Deformable motion compensation for interventional cone-beam CT.

Image-guided therapies in the abdomen and pelvis are often hindered by motion artifacts in cone-beam CT (CBCT) arising from complex, non-periodic, deformable organ motion during long scan times (5-30 s). We propose a deformable image-based motion compensation method to address these challenges and improve CBCT guidance. Motion compensation is achieved by selecting a set of small regions of interest in the uncompensated image to minimize a cost function consisting of an autofocus objective and spatiotemporal regularization penalties. Motion trajectories are estimated using an iterative optimization algorithm (CMA-ES) and used to interpolate a 4D spatiotemporal motion vector field. The motion-compensated image is reconstructed using a modified filtered backprojection approach. Being image-based, the method does not require additional input besides the raw CBCT projection data and system geometry that are used for image reconstruction. Experimental studies investigated: (1) various autofocus objective functions, analyzed using a digital phantom with a range of sinusoidal motion magnitude (4, 8, 12, 16, 20 mm); (2) spatiotemporal regularization, studied using a CT dataset from The Cancer Imaging Archive with deformable sinusoidal motion of variable magnitude (10, 15, 20, 25 mm); and (3) performance in complex anatomy, evaluated in cadavers undergoing simple and complex motion imaged on a CBCT-capable mobile C-arm system (Cios Spin 3D, Siemens Healthineers, Forchheim, Germany). Gradient entropy was found to be the best autofocus objective for soft-tissue CBCT, increasing structural similarity (SSIM) by 42%-92% over the range of motion magnitudes investigated. The optimal temporal regularization strength was found to vary widely (0.5-5 mm-2) over the range of motion magnitudes investigated, whereas optimal spatial regularization strength was relatively constant (0.1). In cadaver studies, deformable motion compensation was shown to improve local SSIM by ∼17% for simple motion and ∼21% for complex motion and provided strong visual improvement of motion artifacts (reduction of blurring and streaks and improved visibility of soft-tissue edges). The studies demonstrate the robustness of deformable motion compensation to a range of motion magnitudes, frequencies, and other factors (e.g. truncation and scatter).

Accelerated 3D image reconstruction with a morphological pyramid and noise-power convergence criterion.

Model-based iterative reconstruction (MBIR) for cone-beam CT (CBCT) offers better noise-resolution tradeoff and image quality than analytical methods for acquisition protocols with low x-ray dose or limited data, but with increased computational burden that poses a drawback to routine application in clinical scenarios. This work develops a comprehensive framework for acceleration of MBIR in the form of penalized weighted least squares optimized with ordered subsets separable quadratic surrogates. The optimization was scheduled on a set of stages forming a morphological pyramid varying in voxel size. Transition between stages was controlled with a convergence criterion based on the deviation between the mid-band noise power spectrum (NPS) measured on a homogeneous region of the evolving reconstruction and that expected for the converged image, computed with an analytical model that used projection data and the reconstruction parameters. A stochastic backprojector was developed by introducing a random perturbation to the sampling position of each voxel for each ray in the reconstruction within a voxel-based backprojector, breaking the deterministic pattern of sampling artifacts when combined with an unmatched Siddon forward projector. This fast, forward and backprojector pair were included into a multi-resolution reconstruction strategy to provide support for objects partially outside of the field of view. Acceleration from ordered subsets was combined with momentum accumulation stabilized with an adaptive technique that automatically resets the accumulated momentum when it diverges noticeably from the current iteration update. The framework was evaluated with CBCT data of a realistic abdomen phantom acquired on an imaging x-ray bench and with clinical CBCT data from an angiography robotic C-arm (Artis Zeego, Siemens Healthineers, Forchheim, Germany) acquired during a liver embolization procedure. Image fidelity was assessed with the structural similarity index (SSIM) computed with a converged reconstruction. The accelerated framework provided accurate reconstructions in 60 s (SSIM = 0.97) and as little as 27 s (SSIM = 0.94) for soft-tissue evaluation. The use of simple forward and backprojectors resulted in 9.3× acceleration. Accumulation of momentum provided extra ∼3.5× acceleration with stable convergence for 6-30 subsets. The NPS-driven morphological pyramid resulted in initial faster convergence, achieving similar SSIM with 1.5× lower runtime than the single-stage optimization. Acceleration of MBIR to provide reconstruction time compatible with clinical applications is feasible via architectures that integrate algorithmic acceleration with approaches to provide stable convergence, and optimization schedules that maximize convergence speed.

Cone-beam CT for imaging of the head/brain: Development and assessment of scanner prototype and reconstruction algorithms.

PURPOSE: Our aim was to develop a high-quality, mobile cone-beam computed tomography (CBCT) scanner for point-of-care detection and monitoring of low-contrast, soft-tissue abnormalities in the head/brain, such as acute intracranial hemorrhage (ICH). This work presents an integrated framework of hardware and algorithmic advances for improving soft-tissue contrast resolution and evaluation of its technical performance with human subjects. METHODS: Four configurations of a CBCT scanner prototype were designed and implemented to investigate key aspects of hardware (including system geometry, antiscatter grid, bowtie filter) and technique protocols. An integrated software pipeline (c.f., a serial cascade of algorithms) was developed for artifact correction (image lag, glare, beam hardening and x-ray scatter), motion compensation, and three-dimensional image (3D) reconstruction [penalized weighted least squares (PWLS), with a hardware-specific statistical noise model]. The PWLS method was extended in this work to accommodate multiple, independently moving regions with different resolution (to address both motion compensation and image truncation). Imaging performance was evaluated quantitatively and qualitatively with 41 human subjects in the neurosciences critical care unit (NCCU) at our institution. RESULTS: The progression of four scanner configurations exhibited systematic improvement in the quality of raw data by variations in system geometry (source-detector distance), antiscatter grid, and bowtie filter. Quantitative assessment of CBCT images in 41 subjects demonstrated: ~70% reduction in image nonuniformity with artifact correction methods (lag, glare, beam hardening, and scatter); ~40% reduction in motion-induced streak artifacts via the multi-motion compensation method; and ~15% improvement in soft-tissue contrast-to-noise ratio (CNR) for PWLS compared to filtered backprojection (FBP) at matched resolution. Each of these components was important to improve contrast resolution for point-of-care cranial imaging. CONCLUSIONS: This work presents the first application of a high-quality, point-of-care CBCT system for imaging of the head/ brain in a neurological critical care setting. Hardware configuration iterations and an integrated software pipeline for artifacts correction and PWLS reconstruction mitigated artifacts and noise to achieve image quality that could be valuable for point-of-care detection and monitoring of a variety of intracranial abnormalities, including ICH and hydrocephalus.

Quantitative Assessment of Weight-Bearing Fracture Biomechanics Using Extremity Cone-Beam CT.

PURPOSE: We investigate an application of multisource extremity Cone-Beam CT (CBCT) with capability of weight-bearing tomographic imaging to obtain quantitative measurements of load-induced deformation of metal internal fixation hardware (e.g. tibial plate). Such measurements are desirable to improve the detection of delayed fusion or non-union of fractures, potentially facilitating earlier return to weight-bearing activities. METHODS: To measure the deformation, we perform a deformable 3D-2D registration of a prior model of the implant to its CBCT projections under load-bearing. This Known-Component Registration (KC-Reg) framework avoids potential errors that emerge when the deformation is estimated directly from 3D reconstructions with metal artifacts. The 3D-2D registration involves a free-form deformable (FFD) point cloud model of the implant and a 3D cubic B-spline representation of the deformation. Gradient correlation is used as the optimization metric for the registration. The proposed approach was tested in experimental studies on the extremity CBCT system. A custom jig was designed to apply controlled axial loads to a fracture model, emulating weight-bearing imaging scenarios. Performance evaluation involved a Sawbone tibia phantom with an ~4 mm fracture gap. The model was fixed with a locking plate and imaged under five loading conditions. To investigate performance in the presence of confounding background gradients, additional experiments were performed with a pre-deformed femoral plate placed in a water bath with Ca bone mineral density inserts. Errors were measured using eight reference BBs for the tibial plate, and surface point distances for the femoral plate, where a prior model of deformed implant was available for comparison. RESULTS: Both in the loaded tibial plate case and for the femoral plate with confounding background gradients, the proposed KC-Reg framework estimated implant deformations with errors of <0.2 mm for the majority of the investigated deformation magnitudes (error range 0.14 - 0.25 mm). The accuracy was comparable between 3D-2D registrations performed from 12 x-ray views and registrations obtained from as few as 3 views. This was likely enabled by the unique three-source x-ray unit on the extremity CBCT scanner, which implements two off-central-plane focal spots that provided oblique views of the field-of-view to aid implant pose estimation. CONCLUSION: Accurate measurements of fracture hardware deformations under physiological weight-bearing are feasible using an extremity CBCT scanner and FFD 3D-2D registration. The resulting deformed implant models can be incorporated into tomographic reconstructions to reduce metal artifacts and improve quantification of the mineral content of fracture callus in CBCT volumes.

Quantitative Cone-Beam CT of Bone Mineral Density Using Model-Based Reconstruction.

PURPOSE: We develop and validate a model-based framework for artifact correction and image reconstruction to enable application of Cone-Beam CT (CBCT) in quantitative assessment of bone mineral density (BMD). Compared to conventional quantitative CT, this approach does not require a BMD calibration phantom in the field-of-view during an object scan. METHODS: The quantitative CBCT (qCBCT) imaging framework combined fast Monte Carlo (MC) scatter estimation, accurate models of detector response, and polyenergetic Poisson likelihood (PolyPL, Elbakri et al 2003). The underlying object model assumed that the tissues were ideal mixtures of water and calcium carbonate (CaCO3). Accuracy and reproducibility of qCBCT was evaluated in benchtop test-retest studies emulating a compact extremity CBCT system (axis-detector distance=56 cm, 90 kVp x-ray beam, ~16 mGy central dose). Various arrangements of Ca inserts (50-500 mg/mL) were placed in water cylinders of ~11 cm to ~15 cm diameter and scanned at multiple positions inside the field-of-view for a total of 20 configurations. In addition, a cadaveric ankle was imaged in five configurations (with and without Ca inserts and water bath). Coefficient of variation (CV) of BMD values across different experimental configurations was used to assess reproducibility under varying imaging conditions. The performance of the model-based qCBCT framework (MC + PolyPL) was compared to FDK with water beam hardening correction and MC scatter correction. RESULTS: The PolyPL framework achieved accuracy of 20 mg/mL or better across all insert densities and experimental configurations. By comparison, the accuracy of the FDK-based BMD estimates deteriorated with higher mineralization, resulting in ~120 mg/mL error for a 500 mg/mL Ca insert. Additionally, the model-based approach mitigated residual streaks that were present in FDK reconstructions. The CV of both methods was ~15% at 50 mg/mL Ca and less than ~8% for higher density inserts, where the PolyPL framework achieved 20-25% lower CV than the FDK-based approach. CONCLUSION: Accurate and reproducible BMD measurements can be achieved in extremity CBCT, supporting clinical applications in quantitative monitoring of fracture risk, osteoporosis treatment, and early osteoarthritis.

Known-Component Model-Based Material Decomposition for Dual Energy Imaging of Bone Compositions in the Presence of Metal Implant.

Dual energy computed tomography (DE CT) is a promising technology for the assessment of bone compositions. One of potential applications involves evaluations of fracture healing using longitudinal measurements of callus mineralization. However, imaging of fractures is often challenged by the presence of metal fixation hardware. In this work, we report on a new simultaneous DE reconstruction-decomposition algorithm that integrates the previously introduced Model-Based Material Decomposition (MBMD) with a Known-Component (KC) framework to mitigate metal artifacts. The algorithm was applied to the DE data obtained on a dedicated extremity cone-beam CT (CBCT) with capability for weight-bearing imaging. To acquire DE projections in a single gantry rotation, we exploited a unique multisource design of the system, where three X-ray sources were mounted parallel to the axis of rotation. The central source provided high energy (HE) data at 120 kVp, while the two remaining sources were operated at a low energy (LE) of 60 kVp. This novel acquisition trajectory further motivates the use of MBMD to accommodate this complex DE sampling pattern. The algorithm was validated in a simulation study using a digital extremity phantom. The phantom consisted of a water background with an insert containing varying concentrations of calcium (50 - 175 mg/mL). Two configurations of titanium implants were considered: a fixation plate and an intramedullary nail. The accuracy of calcium-water decompositions obtained with the proposed KC-MBMD algorithm was compared to MBMD without metal component model. Metal artifacts were almost completely removed by KC-MBMD. Relative absolute errors of calcium concentration in the vicinity of metal were 6% - 31% for KC-MBMD (depending on the calcium insert and implant configuration), compared favorably to 48% - 273% for MBMD. Moreover, accuracy of concentration estimates for KC-MBMD in the presence of metal implant approached that of MBMD in a configuration without implant (6%-23%). The proposed algorithm achieved accurate DE material decomposition in the presence of metal implants using a non-conventional, axial multisource DE acquisition pattern.

Known-component metal artifact reduction (KC-MAR) for cone-beam CT.

Intraoperative cone-beam CT (CBCT) is increasingly used for surgical navigation and validation of device placement. In spinal deformity correction, CBCT provides visualization of pedicle screws and fixation rods in relation to adjacent anatomy. This work reports and evaluates a method that uses prior information regarding such surgical instrumentation for improved metal artifact reduction (MAR). The known-component MAR (KC-MAR) approach achieves precise localization of instrumentation in projection images using rigid or deformable 3D-2D registration of component models, thereby overcoming residual errors associated with segmentation-based methods. Projection data containing metal components are processed via 2D inpainting of the detector signal, followed by 3D filtered back-projection (FBP). Phantom studies were performed to identify nominal algorithm parameters and quantitatively investigate performance over a range of component material composition and size. A cadaver study emulating screw and rod placement in spinal deformity correction was conducted to evaluate performance under realistic clinical imaging conditions. KC-MAR demonstrated reduction in artifacts (standard deviation in voxel values) across a range of component types and dose levels, reducing the artifact to 5-10 HU. Accurate component delineation was demonstrated for rigid (screw) and deformable (rod) models with sub-mm registration errors, and a single-pixel dilation of the projected components was found to compensate for partial-volume effects. Artifacts associated with spine screws and rods were reduced by 40%-80% in cadaver studies, and the resulting images demonstrated markedly improved visualization of instrumentation (e.g. screw threads) within cortical margins. The KC-MAR algorithm combines knowledge of surgical instrumentation with 3D image reconstruction in a manner that overcomes potential pitfalls of segmentation. The approach is compatible with FBP-thereby maintaining simplicity in a manner that is consistent with surgical workflow-or more sophisticated model-based reconstruction methods that could further improve image quality and/or help reduce radiation dose.

Volume-of-interest Imaging Using Multiple Aperture Devices.

Volume-of-interest (VOI) imaging is a promising strategy for dose reduction in computed tomography (CT) while retaining image quality. However, implementation of VOI-CT has been challenged by the lack of adequate hardware and the interior tomography reconstruction problem. Multiple aperture devices (MAD) are a novel filtration scheme that can achieve x-ray fluence field modulation in a compact design with small translations. In this work, we propose a general approach for VOI imaging using MADs. MAD trajectories are designed to dynamically tailor the fluence for prescribed VOI. A penalized-likelihood reconstruction algorithm is proposed for fully truncated projections extended with scout views. Physical experiments were conducted to verify the feasibility for non-centered elliptic VOIs. Image quality and dose were estimated and compared with standard fullfield protocols. The ability of MAD-based VOI imaging to retain high image quality while significantly decreasing the total dose is demonstrated, suggesting the potential for dose reduction in clinical CT applications.

Convergence criterion for MBIR based on the local noise-power spectrum: Theory and implementation in a framework for accelerated 3D image reconstruction with a morphological pyramid.

Model-based iterative reconstruction (MBIR) offers improved noise-resolution tradeoffs and artifact reduction in cone-beam CT compared to analytical reconstruction, but carries increased computational burden. An important consideration in minimizing computation time is reliable selection of the stopping criterion to perform the minimum number of iterations required to obtain the desired image quality. Most MBIR methods rely on a fixed number of iterations or relative metrics on image or cost-function evolution, and it would be desirable to use metrics that are more representative of the underlying image properties. A second front for reduction of computation time is the use of acceleration techniques (e.g. subsets or momentum). However, most of these techniques do not strictly guarantee convergence of the resulting MBIR method. A data-dependent analytical model of noise-power spectrum (NPS) for penalized weighted least squares (PWLS) reconstruction is proposed as an absolute metric of image properties for the fully converged volume. Distance to convergence is estimated as the root mean squared error (RMSE) between the estimated NPS and an NPS measured on a uniform region of interest (ROI) in the evolving volume. Iterations are stopped when the RMSE falls below a threshold directly related with the properties of the target image. Further acceleration was achieved by combining the spectral stopping criterion with a morphological pyramid (mPyr) in which the minimization of the PWLS cost-function is divided in a cascade of stages. The algorithm parameters (voxel size in this work) change between stages to achieve faster evolution in early stages, and a final stage with the target parameters to guarantee convergence. Transition between stages is governed by the spectral stopping criterion. The approach was evaluated on simulated CBCT data of a realistic digital abdomen phantom. Accuracy of the NPS model and evolution with time of the distance from the measured NPS was assessed in two ROIs. Performance of the spectrally-driven mPyr architecture was compared to a conventional, single stage, PWLS, and to two mPyr designs running a fixed number of iterations. The spectrally-driven mPyr achieved faster convergence, with 40% lower RMSE than the single stage PWLS, and between 10% and 20% RMSE reduction compared to other mPyr designs. The proposed spectral stopping criterion proved to be a suitable choice for a stopping rule, and, in particular, to govern mPyr stage transition.

3D-2D Image Registration in Virtual Long-Film Imaging: Application to Spinal Deformity Correction.

PURPOSE: Intraoperative 2D virtual long-film (VLF) imaging is investigated for 3D guidance and confirmation of the surgical product in spinal deformity correction. Multi-slot-scan geometry (rather than a single-slot "topogram") is exploited to produce parallax views of the scene for accurate 3D colocalization from a single radiograph. METHODS: The multi-slot approach uses additional angled collimator apertures to form fan-beams with disparate views (parallax) of anatomy and instrumentation and to extend field-of-view beyond the linear motion limits. Combined with a knowledge of surgical implants (pedicle screws and/or spinal rods modeled as "known components"), 3D-2D image registration is used to solve for pose estimates via optimization of image gradient correlation. Experiments were conducted in cadaver studies emulating the system geometry of the O-arm (Medtronic, Minneapolis MN). RESULTS: Experiments demonstrated feasibility of multi-slot VLF and quantified the geometric accuracy of 3D-2D registration using VLF acquisitions. Registration of pedicle screws from a single VLF yielded mean target registration error of (2.0±0.7) mm, comparable to the accuracy of surgical trackers and registration using multiple radiographs (e.g., AP and LAT). CONCLUSIONS: 3D-2D registration in a single VLF image offers a promising new solution for image guidance in spinal deformity correction. The ability to accurately resolve pose from a single view absolves workflow challenges of multiple-view registration and suggests application beyond spine surgery, such as reduction of long-bone fractures.

Statistical weights for model-based reconstruction in cone-beam CT with electronic noise and dual-gain detector readout.

Cone-beam CT (CBCT) systems commonly incorporate a flat-panel detector (FPD) with multiple-gain readout capability to reduce electronic noise and extend dynamic range. In this work, we report a penalized weighted least-squares (PWLS) method for CBCT image reconstruction with a system model that includes the electronic noise characteristics of FPDs, including systems with dynamic-gain or dual-gain (DG) readout in which the electronic noise is spatially varying. Statistical weights in PWLS were modified to account for the contribution of the electronic noise (algorithm denoted [Formula: see text]), and the method was combined with a certainty-based approach that improves the homogeneity of spatial resolution (algorithm denoted [Formula: see text]). The methods were tested in phantom studies designed to stress DG readout characteristics and translated to a clinical study for CBCT of patients with head traumas. The [Formula: see text] method demonstrated superior noise-resolution tradeoffs compared to filtered back-projection (FBP) and conventional PWLS. For example, with spatial resolution (edge-spread function width) matched at 0.65 mm, [Formula: see text] reduced variance by 28%-39% and 15%-25% compared to FBP and PWLS, respectively. The [Formula: see text] method achieved more homogeneous spatial resolution than [Formula: see text] while maintaining similar variance reduction. These findings were confirmed in clinical studies, which showed ~20% variance reduction in peripheral regions of the brain, potentially improving visual image quality in detection of epidural and/or subdural intracranial hemorrhage. The results are consistent with the general notion that incorporating a more accurate system model improves performance in optimization-based statistical CBCT reconstruction-in this case, a more accurate model for (spatially varying) electronic noise to improve detectability of low-contrast lesions.

Image quality and dose characteristics for an O-arm intraoperative imaging system with model-based image reconstruction.

PURPOSE: To assess the imaging performance and radiation dose characteristics of the O-arm CBCT imaging system (Medtronic Inc., Littleton MA) and demonstrate the potential for improved image quality and reduced dose via model-based image reconstruction (MBIR). METHODS: Two main studies were performed to investigate previously unreported characteristics of the O-arm system. First is an investigation of dose and 3D image quality achieved with filtered back-projection (FBP) - including enhancements in geometric calibration, handling of lateral truncation and detector saturation, and incorporation of an isotropic apodization filter. Second is implementation of an MBIR algorithm based on Huber-penalized likelihood estimation (PLH) and investigation of image quality improvement at reduced dose. Each study involved measurements in quantitative phantoms as a basis for analysis of contrast-to-noise ratio and spatial resolution as well as imaging of a human cadaver to test the findings under realistic imaging conditions. RESULTS: View-dependent calibration of system geometry improved the accuracy of reconstruction as quantified by the full-width at half maximum of the point-spread function - from 0.80 to 0.65 mm - and yielded subtle but perceptible improvement in high-contrast detail of bone (e.g., temporal bone). Standard technique protocols for the head and body imparted absorbed dose of 16 and 18 mGy, respectively. For low-to-medium contrast (<100 HU) imaging at fixed spatial resolution (1.3 mm edge-spread function) and fixed dose (6.7 mGy), PLH improved CNR over FBP by +48% in the head and +35% in the body. Evaluation at different dose levels demonstrated 30% increase in CNR at 62% of the dose in the head and 90% increase in CNR at 50% dose in the body. CONCLUSIONS: A variety of improvements in FBP implementation (geometric calibration, truncation and saturation effects, and isotropic apodization) offer the potential for improved image quality and reduced radiation dose on the O-arm system. Further gains are possible with MBIR, including improved soft-tissue visualization, low-dose imaging protocols, and extension to methods that naturally incorporate prior information of patient anatomy and/or surgical instrumentation.

Reconstruction-of-difference (RoD) imaging for cone-beam CT neuro-angiography.

Timely evaluation of neurovasculature via CT angiography (CTA) is critical to the detection of pathology such as ischemic stroke. Cone-beam CTA (CBCT-A) systems provide potential advantages in the timely use at the point-of-care, although challenges of a relatively slow gantry rotation speed introduce tradeoffs among image quality, data consistency and data sparsity. This work describes and evaluates a new reconstruction-of-difference (RoD) approach that is robust to such challenges. A fast digital simulation framework was developed to test the performance of the RoD over standard reference reconstruction methods such as filtered back-projection (FBP) and penalized likelihood (PL) over a broad range of imaging conditions, grouped into three scenarios to test the trade-off between data consistency, data sparsity and peak contrast. Two experiments were also conducted using a CBCT prototype and an anthropomorphic neurovascular phantom to test the simulation findings in real data. Performance was evaluated primarily in terms of normalized root mean square error (NRMSE) in comparison to truth, with reconstruction parameters chosen to optimize performance in each case to ensure fair comparison. The RoD approach reduced NRMSE in reconstructed images by up to 50%-53% compared to FBP and up to 29%-31% compared to PL for each scenario. Scan protocols well suited to the RoD approach were identified that balance tradeoffs among data consistency, sparsity and peak contrast-for example, a CBCT-A scan with 128 projections acquired in 8.5 s over a 180° + fan angle half-scan for a time attenuation curve with ~8.5 s time-to-peak and 600 HU peak contrast. With imaging conditions such as the simulation scenarios of fixed data sparsity (i.e. varying levels of data consistency and peak contrast), the experiments confirmed the reduction of NRMSE by 34% and 17% compared to FBP and PL, respectively. The RoD approach demonstrated superior performance in 3D angiography compared to FBP and PL in all simulation and physical experiments, suggesting the possibility of CBCT-A on low-cost, mobile imaging platforms suitable to the point-of-care. The algorithm demonstrated accurate reconstruction with a high degree of robustness against data sparsity and inconsistency.

Spatial Resolution and Noise Prediction in Flat-Panel Cone-Beam CT Penalized-likelihood Reconstruction.

PURPOSE: Model based iterative reconstruction (MBIR) algorithms such as penalized-likelihood (PL) methods have data-dependent and shift-variant image properties. Predictors of local reconstructed noise and resolution have found application in a number of methods that seek to understand, control, and optimize CT data acquisition and reconstruction parameters in a prospective fashion (as opposed to studies based on exhaustive evaluation). However, previous MBIR prediction methods have relied on idealized system models. In this work, we develop and validate new predictors using accurate physical models specific to flat-panel CT systems. METHODS: Novel predictors for estimation of local spatial resolution and noise properties are developed for PL reconstruction that include a physical model for blur and correlated noise in flat-panel cone-beam CT (CBCT) acquisitions. Prospective predictions (e.g., without reconstruction) of local point spread function and and local noise power spectrum (NPS) model are applied, compared, and validated using a flat-panel CBCT test bench. RESULTS: Comparisons between prediction and physical measurements show excellent agreement for both spatial resolution and noise properties. In comparison, traditional prediction methods (that ignore blur/correlation found in flat-panel data) fail to capture important data characteristics and show significant mismatch. CONCLUSION: Novel image property predictors permit prospective assessment of flat-panel CBCT using MBIR. Such predictors enable standard and task-based performance assessments, and are well-suited to evaluation, control, and optimization of the CT imaging chain (e.g., x-ray technique, reconstruction parameters, novel data acquisition methods, etc.) for improved imaging performance and/or dose utilization.

High-Resolution Extremity Cone-Beam CT with a CMOS Detector: Evaluation of a Clinical Prototype in Quantitative Assessment of Bone Microarchitecture.

PURPOSE: A prototype high-resolution extremity cone-beam CT (CBCT) system based on a CMOS detector was developed to support quantitative in vivo assessment of bone microarchitecture. We compare the performance of CMOS CBCT to an amorphous silicon (a-Si:H) FPD extremity CBCT in imaging of trabecular bone. METHODS: The prototype CMOS-based CBCT involves a DALSA Xineos3030 detector (99 µm pixels) with 400 µm-thick CsI scintillator and a compact 0.3 FS rotating anode x-ray source. We compare the performance of CMOS CBCT to an a-Si:H FPD scanner built on a similar gantry, but using a Varian PaxScan2530 detector with 0.137 mm pixels and a 0.5 FS stationary anode x-ray source. Experimental studies include measurements of Modulation Transfer Function (MTF) for the detectors and in 3D image reconstructions. Image quality in clinical scenarios is evaluated in scans of a cadaver ankle. Metrics of trabecular microarchitecture (BV/TV, Bone Volume/Total Volume, TbSp, Trabecular Spacing, and TbTh, trabecular thickness) are obtained in a human ulna using CMOS CBCT and a-Si:H FPD CBCT and compared to gold standard µCT. RESULTS: The CMOS detector achieves ~40% increase in the f20 value (frequency at which MTF reduces to 0.20) compared to the a-Si:H FPD. In the reconstruction domain, the FWHM of a 127 µm tungsten wire is also improved by ~40%. Reconstructions of a cadaveric ankle reveal enhanced modulation of trabecular structures with the CMOS detector and soft-tissue visibility that is similar to that of the a-Si:H FPD system. Correlations of the metrics of bone microarchitecture with gold-standard µCT are improved with CMOS CBCT: from 0.93 to 0.98 for BV/TV, from 0.49 to 0.74 for TbTh, and from 0.9 to 0.96 for TbSp. CONCLUSION: Adoption of a CMOS detector in extremity CBCT improved spatial resolution and enhanced performance in metrics of bone microarchitecture compared to a conventional a-Si:H FPD. The results support development of clinical applications of CMOS CBCT in quantitative imaging of bone health.

Advanced Image Registration and Reconstruction using the O-Arm System: Dose Reduction, Image Quality, and Guidance using Known-Component Models.

PURPOSE: Model-based image registration and reconstruction offer strong potential for improved safety and precision in image-guided interventions. Advantages include reduced radiation dose, improved soft-tissue visibility (detection of complications), and accurate guidance with/without a dedicated navigation system. This work reports the development and performance of such methods on an O-arm system for intraoperative imaging and translates them to first clinical studies. METHODS: Two novel methodologies predicate the work: (1) Known-Component Registration (KC-Reg) for 3D localization of the patient and interventional devices from 2D radiographs; and (2) Penalized-Likelihood reconstruction (PLH) for improved 3D image quality and dose reduction. A thorough assessment of geometric stability, dosimetry, and image quality was performed to define algorithm parameters for imaging and guidance protocols. Laboratory studies included: evaluation of KC-Reg in localization of spine screws delivered in cadaver; and PLH performance in contrast, noise, and resolution in phantoms/cadaver compared to filtered backprojection (FBP). RESULTS: KC-Reg was shown to successfully register screw implants within ~1 mm based on as few as 3 radiographs. PLH was shown to improve soft-tissue visibility (61% improvement in CNR) compared to FBP at matched resolution. Cadaver studies verified the selection of algorithm parameters and the methods were successfully translated to clinical studies under an IRB protocol. CONCLUSIONS: Model-based registration and reconstruction approaches were shown to reduce dose and provide improved visualization of anatomy and surgical instrumentation. Immediate future work will focus on further integration of KC-Reg and PLH for Known-Component Reconstruction (KC-Recon) to provide high-quality intraoperative imaging in the presence of dense instrumentation.

A line fiducial method for geometric calibration of cone-beam CT systems with diverse scan trajectories.

Modern cone-beam CT systems, especially C-arms, are capable of diverse source-detector orbits. However, geometric calibration of these systems using conventional configurations of spherical fiducials (BBs) may be challenged for novel source-detector orbits and system geometries. In part, this is because the BB configurations are designed with careful forethought regarding the intended orbit so that BB marker projections do not overlap in projection views. Examples include helical arrangements of BBs (Rougee et al 1993 Proc. SPIE 1897 161-9) such that markers do not overlap in projections acquired from a circular orbit and circular arrangements of BBs (Cho et al 2005 Med. Phys. 32 968-83). As a more general alternative, this work proposes a calibration method based on an array of line-shaped, radio-opaque wire segments. With this method, geometric parameter estimation is accomplished by relating the 3D line equations representing the wires to the 2D line equations of their projections. The use of line fiducials simplifies many challenges with fiducial recognition and extraction in an orbit-independent manner. For example, their projections can overlap only mildly, for any gantry pose, as long as the wires are mutually non-coplanar in 3D. The method was tested in application to circular and non-circular trajectories in simulation and in real orbits executed using a mobile C-arm prototype for cone-beam CT. Results indicated high calibration accuracy, as measured by forward and backprojection/triangulation error metrics. Triangulation errors on the order of microns and backprojected ray deviations uniformly less than 0.2 mm were observed in both real and simulated orbits. Mean forward projection errors less than 0.1 mm were observed in a comprehensive sweep of different C-arm gantry angulations. Finally, successful integration of the method into a CT imaging chain was demonstrated in head phantom scans.

Task-Driven Orbit Design and Implementation on a Robotic C-Arm System for Cone-Beam CT.

PURPOSE: This work applies task-driven optimization to the design of non-circular orbits that maximize imaging performance for a particular imaging task. First implementation of task-driven imaging on a clinical robotic C-arm system is demonstrated, and a framework for orbit calculation is described and evaluated. METHODS: We implemented a task-driven imaging framework to optimize orbit parameters that maximize detectability index d'. This framework utilizes a specified Fourier domain task function and an analytical model for system spatial resolution and noise. Two experiments were conducted to test the framework. First, a simple task was considered consisting of frequencies lying entirely on the fz-axis (e.g., discrimination of structures oriented parallel to the central axial plane), and a "circle + arc" orbit was incorporated into the framework as a means to improve sampling of these frequencies, and thereby increase task-based detectability. The orbit was implemented on a robotic C-arm (Artis Zeego, Siemens Healthcare). A second task considered visualization of a cochlear implant simulated within a head phantom, with spatial frequency response emphasizing high-frequency content in the (fy , fz ) plane of the cochlea. An optimal orbit was computed using the task-driven framework, and the resulting image was compared to that for a circular orbit. RESULTS: For the fz -axis task, the circle + arc orbit was shown to increase d' by a factor of 1.20, with an improvement of 0.71 mm in a 3D edge-spread measurement for edges located far from the central plane and a decrease in streak artifacts compared to a circular orbit. For the cochlear implant task, the resulting orbit favored complementary views of high tilt angles in a 360° orbit, and d' was increased by a factor of 1.83. CONCLUSIONS: This work shows that a prospective definition of imaging task can be used to optimize source-detector orbit and improve imaging performance. The method was implemented for execution of non-circular, task-driven orbits on a clinical robotic C-arm system. The framework is sufficiently general to include both acquisition parameters (e.g., orbit, kV, and mA selection) and reconstruction parameters (e.g., a spatially varying regularizer).

High-resolution extremity cone-beam CT with a CMOS detector: Task-based optimization of scintillator thickness.

PURPOSE: CMOS x-ray detectors offer small pixel sizes and low electronic noise that may support the development of novel high-resolution imaging applications of cone-beam CT (CBCT). We investigate the effects of CsI scintillator thickness on the performance of CMOS detectors in high resolution imaging tasks, in particular in quantitative imaging of bone microstructure in extremity CBCT. METHODS: A scintillator thickness-dependent cascaded systems model of CMOS x-ray detectors was developed. Detectability in low-, high- and ultra-high resolution imaging tasks (Gaussian with FWHM of ~250 µm, ~80 µm and ~40 µm, respectively) was studied as a function of scintillator thickness using the theoretical model. Experimental studies were performed on a CBCT test bench equipped with DALSA Xineos3030 CMOS detectors (99 µm pixels) with CsI scintillator thicknesses of 400 µm and 700 µm, and a 0.3 FS compact rotating anode x-ray source. The evaluation involved a radiographic resolution gauge (0.6-5.0 lp/mm), a 127 µm tungsten wire for assessment of 3D resolution, a contrast phantom with tissue-mimicking inserts, and an excised fragment of human tibia for visual assessment of fine trabecular detail. RESULTS: Experimental studies show ~35% improvement in the frequency of 50% MTF modulation when using the 400 µm scintillator compared to the standard nominal CsI thickness of 700 µm. Even though the high-frequency DQE of the two detectors is comparable, theoretical studies show a 14% to 28% increase in detectability index (d'2) of high- and ultrahigh resolution tasks, respectively, for the detector with 400 µm CsI compared to 700 µm CsI. Experiments confirm the theoretical findings, showing improvements with the adoption of 400 µm panel in the visibility of the radiographic pattern (2× improvement in peak-to-through distance at 4.6 lp/mm) and a 12.5% decrease in the FWHM of the tungsten wire. Reconstructions of the tibial plateau reveal enhanced visibility of trabecular structures with the CMOS detector with 400 µm scinitllator. CONCLUSION: Applications on CMOS detectors in high resolution CBCT imaging of trabecular bone will benefit from using a thinner scintillator than the current standard in general radiography. The results support the translation of the CMOS sensor with 400 µm CsI onto the clinical prototype of CMOS-based extremity CBCT.

Correction of patient motion in cone-beam CT using 3D-2D registration.

Cone-beam CT (CBCT) is increasingly common in guidance of interventional procedures, but can be subject to artifacts arising from patient motion during fairly long (~5-60 s) scan times. We present a fiducial-free method to mitigate motion artifacts using 3D-2D image registration that simultaneously corrects residual errors in the intrinsic and extrinsic parameters of geometric calibration. The 3D-2D registration process registers each projection to a prior 3D image by maximizing gradient orientation using the covariance matrix adaptation-evolution strategy optimizer. The resulting rigid transforms are applied to the system projection matrices, and a 3D image is reconstructed via model-based iterative reconstruction. Phantom experiments were conducted using a Zeego robotic C-arm to image a head phantom undergoing 5-15 cm translations and 5-15° rotations. To further test the algorithm, clinical images were acquired with a CBCT head scanner in which long scan times were susceptible to significant patient motion. CBCT images were reconstructed using a penalized likelihood objective function. For phantom studies the structural similarity (SSIM) between motion-free and motion-corrected images was >0.995, with significant improvement (p < 0.001) compared to the SSIM values of uncorrected images. Additionally, motion-corrected images exhibited a point-spread function with full-width at half maximum comparable to that of the motion-free reference image. Qualitative comparison of the motion-corrupted and motion-corrected clinical images demonstrated a significant improvement in image quality after motion correction. This indicates that the 3D-2D registration method could provide a useful approach to motion artifact correction under assumptions of local rigidity, as in the head, pelvis, and extremities. The method is highly parallelizable, and the automatic correction of residual geometric calibration errors provides added benefit that could be valuable in routine use.