Methods and apparatus for improving scatter assessment and scatter correction in imaging

Abstract

An X-ray imaging apparatus and related method are provided that receive measured projection data 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 determine estimated scatter in the wide axial region using an optimized scatter estimation technique. The optimized scatter estimation technique is based on the difference between the measured scatter in the narrow axial region and the estimated scatter in the narrow axial region. A kernel-based scatter estimation / scatter correction technique can be fitted to minimize the scatter difference in the narrow axial region. The fitted (optimized) kernel-based scatter estimation / scatter correction is then applied to the wide axial region. The optimization can occur in the projection data domain or the reconstruction domain. An iterative process can also be utilized.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation of U.S. Provisional Patent Application No. 62 / 773,712 (Attorney Docket No. 38935 / 04001), filed November 30, 2018; U.S. Provisional Patent Application No. 62 / 773,700 (Attorney Docket No. 38935 / 04002), filed November 30, 2018; and U.S. Provisional Patent Application No. 62 / 796,831 (Attorney Docket No. U.S. Provisional Patent Application No. 62 / 800,287 (Attorney Docket No. 38935 / 04003), filed February 1, 2019; U.S. Provisional Patent Application No. 62 / 801,260 (Attorney Docket No. 38935 / 04006), filed February 5, 2019; U.S. Provisional Patent Application No. 62 / 813,335 (Attorney Docket No. 38935 / 04004), filed March 4, 2019 No. 38935 / 04007; U.S. Provisional Patent Application No. 62 / 821,116, filed March 20, 2019 (Attorney Docket No. 38935 / 04009); U.S. Provisional Patent Application No. 62 / 836,357, filed April 19, 2019 (Attorney Docket No. 38935 / 04016); U.S. Provisional Patent Application No. 62 / 836,352, filed April 19, 2019 No. 62 / 843,796, filed May 6, 2019 (Attorney Docket No. 38935 / 04005); and U.S. Provisional Patent Application No. 62 / 878,364, filed July 25, 2019 (Attorney Docket No. 38935 / 04008). This application is also incorporated by reference in its entirety as follows: Attorney Docket No. 38935 / 04019, entitled "MULTIMODAL RADIATION APPARATUS AND METHODS"; Attorney Docket No. 38935 / 04020, entitled "APPARATUS AND METHODS FOR SCALABLE FIELD OF VIEW IMAGING USING A MULTI-SOURCE SYSTEM"; Attorney Docket No. 38935 / 04011, entitled "INTEGRATED HELICAL FAN-BEAM COMPUTED TOMOGRAPHY IN IMAGE-GUIDED RADIATION TREATMENT DEVICE";Attorney Docket No. 38935 / 04010, entitled "COMPUTED TOMOGRAPHY SYSTEM AND METHOD FOR IMAGE IMPROVEMENT USING PRIOR IMAGE"; Attorney Docket No. 38935 / 04013, entitled "OPTIMIZED SCANNING METHODS AND TOMOGRAPHY SYSTEM USING REGION OF INTEREST DATA"; Attorney Docket No. 38935 / 04015, entitled "HELICAL CONE-BEAM COMPUTED TOMOGRAPHY IMAGING WITH AN OFF-CENTERED DETECTOR"; Attorney Docket No. 38935 / 04021, entitled "MULTI-PASS COMPUTED TOMOGRAPHY SCANS FOR IMPROVED WORKFLOW AND PERFORMANCE"; and Attorney Docket No. 38935 / 04021, entitled "METHOD AND APPARATUS FOR SCATTER ESTIMATION IN CONE-BEAM COMPUTED This application relates to ten concurrently filed non-provisional U.S. patent applications, including Attorney Docket No. 38935 / 04012, entitled "ASYMMETRIC SCATTER FITTING FOR OPTIMAL PANEL READOUT IN CONE-BEAM COMPUTED TOMOGRAPHY"; Attorney Docket No. 38935 / 04014, entitled "ASYMMETRIC SCATTER FITTING FOR OPTIMAL PANEL READOUT IN CONE-BEAM COMPUTED TOMOGRAPHY"; and Attorney Docket No. 38935 / 04022, entitled "METHOD AND APPARATUS FOR IMAGE RECONSTRUCTION AND CORRECTION USING INTER-FRACTIONAL INFORMATION." The contents of all of the above-identified patent application(s) and patent(s) are incorporated herein by reference in their entirety.

[0002] Aspects of the disclosed techniques relate to assessing scatter in projection data, and more particularly to the use of narrow aperture scans to assess scatter in wider aperture scans, including X-ray, computed tomography (CT), and cone-beam computed tomography (CBCT) scans, during various imaging techniques. [Background technology]

[0003] Scatter in cone-beam CT can account for a significant fraction of detected photons, especially when an anti-scatter grid is not used with a wide collimation aperture. Scatter can negatively impact image quality, including contrast and quantitative accuracy. Consequently, scatter measurement, scatter assessment, and scatter correction can be applied to cone-beam CT data processing and image reconstruction, including in the context of image-guided radiation therapy (IGRT). IGRT utilizes medical imaging modalities, such as CT, to collect images of patients before, during, and / or after treatment.

[0004] For flat-panel cone-beam computed tomography (CBCT), a pair of highly attenuated blades as part of the collimator is used to create an aperture that limits the axial extent of the x-ray beam within the patient / panel. A larger aperture allows for a larger axial coverage of the patient during the scan. Therefore, using a wider aperture can reduce the total scan time when a larger axial extent of the patient needs to be imaged. However, the amount of scatter also increases with the aperture, although the primary data remains similar. Without scatter correction, the increased scatter negatively impacts image quality and volume.

[0005] Hardware-based scatter reduction includes the use of anti-scatter grids on the detector panel surface, very narrow apertures, dose compensation filters, and the use of air separation between the patient and the detector. Traditional anti-scatter grids can significantly reduce the amount of x-ray scatter. A major drawback is that the system is more complex and also reduces the amount of primary data. Using very narrow apertures, scatter can be significantly reduced (effectively to negligible levels). However, the axial coverage is very small, resulting in an impractical overall scan time.

[0006] Software-based scatter reduction / scatter correction can evaluate scatter in acquired data using physical models. These methods can examine both the data acquisition system and the interaction process between x-rays and matter. The former requires detailed knowledge of the key components of the overall imaging chain and patient information, which can be obtained from treatment planning CT or initial reconstructions that do not include scatter correction. These methods can be achieved either probabilistically (e.g., Monte Carlo simulation-based approaches) or deterministically (e.g., radiative transfer equation-based approaches). The former is computationally expensive, while the latter is generally considered an open problem in the field. Model-based methods are typically patient-specific and can be more accurate. However, they require a significant amount of prior information about the data acquisition system and the patient. The effectiveness of these methods is highly dependent on the accuracy of the modeling. Furthermore, these methods have high demands in terms of computational power and time, which significantly negatively impact workflow and throughput. The estimated scatter is then used to correct data prior to or during image reconstruction.

[0007] Software-based scatter correction approaches include kernel-based scatter estimation and correction. In kernel-based approaches, the scatter kernel is determined by physical measurements or Monte Carlo simulations that estimate a complex of materials. For example, one typical approach is to measure scatter kernels with different water layer thicknesses for a given X-ray spectrum and aperture. The aperture projected onto the detector plane is equivalent to the axial dimension of the panel. When kernels for different water layers are measured / determined, the kernels are used for scatter correction in patient scans, estimating that the patient's tissue is equivalent to water layers of different thicknesses. The application of kernels for scatter estimation and correction can include scatter deconvolution using kernels in either the spatial or frequency domain. Furthermore, it can adapt to the local variance of the object. For example, the measured scatter data can be considered to be the result of the superposition of a primary kernel and a scatter kernel. By performing the deconvolution process and using appropriate pre-constructed kernels, the primary and scatter components can be separated.

[0008] Kernel-based scatter estimation / correction is widely used in CBCT due to its simplicity. However, a fundamental challenge with this type of approach is that its accuracy can deteriorate when the patient tissue distribution is highly non-uniform, especially in the chest and pelvic regions. Furthermore, when the aperture size is large, the performance of the approach can deteriorate due to the enhanced scattering associated with the large aperture. Summary of the Invention

[0009] In one embodiment, the imaging device includes a rotating imaging source for emitting a radiation beam, a detector positioned to receive radiation from the imaging source, and a beamformer configured to adjust the shape of the radiation beam emitted by the imaging source for wide aperture scanning of a wide axial region and narrow aperture scanning of a narrow axial region within the wide axial region, where estimated scatter in the wide axial region is based on projection data from the narrow axial region.

[0010] Features described and / or illustrated with respect to one embodiment may be used in the same or similar manner in one or more other embodiments and / or in combination with or in place of features of the other embodiments.

[0011] The description of the invention does not limit the words used in the claims or the scope of the claims or the invention in any way. Terms used in the claims have all of their full ordinary meanings.

[0012] In the accompanying drawings, which are incorporated in and constitute a part of this specification, embodiments of the present specification are illustrated and, together with the general description of the invention provided above and the detailed description provided below, serve to illustrate embodiments of the present invention. It will be understood that the boundaries of elements illustrated 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 component may be implemented as an external component, and vice versa. Furthermore, elements may not be drawn to scale. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a perspective view of an exemplary X-ray imaging device in accordance with one aspect of the disclosed technique. [Figure 2] FIG. 1 is a schematic diagram of an X-ray imaging device integrated into an exemplary radiation therapy device, in accordance with one aspect of the disclosed technique. [Figure 3] FIG. 1 is a schematic diagram of an exemplary scan design for imaging an axial region of a target. [Figure 4] 10 is a flowchart illustrating an exemplary method for scattering estimation in the domain of projection data using a scan design with a narrow scan region within a wider scan region. [Figure 5] 10 is a flowchart illustrating another exemplary method for scattering estimation in the domain of projection data using a scan design having a narrow scan region within a wider scan region. [Figure 6] 10 is a flowchart illustrating an exemplary iterative method for scattering estimation in the domain of projection data using a scan design having a narrow scan region within a wide scan region. [Figure 7] 10 is a flowchart illustrating an exemplary method for scatter correction in the reconstruction domain using a scan design having a narrow scan region within a wide scan region. [Figure 8] 10 is a flowchart illustrating an exemplary iterative method for scatter correction in the reconstruction domain using a scan design having a narrow scan region within a wide scan region. [Figure 9] 1 is a flowchart illustrating an exemplary method for determining a narrow scan from prior image data for use in narrow / wide scan design. [Figure 10] 10 is a flowchart illustrating an exemplary method for determining a narrow scan from wide scan data for use in a narrow / wide scan design. [Figure 11] 1 is a flowchart illustrating an exemplary method of IGRT using a radiation therapy device. [Figure 12]FIG. 1 is a block diagram illustrating an exemplary image-based pre-delivery step. [Figure 13] FIG. 1 is a block diagram representing exemplary data sources that may be used during imaging or image-based pre-delivery steps. DETAILED DESCRIPTION OF THE INVENTION

[0014] The following include definitions of exemplary terms that may be used throughout this disclosure: Both the singular and plural forms of all words are within their respective meanings.

[0015] As used herein, a "component" may be defined as a portion of hardware, a portion of software, or a combination thereof. A portion of hardware includes at least a processor and a portion of memory, which includes instructions for execution. A component may be associated with an apparatus.

[0016] As used herein, "logic," which is synonymous with "circuitry," includes, but is not limited to, hardware, firmware, software, and / or combinations of each for performing one or more functions or operations. For example, based on the desired application or need, logic may include discrete logic such as a software-controlled microprocessor, an application-specific integrated circuit (ASIC), or other programmed logic device and / or controller. Logic may also be embodied entirely as software.

[0017] As used herein, a "processor" includes, but is not limited to, one or more of substantially any number of processor systems, such as microprocessors, microcontrollers, central processing units (CPUs), and digital signal processors (DSPs), in any combination, or stand-alone processors. A 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), clocks, decoders, memory controllers, or interrupt controllers. These support circuits may be internal or external to the processor or its associated electronic package. The support circuits are in operative communication with the processor. The support circuits are not necessarily shown separate from the processor in block diagrams or other illustrations.

[0018] As used herein, a "signal" includes, but is not limited to, an analog or digital signal, one or more electrical signals containing one or more computer instructions, a bit or bitstream, etc.

[0019] 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 a function, act, and / or operate in a desired manner. Instructions may be embodied in various forms, such as routines, algorithms, modules, or programs with specific applications, or may be coded from dynamically linked sources or libraries.

[0020] Although exemplary definitions are provided above, it is Applicant's intention that these and other terms be given the broadest reasonable interpretation consistent with this specification.

[0021] As described in more detail below, embodiments of the disclosed techniques relate to assessing scatter in imaging projection data during X-ray, CT, and CBCT scans, including using data from narrow aperture scans within wider aperture scans to assess scatter in data from wider aperture scans. In some embodiments, radiation therapy delivery devices and methods can utilize CT's integrated low-energy radiation source for use in conjunction with or as part of IGRT. In particular, for example, radiation therapy delivery devices and methods can use rotational (e.g., helical or step-and-shoot) image acquisition in conjunction with a high-energy radiation source for treatment, combined with a low-energy focused radiation source for imaging at the gantry.

[0022] For imaging, low-energy radiation sources (e.g., kilovoltage (kV)) can produce higher quality images than those produced by using high-energy radiation sources (e.g., megavoltage (MV)). Images produced with kV energy typically have better tissue contrast than those produced by MV energy. High-quality volumetric imaging may be required for visualization of target and organs at risk (OARS) for adaptive treatment monitoring and for treatment planning / treatment re-planning purposes. In some embodiments, kV imaging systems may also be used for localization, motion tracking, and / or characterization or correction capabilities.

[0023] Image acquisition techniques can include, but are not limited to, multiple rotational scans, which can be, for example, continuous scans (e.g., with a helical source trajectory about a central axis with longitudinal movement of the patient support through the gantry bore), non-continuous stop-and-reverse circumferential scans with incremental longitudinal movement of the patient support, step-and-shoot circumferential scans, etc.

[0024] In connection with various embodiments, the imaging equipment focuses the radiation source, including, for example, using a beamformer to focus the radiation into, for example, a cone beam or a fan beam. In one embodiment, the focused beam is combined with a gantry that rotates continuously while the patient is moved, thereby providing helical image acquisition.

[0025] In some embodiments, the time associated with increased scan rotations to complete a high-quality volumetric image can be reduced by using a high gantry rate / speed (e.g., using high-speed slip-ring rotation, including up to 10 revolutions per minute (rpm), up to 20 rpm, up to 60 rpm, or even higher rpm), a high kV frame rate, and / or sparse data reconstruction techniques, providing kV CT imaging on a radiation therapy delivery platform. Detectors (with various row / slice sizes, configurations, dynamic ranges, etc.), scan pitch, and / or dynamic collimation are additional features in various embodiments. This includes selectively illuminating portions of the detector and selectively defining the effective readout area, as described in more detail below. In particular, using an adjustable beamformer / collimator on an x-ray (low-energy) imaging radiation source and / or optimizing the detector readout range can improve image quality (by assessing scatter, as described below).

[0026] Imaging devices and methods can provide selective and variable collimation of a radiation beam emitted by a radiation source. This includes adjusting the shape of the radiation beam to irradiate 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, a beamformer in an imaging device can adjust the shape of the radiation beam to accommodate pitch variations during helical scanning. In another example, the beam aperture can be adjusted by the beamformer for various axial field of view (aFOV) requirements. In particular, the aFOV can be adjusted to scan regions with various axial (longitudinal) lengths, including narrow and wide regions. Furthermore, by irradiating only the primary region of the detector with direct radiation, the shadow region of the detector can receive only scatter. In some embodiments, scatter measurements in the shadow region of the detector (and in some embodiments, measurements in the peripheral region) can be used to evaluate scatter in the primary region of the detector receiving projection data.

[0027] The imaging device and method provide selective and variable detector readout area and range. This includes adjusting the detector readout range to limit the effective detector area for improved readout speed. For example, it is possible to read out less data than the available shadow area and use it for scatter evaluation. The combination of selective readout and beamforming allows for various optimizations of scatter fitting techniques.

[0028] 1 and 2, an imaging device 10 (e.g., an X-ray imaging device) is shown. It will be understood that the imaging device 10 may be associated with and / or incorporated into a radiation therapy device (shown in FIG. 2) that may be used for various applications, including, but not limited to, IGRT. The imaging device 10 includes a rotatable gantry system, referred to as a gantry 12, which is supported by or otherwise housed within a support unit or housing 14. A gantry, as used herein, refers to a gantry system comprising one or more gantries (e.g., rings or C-arms) capable of supporting one or more radiation sources and / or associated detectors as they rotate around a target. 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, multiple radiation sources and one or more associated detectors may be mounted to the same gantry of the gantry system. This includes, for example, when the gantry system consists of only one gantry. Various combinations of gantries, radiation sources, and radiation detectors may be combined into various gantry system configurations for imaging and / or treating the same volume within the same device. For example, kV and MV radiation sources can be mounted on the same or different gantries of a gantry system and selectively used to image and / or treat as part of an IGRT system. When mounted on different gantries, the radiation sources can be independently rotated, although simultaneous imaging of the same (or nearly the same) volume is still possible. The rotatable ring gantry 12 may have a 10 rpm or greater capability, as described above. The rotatable gantry 12 defines a gantry bore 16 into and through which a patient can be moved and positioned for imaging and / or treatment.According to one embodiment, the rotatable gantry 12 is configured as a slip-ring gantry to provide continuous rotation of the imaging radiation source (X-rays) and associated radiation detectors while providing sufficient bandwidth for high-quality imaging data received by the detectors. The slip-ring gantry eliminates the need for gantry rotation in alternating directions to wind and unwind cables carrying power and signals associated with the device. Such a configuration enables continuous helical tomography, including CBCT, even when incorporated into an IGRT system.

[0029] A patient support 18 is positioned adjacent to the rotatable gantry 12 and is configured, typically in a horizontal position, to support a patient 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 operably coupled to a patient support controller for controlling the movement of the patient and the patient support 18. The patient support controller can be synchronized with the rotatable gantry 12 and a radiation source attached to the rotating gantry for rotation about the patient's longitudinal axis in accordance with a commanded imaging and / or treatment plan. The patient support can also be moved up and down and side to side within a limited range when the patient support is within the bore 16 to adjust the patient position for optimal treatment. When viewed from the front of the gantry 12, axes x, y, and z are indicated. The x-axis is horizontal and points to the right, the y-axis points in the plane of the gantry, and the z-axis is vertical and points up. The x-, y-, and z-axes follow the right-hand rule.

[0030] It will be understood that other variations may be used without departing from the scope of the disclosed techniques. For example, the rotatable gantry 12 and patient support 18 may be controlled so that the gantry 12 rotates (as opposed to a continuous manner, as described above) around a patient supported on the patient support in a "reciprocating" manner (e.g., alternating clockwise and counterclockwise rotations) while the support is controlled to move (at a constant or variable speed) relative to the rotatable gantry 12. In another embodiment, continuous step-and-shoot circumferential scanning is used, whereby longitudinal movement of the patient support 18 (steps) is alternated with scanning rotations (shoots) by the rotatable gantry 12 until the desired volume is captured. The apparatus 10 is capable of performing volume-based and planar-based image acquisition. For example, in various embodiments, the apparatus 10 may be used to acquire volumetric and / or planar images and perform the associated processing methods described below.

[0031] Various other types of radiation source and / or patient support movements may be used to capture relative motion of the radiation source and patient for generation of projection data. Non-continuous motion of the radiation source and / or patient support, continuous but variable / non-constant (including linear and non-linear) linear motion, velocity, and / or trajectory, etc., and combinations thereof, may be used, including in combination with various embodiments of the radiation therapy device 10 described above.

[0032] As shown in FIG. 2, the X-ray imaging apparatus 10 includes an imaging radiation source 30 coupled to or otherwise supported by a rotatable gantry 12. The imaging radiation source 30 emits a radiation beam (generally shown as 32) for producing high-quality images. In this embodiment, the imaging radiation source is an X-ray source 30, which is configured as a kilovoltage (kV) source (e.g., a medical X-ray source having an energy level ranging from about 20 kV to about 150 kV). In one embodiment, a kV source of radiation includes a kiloelectron-volt peak photon energy (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 may be, for example, an X-ray source (including those for CT) or other method, using sufficient energy and flux to generate photons (e.g., a gamma ray source (e.g., cobalt-57, energy peak at 122 keV), an X-ray fluorescence source (e.g., a fluorescence source passing through Pb k-lines, two peaks at about 70 keV and about 82 keV), etc.). References herein to X-rays, X-ray imaging, X-ray imaging sources, etc. are exemplary for certain embodiments. Other imaging transmission sources may be interchangeably used in various other embodiments.

[0033] The X-ray imaging apparatus 10 may also include another radiation source 20 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, such as a high-energy radiation source used to treat tumors within a patient within a region of interest. It will be understood that the therapeutic radiation source may be a high-energy X-ray beam (e.g., a megavoltage (MV) X-ray beam) and / or a high-energy particle beam (e.g., an electron beam, a photon beam, or a beam of heavy ions such as carbon) or another suitable form of high-energy radiation without departing from the scope of the disclosed techniques. In one embodiment, the radiation source 20 includes a megaelectron-volt peak photon energy (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, radiation source 20 has a higher energy level (eg, peak and / or average) than imaging radiation source 30 .

[0034] In one embodiment, radiation source 20 is a LINAC that generates therapeutic radiation (e.g., MV), and the imaging system includes a separate imaging radiation source 30 that produces relatively low-intensity, low-energy imaging radiation (e.g., kV). In other embodiments, radiation source 20 may be a radioisotope, such as Co-60, which may generally have an energy greater than 1 MeV. Radiation source 20 is capable of emitting one or more radiation beams (generally indicated by 22) to a region of interest (ROI) within a patient supported on patient support 18 according to a treatment plan.

[0035] In some embodiments, radiation sources 20, 30 may be used in conjunction with one another to provide higher quality and better utilization images. In other embodiments, at least one additional radiation source may be coupled to rotatable gantry 12 and operated to acquire projection data at a peak photon energy other than that of radiation sources 20, 30.

[0036] While FIGS. 1 and 2 depict an X-ray imaging device 10 having a radiation source 30 mounted on a ring gantry 12, other embodiments may include other types of rotatable imaging devices, including, for example, C-arm gantries and robotic arm-based systems. In a gantry-based system, the gantry rotates the imaging radiation source 30 about an axis passing through the isocenter. Gantry-based systems include a C-arm gantry, on which the imaging radiation source 30 is mounted in a cantilever-like manner and rotates about an axis passing through the isocenter. Gantry-based systems also include ring gantries, such as the rotatable gantry 12, which generally have an annular shape within which the patient's body extends through the bore of the ring / toroid. Additionally, the imaging radiation source 30 is mounted on the ring circumference 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 repeatedly and counter-rotates.

[0037] A detector 34 (e.g., a two-dimensional flat detector or a curved detector) may be coupled to 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 is rotatable relative to the X-ray source 30. The detector 34 can detect or measure the amount of unattenuated radiation. Thus, it is possible to infer the actual attenuation by the patient or a related patient ROI (compared to that initially generated). The detector 34 can detect or otherwise collect attenuation data from different angles as the radiation source 30 rotates around and emits radiation toward the patient.

[0038] It will be understood that the detector 34 may take on a multitude of configurations without departing from the scope of the disclosed techniques. As illustrated in Figure 2, the detector 34 may be configured as a flat panel detector (e.g., a multi-slice flat panel detector). According to another exemplary embodiment, the detector 34 may be configured as a curved detector.

[0039] A collimator or beamformer assembly (generally shown as 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 to selectively irradiate locations or regions of the active area of ​​the detector 34. The beamformer can also control how the radiation beam 32 is positioned on the detector 34. In one embodiment, the beamformer 36 may have a single degree / dimension of motion (e.g., to create thinner or thicker slits). In another embodiment, the beamformer 36 may have two degrees / dimensions of motion (e.g., to create variously sized rectangles). In other embodiments, the beamformer 36 may have the capability of various other dynamically controlled shapes, including, for example, a parallelogram. All of these shapes can be dynamically adjusted during a scan. In some embodiments, the blocking portions of the beamformer can be rotated and translated.

[0040] The beamformer 36 can be controlled to dynamically adjust the shape of the radiation beam 32 emitted by the x-ray source 30 in a number of geometries, including, but not limited to, fan beams or cone beams with low beam thicknesses (widths), as well as those with single-row or multi-row detectors (which are only a portion of the detector's active area). In various embodiments, the beam thickness may illuminate several centimeters of the active area of ​​a larger detector. For example, of a 5-6 centimeter detector, 3-4 centimeters (measured in the longitudinal direction of the detector face) may be selectively exposed to imaging radiation 32. In this embodiment, 3-4 centimeters of projection image data may be captured using approximately 1-2 centimeters of unilluminated detector area on one or each side, which may be used to capture scatter data using respective readings, as described below.

[0041] In other embodiments, a substantial portion of the active detector may be selectively exposed to imaging radiation. For example, in some embodiments, the beam thickness may be reduced to about 2 centimeters, about 1 centimeter, less than 1 centimeter, or a similar size range. This includes smaller detectors. In other embodiments, the beam thickness may be increased to about 4 centimeters, about 5 centimeters, more than 5 centimeters, or a similar size range. This includes larger detectors. In various embodiments, the ratio of illumination to active detector area may be 30-90%, or 50-75%. In other embodiments, the ratio of illumination to active detector area may be 60-70%. However, in other embodiments, various other illumination area and active area sizes or illumination to active detector area ratios may be suitable. The beam and detector may be configured such that the shadow region of the detector (active but not directly exposed to radiation) is sufficient to capture scatter data beyond the peripheral region.

[0042] Various embodiments may include optimizing features that control the selective illumination of the detector (e.g., beam size, beam / aperture center, collimation, collimation, pitch, detector readout range, detector readout center, etc.) so that measurement data is sufficient for the primary (illuminated) and shadow regions, but also optimized for speed and dose control. The shape / position of the beamformer 36 and the readout range of the detector 34 may be controlled so that the radiation beam 32 from the X-ray source 30 ranges an equivalent or smaller X-ray detector 34 based on the particular imaging task and scatter evaluation process being performed, including, for example, a combination of narrow and wide aFOV scans.

[0043] The beamformer may 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 may be configured to include a series of jaws or other suitable members that define and selectively adjust the size of an aperture through which the radiation beam from the X-ray source 30 may pass in a focused manner. According to one exemplary configuration, the collimator 36 may include upper and lower jaws that are movable in different (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 adjust the beam position relative to the patient to irradiate only a portion of the patient being imaged for optimized imaging and minimized patient dose. For example, the collimator may be configured as a multi-leaf collimator (MLC), which may include multiple interdigitated leaves operable to move to one or more positions between a minimally open or closed position and a maximally open position. It will be understood that the leaves may be moved to desired positions to obtain a desired shape of the radiation beam emitted by the radiation source. In one embodiment, the MLC allows for sub-millimeter targeting accuracy.

[0044] According to one embodiment, the shape of the radiation beam 32 from the x-ray source 30 may be changed during image acquisition. Stated another way, according to an exemplary embodiment, the leaf positions and / or aperture width of the beamformer 36 may be adjusted before or during a scan. For example, according to one embodiment, the beamformer 36 may be selectively controlled and dynamically adjusted during rotation of the x-ray source 30 such that the radiation beam 32 has a shape with sufficient primary / shadow regions and is adjusted to include only the subject of interest (e.g., the prostate) during imaging. The shape of the radiation beam 32 emitted by the x-ray source 30 may be changed during or after a scan depending on the desired image acquisition. This may be based on imaging feedback and / or therapeutic feedback, as described in more detail below.

[0045] A detector 24 may be coupled to or otherwise supported by the rotatable gantry 12 and positioned to receive radiation 22 from the therapeutic radiation source 20. The detector 24 may detect or measure the unattenuated radiation dose, thus allowing an inference to be made of the actual attenuation by the patient or associated patient ROI (compared to that initially generated). The detector 24 may detect or otherwise collect attenuation data from different angles as the therapeutic radiation source 20 rotates around and emits radiation toward the patient.

[0046] It will be understood that the therapeutic radiation source 20 may include or otherwise be associated with a beamformer or collimator. The collimator / beamformer associated with the therapeutic radiation source 20, like the collimator / beamformer 36 for the imaging source 30, may be configured in many ways.

[0047] The therapeutic radiation source 20 may be mounted, configured, and / or moved in the same plane as the imaging source 30, or in a different plane (offset) therefrom. In some embodiments, scattering caused by simultaneous activation of the radiation sources 20, 30 may be reduced by offsetting the emission planes.

[0048] When integrated with a radiation therapy machine, the imaging device 10 can provide images that are used to set up (e.g., align and / or register), plan, and / or manage the radiation delivery procedure (treatment). Setup is typically accomplished by comparing current (in-treatment) images with pre-treatment image information. Pre-treatment image information may include, for example, X-rays, 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 the aforementioned devices or other imaging diagnostic modalities. In some embodiments, the imaging device 10 can track the movement of the patient, target, or ROI during treatment.

[0049] 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 patient images based on radiation from the radiation sources 20, 30 received by the detectors 24, 34. It will be understood that the reconstruction processor 40 may be configured to be used to perform methods described more fully below. The apparatus 10 may also include a memory 44 suitable for storing information including, but not limited to, processing and reconstruction algorithms and software, imaging parameters, image data from prior or otherwise pre-acquired images (e.g., planning images), treatment plans, etc.

[0050] The x-ray imaging equipment 10 may include an operator / user interface 48, in which an operator of the x-ray imaging equipment 10 may interact with or otherwise control the x-ray imaging equipment 10, provide input related to a scan, imaging parameters, etc. The operator interface 48 may include any suitable input device, such as a keyboard, mouse, voice-activated controller, etc. The x-ray imaging equipment 10 may also include a display 52 or other human-readable element to provide output to an operator of the imaging equipment 10. For example, the display 52 may allow the operator to observe reconstructed patient images and other information related to the operation of the x-ray imaging equipment 10, such as imaging or scan parameters.

[0051] 2, X-ray imaging equipment 10 includes a controller (generally shown as 60) operatively coupled to one or more components of equipment 10. Controller 60 controls the overall function and operation of equipment 10, including providing power and timing signals to X-ray source 30 and / or therapeutic radiation source 20, and a gantry motor controller that controls the rotational speed and position of rotatable gantry 12. It will be understood that controller 60 may include one or more of a patient support controller, a gantry controller, a controller coupled to therapeutic radiation source 20 and / or X-ray source 30, a controller of beamformer 36, a controller coupled to detector 24 and / or detector 34, etc. In one embodiment, controller 60 is a system controller capable of controlling other components, devices, and / or controllers.

[0052] 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.

[0053] The device 10 may include various components, logic, and software. In one embodiment, the controller 60 includes a processor, memory, and software. By way of example and not limitation, an x-ray imaging device and / or radiation therapy system may include various other devices and components (e.g., a gantry, radiation source, collimator, detector, controller, power supply, patient support, among others) capable of performing one or more routines or steps related to imaging and / or IGRT for a particular application. Routines may include imaging, image-based pre-delivery steps, and / or treatment delivery, including individual device settings, configurations, and / or positions (e.g., path / trajectory), which may be stored in memory. Furthermore, one or more controllers may directly or indirectly control one or more devices and / or components according to one or more routines or processes stored in memory. An example of direct control is setting various radiation source or collimator parameters (power, speed, position, timing, adjustment, etc.) related to imaging or treatment. An example of indirect control is communicating position, path, speed, etc. to a patient support controller or other peripheral device. The hierarchy of the various controllers that may be associated with the imaging equipment may be arranged in any suitable manner to convey appropriate commands and / or information to the desired devices and components.

[0054] Additionally, those skilled in the art will appreciate that the system and method may be implemented with other computer system configurations. The illustrated aspects of the present invention may be practiced in distributed computing environments, where certain tasks are performed by local and remote processing devices that are linked through a communications network. For example, in one embodiment, the reconstruction processor 40 may be associated with a separate system. In a distributed computing environment, program modules may be located in both local and remote memory storage devices. For example, a remote database, a local database, a cloud computing platform, a cloud database, or a combination thereof may be utilized with the X-ray imaging device 10.

[0055] The X-ray imaging equipment 10 can utilize an exemplary environment for implementing various aspects of the present invention, including a computer. The computer includes a controller 60 (including a processor and memory, which may be, for example, memory 44) and a system bus. The system bus can couple system components, including, but not limited to, memory for the processor, and can communicate with other systems, controllers, components, devices, and processors. The memory can include read-only memory (ROM), random access memory (RAM), hard drives, flash drives, and other forms of computer-readable media. The memory can store various software, including routines and parameters, and data, which may include, for example, a treatment plan.

[0056] The therapeutic radiation source 20 and / or the X-ray source 30 may be operably coupled to a controller 60 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 may be controlled by and simultaneously operable with the therapeutic radiation source 20. Additionally or alternatively, the X-ray source 30 may be controlled by and sequentially operated with the therapeutic radiation source 20 depending on the particular treatment and / or imaging plan being performed.

[0057] It will be appreciated that the X-ray source 30 and X-ray detector 34 can be configured to provide rotation around the patient during an imaging scan in many ways. In one embodiment, synchronizing the movement and irradiation of the X-ray source 30 with longitudinal movement of the patient support 18 can provide continuous helical acquisition of patient images throughout the procedure. In addition to continuous rotation of the radiation sources 20, 30 and one or more detectors 24, 34 (e.g., continuous and constant gantry rotation with continuous patient motion speed), it will be appreciated that other variations can be used without departing from the scope of the disclosed techniques. For example, the rotatable gantry 12 and patient support can be controlled such that the gantry 12 rotates around a patient supported on the patient support in a “reciprocating” manner (e.g., alternating clockwise and counterclockwise rotations) as the support is controlled to move (at a constant or variable speed) relative to the rotatable gantry 12 (as opposed to a continuous manner, as described above). In another embodiment, continuous step-and-shoot circumferential scanning is used, whereby longitudinal movement of the patient support 18 (step) is alternated with scan rotation (shoot) by the rotatable gantry 12 until the desired volume is captured. The x-ray imaging device 10 is capable of volume-based and planar-based image acquisition. For example, in various embodiments, the x-ray imaging device 10 can be used to acquire volumetric and / or planar images (e.g., by using the x-ray source 30 and detector 34) and perform associated processing, including the scatter estimation / scatter correction methods described below.

[0058] Various other types of radiation source and / or patient support movements may be used to capture relative motion of the radiation source and patient for generation of projection data. Non-continuous motion of the radiation source and / or patient support, continuous but variable / non-constant (including linear and non-linear) movements, velocities, and / or trajectories, etc., and combinations thereof, may be used, including in combination with various embodiments of the radiation therapy device 10 described above.

[0059] In one embodiment, the rotational speed of the gantry 12, the velocity of the patient support 18, the geometry of the beamformer 36, and / or the readings of the detector 34 may all be constant during image acquisition. In other embodiments, one or more of these variables may be dynamically changed during image acquisition. The rotational speed of the gantry 12, the velocity of the patient support 18, the geometry of the beamformer 36, and / or the readings of the detector 34 may be varied to balance different factors, including, for example, image quality and image acquisition time.

[0060] In other embodiments, these features are combined with one or more other image-based actions or procedures, including, for example, patient setup, adaptive therapy monitoring, therapy planning, and the like.

[0061] There are many determinants of image quality (e.g., focal spot size of the x-ray source, dynamic range of the detector, etc.). A limitation of kV CBCT image quality is scatter. Various approaches can be used to reduce scatter. One approach is to use an anti-scatter grid (which narrows the scatter). However, implementing a scatter grid on a kV imaging system, including motion tracking and correction, can be problematic. Accurate assessment of scatter in projection data is essential to improving the quality of image data. In various embodiments, scatter in projection data acquired in a wide aFOV region of the detector 34 can be assessed based on (relatively scatter-free) projection data acquired in a narrow aFOV region within the wide aFOV region.

[0062] In particular, data can be acquired over a narrow region of a target using a narrow aperture, where scatter is either minimal / negligible or can be accurately obtained using simple techniques. For example, the narrow aperture data can be scatter-free, contain little scatter, or be scatter-corrected by itself, using kernel-based scatter correction, collimator shadow fitting estimation, etc. The narrow aperture can be any size suitable for a particular application, including, for example, in some embodiments, 2-3 mm, 1 cm, 2 cm, and / or any size smaller than the wide aperture. Data can also be acquired over a wide region of a target using a wide aperture, where the narrow region is within the wide region. The wide aperture can also be any size suitable for a particular application, including, for example, in some embodiments, 5 cm, 10 cm, 15 cm, 20 cm, and / or any size larger than the narrow aperture. In various embodiments, the narrow aperture data can be used to improve kernel-based scatter estimation and correction of CBCT data acquired over a wide region. The process of improving scatter estimation using a narrow scan within a wide scan can be completed in either the projection domain or reconstruction, as described in detail below. The process can also be performed in either a non-iterative or iterative manner.

[0063] In an exemplary embodiment, FIG. 3 shows an illustration of an exemplary scan design 300 for imaging an axial region of a target 310. A large / wide aFOV beam 312 is used to scan a wide region 314 of the target 310, shown with an axial length W. A small / narrow aFOV beam 316 is used to scan a narrow region 318, shown with 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, multiple narrow scans can be utilized to improve accuracy (scatter assessment), especially if portions of the wide region 314 exhibit axial variation. For example, in one embodiment, another narrow aFOV beam 320 can be used to scan another narrow region 322, shown with 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. Exemplary beams 312, 316, 320 are all shown projected from a (focused) source 330 through a target 310 and incident on a detector 334. Any number of narrow scans may be used within the wide region 314.

[0064] The axial length N1 is small enough that the projection data of the narrow scan for the narrow region 318 is free of scatter, has minimal scatter, and / or has scatter that is easily obtained / corrected for. A portion of the projection data of the wide scan for the wide region 314 (which contains scatter from the wide scan) overlaps with the narrow region 318. Comparing (e.g., finding the difference between) the projection data (including scatter) from the wide scan in the narrow region 318 with the projection data (without scatter) from the narrow scan in the narrow region 318 provides an accurate assessment (essentially a measurement) of the true scatter in the narrow region 318. The comparison can be performed in either the projection domain or in a reconstruction, as described in more detail below. In this embodiment, the wide scan is a circumferential scan. However, in other embodiments, a helical and / or other scan trajectory can be utilized.

[0065] After this comparison, the true scatter for the narrow region 318 can be used to reliably optimize the scatter estimation technique applied to the entire wide region 314. This is particularly useful if the target varies minimally across the wide region 314. The optimization can be performed in either a non-iterative or iterative manner, as described in more detail below. In some embodiments, multiple narrow aperture data sets (e.g., narrow regions 318, 322) are acquired across the axial extent of the wide aFOV CBCT scan (e.g., wide region 314) to improve scatter correction.

[0066] In one embodiment, the scatter estimation technique utilizes kernel-based scatter estimation / scatter correction. For example, because the true scatter is known for the narrow region 318, the kernel-based scatter estimation technique applied to projection data from a wide scan in the narrow region 318 can be suppressed to obtain an accurate scatter estimate determined for the narrow region 318, such that the scatter estimate generated by the kernel-based scatter estimation technique is suppressed. As such, the suppressed (optimized) kernel-based scatter estimation technique can be applied to the remainder of the wide region 314 with improved results (e.g., relative to unsuppressed applications). The kernel-based technique can improve accuracy based on patient-dependent and / or system-dependent factors.

[0067] In some embodiments, multiple wide aFOV regions (e.g., 314) may be scanned as part of a larger axial range, and each of these wide aFOV regions 314 may contain one or more narrow aFOV regions (e.g., 318, 322).

[0068] As shown in FIG. 3 , one embodiment of scan design 300 may include a large aFOV CBCT scan of the patient's chest (314) and a complementary scan of a region with a narrow aperture (318). In some embodiments, multiple narrow aperture scans (318, 322) whose locations are distributed within the large aFOV (314) may be determined and acquired for more optimal performance. The narrow aperture scan or scans associated with the regions 318, 322 may use medically relevant protocols. This allows accurate reconstruction of the areas covered by the narrow apertures 316, 320 to be used for medical applications as well. In some embodiments, narrow aperture scans, when used only to improve scatter correction, may use fast gantry rotation and sparse angular sampling, minimizing their impact on overall scan time and patient dose.

[0069] If the aperture created by the beamformer 36 is sufficiently narrow (e.g., each of the beams 316, 320 associated with narrow regions 318, 322), scatter in the projection data is essentially negligible. Thus, in one embodiment, the narrow aperture data may be used as scatter-free data. In another embodiment, several simple techniques are effective and accurate and can account for small amounts of scatter in the projection data. In this manner, the narrow aperture data is scatter corrected to provide scatter-free data. For example, as described above, simple and effective scatter correction approaches for narrow aperture data may include fitting using data in the shadow of the beamformer collimator forming aperture, kernel-based scatter correction, etc. The reference to narrow aperture data as scatter-free data may be the result of initial scatter correction on the narrow aperture data.

[0070] The following flow charts and block diagrams illustrate exemplary configurations and methodologies associated with scatter assessment and scatter correction in accordance with the above-described systems. The exemplary methodologies may be implemented in logic, software, hardware, or a combination thereof. Additionally, while the actions and methods are depicted sequentially, the blocks may be executed in a different order, including serially and / or in parallel. Furthermore, additional or fewer steps may be used.

[0071] FIG. 4 is a flowchart illustrating an exemplary method 400 for scattering evaluation in the domain of projection data using a scan design having a narrow scan region within a wide scan region, such as that 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. The narrow region is within the wide region, as described above in FIG. 3, for example. The narrow scan data 410 does not include scattering, while the wide scan data 420 does include scattering. In this embodiment, step 412 separates a portion of the wide scan data 420 that overlaps with the narrow region. Then, in step 414, method 400 subtracts the narrow scan data 410 (which does not include scattering) from the portion of the wide scan data 420 (which includes scattering) that corresponds to the separated narrow region. The resulting data is the true (measured) scattering 416 in the narrow region.

[0072] In step 422, the method 400 estimates scatter in the wide scan data 420 using a scatter estimation technique, which may include, for example, a kernel-based scatter estimation technique. Then, in step 424, the estimated scatter in the narrow region is separated from the estimated scatter for the wide region. The resulting data is estimated scatter 426 in the narrow region using the scatter estimation technique.

[0073] Next, in step 430, the method 400 determines the difference between the true (measured) scattering 416 and the estimated scattering 426 in the narrow region. This difference can be used to optimize the scattering estimation technique in step 432. For example, the scattering estimation technique can be optimized by minimizing the difference between the estimated scattering 426 and the true scattering 416. Minimizing the difference can include various types of fitting processes. In one non-iterative embodiment, the optimization process can include a least-squares solution. Then, in step 434, the optimized (e.g., fitted kernel-based) scattering estimation technique can be used to re-estimate the scattering in the remainder of the wide scan data 420 with improved accuracy. The scattering estimation can be used during wide-region reconstruction.

[0074] 5 is a flowchart illustrating another exemplary method 500 of scattering estimation in the domain of projection data using a scan design having a narrow scan region within a wide scan region, such as that described above. Method 500 is similar to method 400, except that in this embodiment, in step 522, method 500 only first estimates scattering in a separated portion of wide scan data 420 that overlaps with the narrow region using a scattering estimation technique. This is computationally less independent than evaluating scattering 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 separated wide scan data can be derived directly from step 412. The resulting data is estimated scattering 426 in the narrow region using a scattering estimation technique. Other steps are performed as in method 400, etc.

[0075] 6 is a flowchart illustrating an exemplary iterative method 600 for scattering estimation in the domain of projection data using a scan design having a narrow scan region within a wider scan region, such as those described above. Method 600 is similar to method 500, except that in this embodiment, after step 430, method 600 performs an iterative optimization of the scattering estimation technique. In particular, in step 632, method 600 determines whether the difference between the true (measured) scattering 416 and the estimated scattering 426 in the narrow region requires further refinement or optimization. In various embodiments, the difference from step 430 (representing how close the estimated scattering 426 from the scattering estimation technique is to the true scattering 416) may be subjected to various conditions / analyses to determine whether further refinement is needed in step 632. This may include, for example, the difference may be compared to a threshold, the difference between the current iteration and one or more prior iterations may be compared to a threshold or rate (e.g., to determine the convergence rate of the iteration / incremental improvement to the evaluation), the number of iterations (loopback to step 522) may be compared to a threshold, the time associated with the scan and / or iteration process may be compared to a threshold (e.g., to take into account the overall workflow), and combinations of these and / or other factors, including weighted averages, etc.

[0076] If the analysis in step 632 determines that the differences from step 430 require further refinement, method 600 proceeds to step 634 to optimize the scattering estimation technique taking into account the differences from step 430. For example, the scattering estimation technique may be optimized by minimizing the difference between estimated scattering 426 and true scattering 416. Minimizing the difference may involve various types of fitting processes. For multiple iterations, step 634 may be further optimization.

[0077] If the analysis in step 632 determines that the differences from step 430 do not require further refinement, method 600 proceeds to step 636 and applies an optimized (e.g., fitted kernel-based) scatter estimation technique to the remainder of the wide scan data 420 with improved accuracy.

[0078] In this manner, acquired narrow aperture scan data, including in conjunction with kernel-based scatter estimation, can be used to improve scatter estimation of wide aperture scan data in imaging diagnostic procedures. For example, imaging includes X-ray imaging, CT imaging, CBCT imaging, etc. Kernel-based scatter estimation and scatter correction, including improved / optimized embodiments, can be used to improve image quality and quantity. A beamformer (e.g., having a set of collimators) can effectively block a portion of the beam to form an aperture for imaging. In this case, the aperture size can be changed to enable acquisition of very narrow aperture data. The aperture position relative to the patient can be changed relative to the patient. In various embodiments, kernel-based scatter estimation of data from a large aFOV (wide field of view) scan is compared to measured scatter from a small aFOV (narrow field of view) at the same angle. The measured scatter is the result of subtracting the scatter-free data of the narrow aperture scan from the scatter-containing data in a similar region at the same angle / perspective.

[0079] The kernel-based scatter estimation can be optimized by minimizing the difference between estimated and measured scatter. The optimized kernel-based scatter estimation can then be applied to the remainder of the large aFOV data, improving the accuracy of the scatter correction.

[0080] As described above, optimization of scatter assessment techniques can also occur in the reconstruction domain. An image reconstructed from narrow aperture scan data can be considered a scatter-free image. Reconstruction of a similar region from wide aperture scan data, for example, using a kernel-based scatter correction technique, can be compared to the scatter-free image. The scatter correction technique can be optimized to minimize the discrepancy. In some embodiments, for example, for the intended medical application, the discrepancy can be focused on only a subset of image planes. For example, when wide aFOV images are used for adaptive planning of radiation therapy, quantitative accuracy is important for dose calculation, and low-contrast recovery is important for tumor detection and delineation for dose planning.

[0081] 7 is a flowchart illustrating an exemplary method 700 of scatter correction in the reconstruction domain using a scan design having a narrow scan region within a wide scan region, such as that described above. Narrow scan data 410 from the narrow region and wide scan data 420 from the wide region are provided or received from data acquisition using, for example, the imaging device 10 described above. The narrow region is within the wide region, as described above, for example in FIG. 3 . Narrow scan data 410 does not contain scatter, while wide scan data 420 does contain scatter. In this embodiment, step 712 reconstructs the narrow region using the narrow scan data 410. The resulting image is a scatter-free narrow region image 714.

[0082] In step 722, the method 700 isolates and reconstructs a narrow region using the wide scan data 420 with a scatter correction technique, which may include, for example, a kernel-based scatter estimation / scatter correction technique. The resulting image is a scatter-corrected narrow region image 724.

[0083] Next, in step 730, the method 700 determines the difference between the scatter-free narrow area image 714 and the scatter-corrected narrow area image 724. This difference can be used to optimize the scatter correction technique in step 732. For example, the scatter correction technique can be optimized by minimizing the difference between the scatter-free narrow area image 714 and the scatter-corrected narrow area image 724. Minimizing the difference can include various types of fitting processes. In one non-iterative embodiment, the optimization process can include a least-squares solution. Then, in step 734, the optimized (e.g., fitted kernel-based) scatter correction technique can be used to reconstruct the wide area using the wide scan data 420 with improved accuracy.

[0084] 8 is a flowchart illustrating an exemplary iterative method 800 for scatter correction in the reconstruction domain using a scan design having a narrow scan region within a wide scan region, such as that described above. Method 800 is similar to method 700, except that in this embodiment, after step 730, method 800 performs an iterative optimization of the scatter correction technique. In particular, in step 832, method 800 determines whether the difference between the scatter-free narrow area image 714 and the scatter-corrected narrow area image 724 requires further refinement or optimization. In various embodiments, the difference from step 730 (representing how close the scatter-corrected narrow area image 724 using the scatter correction technique is to the scatter-free narrow area image 714) may be subjected to various conditions / analyses to determine whether further refinement is needed in step 832. This may include, for example, differences may be compared to a threshold, differences between the current iteration and one or more previous iterations may be compared to a threshold or rate (e.g., to determine the convergence rate of iterations / incremental improvements to the evaluation), the number of iterations (loopback to step 722) may be compared to a threshold, the time associated with the scan and / or iteration process may be compared to a threshold (e.g., to take into account the overall workflow), and combinations of these factors and / or other factors, including weighted averages, etc.

[0085] If the analysis in step 832 determines that the differences from step 730 require further refinement, method 800 proceeds to step 834, where the scatter correction technique is optimized taking into account the differences from step 730. For example, the scatter correction technique may be optimized by minimizing the difference between the scatter-corrected small area image 724 and the scatter-free small area image 714. Minimizing the difference may include various types of fitting processes. With multiple iterations, step 834 may be further optimization.

[0086] If the analysis in step 832 determines that the differences from step 730 do not require further refinement, method 800 proceeds to step 836 to reconstruct the wide area by applying an optimized (e.g., fitted kernel-based) scatter correction technique to the remainder of the wide scan data 420 with improved accuracy.

[0087] As described above, the narrow aperture data can be acquired using a medically appropriate protocol. In these embodiments, the data can be used to accurately reconstruct an image of this portion of the patient. An image reconstructed from large aFOV data of the same portion of the patient can be compared to the image from the narrow aperture reconstruction. Kernel-based scatter correction of the large aFOV data (wide region) can be optimized so that the reconstructed image matches the narrow aperture image (narrow region) of the same portion. Consequently, the remaining reconstructed image of the wide region is enhanced with the optimized kernel-based scatter correction. In one embodiment, kernel-based scatter correction can be optimized to match the large aFOV (wide region) image with the narrow aperture image (narrow region) of the same portion of the patient using medically desired criteria. For example, one criterion is matching low-contrast recovery for tumor detection and delineation. Another criterion is matching quantitative accuracy for dose simulation and planning for adaptive radiation therapy.

[0088] Various factors may be considered to determine whether to perform the above method in the projection data domain and / or the reconstruction domain, including, for example, criteria such as accuracy, time, workflow, available data, etc. In some situations, only one domain may be available or may be preferred. For example, with reference to FIG. 3 , when narrow area beam 320 is tilted as shown, narrow aperture data does not allow for accurate image reconstruction. Therefore, only narrow scan data associated with narrow area 322 may be used to improve scatter assessment in the projection domain.

[0089] In various embodiments, the image reconstruction can be an analytical reconstruction and / or an iterative reconstruction.

[0090] The details of one or more narrow scans (including number, axial position, angle, size, narrow / wide size ratio, etc.) for one or more narrow regions (e.g., 318, 322 shown in FIG. 3 ) can be determined and / or optimized using various techniques. In embodiments where one or more scans are not yet complete, determining the details of one or more narrow scans can include determining the details of one or more similar wide scans, including, for example, number, size, ratio, etc. An optimization process is performed to determine the narrow and / or wide scan details (including number, axial position, angle, size, narrow / wide size ratio, etc.) and optimize the various factors described above, including overall scan time, workflow, etc. For example, in some embodiments, narrow scans can be determined from prior images (e.g., planning CT images, CBCT images from a prior treatment sub-session, etc.). In some embodiments, narrow scans can be selected from a bank of pre-determined narrow scans suitable for a particular wide region, including those based on typical uniformity / variation and narrow areas suitable as the basis for a wider region. In other embodiments, for example, if no prior images are available, the narrow scan can be determined on the fly using images reconstructed from a scout scan and / or a wide area scan.

[0091] For example, in one embodiment, after a wide-area scan acquires enough data for acceptable image reconstruction, a relatively fast reconstruction of the wide-scan data can begin. The wide-area reconstructed image can then be used to identify one or more narrow scans based on, for example, uniformity (or lack thereof), axial length, clinical protocol, or the use of a protocol solely for scatter correction. These may include a slight projection angle, a larger pitch for helical scans, etc. In some embodiments, other factors, such as workflow, may be considered in determining the number of narrow scans. In one embodiment, a computer algorithm / analysis can automatically determine the details of one or more narrow scans based on the wide-area reconstructed image. In another embodiment, a user can determine the details of one or more narrow scans based on a review of the wide-area reconstructed image. The narrow-area information can then be fed back into the system to control the narrow scans.

[0092] For example, FIG. 9 is a flowchart illustrating an exemplary method 900 for determining narrow scans from prior image data for use in narrow / wide scan designs, such as those described above. Prior image data 905 of a patient (e.g., a prior image, which may be a pre-acquired planning image, including a prior CT image) is provided or received, for example, from another source or from data acquisition using the X-ray imaging device 10. In step 910, the method 900 determines narrow scan details based on the prior image data 905. As described above, in this embodiment, determining one or more narrow scan details may include determining one or more wide scan details, including an optimization process. Next, in step 920, the method 900 initiates narrow and wide area scans, for example, using the imaging device 10. The resulting data is narrow scan data 410 for one or more narrow areas and wide scan data 420 for one or more wide areas. The scan data 410, 420 may be used according to the scatter evaluation and scatter correction methods described above.

[0093] In another embodiment, FIG. 10 is a flowchart illustrating an exemplary method 1000 for determining narrow scans from wide scan data for use in a narrow / wide scan design, such as those described above. In step 1010, method 1000 performs a wide area scan of a patient to support imaging and / or treatment targets, using, for example, the imaging device 10 described above. The resulting data is wide scan data 420 for the wide area. Next, in step 1020, method 1000 begins to reconstruct the wide scan data 420. In step 1030, based on at least a partial reconstructed image of the patient, method 1000 determines narrow scan details based on the reconstructed image, as described above. Next, in step 1040, method 1000 initiates one or more narrow scans, using, for example, the imaging device 10 described above. The resulting data is narrow scan data 410 for one or more narrow areas. The scan data 410, 420 may be used in accordance with the scatter evaluation and scatter correction methods described above.

[0094] In this manner, the narrow aperture scans (e.g., number, position, angle, size, etc.) can be determined using pre-images or on-the-fly, depending on the availability of data / image information from the wide aperture scan. For example, if the size and position of the narrow aperture scan, as well as the angle at which the narrow aperture data is acquired, are determined on-the-fly, patient images are first acquired from a wide area scan. Then, patient images, including image reconstruction, are acquired using the position or entirety of the wide scan data, while the large aFOV data acquisition (wide area scan) is still ongoing (simultaneous reconstruction / acquisition) or reconstruction is ongoing after the large aFOV scan is completed. The determination of the narrow aperture scan details can use algorithms / software that use image non-uniformity determined from the acquired patient images.

[0095] When using the above-described apparatus and method for scatter correction in the projection domain, if each projection viewpoint is a planar image, scatter correction can be applied to each projection viewpoint. In one embodiment, one or more planar X-ray images (e.g., for motion tracking) can be used with a pre-available volume image in conjunction with a kernel-based scatter estimation technique to estimate scatter in the planar image for scatter correction (e.g., for contrast enhancement). The method can use measured scatter in narrow aperture data to enhance the kernel-based scatter estimation.

[0096] In another embodiment, a first planar image can be acquired with a wide aperture and a collimator shadow region. The collimator shadow can then be used to evaluate scattering in the planar image using a shadow fitting technique. Next, the narrow aperture data can be used to measure scattering in a narrow region. The results can be used to refine the shadow fitting technique for wide aperture scattering evaluation.

[0097] The above-described devices and methods offer several advantages over existing techniques. For example, the devices and methods can improve the performance of conventional kernel-based scatter estimation and scatter correction approaches in CBCT. Improvements can be demonstrated particularly for large axial volumes in the context of patient scans of highly heterogeneous regions.

[0098] In one embodiment, the use of a kernel-based model for scatter estimation / scatter correction when optimizing the area spanned by the narrow aperture is more accurate for the remainder of the wide area than traditional kernel-based approaches. The narrow aperture data (not including scatter) provides complementary information for optimizing or suppressing the kernel-based model, thereby improving the accuracy of the kernel-based model during scatter estimation / scatter correction. In this way, the optimization process can be very straightforward, yet very effective.

[0099] As described above, narrow area scans can use medically relevant protocols that allow for accurate reconstruction of the narrow area spanned by the aperture. Thus, the dose and scan time associated with narrow scans are fully utilized and not wasted. In other embodiments, narrow area scans can be for scatter correction purposes only. In these embodiments, the acquisition can use fast gantry rotation and / or acquire angularly sparse data. As a result, the impact of narrow area scans on patient dose and scan time can be minimized.

[0100] Various embodiments can utilize different scan geometries, detector positioning (including offset detectors), and / or beamformer window shapes. In some embodiments, the narrow and / or wide scan trajectories can be 180 degrees when the detectors are centered, or up to 360 degrees when the detectors are offset.

[0101] As noted above, aspects of the disclosed techniques may be utilized in methods utilizing integrated kilovoltage (kV) CT for use in conjunction with or as part of a radiation therapy device and IGRT. According to one embodiment, an image acquisition methodology includes or otherwise utilizes helical source trajectory (e.g., continuous source rotation about a central axis accompanied by longitudinal movement of a patient support through a gantry bore) accompanied by high-speed slip-ring rotation, or full-circle scanning accompanied by kV beam collimation, to provide kV CT imaging of the radiation therapy delivery platform. It will be appreciated that such implementations may provide reduced scatter and improved scatter assessment, enabling higher quality kV images than conventional systems.

[0102] It will be further understood that any potential increase in scan time associated with multiple beam rotations to complete a volumetric image can be mitigated or otherwise offset by a high kV frame rate, a high gantry rate, and / or a sparse data reconstruction technique. It will be further understood that providing a selectively controllable collimator / beamformer as described above enables a system in which the user can trade off or otherwise modify image acquisition time for image quality depending on the particular application and / or medical need. It will also be understood that the radiation therapy delivery device can be controlled to provide half-rotation or single-rotation cone-beam CT scans (which have the potential to reduce image quality due to scatter) with fast image acquisition times (e.g., for motion tracking), and full-circle or continuous helical acquisitions with narrow / slit fan beams that have longer acquisition times but increase image quality by reducing scatter. One or more optimization processes can also be applied to all of the above embodiments to determine beam positioning, determine readout ranges, evaluate scatter, etc.

[0103] FIG. 11 is a flowchart illustrating an exemplary method 1100 of IGRT using a radiation therapy device (e.g., including imaging device 10). Patient prior image data 1105 is available for use (e.g., prior images, including the prior CT images described above, which may be pre-acquired planning images). In some embodiments, the prior image data 1105 is generated by a similar radiation therapy device, but at an earlier time. In step 1110, patient imaging is performed using a low-energy radiation source (e.g., kV radiation from x-ray source 30). In one embodiment, imaging includes a full-circle scan with a fan-beam or cone-beam geometry. Step 1110 generates one or more high-quality (HQ) images or imaging data 1115 using the scatter assessment and scatter correction techniques described above. In some embodiments, image quality may be adjusted to optimize a balance between image quality / resolution and dose. In other words, not all images need to be of the highest quality. Alternatively, image quality may be adjusted to optimize or trade off image quality / resolution and image acquisition time. The imaging step 1110 may also include image processing 1120 to generate patient images based on the imaging / scan data (e.g., according to the methods described above). 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 where image processing is performed by a separate device.

[0104] Next, in step 1130, one or more image-based pre-delivery steps described below are performed based at least in part on the imaging data 1115 from step 1110. As described in more detail below, step 1130 may include determining various parameters related to the treatment procedure and (subsequent) imaging planning. In some embodiments, the image-based pre-delivery step (1130) may require more imaging (1110) before treatment delivery (1140). Step 1130 may include adapting the treatment plan based on the imaging data 1115 as part of an adaptive radiation therapy routine. In some embodiments, the image-based pre-delivery step 1130 may include real-time treatment planning. Embodiments may also include simultaneous, overlapping, and / or alternating activation of the imaging and therapeutic radiation sources. Real-time treatment planning may involve any or all of these types of imaging and therapeutic radiation activation techniques (simultaneous, overlapping, and / or alternating).

[0105] Next, in step 1140, therapeutic treatment delivery is performed using a source of high-energy radiation (e.g., MV radiation from therapeutic radiation source 20). Step 1140 delivers a therapeutic dose 1145 to the patient according to the treatment plan. In some embodiments, IGRT method 1100 may include returning to step 1110 for additional imaging at various intervals, followed by image-based pre-delivery steps (1130) and / or treatment delivery (1140) as needed. In this manner, high-quality imaging data 1115 may be generated and utilized during IGRT using an adaptive therapy-capable device 10. As described above, steps 1110, 1130, and / or 1140 may be performed simultaneously, overlapping, and / or interleaved.

[0106] IGRT may include at least two general goals: (i) delivering a highly conformal dose distribution to the target volume, and (ii) delivering the treatment beam with high precision throughout the entire treatment. A third goal may be achieving the two general goals in the least amount of time per segment possible. Accurate delivery of the treatment beam requires the ability to identify and / or track the position of the target volume using high-quality images. The ability to increase delivery rate requires the ability to move the radiation source accurately, precisely, and rapidly according to the treatment plan.

[0107] FIG. 12 is a block diagram 1200 illustrating exemplary image-based pre-delivery steps / options that may be related to step 1130 above. The imaging device 10 (e.g., as part of a radiation therapy device) described above can generate kV images that can be used in a variety of ways. It will be understood that this includes targeting the image-based pre-delivery step (1130) without departing from the scope of the present invention. For example, images 1115 generated by the radiation therapy device can be used to align the patient pre-treatment (1210). Patient alignment can include correlating or registering the current imaging data 1115 with imaging data related to the plan, including an earlier pre-treatment scan and / or treatment plan. Patient alignment can also include feedback about the patient's physical position relative to the radiation source to ensure the patient is physically within range of the delivery system. If necessary, the patient can be adjusted accordingly. In some embodiments, patient alignment imaging can be intentionally lower quality to minimize dose but provide adequate alignment information.

[0108] The images generated by the imaging device 10 can also be used for treatment planning or treatment re-planning (1220). In various embodiments, step 1220 can include confirming the treatment plan, modifying the treatment plan, creating a new treatment plan, and / or selecting a treatment plan from a set of treatment plans (sometimes called a "daily plan"). For example, the imaging data 1115 shows that the target volume or ROI is the same as that for which the treatment plan was developed. The treatment plan can then be confirmed. However, if the target volume or ROI is not the same, re-planning of the treatment procedure may be necessary. In the case of treatment re-planning, because the imaging data 1115 (generated by the x-ray imaging device 10 in step 1110) is of high quality, the imaging data 1115 can be used for treatment planning or treatment re-planning (e.g., creating a new or revised treatment plan). In this way, pre-treatment CT imaging with a different device is not required. In some embodiments, confirmation and / or treatment re-planning can be an ongoing procedure before and / or after various treatments.

[0109] According to another exemplary use case, images generated by the imaging device 10 can be used to calculate an imaging dose (1230), which may be used to determine the overall dose to the patient on-the-fly and / or for subsequent imaging planning. The quality of the subsequent imaging may also be determined as part of the treatment planning, e.g., to balance quality and dose. According to another exemplary use case, images generated by the imaging device 10 can be used to calculate a treatment dose (1240), which may be used to determine the overall dose to the patient on-the-fly and / or may be included as part of the treatment planning or treatment re-planning.

[0110] According to another exemplary use case, images generated by the imaging device 10 may be used in connection with planning or adjusting other imaging (1250) and / or other treatment (1260) parameters or plans, such as included as part of creating an adaptive treatment and / or treatment plan. According to another exemplary use case, images generated by the imaging device 10 may be used in connection with adaptive treatment monitoring (1270), which may include monitoring and adapting treatment delivery as needed.

[0111] The image-based pre-delivery steps (1130) are not mutually exclusive. For example, in various embodiments, calculated treatment dose (1240) can be a stand-alone step and / or part of adaptive treatment monitoring (1270) and / or treatment planning (1220). In various embodiments, the image-based pre-delivery steps (1130) can be performed automatically and / or manually with human intervention.

[0112] The above-described apparatus and method, including adjustable collimation (aperture) of imaging radiation and scatter assessment and scatter correction schemes, provide improved scatter assessment, resulting in higher quality kV-generated images than conventional intra-treatment imaging systems using CBCT.

[0113] FIG. 13 is a block diagram 1300 illustrating exemplary data sources that may be utilized during imaging (1110) and / or the subsequent image-based pre-delivery step (1130). Detector data 1310 represents all data received by the imaging radiation detector 34. Projection data 1320 is data generated by radiation incident in the narrowed beam region, referred to above as the scan region. Penumbra data 1330 is data generated by radiation incident in the penumbra region. Scatter data 1340 is data generated by radiation incident in a peripheral region outside the penumbra region and / or the determined scatter, as described above. In another embodiment, the scatter data 1340 can be used to determine residual effects of scatter from the therapeutic radiation source 20 (e.g., MV) when two sources 20, 30 are operated simultaneously or in an interleaved manner.

[0114] In this manner, the penumbra data 1330 and / or scatter data 1340 may be utilized to improve the quality of the image generated by the imaging step 1110. In some embodiments, the penumbra data 1330 and / or scatter data 1340 may be combined with the projection data 1320 and / or analyzed at the time of data collection at the imaging detector 34 in terms of applicable imaging settings 1350, treatment settings 1360 (e.g., in the case of simultaneous imaging and treatment radiation), and any other data 1370 related to the imaging device 10. In other embodiments, the data may be used for the treatment planning step 1130.

[0115] While the disclosed methodologies have been shown and described with respect to particular aspects, embodiments, or embodiments, it will be apparent that equivalent alterations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. In particular, with respect to the various functions performed by the above-described elements (components, assemblies, devices, members, compositions, etc.), the terms used to describe such elements (including references to "means") are intended, unless otherwise indicated, to correspond to any element that performs the specified function of the described element (i.e., that is functionally equivalent), even if it is not structurally equivalent to the disclosed structure that performs that function in the exemplary aspects, embodiments, or embodiments of the disclosed technology shown herein. Moreover, while particular features of the disclosed methodologies may be described above with respect to only one or more of some illustrated aspects or embodiments, such features can be combined with one or more other features of other embodiments, as may be desirable or advantageous for any given or particular application.

[0116] While the embodiments described herein relate to the systems and methods described above, these embodiments are intended to be exemplary and are not intended to limit the applicability of these embodiments solely to the descriptions set forth herein. While the present invention has been illustrated by the description of its embodiments, and while the embodiments have been described in some detail, it is not the intention of the applicant to limit, or in any way limit, the scope of the appended claims to such details. Additional advantages and modifications will be readily apparent to those skilled in the art. Accordingly, the invention in its broader aspects is not limited to the specific details, exemplary apparatus and methods, and illustrative examples shown and described. Accordingly, departures may be made from such details without departing from the spirit or scope of applicant's general inventive concept.

Claims

1. 1. An imaging device comprising: a rotating imaging source for emitting a radiation beam; a detector positioned to receive radiation from the rotating imaging source; a beamformer configured to adjust the shape of the radiation beam emitted by the rotating 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; 1. A data processing system comprising: determining estimated scatter in the wide axial region using a first optimized scatter estimation technique based on the difference between scatter measured in the narrow axial region based on the projection data of the narrow aperture scan and the projection data of the wide aperture scan overlapping the narrow axial region, and scatter estimated in the narrow axial region using a scatter estimation technique based on the projection data of the wide aperture scan overlapping the narrow axial region; or and reconstructing a scatter-corrected wide area image using a second optimized scatter estimation technique based on a calculated difference between a substantially scatter-free narrow area image reconstructed based on the projection data of the narrow aperture scan and a scatter-corrected narrow area image using a scatter estimation technique based on the projection data of the narrow aperture scan and projection data of the wide aperture scan overlapping the narrow axial area. Imaging equipment.

2. 1. An imaging device comprising: a rotating imaging source for emitting a radiation beam; a detector positioned to receive radiation from the rotating imaging source; a beamformer configured to adjust the shape of the radiation beam emitted by the rotating 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; determining measured scatter in the narrow axial region based on projection data of the narrow aperture scan and projection data of the wide aperture scan overlapping the narrow axial region; determining estimated scatter in the narrow axial region based on projection data of the wide aperture scan overlapping the narrow axial region using a scatter estimation technique; calculating a difference between the measured scattering in the narrow axial region and the estimated scattering in the narrow axial region; optimizing the scattering estimation technique based on the difference between the measured scattering in the narrow axial region and the estimated scattering in the narrow axial region; determining estimated scatter over a wide axial region based on projection data of the wide aperture scan using the optimized scatter estimation technique; Imaging equipment.

3. and receiving projection data measured at the wide axial region and the narrow axial region, and determining the estimated scatter at the wide axial region using a kernel-based approach.

3. The imaging apparatus of claim 1, further comprising a data processing system.

4. The imaging apparatus of claim 1 or 2, wherein the wide aperture scan and the narrow aperture scan comprise a full-circle scan.

5. 1. A method for correcting scattering in an image, comprising: receiving measured projection data 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 area image based on the projection data of the narrow aperture scan; reconstructing a scatter-corrected narrow-area image based on projection data of the wide aperture scan that overlaps the narrow axial region using a scatter correction technique; and calculating the difference between the scatter-free small area image and the scatter-corrected small area image; optimizing the scatter correction technique based on differences between the scatter-free small area image and the scatter-corrected small area image; reconstructing a scatter-corrected wide area image based on the projection data of the wide aperture scan using the optimized scatter correction technique; and the scatter correction technique comprises a kernel-based scatter correction technique.

6. 1. A radiation therapy delivery device comprising: a rotatable gantry system positioned at least partially around the patient support; a first radiation source coupled to the rotatable gantry system and configured as a therapeutic radiation source; and a second radiation source coupled to the rotatable gantry system and configured as an imaging radiation source having an energy level less 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 beamformer 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 wide aperture scanning of a wide axial region and narrow aperture scanning of a narrow axial region within the wide axial region; 1. A data processing system comprising: receiving projection data measured in the wide region in the body axis direction and the narrow region in the body axis direction; determining estimated scatter in the wide axial region using a first optimized scatter estimation technique based on a difference between measured scatter in the narrow axial region based on projection data of the narrow aperture scan and projection data of the wide aperture scan overlapping the narrow axial region, and estimated scatter in the narrow axial region using a scatter estimation technique based on projection data of the wide aperture scan overlapping the narrow axial region; reconstructing an image of the patient based on the estimated scattering; or reconstructing the patient image based on a scatter-corrected wide area image using a second optimized scatter estimation technique based on a calculated difference between a substantially scatter-free narrow area image reconstructed based on projection data of the narrow aperture scan and a scatter-corrected narrow area image using a scatter estimation technique based on projection data of the wide aperture scan that overlaps the narrow axial area; a data processing system configured to deliver a dose of therapeutic radiation to the patient by the first radiation source based on the patient image during adaptive IGRT.

7. 1. A radiation therapy delivery device comprising: a rotatable gantry system positioned at least partially around the patient support; a first radiation source coupled to the rotatable gantry system and configured as a therapeutic radiation source; and a second radiation source coupled to the rotatable gantry system and configured as an imaging radiation source having an energy level less 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 beamformer 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 wide aperture scanning of a wide axial region and narrow aperture scanning of a narrow axial region within the wide axial region; determining measured scatter in the narrow axial region based on projection data of the narrow aperture scan and projection data of the wide aperture scan overlapping the narrow axial region; determining estimated scatter in the narrow axial region based on projection data of the wide aperture scan overlapping the narrow axial region using a scatter estimation technique; calculating a difference between the measured scattering in the narrow axial region and the estimated scattering in the narrow axial region; optimizing the scattering estimation technique based on the difference between the measured scattering in the narrow axial region and the estimated scattering in the narrow axial region; determining an estimated scatter over a wide axial region based on projection data of the wide aperture scan using the optimized scatter estimation technique; reconstructing an image of the patient based on the estimated scattering; a radiation therapy delivery device that delivers a dose of therapeutic radiation to the patient by the first radiation source based on the patient image during adaptive IGRT;

Images