV). In other embodiments, the radiation source 20 can be a radioisotope, such as cobalt-60, which typically can have an energy greater than 1 MeV. The radiation source 20 can emit one or more radiation beams (generally denoted by 22) into a region of interest (ROI) within a patient supported on the patient support 18 according to a treatment plan.

[0048] In some embodiments, the radiation sources 20, 30 can be used in combination with each other to provide higher-quality and better-utilized images. In other embodiments, at least one additional radiation source can be coupled to the rotatable gantry 12 and operated to acquire projection data at a peak photon energy different from the peak photon energies of the radiation sources 20, 30.

[0049] Although Figure 1 and Figure 2 an x-ray imaging device 10 with a radiation source 30 mounted to a ring gantry 12 is depicted, other embodiments can include other types of rotatable imaging devices, including, for example, C-arm gantry-based systems and robotic-arm-based systems. In gantry-based systems, the gantry rotates the imaging radiation source 30 about an axis passing through the isocenter. Gantry-based systems include C-arm gantries in which the imaging radiation source 30 is mounted in a cantilevered manner above and around an axis passing through the isocenter. Gantry-based systems also include ring gantries, such as the rotatable gantry 12, which has a generally ring shape, wherein the patient's body extends through the hole of the ring / torus, and the imaging radiation source 30 is mounted on the perimeter of the ring and rotates about an axis passing through the isocenter. In some embodiments, the gantry 12 rotates continuously. In other embodiments, the gantry 12 utilizes a cable-based system that rotates and reverses repeatedly.

[0050] The detector 34 (e.g., a two-dimensional planar detector or a curved detector) can be coupled to the rotatable gantry 12 or otherwise supported by the rotatable gantry 12. The detector 34 (e.g., an x-ray detector) is positioned to receive radiation from the x-ray source 30 and can rotate with the x-ray source 30. The detector 34 can detect or otherwise measure the amount of unattenuated radiation and thus infer the amount of radiation that has actually been attenuated due to the patient or the associated patient ROI (compared to the amount of radiation initially generated). As the radiation source 30 rotates around the patient and emits radiation towards the patient, the detector 34 can detect or otherwise collect attenuation data from different angles.

[0051] It should be understood that the detector 34 can take a variety of configurations without departing from the scope of the disclosed technology. AsFigure 2 As shown, the detector 34 can be configured as a flat panel detector (e.g., a multi-row flat panel detector). According to another exemplary embodiment, the detector 34 can be configured as a curved detector.

[0052] The collimator or beam shaper assembly (generally designated 36) is positioned relative to the imaging (x-ray) source 30 to selectively control and adjust the shape of the radiation beam 32 emitted by the x-ray source 30, thereby selectively exposing a portion or section of the active area of the detector 34. The beam shaper can also control how the radiation beam 32 is positioned on the detector 34. In one embodiment, the beam shaper 36 can have one degree / dimension of movement (e.g., to form a thinner or wider slit). In another embodiment, the beam shaper 36 can have two degrees / dimensions of movement (e.g., to form rectangles of various sizes). In other embodiments, the beam shaper 36 can have various other dynamically controlled shapes, including for example a parallelogram. All of these shapes can be dynamically adjusted during the scan. In some embodiments, the blocking portion of the beam shaper can be rotated and translated.

[0053] The beam shaper 36 can be controlled to dynamically adjust the shape of the radiation beam 32 emitted by the x-ray source 30 in accordance with a number of geometries, including but not limited to a fan beam or a cone beam, which can have a beam thickness (width) as low as the width of one detector row or include multiple detector rows, where the multiple detector rows will be only a portion of the active area of the detector. In various embodiments, the thickness of the beam can expose a larger detector active area of several centimeters. For example, 3-4 centimeters (measured in the longitudinal direction in the detector plane) of a 5-6 centimeter detector can be selectively exposed to the imaging radiation 32. In this embodiment, projection image data of 3-4 centimeters can be captured at each read, with approximately 1-2 centimeters of unexposed detector area on one side or each side, which can be used to capture scatter data, as described below.

[0054] In other embodiments, more or less of the active detector can be selectively exposed to the imaging radiation. For example, in some embodiments, the beam thickness can be reduced to a range of about two centimeters, one centimeter, less than one centimeter, or similar sizes, including using a smaller detector. In other embodiments, the beam thickness can be increased to a range of about 4 centimeters, 5 centimeters, greater than 5 centimeters, or similar sizes, including using a larger detector. In various embodiments, the ratio of the exposed detector area to the active detector area can be 30 - 90% or 50 - 75%. In other embodiments, the ratio of the exposed detector area to the active detector area can be 60 - 70%. However, in other embodiments, various other exposed area sizes and active area sizes or ratios of the exposed detector area to the active detector area may be suitable. The beam and detector can be configured such that the shadow area of the detector (active but not exposed to direct radiation) is sufficient to capture scatter data outside the penumbra region.

[0055] Various embodiments can include optimization of features that control the selective exposure of the detector (e.g., beam size, beam / aperture center, collimation, pitch, detector read range, detector read center, etc.) such that the measured data is sufficient for both the primary (exposed) region and the shadow region, but is also optimized for speed and dose control. The shape / position of the beam shaper 36 and the read range of the detector 34 can be controlled such that, based on the particular imaging task being performed and the scatter estimation process, the radiation beam 32 from the x-ray source 30 covers as much or as little of the x-ray detector 34 as possible, including, for example, a combination of narrow aFOV scans and wide aFOV scans.

[0056] The beam shaper can be configured in various ways to allow it to adjust the shape of the radiation beam 32 emitted by the x-ray source 30. For example, the collimator 36 can be configured to include a set of jaws or other suitable members that define and selectively adjust the size of the aperture through which the radiation beam from the x-ray source 30 can pass in a collimated manner. According to one exemplary configuration, the collimator 36 can include an upper jaw and a lower jaw, where the upper jaw and the lower jaw can be moved in different directions (e.g., parallel directions) to adjust the size of the aperture through which the radiation beam from the x-ray source 30 passes, and also to adjust the beam position relative to the patient to irradiate only the portion of the patient to be imaged, thereby optimizing the imaging and minimizing the patient dose. For example, the collimator can be configured as a multi-leaf collimator (MLC), which can include a plurality of interleaved blades that are operable to move to one or more positions between a minimum open or closed position and a maximum open position. It should be understood that the blades can be moved to a desired position to achieve the desired shape of the radiation beam emitted by the radiation source. In one embodiment, the MLC can achieve sub-millimeter aiming accuracy.

[0057] According to one embodiment, the shape of the radiation beam 32 from the x-ray source 30 can be changed during image acquisition. In other words, according to an exemplary implementation, the blade positions and / or aperture widths of the beam shaper 36 can be adjusted before or during the scan. For example, according to one embodiment, the beam shaper 36 can be selectively controlled and dynamically adjusted during the rotation of the x-ray source 30 such that the shape of the radiation beam 32 has sufficient primary / shadow regions and is adjusted to include only the object of interest (e.g., the prostate) during imaging. The shape of the radiation beam 32 emitted by the x-ray source 30 can be changed during or after the scan according to the desired image acquisition, which can be based on imaging and / or treatment feedback, as discussed in more detail below.

[0058] The detector 24 can be coupled to or otherwise supported by the rotatable gantry 12 and is positioned to receive the radiation 22 from the therapeutic radiation source 20. The detector 24 can detect or otherwise measure the amount of unattenuated radiation and thus infer the amount of radiation that has actually been attenuated due to the patient or associated patient ROI (compared to the initially generated amount of radiation). As the therapeutic radiation source 20 rotates around the patient and emits radiation towards the patient, the detector 24 can detect or otherwise collect attenuation data from different angles.

[0059] It will be further understood that the therapeutic radiation source 20 can include a beam shaper or collimator or be otherwise associated therewith. The collimator / beam shaper associated with the therapeutic radiation source 20 can be configured in a variety of ways, similar to the collimator / beam shaper 36 associated with the imaging source 30.

[0060] The therapeutic radiation source 20 can be mounted, configured, and / or moved into the same plane or a different plane (offset) as the imaging source 30. In some embodiments, the scatter caused by the simultaneous activation of the radiation sources 20, 30 can be reduced by offsetting the radiation planes.

[0061] When integrated with a radiation therapy device, the imaging device 10 can provide images that are used to set up (e.g., align and / or register), plan, and / or guide a radiation delivery procedure (treatment). A typical setup is accomplished by comparing the current (during-treatment) image with the pre-treatment image information. The pre-treatment image information can include, for example, x-ray, CT data, CBCT data, magnetic resonance imaging (MRI) data, positron emission tomography (PET) data, or 3D rotational angiography (3DRA) data and / or any information obtained from these or other imaging modalities. In some embodiments, the imaging device 10 can track the movement of the patient, target object, or ROI during treatment.

[0062] The reconstruction processor 40 may be operatively coupled to the detector 24 and / or the x-ray detector 34. In one embodiment, the reconstruction processor 40 is configured to generate a patient image based on the radiation received by the detectors 24, 34 from the radiation sources 20, 30. It should be understood that the reconstruction processor 40 may be configured to perform the methods described more fully below. The apparatus 10 may further include a memory 44 suitable for storing information, including but not limited to processing and reconstruction algorithms and software, imaging parameters, image data from previous or otherwise previously acquired images (e.g., planning images), treatment plans, and the like.

[0063] The x-ray imaging apparatus 10 may include an operator / user interface 48 at which an operator of the x-ray imaging apparatus 10 may interact with or otherwise control the x-ray imaging apparatus 10 to provide inputs related to scan or imaging parameters, etc. The operator interface 48 may include any suitable input device, such as a keyboard, a mouse, a voice controller, and the like. The x-ray imaging apparatus 10 may further include a display 52 or other human-readable element for providing an output to the operator of the imaging apparatus 10. For example, the display 52 may allow the operator to observe the reconstructed patient image and other information, such as imaging or scan parameters related to the operation of the x-ray imaging apparatus 10.

[0064] As Figure 2 shown, the x-ray imaging apparatus 10 includes a controller (generally designated 60) that is operatively coupled to one or more components of the apparatus 10. The controller 60 controls the overall operation and functioning of the apparatus 10, including providing power and timing signals to the x-ray source 30 and / or the therapeutic radiation source 20 and a gantry motor controller that controls the rotational speed and position of the rotatable gantry 12. It should be understood that the controller 60 may encompass one or more of the following: a patient support controller, a gantry controller, a controller coupled to the therapeutic radiation source 20 and / or the x-ray source 30, a beam shaper 36 controller, a controller coupled to the detector 24 and / or the detector 34, etc. In one embodiment, the controller 60 is a system controller that may control other components, devices, and / or controllers.

[0065] In various embodiments, the reconstruction processor 40, the operator interface 48, the display 52, the controller 60, and / or other components may be combined into one or more components or devices.

[0066] Device 10 may include various components, logic, and software. In one embodiment, controller 60 includes a processor, a memory, and software. By way of example and not limitation, an x-ray imaging device and / or a radiotherapy system may include various other devices and components (e.g., gantry, radiation source, collimator, detector, controller, power supply, patient support, etc.), which may implement one or more routines or steps related to imaging and / or IGRT for a particular application, where the routines may include imaging, image-based steps prior to irradiation, and / or radiotherapy irradiation, including corresponding device settings, configurations, and / or positions (e.g., paths / trajectories) that may be stored in the memory. Additionally, the controller may directly or indirectly control one or more devices and / or components according to one or more routines or processes stored in the memory. Examples of direct control are the setting of various radiation source or collimator parameters (power, speed, position, timing, modulation, etc.) associated with imaging or treatment. An example of indirect control is communicating position, path, speed, etc. to a patient support controller or other peripheral device. The hierarchical structure of various controllers that may be associated with the imaging device may be arranged in any suitable manner to communicate appropriate commands and / or information to the desired devices and components.

[0067] In addition, those skilled in the art will understand that other computer system configurations may be utilized to implement the systems and methods. The illustrated aspects of the present invention may be practiced in a distributed computing environment where certain tasks are performed by local or remote processing devices linked by a communication network. For example, in one embodiment, reconstruction processor 40 may be associated with a separate system. In a distributed computing environment, program modules may be located in local and remote storage devices. For example, a remote database, a local database, a cloud computing platform, a cloud database, or a combination thereof may be used with x-ray imaging device 10.

[0068] X-ray imaging device 10 may utilize an exemplary environment to implement various aspects of the present invention, the exemplary environment including a computer, where the computer includes a controller 60 (e.g., including a processor and a memory (which may be memory 44)) and a system bus. The system bus may couple system components (including but not limited to the memory) to the processor and may communicate with other systems, controllers, components, devices, and processors. The memory may include read-only memory (ROM), random access memory (RAM), a hard disk drive, a flash drive, and any other form of computer-readable medium. The memory may store various software and data, including routines and parameters, which may include, for example, a treatment plan.

[0069] The therapeutic radiation source 20 and / or the x-ray source 30 can be operably coupled to a controller 60 that is configured to control the relative operation of the therapeutic radiation source 20 and the x-ray source 30. For example, the x-ray source 30 can be controlled and the x-ray source 30 can operate simultaneously with the therapeutic radiation source 20. Additionally or alternatively, depending on the particular treatment and / or imaging plan being implemented, the x-ray source 30 can be controlled and the x-ray source 30 can operate sequentially with the therapeutic radiation source 20.

[0070] It will be appreciated that the x-ray source 30 and the x-ray detector 34 can be configured to provide rotation around the patient in a variety of ways during an imaging scan. In one embodiment, synchronizing the movement and exposure of the x-ray source 30 with the longitudinal movement of the patient support 18 can provide continuous helical acquisition of patient images during a procedure. In addition to the continuous rotation of the radiation sources 20, 30 and the detectors 24, 34 (e.g., the gantry rotates continuously and constantly at a constant patient movement speed), it should be understood that other variations can be employed without departing from the scope of the disclosed technology. For example, the rotatable gantry 12 and the patient support can be controlled such that when the support is controlled to move (at a constant or variable speed) relative to the rotatable gantry 12, the gantry 12 rotates around the patient supported on the patient support in a "back-and-forth" manner (e.g., alternately rotating clockwise and counterclockwise) (as opposed to the continuous manner described above). In another embodiment, in the case of a continuous stepped acquisition circular scan, the movement (stepping) of the patient support 18 in the longitudinal direction alternates with the scan rotation (acquisition) of the rotatable gantry 12 until the desired volume is captured. The x-ray imaging device 10 is capable of performing volume-based and plane-based imaging acquisitions. For example, in various embodiments, the x-ray imaging device 10 can be used to acquire volume images and / or plane images (e.g., by using the x-ray source 30 and the detector 34) and perform associated processing, including the scatter estimation / correction methods described below.

[0071] The relative movement of the radiation source and the patient to generate projection data can be achieved using various other types of radiation sources and / or patient support movements. Discontinuous movements, continuous but variable / non-constant (including linear and non-linear) movements, speeds, and / or trajectories, etc., of the radiation source and / or the patient support can be used, as well as combinations thereof, including in combination with the various embodiments of the radiotherapy device 10 described above.

[0072] In one embodiment, the rotation speed of the gantry 12, the speed of the patient support 18, the shape of the beam former 36, and / or the readout of the detector 34 can all remain constant during image acquisition. In other embodiments, one or more of these variables can be changed dynamically during image acquisition. The rotation speed of the gantry 12, the speed of the patient support 18, the shape of the beam former 36, and / or the readout of the detector 34 can be changed to balance different factors, including for example image quality and image acquisition time.

[0073] In other embodiments, these features can be combined with one or more other image-based activities or procedures, including for example patient setup, adaptive treatment monitoring, treatment planning, etc.

[0074] There are many determinants of image quality (e.g., x-ray source focal spot size, detector dynamic range, etc.). The limiting factor for kV CBCT image quality is scatter. Various methods can be used to reduce scatter. One method is to use an anti-scatter grid (which collimates scatter). However, implementing a scatter grid on a kV imaging system can be problematic, including for motion tracking and correction. To improve the quality of image data, it is necessary to accurately estimate the scatter in the projection data. In various embodiments, the scatter in the projection data acquired in the wide aFOV region of the detector 34 can be estimated based on the (relatively scatter-free) projection data acquired in a narrow aFOV region within the wide aFOV region.

[0075] Specifically, data can be acquired in a narrow region of the target object using a narrow aperture such that scatter is minimal / negligible, or simple techniques can be used to accurately obtain the scatter. For example, using kernel-based scatter correction, collimator shadow fitting estimation, etc., the narrow aperture data can be scatter-free, nearly scatter-free, or already scatter-corrected itself. The narrow aperture can have any size suitable for a particular application, including for example 2-3 mm, 1 cm, 2 cm, and / or any size less than the wide aperture in some embodiments. Data can also be acquired in a wide region of the target object using a wide aperture, where the narrow region is within the wide region. The wide aperture can also have any size suitable for a particular application, including for example 5 cm, 10 cm, 15 cm, 20 cm, and / or any size larger than the narrow aperture in some embodiments. In various embodiments, the narrow aperture data can be used to improve the kernel-based scatter estimation and correction of the CBCT data acquired in the wide region. As discussed in detail below, the process of using a narrow scan to improve scatter estimation in a wide scan can be done in the projection domain or during reconstruction. This process can also be performed in a non-iterative or iterative manner.

[0076] In an exemplary embodiment, Figure 3FIG. shows an illustration of an exemplary scan design 300 for imaging an axial region of a target object 310. A large / wide aFOV beam 312 is used to scan a wide region 314 of the target object 310, the wide region 314 being shown as having an axial length W. A small / narrow aFOV beam 316 is used to scan a narrow region 318, the narrow region 318 being shown as having an axial length N1. The narrow region 318 is within the wide region 314, and the axial length N1 is less than the axial length W. In some embodiments, especially if portions of the wide region 314 exhibit axial variations, multiple narrow scans can be utilized to improve accuracy (scatter estimation). For example, in one embodiment, another narrow aFOV beam 320 can be used to scan another narrow region 322, the other narrow region 322 being shown as having an axial length N2. The narrow region 322 is also within the wide region 314, and the axial length N2 is less than the axial length W. All exemplary beams 312, 316, 320 are shown as projecting from a (collimated) source 330 through the target object 310 and incident on a detector 334. Any number of narrow scans can be used within the wide region 314.

[0077] The axial length N1 is small enough such that the narrow scan projection data of the narrow region 318 is scatter-free, has minimal scatter and / or has scatter that can be easily acquired / corrected. A portion of the wide scan projection data of the wide region 314 (which does contain scatter due to the wide scan) overlaps with the narrow region 318. Comparing the projection data (with scatter) from the wide scan in the narrow region 318 with the projection data (scatter-free) from the narrow scan in the narrow region 318 (e.g., finding the difference between them) yields an accurate estimate (essentially a measurement) of the true scatter in the narrow region 318. The comparison can be done in the projection domain or in the reconstruction, as discussed in detail below. In this embodiment, the wide scan is a circular scan, but other embodiments can utilize helical and / or other scan trajectories.

[0078] After this comparison, the true scatter in the narrow region 318 can be used to optimize the scatter estimation technique applied to the entire wide region 314 with high confidence. This can be particularly effective if the target object has minimal variations in the wide region 314. As discussed in detail below, the optimization can be done in a non-iterative or iterative manner. In some embodiments, multiple narrow aperture datasets (e.g., from narrow regions 318, 322) can be acquired within the axial extent of a wide aFOV CBCT scan (e.g., from the wide region 314) to improve scatter correction.

[0079] In one embodiment, the scatter estimation technique utilizes kernel-based scatter estimation / correction. For example, the kernel-based scatter estimation technique applied to the projection data from a wide scan in the narrow region 318 can be constrained such that the scatter estimation generated by the kernel-based scatter estimation technique produces a determined accurate scatter estimation for the narrow region 318, since the true scatter for the narrow region 318 is known. Then, the constrained (optimized) kernel-based scatter estimation technique can be applied to the remainder of the wide region 314, thereby obtaining improved results (e.g., compared to an unconstrained application). The kernel-based technique can improve the accuracy based on patient-related and / or system-related factors.

[0080] In some embodiments, more than one wide aFOV region (e.g., 314) can be scanned as part of a larger axial range. Each of these wide aFOV regions 314 can include one or more narrow aFOV regions (e.g., 318, 322).

[0081] As Figure 3 shown, one embodiment of the scan design 300 can include a large aFOV CBCT scan (314) of the patient's chest and a complementary scan (318) of the region with a narrow aperture. In some embodiments, for better performance, multiple narrow aperture scans (318, 322) can be determined and acquired, where the positions are distributed inside the large aFOV (314). The narrow aperture scans associated with the regions 318, 322 can use clinically effective protocols, and the accurate reconstruction of the range covered by these narrow apertures 316, 320 can also be used for clinical applications. In some embodiments, when only used to improve scatter correction, the narrow aperture scans can use fast gantry rotation and sparse angular sampling to minimize the impact on the total scan time and patient dose.

[0082] When the aperture created by the beam former 36 is narrow enough (e.g., the beams 316, 320 associated with the narrow regions 318, 322 respectively), the scatter in the projection data is substantially negligible. Thus, in one embodiment, the narrow aperture data can be used as scatter-free data. In another embodiment, some simple techniques can effectively and accurately estimate the small amount of scatter in the projection data. In this way, the narrow aperture data is scatter-corrected to become scatter-free data. For example, as described above, simple and effective scatter correction methods for narrow aperture data can include using the data in the shadow of the beam former collimator that forms the aperture for fitting, kernel-based scatter correction, etc. Referring to the narrow aperture data as scatter-free data can be the result of an initial scatter correction of the narrow aperture data.

[0083] The following flowcharts and block diagrams illustrate exemplary configurations and methods associated with scatter estimation and correction according to the above-described system. The exemplary methods may be implemented in logic, software, hardware, or a combination thereof. Additionally, although the programs and methods are presented in sequence, the blocks may be executed in a different order, including serially and / or in parallel. Moreover, additional steps or fewer steps may be used.

[0084] Figure 4 FIG. 4 is a flowchart depicting an exemplary method 400 for scatter estimation in the projection data domain using a scan design with a narrow scan region within a wide scan region (e.g., those described above). Narrow scan data 410 from the narrow region and wide scan data 420 from the wide region are provided or received, for example, from data acquisition using the imaging device 10 described above. As described above, for example, in Figure 3 FIG. 4, the narrow region is within the wide region. The narrow scan data 410 is scatter-free, while the wide scan data 420 contains scatter. In this embodiment, step 412 isolates the portion of the wide scan data 420 that overlaps with the narrow region. Next, at step 414, method 400 subtracts the narrow scan data 410 (scatter-free) from the isolated portion (with scatter) of the wide scan data 420 corresponding to the narrow region. The resulting data is the true (measured) scatter 416 in the narrow region.

[0085] At step 422, method 400 uses a scatter estimation technique to estimate the scatter in the wide scan data 420, which may include, for example, a kernel-based scatter estimation technique. Next, at step 424, the estimated scatter in the narrow region is isolated from the estimated scatter in the wide region. The resulting data is the estimated scatter 426 in the narrow region using the scatter estimation technique.

[0086] Then, at step 430, method 400 determines the difference between the true (measured) scatter 416 and the estimated scatter 426 in the narrow region. This difference can be used to optimize the scatter estimation technique at step 432. For example, the scatter estimation technique can be optimized by minimizing the difference between the estimated scatter 426 and the true scatter 416. Minimizing this difference can include various types of fitting processes. In a non-iterative embodiment, the optimization process can include a least-squares solution. Then, at step 434, the optimized (e.g., fitted kernel-based) scatter estimation technique can be used to re-estimate the scatter in the remaining wide scan data 420 with improved accuracy. The scatter estimation can be used in the reconstruction process of the wide region.

[0087] Figure 5It is a flowchart depicting another exemplary method 500 for performing scatter estimation in the projection data domain using a scan design with a narrow scan region within a wide scan region (e.g., those described above). Method 500 is similar to method 400, except that in this embodiment, at step 522, method 500 only uses scatter estimation techniques to initially estimate the scatter in the isolated portion of the wide scan data 420 that overlaps with the narrow region. This is less computationally intensive compared to estimating the scatter in the entire wide scan data 420 before isolating the narrow region (as in steps 422 and 424 of method 400). In this embodiment, the isolated wide scan data can directly come from step 412. The resulting data is the estimated scatter 426 in the narrow region using scatter estimation techniques. Other steps are performed as in method 400.

[0088] Figure 6 It is a flowchart depicting an exemplary iterative method 600 for performing scatter estimation in the projection data domain using a scan design with a narrow scan region within a wide scan region (e.g., those described above). Method 600 is similar to method 500, except that in this embodiment, after step 430, method 600 implements an iterative optimization of the scatter estimation technique. Specifically, at step 632, method 600 determines whether the difference between the true (measured) scatter 416 and the estimated scatter 426 in the narrow region requires further correction or optimization. In various embodiments, in order to determine at step 632 whether further correction is needed, the difference from step 430 (which represents the closeness of the estimated scatter 426 from the scatter estimation technique to the true scatter 416) can be subject to various conditions / analyses, including for example, the difference can be compared with a threshold, the difference between the current iteration and the previous iteration can be compared with a threshold or a threshold rate (e.g., to determine the convergence rate of the iterative / step - by - step improvement of the estimate), the number of iterations (looping back to step 522) can be compared with a threshold, the time associated with the scan and / or the iterative process can be compared with a threshold (e.g., to consider the overall workflow), combinations of these and / or other factors (including weighted averages), etc.

[0089] If the analysis at step 632 determines that the difference from step 430 requires further correction, method 600 proceeds to step 634 to optimize the scatter estimation technique taking into account the difference from step 430. For example, the scatter estimation technique can be optimized by minimizing the difference between the estimated scatter 426 and the true scatter 416. Minimizing the difference can include various types of fitting processes. In the case of multiple iterations, step 634 can be a further optimization.

[0090] If the analysis at step 632 determines that the differences from step 430 do not require further correction, method 600 proceeds to step 636, thereby applying an optimized (e.g., kernel-based and fit) scatter estimation technique to the remainder of the wide scan data 420 with increased accuracy.

[0091] In this manner, the acquired narrow aperture scan data, in combination with kernel-based scatter estimation, can be used to improve scatter estimation of wide aperture scan data in an imaging mode. For example, the imaging can include x-ray imaging, CT imaging, CBCT imaging, etc. Kernel-based scatter estimation and correction, including modified / optimized embodiments, can be used to improve image quality and quantification. A beam shaper (e.g., having a set of collimators) can effectively block portions of the beam to form an aperture for imaging, where the size of the aperture can be varied to allow for very narrow aperture data acquisition. The aperture position relative to the patient can vary with respect to the patient. In various embodiments, the kernel-based scatter estimation of data from a large aFOV (wide region) scan is compared to the measured scatter in a small aFOV (narrow region) at the same angle. The measured scatter is the result of subtracting the scatter-free data of the narrow aperture scan from data including scatter at the same region at the same angle / viewpoint.

[0092] The kernel-based scatter estimation can be optimized by minimizing the difference between the estimated scatter and the measured scatter. The optimized kernel-based scatter estimation can then be applied to the remainder of the large aFOV data to improve the accuracy of scatter correction.

[0093] As described above, the optimization of the scatter estimation technique can also occur in the reconstruction domain, where an image reconstructed from narrow aperture scan data can be considered a scatter-free image. For example, through a kernel-based scatter correction technique, the reconstruction of the same region from wide aperture scan data can be compared to the scatter-free image. The scatter correction technique can be optimized to minimize the difference. In some embodiments, e.g., for an intended clinical application, the difference can be focused only on certain image aspects. For example, if a wide aFOV image is used for radiotherapy adaptive planning, quantification accuracy is crucial for dose calculation, while low contrast recovery is crucial for tumor detection and contouring for dose planning.

[0094] Figure 7 is a flowchart depicting an exemplary method 700 for scatter correction in the reconstruction domain using a scan design (e.g., those described above) having a narrow scan region within a wide scan region. Narrow scan data 410 from the narrow region and wide scan data 420 from the wide region are provided or received, for example, from data acquisition using the imaging device 10 described above. As described above, for example, in Figure 3In it, the narrow region is within the wide region. The narrow scan data 410 is scatter-free, while the wide scan data 420 contains scatter. In this embodiment, step 712 reconstructs the narrow region using the narrow scan data 410. The resulting image is the scatter-free narrow region image 714.

[0095] At step 722, method 700 isolates and reconstructs the narrow region using the wide scan data 420 through a scatter correction technique, which can include, for example, a kernel-based scatter estimation / correction technique. The resulting image is the scatter-corrected narrow region image 724.

[0096] Then, at step 730, method 700 determines the difference between the scatter-free narrow region image 714 and the scatter-corrected narrow region image 724. This difference can be used to optimize the scatter correction technique at step 732. For example, the scatter correction technique can be optimized by minimizing the difference between the scatter-free narrow region image 714 and the scatter-corrected narrow region image 724. Minimizing the difference can include various types of fitting processes. In a non-iterative embodiment, the optimization process can include a least squares solution. Then, at step 734, the optimized (e.g., fitted kernel-based) scatter correction technique can be used to reconstruct the wide region using the wide scan data 420 with improved accuracy.

[0097] Figure 8 is a flowchart depicting an exemplary iterative method 800 for scatter correction in a reconstruction domain using a scan design (such as those described above) having a narrow scan region within a wide scan region. Method 800 is similar to method 700, except that in this embodiment, after step 730, method 800 implements iterative optimization of the scatter correction technique. Specifically, at step 832, method 800 determines whether the difference between the scatter-free narrow region image 714 and the scatter-corrected narrow region image 724 requires further correction or optimization. In various embodiments, to determine at step 832 whether further correction is needed, the difference from step 730 (which represents the closeness of the scatter-corrected narrow region image 724 to the scatter-free narrow region image 714 using the scatter correction technique) can be subject to various conditions / analyses, including, for example, comparing the difference to a threshold, comparing the difference between the current iteration and a previous iteration to a threshold or a threshold rate (e.g., to determine the convergence rate of the progressive improvement of the corrected image), comparing the number of iterations (looping back to step 722) to a threshold, comparing the time associated with the scan and / or iterative process to a threshold (e.g., to consider the overall workflow), combinations of these and / or other factors (including weighted averages), etc.

[0098] If the analysis at step 832 determines that the differences from step 730 require further correction, method 800 proceeds to step 834 to optimize the scatter correction technique taking into account the differences from step 730. For example, the scatter correction technique can be optimized by minimizing the difference between the scatter-free narrow region image 714 and the scatter-corrected narrow region image 724. Minimizing the difference can include various types of fitting processes. In the case of multiple iterations, step 834 can be a further optimization.

[0099] If the analysis at step 832 determines that the differences from step 730 do not require further correction, method 800 proceeds to step 836 to reconstruct the wide region by applying the optimized (e.g., kernel-based and fitted) scatter correction technique to the remainder of the wide scan data 420 with increased accuracy.

[0100] As described above, a clinically valid protocol can be used to acquire the narrow aperture data. In these embodiments, the data can be used to accurately reconstruct an image of the region of the patient. An image reconstructed from the large aFOV data of the same region of the patient can be compared to the image from the narrow aperture reconstruction. The kernel-based scatter correction of the large aFOV data (wide region) can be optimized such that the reconstructed image matches the narrow aperture image at the same region (narrow region). Thus, the image reconstructed for the remainder of the wide region is improved by the optimized kernel-based scatter correction. In one embodiment, the kernel-based scatter correction can be optimized by matching the large aFOV (wide region) image and the narrow aperture image at the same region (narrow region) of the patient using clinically desired criteria. For example, one criterion is to match the low contrast recovery for tumor detection and contouring. Another criterion is to match the quantitative accuracy for dose simulation and dose planning for adaptive radiotherapy.

[0101] Various factors can be considered to determine whether to perform the above methods in the projection data domain and / or the reconstruction domain, including for example based on accuracy, time, workflow, available data, etc. In some cases, only one domain is possible, or one domain may be more preferred. For example, referring to Figure 3 , where the narrow region beam 320 is tilted as shown, the narrow aperture data does not allow for the reconstruction of an accurate image. Thus, the narrow scan data associated with the narrow region 322 can be used only to improve the scatter estimation in the projection domain.

[0102] In various embodiments, the reconstruction of the image can be analytical reconstruction and / or iterative reconstruction.

[0103] Various techniques can be used to determine and / or optimize for the narrow region (e.g., as Figure 3As shown in, details of the narrow scan (including number, axial position, angle, size, narrow / width dimension ratio, etc.) of 318, 322). In embodiments where the wide scan has not been completed, determining the details of the narrow scan may also include determining the details of the wide scan, including, for example, number, size, ratio, etc. An optimization process may be performed to determine the details of the narrow and / or wide scan (including number, axial position, angle, size, narrow / width dimension ratio, etc.) to optimize the various factors described above, including total scan time, workflow, etc. For example, in some embodiments, the narrow scan may be determined from a previous image (e.g., a planned CT image, a CBCT image from a previous treatment sub - section, etc.). In some embodiments, the narrow scan may be selected from a predetermined narrow scan library suitable for a specific wide area, including based on typical uniformity / variance and narrow areas suitable as a basis for the wider area. In other embodiments, for example, when a previous image is not available, the narrow scan may be determined on - the - fly by using an image reconstructed from a scout scan and / or a wide area scan.

[0104] For example, in one embodiment, after sufficient data has been acquired in the wide area scan for acceptable image reconstruction, reconstruction of the relatively fast wide scan data may be started. Then the reconstructed image of the wide area may be used to identify one or more narrow scans, for example, based on the following: uniformity (or lack of uniformity) of the wide area, axial length, use of a clinical protocol or a protocol only for scatter correction (which may include a smaller projection angle, a larger pitch, etc. for helical scans). In some embodiments, other factors, such as workflow, may be considered when determining the number of narrow scans. In one embodiment, a computer algorithm / analysis may automatically determine the details of the narrow scan based on the reconstructed image of the wide area. In another embodiment, the user may determine the details of the narrow scan based on a review of the reconstructed image of the wide area. Then the narrow area information may be fed back into the system to control the narrow scan.

[0105] For example, Figure 9is a flowchart depicting an exemplary method 900 for determining a narrow scan from prior image data for narrow / wide scan designs (such as those described above). Prior patient image data 905 (e.g., a prior image, which may be a previously acquired planning image, including a prior CT image) may be provided or received, for example, from another source or using data acquisition of the above-described x-ray imaging device 10. At step 910, as described above, method 900 determines the details of the narrow scan based on the prior image data 905. As described above, in this embodiment, determining the details of the narrow scan may include determining the details of the wide scan, including an optimization process. Then, at step 920, method 900 initiates a narrow region scan and a wide region scan, for example, using the above-described imaging device 10. The resulting data is narrow scan data 410 for the narrow region and wide scan data 420 for the wide region. The scan data 410, 420 may be used according to the above-described scatter estimation and correction methods.

[0106] In another embodiment, Figure 10 is a flowchart depicting an exemplary method 1000 for determining a narrow scan from wide scan data for narrow / wide scan designs (such as those described above). At step 1010, method 1000 performs a wide region scan of a patient, for example, using the above-described imaging device 10 to support imaging and / or treatment purposes. The resulting data is wide scan data 420 for the wide region. Then, at step 1020, method 1000 begins to reconstruct the wide scan data 420. At step 1030, based at least in part on a partially reconstructed image of the patient, method 1000 determines the details of the narrow scan based on the reconstructed image, as discussed above. Then, at step 1040, method 1000 initiates a narrow scan, for example, using the above-described imaging device 10. The resulting data is narrow scan data 410 for the narrow region. The scan data 410, 420 may be used according to the above-described scatter estimation and correction methods.

[0107] In this way, the narrow aperture scan (including, for example, the number, position, angle, size, etc.) can be determined using prior images or determined on the fly when data / image information from a wide aperture scan is available. For example, when determining the size and position of the narrow aperture scan and the angle for acquiring narrow aperture data on the fly, an image of the patient is first obtained from the wide region scan. Then, a portion or all of the wide scan data is used to obtain an image of the patient, including image reconstruction (simultaneous reconstruction / acquisition) while the large aFOV data acquisition (wide region scan) is still in progress or reconstruction after the large aFOV scan is completed. The determination of the narrow aperture scan details can use an algorithm / software that uses image non-uniformity determined from the acquired patient image.

[0108] When the above devices and methods are used for scatter correction in the projection domain, they can be applied to each projection view, where each projection view is a planar image. In one embodiment, using planar x-ray images (e.g., for motion tracking), previously available volume images can be used with kernel-based scatter estimation techniques to estimate scatter in the planar image for scatter correction (e.g., to improve contrast). The above methods can utilize scatter measured in the narrow aperture data to improve kernel-based scatter estimation.

[0109] In another embodiment, a planar image can first be acquired through the wide aperture and collimator shadow regions. Next, the collimator shadow can be used to estimate scatter in the planar image using shadow fitting techniques. Then, the narrow aperture data can be used to measure scatter in the narrow region. This result can be used to correct the shadow fitting technique used for wide aperture scatter estimation.

[0110] Compared with the prior art, the above devices and methods have several advantages. For example, the devices and methods can improve the performance of conventional kernel-based scatter estimation and correction methods in CBCT. In particular, these improvements can be demonstrated in the context of scans of regions with highly heterogeneous patients and having a large axial field of view.

[0111] In one embodiment, compared with conventional kernel-based methods, when optimized for the region covered by the narrow aperture, using a kernel-based model for scatter estimation / correction is more accurate for the rest of the wide region. The narrow aperture data (scatter-free) provides complementary information to optimize or constrain the kernel-based model, thereby improving the accuracy of the kernel-based model during the scatter estimation / correction process. In this way, the optimization process can be very straightforward but very effective.

[0112] As described above, the narrow region scan can use a clinically effective protocol that allows accurate reconstruction of the narrow region covered by the aperture. Thus, the dose and scan time associated with the narrow scan are fully utilized without waste. In other embodiments, the narrow region scan can be used only for scatter correction purposes. In these embodiments, the acquisition can use fast gantry rotation and / or acquire angularly sparse data. Thus, the impact of the narrow region scan on patient dose and scan time can be minimized.

[0113] Various embodiments can utilize different scan geometries, detector positioning (including offset detectors), and / or beam shaper window shapes. In some embodiments, if the detector is centered, the narrow and / or wide scan trajectories can be 180 degrees, while if the detector is offset, the narrow and / or wide scan trajectories can be up to 360 degrees.

[0114] As described above, aspects of the disclosed technology can be used in radiotherapy devices and methods that utilize an integrated kilovolt (kV) CT for use in conjunction with or as part of IGRT. According to one embodiment, the image acquisition method includes or otherwise utilizes a helical source trajectory (e.g., continuous source rotation about a central axis and longitudinal movement of the patient support through the gantry aperture) or a circular scan with kV beam collimation, and a rapid slip-ring rotation, e.g., to provide kV CT imaging on a radiotherapy delivery platform. It should be understood that such an implementation can provide reduced scatter and improved scatter estimation to achieve higher quality kV images than conventional systems.

[0115] It will be further understood that any potential increased scan time associated with multiple beam rotations to complete a volumetric image can be mitigated or otherwise offset by high kV frame rates, high gantry rates, and / or sparse data reconstruction techniques. It will also be recognized that the selectively controllable collimator / beam shaper provided above allows for systems where the user can trade off or otherwise vary the relationship between image acquisition time and image quality according to specific applications and / or clinical needs. It should also be understood that the radiotherapy delivery device can be controlled to provide a half-rotation or single-rotation cone beam CT scan with a rapid image acquisition time (e.g., for motion tracking) that may have reduced image quality due to scatter, as well as a circular or continuous helical acquisition through a narrow / slit fan beam that has a longer acquisition time but improved image quality due to reduced scatter. One or more optimization processes can also be applied to all of the above embodiments to determine beam positioning, determine read ranges, estimate scatter, etc.

[0116] Figure 11is a flowchart depicting an exemplary method 1100 of IGRT using a radiotherapy device (including, for example, imaging device 10). Patient prior image data 1105 can be used (e.g., prior images, which can be previously acquired planning images, including prior CT images, as described above). In some embodiments, the prior image data 1105 is generated by the same radiotherapy device but at an earlier time. At step 1110, imaging of the patient is performed using a low-energy radiation source (e.g., kV radiation from x-ray source 30). In one embodiment, the imaging includes a circular scan with a fan beam or cone beam geometry. Step 1110 can use the above-described scatter estimation and correction techniques to produce high-quality (HQ) images or imaging data 1115. In some embodiments, the image quality can be adjusted to optimize the balance between image quality / resolution and dose. In other words, not all images need to have the highest quality, or the image quality can be adjusted to optimize or trade off the balance between image quality / resolution and image acquisition time. The imaging step 1110 can also include image processing 1120 for generating a patient image based on the imaging / scan data (e.g., according to the method described above). Although the image processing step 1120 is shown as part of the imaging step 1110, in some embodiments, the image processing step 1120 is a separate step, including image processing performed by a separate device.

[0117] Next, at step 1130, one or more pre-irradiation image-based steps discussed below are performed, at least in part based on the imaging data 1115 from step 1110. As discussed in more detail below, step 1130 can include: determining various parameters associated with the therapeutic treatment and (subsequent) imaging plan. In some embodiments, the pre-irradiation image-based step (1130) may require additional imaging (1110) before radiotherapy delivery (1140). Step 1130 can include adjusting the treatment plan based on the imaging data 1115 as part of an adaptive radiotherapy routine. In some embodiments, the pre-irradiation image-based step 1130 can include real-time treatment planning. Embodiments can also include simultaneous, overlapping, and / or alternating activation of the imaging and therapeutic radiation sources. Real-time treatment planning may involve any one or all of these types of imaging and treatment radiation activation techniques (simultaneous, overlapping, and / or alternating).

[0118] Next, at step 1140, a therapeutic treatment delivery is performed using a high-energy radiation source (e.g., MV radiation from the therapeutic radiation source 20). Step 1140 delivers a treatment dose 1145 to the patient according to the treatment plan. In some embodiments, the IGRT method 1100 can include returning to step 1110 to perform additional imaging at various intervals, followed by pre-irradiation image-based steps (1130) and / or radiotherapy delivery (1140) as needed. In this way, a device 10 capable of adaptive treatment can be used during IGRT to generate and utilize high-quality imaging data 1115. As described above, steps 1110, 1130, and / or 1140 can be performed simultaneously, overlapping, and / or alternately.

[0119] IGRT can include at least two general goals: (i) delivering a highly conformal dose distribution to the target volume; (ii) delivering the treatment beam with high accuracy throughout the course of each treatment fraction. A third goal can be to accomplish the two general goals in as little time as possible per fraction. Delivering the treatment beam accurately requires the ability to identify and / or track the position of the target volume within the fraction using high-quality images. The ability to increase the delivery speed requires the ability to move the radiation source accurately, precisely, and quickly according to the treatment plan.

[0120] Figure 12 FIG. 1200 is a block diagram depicting exemplary pre-irradiation image-based steps / options that can be associated with step 1130 above. It will be understood that, without departing from the scope of the present invention, the imaging device 10 described above (e.g., as part of a radiotherapy device) can generate kV images that can be used in a variety of ways, including for pre-irradiation image-based steps (1130). For example, the image 1115 generated by the radiotherapy device can be used to align the patient (1210) before treatment. Patient alignment can include correlating or registering the current imaging data 1115 with imaging data associated with an earlier pre-treatment scan and / or plan (including the treatment plan). Patient alignment can also include feedback regarding the physical position of the patient relative to the radiation source to verify that the patient is within the range of the delivery system. If necessary, the patient can be adjusted accordingly. In some embodiments, the patient alignment imaging can be purposefully of lower quality to minimize dose but provide sufficient alignment information.

[0121] The images generated by the imaging device 10 can also be used for treatment planning or replanning (1220). In various embodiments, step 1220 can include validating a treatment plan, modifying a treatment plan, generating a new treatment plan, and / or selecting a treatment plan from a set of treatment plans (sometimes referred to as a “daily plan”). For example, if the imaging data 1115 indicates that the target volume or ROI is the same as when the treatment plan was developed, the treatment plan can be validated. However, if the target volume or ROI is different, a replan of the therapeutic treatment may be required. In the case of a replan, due to the high quality of the imaging data 1115 (generated by the x-ray imaging device 10 at step 1110), the imaging data 1115 can be used for treatment planning or replanning (e.g., generating a new or modified treatment plan). In this way, pre-treatment CT imaging via a different device is not required. In some embodiments, validation and / or replanning can be an ongoing procedure before and / or after various treatments.

[0122] According to another exemplary use case, the images generated by the imaging device 10 can be used to calculate an imaging dose (1230), which can be used for determining the total dose to the patient ongoing and / or for subsequent imaging planning. The quality of subsequent imaging can also be determined as part of the treatment plan, e.g., to balance quality and dose. According to another exemplary use case, the images generated by the imaging device 10 can be used to calculate a treatment dose (1240), which can be used for determining the total dose to the patient ongoing and / or can be included as part of a treatment plan or replan.

[0123] According to other exemplary use cases, the images generated by the imaging device 10 can be used in conjunction with planning or adjusting other imaging (1250) and / or other treatment (1260) parameters or plans, e.g., including as part of adaptive treatment and / or treatment plan generation. According to another exemplary use case, the images generated by the imaging device 10 can be used in conjunction with adaptive treatment monitoring (1270), which can include monitoring radiotherapy delivery and adapting as needed.

[0124] It should be understood that the pre-treatment image-based steps (1130) are not mutually exclusive. For example, in various embodiments, calculating a treatment dose (1240) itself can be a step and / or can be part of adaptive treatment monitoring (1270) and / or treatment planning (1220). In various embodiments, the pre-treatment image-based steps (1130) can be performed automatically and / or manually with human involvement.

[0125] The above-described apparatus and method, including adjustable collimation (aperture) of image radiation and a scatter estimation and correction scheme, provide improved scatter estimation, which results in higher quality kV-generated images compared to conventional imaging systems used in treatment with CBCT.

[0126] Figure 13 FIG. 1300 is a block diagram depicting exemplary data sources that may be used during imaging (1110) and / or subsequent image-based steps (1130) prior to irradiation. Detector data 1310 represents all data received by the image radiation detector 34. Projection data 1320 is data generated by radiation incident in the collimated beam region (referred to above as the scan region). Penumbra data 1330 is data generated by radiation incident in the penumbra region. As described above, scatter data 1340 is data generated by radiation incident in the peripheral region outside the penumbra region. In another embodiment, scatter data 1340 may be used to determine the residual effects of scatter from the therapeutic radiation source 20 (e.g., MV) when the two sources 20, 30 are operating simultaneously or in a staggered manner.

[0127] In this way, penumbra data 1330 and / or scatter data 1340 may be used to improve the quality of the images generated by the imaging step 1110. In some embodiments, penumbra data 1330 and / or scatter data 1340 may be combined with projection data 1320 and / or may be analyzed in accordance with applicable imaging settings 1350, treatment settings 1360 (e.g., if imaging and treatment radiation are simultaneous), and any other data 1370 associated with the imaging device 10 when data is collected at the imaging detector 34. In other embodiments, the data may be used in the treatment planning step 1130.

[0128] Although the disclosed techniques have been shown and described with respect to certain aspects, one or more embodiments, it will be apparent to other persons skilled in the art upon reading and understanding this specification and the accompanying drawings that equivalent variations and modifications will occur to them. In particular, with respect to the various functions performed by the above-described elements (components, assemblies, devices, members, compositions, etc.), unless otherwise specified, the terms used to describe such elements (including references to "means") are intended to correspond to any element that performs the specified function of the element (i.e., functionally equivalent), even if not structurally equivalent to the disclosed structure that performs the function in the exemplary aspects or embodiments of the disclosed techniques shown herein. Additionally, although the above may have described a particular feature of the disclosed techniques with respect to only one or more of several illustrated aspects or embodiments, that feature may be combined with one or more other features of other embodiments as desired and this may be advantageous for any given or particular application.

[0129] Although the embodiments discussed herein have been related to the systems and methods discussed above, these embodiments are intended to be exemplary and are not intended to limit the applicability of these embodiments to only those discussions set forth herein. Although the invention has been illustrated by the description of its embodiments and although the embodiments have been described in detail, it is not the intention of the applicant to restrict or in any way limit the scope of the appended claims to these details. Other advantages and modifications will be apparent to those skilled in the art. Accordingly, the invention in its broader aspects is not limited to the specific details, representative devices and methods, and illustrative examples shown and described. Accordingly, departures may be made from such details without departing from the spirit or scope of the applicant's general inventive concept.

Claims

1. An imaging device, comprising: A rotating imaging source for emitting a radiation beam; A detector positioned to receive the radiation from the imaging source; And A beam former configured to adjust the shape of the radiation beam emitted by the imaging source such that the shape of the radiation beam is configured for wide-aperture scanning of a wide axial region and narrow-aperture scanning of a narrow axial region within the wide axial region; A data processing system configured at least to: Determine an estimated scatter in the wide axial region using a scatter estimation technique optimized by minimizing the difference between the measured scatter in the narrow axial region and the estimated scatter in the narrow axial region; And Reconstruct a scatter-corrected wide axial region image using a scatter estimation technique optimized by minimizing the difference between the calculated scatter-free narrow region image and the scatter-corrected narrow region image.

2. The imaging device according to claim 1, further comprising: A data processing system configured to: Receive the measured projection data in the wide axial region and the narrow axial region; And Determine the estimated scatter in the wide axial region using a kernel-based technique.

3. The imaging device according to claim 1, wherein, The wide-aperture scanning and the narrow-aperture scanning include circular scanning.

4. A method for estimating scatter in an image, comprising: Receiving measured projection data from wide-aperture scanning of a wide axial region and narrow-aperture scanning of a narrow axial region within the wide axial region; Determining the measured scatter in the narrow axial region based on the projection data of the narrow-aperture scanning and the projection data of the wide-aperture scanning overlapping the narrow axial region; Using a scatter estimation technique to determine the estimated scatter in the narrow axial region based on the projection data of the wide-aperture scanning overlapping the narrow axial region; Calculating the difference between the measured scatter in the narrow axial region and the estimated scatter in the narrow axial region; Optimizing the scatter estimation technique by minimizing the difference between the measured scatter in the narrow axial region and the estimated scatter in the narrow axial region; And Using the optimized scatter estimation technique to determine the estimated scatter in the wide axial region based on the projection data of the wide-aperture scanning.

5. The method according to claim 4, wherein Determining the measured scatter in the narrow axial region includes: subtracting the projection data of the narrow-aperture scanning from the projection data of the wide-aperture scanning overlapping the narrow axial region.

6. The method according to claim 4 further comprises: Isolating the projection data of the wide-aperture scanning overlapping the narrow axial region from the projection data of the wide-aperture scanning.

7. The method according to claim 4, further comprising: Isolating the estimated scatter in the narrow axial region from the estimated scatter in the wide axial region.

8. The method according to claim 4 further comprises: Based on the difference between the measured scatter in the narrow axial region and the estimated scatter in the narrow axial region, determining whether the scatter estimation technique should be corrected, wherein optimizing the scatter estimation technique includes: an iterative correction process.

9. The method according to claim 8, wherein, Determining whether the scatter estimation technique should be corrected includes: comparing the difference between the measured scatter in the narrow axial region and the estimated scatter in the narrow axial region with a threshold.

10. The method according to claim 4, wherein, The scatter estimation technique includes a kernel-based scatter estimation technique, and wherein optimizing the scatter estimation technique includes: constraining the kernel-based scatter estimation technique.

11. The method according to claim 4 further comprises: Determine the position of the narrow axial region based on a previous image.

12. The method according to claim 4 further comprises: Determine the position of the narrow axial region based on projection data from the wide-aperture scan.

13. The method according to claim 4, wherein The narrow axial region includes a plurality of narrow axial regions within the wide axial region.

14. A method for correcting scatter in an image, comprising: Receiving projection data measured from a wide-aperture scan of a wide axial region and a narrow-aperture scan of a narrow axial region within the wide axial region; Reconstructing a scatter-free narrow region image based on the projection data of the narrow-aperture scan; Using a scatter correction technique, reconstructing a scatter-corrected narrow region image based on the projection data of the wide-aperture scan that overlaps with the narrow axial region; Calculating the difference between the scatter-free narrow region image and the scatter-corrected narrow region image; Optimizing the scatter correction technique by minimizing the difference between the scatter-free narrow region image and the scatter-corrected narrow region image; And Using the optimized scatter correction technique, reconstructing a scatter-corrected wide region image based on the projection data of the wide-aperture scan.

15. The method according to claim 14 further comprises: Determine whether the scatter correction technique should be corrected based on the difference between the scatter-free narrow region image and the scatter-corrected narrow region image, wherein optimizing the scatter correction technique includes: an iterative correction process.

16. The method according to claim 15, wherein, Determining whether the scatter correction technique should be corrected includes: comparing the difference between the scatter-free narrow region image and the scatter-corrected narrow region image with a threshold.

17. The method according to claim 14, wherein The scatter correction technique includes a kernel-based scatter correction technique, and wherein optimizing the scatter correction technique includes: constraining the kernel-based scatter correction technique.

18. The method according to claim 14 further comprises: Determine the position of the narrow axial region based on a previous image.

19. The method according to claim 14 further comprises: Determine the position of the narrow axial region based on the reconstruction of projection data from the wide-aperture scan.

20. A radiotherapy delivery device, comprising: A rotatable gantry system positioned at least partially around a patient support; A first radiation source coupled to the rotatable gantry system, the first radiation source being configured as a therapeutic radiation source; A second radiation source coupled to the rotatable gantry system, the second radiation source being configured as an imaging radiation source having an energy level lower than that of the therapeutic radiation source; A radiation detector coupled to the rotatable gantry system and positioned to receive radiation from the second radiation source; A beam shaper configured to adjust the shape of the radiation beam emitted by the second radiation source such that the shape of the radiation beam is configured for a wide-aperture scan of a wide axial region and a narrow-aperture scan of a narrow axial region within the wide axial region; and A data processing system configured to: Receive measured projection data in the wide axial region and the narrow axial region; Using a scatter estimation technique optimized by minimizing the difference between the measured scatter in the narrow axial region and the estimated scatter in the narrow axial region, determine the estimated scatter in the wide axial region; and Reconstruct a patient image based on the estimated scatter, wherein the reconstruction includes constructing a scatter-corrected wide-area image using a scatter estimation technique optimized by minimizing the difference between the calculated scatter-free narrow-area image and the scatter-corrected narrow-area image; and During adaptive image-guided radiotherapy (IGRT), deliver a therapeutic radiation dose to the patient via the first radiation source based on the patient image.

Images