Assessment of Canalis Sinuosus located in maxillary anterior region by using cone beam computed tomography: a retrospective study

Background

The aim of the study is to determine the distribution, location, diameter, and distance measurements of Canalis Sinusosus (CS) in relation with age and sex.

Methods

300 Cone-Beam Computed Tomography (CBCT) images were evaluated. The distance between CS and nasal cavity floor (NCF), buccal cortical bone margin (BCM), alveolar ridge (AR), respectively.The presence of CS smaller than 1 mm, and the diameter of CS larger than 1 mm were determined. Accessory canals (AC) were classified according to their position relative to the teeth.

Results

435 CS with a diameter of at least 1 mm and 142 CS < 1 mm were identified. The most frequently observed location of CS was the region of the right central incisors. The mean diameter of the canals ( CS ≥ 1) was 1.31 ± 0.19 on the right side and 1.29 ± 0.17 on the left side. No gender differences were found in canal diameter were observed (p > 0.05). There was no significant difference between men and women in the distance between CS and the NCF on the right side, and a significant difference was found in the distance of CS-NCF on the left side (p = 0.047). There were no significant differences between age groups in all parameters.

Conclusion

CBCT is a useful tool for identifying CS. Location and diameter of ACs could not be associated with a specific age group or sex.

Computed Tomography: State-of-the-Art Advancements in Musculoskeletal Imaging

ABSTRACT

Although musculoskeletal magnetic resonance imaging (MRI) plays a dominant role in characterizing abnormalities, novel computed tomography (CT) techniques have found an emerging niche in several scenarios such as trauma, gout, and the characterization of pathologic biomechanical states during motion and weight-bearing. Recent developments and advancements in the field of musculoskeletal CT include 4-dimensional, cone-beam (CB), and dual-energy (DE) CT. Four-dimensional CT has the potential to quantify biomechanical derangements of peripheral joints in different joint positions to diagnose and characterize patellofemoral instability, scapholunate ligamentous injuries, and syndesmotic injuries. Cone-beam CT provides an opportunity to image peripheral joints during weight-bearing, augmenting the diagnosis and characterization of disease processes. Emerging CBCT technologies improved spatial resolution for osseous microstructures in the quantitative analysis of osteoarthritis-related subchondral bone changes, trauma, and fracture healing. Dual-energy CT-based material decomposition visualizes and quantifies monosodium urate crystals in gout, bone marrow edema in traumatic and nontraumatic fractures, and neoplastic disease. Recently, DE techniques have been applied to CBCT, contributing to increased image quality in contrast-enhanced arthrography, bone densitometry, and bone marrow imaging. This review describes 4-dimensional CT, CBCT, and DECT advances, current logistical limitations, and prospects for each technique.

Is the postoperative pedicle screw position after dorsal instrumentation with or without intraoperative cone beam CT imaging worse in patients with obesity than in normal-weight patients?

Background

Intraoperative cone beam CT (CBCT) imaging in dorsal instrumentation facilitates pedicle screw positioning. However, in patients with obesity, the benefit may be reduced due to artifacts that affect image quality. The purpose of this study was to evaluate whether intraoperative CBCT leads to an improved postoperative screw position compared to conventional fluoroscopy independent of body weight.

Methods

A total of 71 patients (18 patients with a BMI > 30 kg/m², 53 patients with a BMI < 30 kg/m²) who underwent dorsal instrumentation with intraoperative CBCT imaging were included in study groups one (SG1) and two (SG2). Two control groups (CG1 and CG2) were randomly sampled to include 22 patients with a BMI > 30 kg/m² and 60 patients with a BMI < 30 kg/m² who underwent dorsal instrumentation without intraoperative CBCT imaging. The pedicle screw position in postoperative computed tomography was assessed using the Gertzbein–Robbins classification.

Results

In SG1 (BMI > 30 kg/m²), a total of 107 (83.6%) pedicle screws showed no relevant perforation (type A + B), and 21 (16.4%) pedicle screws showed relevant perforation (type C − E). In SG2 (BMI < 30 kg/m²), 328 (90.9%) screws were classified as type A + B, and 33 (9.1%) screws were classified as type C − E. In CG1 (BMI > 30 kg/m²), 102 (76.1%) pedicle screws showed no relevant perforation (type A + B), and 32 (23.9%) pedicle screws showed relevant perforation (type C − E). In CG2 (BMI < 30 kg/m²), 279 (76.9%) screws were classified as type A + B, and 84 (23.1%) screws were classified as type C − E. There were significant differences between the values of SG1 and SG2 (p = 0.03) and between the values of SG2 and CG2 (p < 0.0001).

Conclusion

CBCT imaging in dorsal instrumentation can lead to an improved pedicle screw position among both patients with obesity and normal-weight patients. However, patients with obesity showed significantly worse pedicle screw positions postoperatively after dorsal instrumentation with intraoperative CBCT imaging than normal-weight patients.

Extended Intraoperative Longitudinal 3-Dimensional Cone Beam Computed Tomography Imaging With a Continuous Multi-Turn Reverse Helical Scan

OBJECTIVES

Cone beam computed tomography (CBCT) imaging is becoming an indispensable intraoperative tool; however, the current field of view prevents visualization of long anatomical sites, limiting clinical utility. Here, we demonstrate the longitudinal extension of the intraoperative CBCT field of view using a multi-turn reverse helical scan and assess potential clinical utility in interventional procedures.

MATERIALS AND METHODS

A fixed-room robotic CBCT imaging system, with additional real-time control, was used to implement a multi-turn reverse helical scan. The scan consists of C-arm rotation, through a series of clockwise and anticlockwise rotations, combined with simultaneous programmed table translation. The motion properties and geometric accuracy of the multi-turn reverse helical imaging trajectory were examined using a simple geometric phantom. To assess potential clinical utility, a pedicle screw posterior fixation procedure in the thoracic spine from T1 to T12 was performed on an ovine cadaver. The multi-turn reverse helical scan was used to provide postoperative assessment of the screw insertion via cortical breach grading and mean screw angle error measurements (axial and sagittal) from 2 observers. For all screw angle measurements, the intraclass correlation coefficient was calculated to determine observer reliability.

RESULTS

The multi-turn reverse helical scans took 100 seconds to complete and increased the longitudinal coverage by 370% from 17 cm to 80 cm. Geometric accuracy was examined by comparing the measured to actual dimensions (0.2 ± 0.1 mm) and angles (0.2 ± 0.1 degrees) of a simple geometric phantom, indicating that the multi-turn reverse helical scan provided submillimeter and degree accuracy with no distortion. During the pedicle screw procedure in an ovine cadaver, the multi-turn reverse helical scan identified 4 cortical breaches, confirmed via the postoperative CT scan. Directly comparing the screw insertion angles (n = 22) measured in the postoperative multi-turn reverse helical and CT scans revealed an average difference of 3.3 ± 2.6 degrees in axial angle and 1.9 ± 1.5 degrees in the sagittal angle from 2 expert observers. The intraclass correlation coefficient was above 0.900 for all measurements (axial and sagittal) across all scan types (conventional CT, multi-turn reverse helical, and conventional CBCT), indicating excellent reliability between observers.

CONCLUSIONS

Extended longitudinal field-of-view intraoperative 3-dimensional imaging with a multi-turn reverse helical scan is feasible on a clinical robotic CBCT imaging system, enabling long anatomical sites to be visualized in a single image, including in the presence of metal hardware.

Design Optimization of Spatial-Spectral Filters for Cone-Beam CT Material Decomposition

Spectral CT has shown promise for high-sensitivity quantitative imaging and material decomposition. This work presents a new device called a spatial-spectral filter (SSF) which consists of a tiled array of filter materials positioned near the x-ray source that is used to modulate the spectral shape of the x-ray beam. The filter is moved to obtain projection data that is sparse in each spectral channel. To process this sparse data, we employ a one-step direct model-based material decomposition (MBMD) to reconstruct basis material density images directly from the SSF CT data. To evaluate different possible SSF designs, we define a new Fisher-information-based predictive image quality metric called separability index which characterizes the ability of a spectral CT system to distinguish between the signals from two or more materials. This spectral CT performance metric can be used to optimize spectral CT system design. We conducted simulation-based design optimization study to find optimized combinations of filter materials, filter thicknesses, filter widths, and source settings. Finally, we present MBMD results using simulated SSF CT measurements from the optimized designs to demonstrate the ability to reconstruct basis material density images and to show the benefits of the optimized designs. Our results indicate that optimizing SSF CT for separability leads to high-performance at material discrimination tasks.

Model-based dual-energy tomographic image reconstruction of objects containing known metal components

Dual-energy (DE) decomposition has been adopted in orthopedic imaging to measure bone composition and visualize intraarticular contrast enhancement. One of the potential applications involves monitoring of callus mineralization for longitudinal assessment of fracture healing. However, fracture repair usually involves internal fixation hardware that can generate significant artifacts in reconstructed images. To address this challenge, we develop a novel algorithm that combines simultaneous reconstruction-decomposition using a previously reported method for model-based material decomposition (MBMD) augmented by the known-component (KC) reconstruction framework to mitigate metal artifacts. We apply the proposed algorithm to simulated DE data representative of a dedicated extremity cone-beam CT (CBCT) employing an x-ray unit with three vertically arranged sources. The scanner generates DE data with non-coinciding high- and low-energy projection rays when the central source is operated at high tube potential and the peripheral sources at low potential. The proposed algorithm was validated using a digital extremity phantom containing varying concentrations of Ca-water mixtures and Ti implants. Decomposition accuracy was compared to MBMD without the KC model. The proposed method suppressed metal artifacts and yielded estimated Ca concentrations that approached the reconstructions of an implant-free phantom for most mixture regions. In the vicinity of simple components, the errors of Ca density estimates obtained by incorporating KC in MBMD were ∼1.5-5× lower than the errors of conventional MBMD; for cases with complex implants, the errors were ∼3-5× lower. In conclusion, the proposed method can achieve accurate bone mineral density measurements in the presence of metal implants using non-coinciding DE projections acquired on a multisource CBCT system.

Assessment of Eye Lens Dose Reduction When Using Lateral Lead Shields on the Patient's Head during Neurointerventional Fluoroscopic Procedures and Cone-beam Computed Tomography (CBCT) Scans

The purpose of this study was to evaluate the effect of placing small lead shields on the temple region of the skull to reduce radiation dose to the lens of the eye during interventional fluoroscopically-guided procedures and cone-beam computed tomography (CBCT) scans of the head. EGSnrc Monte-Carlo code was used to determine the eye lens dose reduction when using lateral lead shields for single x-ray projections, CBCT scans with different protocols, and interventional neuroradiology procedures with the Zubal computational head phantom. A clinical C-Arm system was used to take radiographic projections and CBCT scans of anthropomorphic head phantoms without and with lead patches, and the images were compared to assess the effect of the shields. For single lateral projections, a 0.1 (0.3)-mm-thick lead patch reduced the dose to the left-eye lens by 40% to 60% (55% to 80%) from 45° to 90° RAO and to the right-eye lens by around 30% (55%) from 70° to 90° RAO. For different CBCT protocols, the reduction of lens dose with a 0.3-mm-thick lead patch ranged from 20% to 53% at 110 kVp. For CBCT scans of the anthropomorphic phantom, the lead patch introduced streak artifacts that were mainly in the orbital regions but were insignificant in the brain region where most neurointerventional activity occurs. The dose to the patient's eye lens can be reduced considerably by placing small lead shields over the temple region of the head without substantially compromising image quality in neuro-imaging procedures.

C-arm orbits for metal artifact avoidance (MAA) in cone-beam CT

Metal artifacts present a challenge to cone-beam CT (CBCT) image-guided surgery, obscuring visualization of metal instruments and adjacent anatomy-often in the very region of interest pertinent to the imaging/surgical tasks. We present a method to reduce the influence of metal artifacts by prospectively defining an image acquisition protocol-viz., the C-arm source-detector orbit-that mitigates metal-induced biases in the projection data. The metal artifact avoidance (MAA) method is compatible with simple mobile C-arms, does not require exact prior information on the patient or metal implants, and is consistent with 3D filtered backprojection (FBP), more advanced (e.g. polyenergetic) model-based image reconstruction (MBIR), and metal artifact reduction (MAR) post-processing methods. The MAA method consists of: (i) coarse localization of metal objects in the field-of-view (FOV) via two or more low-dose scout projection views and segmentation (e.g. a simple U-Net) in coarse backprojection; (ii) model-based prediction of metal-induced x-ray spectral shift for all source-detector vertices accessible by the imaging system (e.g. gantry rotation and tilt angles); and (iii) identification of a circular or non-circular orbit that reduces the variation in spectral shift. The method was developed, tested, and evaluated in a series of studies presenting increasing levels of complexity and realism, including digital simulations, phantom experiment, and cadaver experiment in the context of image-guided spine surgery (pedicle screw implants). The MAA method accurately predicted tilted circular and non-circular orbits that reduced the magnitude of metal artifacts in CBCT reconstructions. Realistic distributions of metal instrumentation were successfully localized (0.71 median Dice coefficient) from 2-6 low-dose scout views even in complex anatomical scenes. The MAA-predicted tilted circular orbits reduced root-mean-square error (RMSE) in 3D image reconstructions by 46%-70% and 'blooming' artifacts (apparent width of the screw shaft) by 20-45%. Non-circular orbits defined by MAA achieved a further ∼46% reduction in RMSE compared to the best (tilted) circular orbit. The MAA method presents a practical means to predict C-arm orbits that minimize spectral bias from metal instrumentation. Resulting orbits-either simple tilted circular orbits or more complex non-circular orbits that can be executed with a motorized multi-axis C-arm-exhibited substantial reduction of metal artifacts in raw CBCT reconstructions by virtue of higher fidelity projection data, which are in turn compatible with subsequent MAR post-processing and/or polyenergetic MBIR to further reduce artifacts.

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.

Image quality improvement in cone-beam CT using the super-resolution technique

This study was conducted to improve cone-beam computed tomography (CBCT) image quality using the super-resolution technique, a method of inferring a high-resolution image from a low-resolution image. This technique is used with two matrices, so-called dictionaries, constructed respectively from high-resolution and low-resolution image bases. For this study, a CBCT image, as a low-resolution image, is represented as a linear combination of atoms, the image bases in the low-resolution dictionary. The corresponding super-resolution image was inferred by multiplying the coefficients and the high-resolution dictionary atoms extracted from planning CT images. To evaluate the proposed method, we computed the root mean square error (RMSE) and structural similarity (SSIM). The resulting RMSE and SSIM between the super-resolution images and the planning CT images were, respectively, as much as 0.81 and 1.29 times better than those obtained without using the super-resolution technique. We used super-resolution technique to improve the CBCT image quality.

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.

Z-Index Parameterization for Volumetric CT Image Reconstruction via 3-D Dictionary Learning

Despite the rapid developments of X-ray cone-beam CT (CBCT), image noise still remains a major issue for the low dose CBCT. To suppress the noise effectively while retain the structures well for low dose CBCT image, in this paper, a sparse constraint based on the 3-D dictionary is incorporated into a regularized iterative reconstruction framework, defining the 3-D dictionary learning (3-DDL) method. In addition, by analyzing the sparsity level curve associated with different regularization parameters, a new adaptive parameter selection strategy is proposed to facilitate our 3-DDL method. To justify the proposed method, we first analyze the distributions of the representation coefficients associated with the 3-D dictionary and the conventional 2-D dictionary to compare their efficiencies in representing volumetric images. Then, multiple real data experiments are conducted for performance validation. Based on these results, we found: 1) the 3-D dictionary-based sparse coefficients have three orders narrower Laplacian distribution compared with the 2-D dictionary, suggesting the higher representation efficiencies of the 3-D dictionary; 2) the sparsity level curve demonstrates a clear Z-shape, and hence referred to as Z-curve, in this paper; 3) the parameter associated with the maximum curvature point of the Z-curve suggests a nice parameter choice, which could be adaptively located with the proposed Z-index parameterization (ZIP) method; 4) the proposed 3-DDL algorithm equipped with the ZIP method could deliver reconstructions with the lowest root mean squared errors and the highest structural similarity index compared with the competing methods; 5) similar noise performance as the regular dose FDK reconstruction regarding the standard deviation metric could be achieved with the proposed method using (1/2)/(1/4)/(1/8) dose level projections. The contrast-noise ratio is improved by ~2.5/3.5 times with respect to two different cases under the (1/8) dose level compared with the low dose FDK reconstruction. The proposed method is expected to reduce the radiation dose by a factor of 8 for CBCT, considering the voted strongly discriminated low contrast tissues.

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.

A model-based scatter artifacts correction for cone beam CT

PURPOSE

Due to the increased axial coverage of multislice computed tomography (CT) and the introduction of flat detectors, the size of x-ray illumination fields has grown dramatically, causing an increase in scatter radiation. For CT imaging, scatter is a significant issue that introduces shading artifact, streaks, as well as reduced contrast and Hounsfield Units (HU) accuracy. The purpose of this work is to provide a fast and accurate scatter artifacts correction algorithm for cone beam CT (CBCT) imaging.

METHODS

The method starts with an estimation of coarse scatter profiles for a set of CBCT data in either image domain or projection domain. A denoising algorithm designed specifically for Poisson signals is then applied to derive the final scatter distribution. Qualitative and quantitative evaluations using thorax and abdomen phantoms with Monte Carlo (MC) simulations, experimental Catphan phantom data, and in vivo human data acquired for a clinical image guided radiation therapy were performed. Scatter correction in both projection domain and image domain was conducted and the influences of segmentation method, mismatched attenuation coefficients, and spectrum model as well as parameter selection were also investigated.

RESULTS

Results show that the proposed algorithm can significantly reduce scatter artifacts and recover the correct HU in either projection domain or image domain. For the MC thorax phantom study, four-components segmentation yields the best results, while the results of three-components segmentation are still acceptable. The parameters (iteration number K and weight β) affect the accuracy of the scatter correction and the results get improved as K and β increase. It was found that variations in attenuation coefficient accuracies only slightly impact the performance of the proposed processing. For the Catphan phantom data, the mean value over all pixels in the residual image is reduced from -21.8 to -0.2 HU and 0.7 HU for projection domain and image domain, respectively. The contrast of the in vivo human images is greatly improved after correction.

CONCLUSIONS

The software-based technique has a number of advantages, such as high computational efficiency and accuracy, and the capability of performing scatter correction without modifying the clinical workflow (i.e., no extra scan/measurement data are needed) or modifying the imaging hardware. When implemented practically, this should improve the accuracy of CBCT image quantitation and significantly impact CBCT-based interventional procedures and adaptive radiation therapy.

Reconstruction of difference in sequential CT studies using penalized likelihood estimation

Characterization of anatomical change and other differences is important in sequential computed tomography (CT) imaging, where a high-fidelity patient-specific prior image is typically present, but is not used, in the reconstruction of subsequent anatomical states. Here, we introduce a penalized likelihood (PL) method called reconstruction of difference (RoD) to directly reconstruct a difference image volume using both the current projection data and the (unregistered) prior image integrated into the forward model for the measurement data. The algorithm utilizes an alternating minimization to find both the registration and reconstruction estimates. This formulation allows direct control over the image properties of the difference image, permitting regularization strategies that inhibit noise and structural differences due to inconsistencies between the prior image and the current data. Additionally, if the change is known to be local, RoD allows local acquisition and reconstruction, as opposed to traditional model-based approaches that require a full support field of view (or other modifications). We compared the performance of RoD to a standard PL algorithm, in simulation studies and using test-bench cone-beam CT data. The performances of local and global RoD approaches were similar, with local RoD providing a significant computational speedup. In comparison across a range of data with differing fidelity, the local RoD approach consistently showed lower error (with respect to a truth image) than PL in both noisy data and sparsely sampled projection scenarios. In a study of the prior image registration performance of RoD, a clinically reasonable capture ranges were demonstrated. Lastly, the registration algorithm had a broad capture range and the error for reconstruction of CT data was 35% and 20% less than filtered back-projection for RoD and PL, respectively. The RoD has potential for delivering high-quality difference images in a range of sequential clinical scenarios including image-guided surgeries and treatments where accurate and quantitative assessments of anatomical change is desired.

Task-driven image acquisition and reconstruction in cone-beam CT

This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d') is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ± 30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d' for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d' by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the tilt angle that reduced quantum noise in the region of the stimulus by avoiding highly attenuating anatomical structures. The task-driven imaging framework offers a potentially valuable paradigm for prospective definition of acquisition and reconstruction protocols that improve task performance without increase in dose.

Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation

PURPOSE

Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction.

METHODS

Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according to Fessler ["Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography," IEEE Trans. Image Process. 5(3), 493-506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map.

RESULTS

Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP is isotropic and independent of location to a first order approximation, whereas the MTF of PL is anisotropic in a manner complementary to the NPS. Task-based detectability demonstrates dependence on the task, object, spatial location, and smoothing parameters. A spatially varying regularization "map" designed from locally optimal regularization can improve overall detectability beyond that achievable with the commonly used constant regularization parameter.

CONCLUSIONS

Analytical models for task-based FBP and PL reconstruction are predictive of nonstationary noise and resolution characteristics, providing a valuable framework for understanding and optimizing system performance in CT and CBCT.

成釉细胞瘤的锥形束CT表现分析

OBJECTIVE

To summarize and analyze the cone-beam CT (CBCT) imaging features of ameloblastomas for clinical preoperative diagnosis.

METHODS

Thirty-seven cases with complete data proven by pathology were retrospectively studied for distinct CBCT features.

RESULTS

Of the 37 cases, 31 were primary and 6 were recurrent. On CBCT images, the 37 cases were composed of 36 cases (97.3%) of intraosseous lesions (17 cases of multilocular lesions, 17 cases of unilocular lesions, and 2 cases of honeycomb lesion) and 1 case (2.7%) of extraosseous lesion (soft tissue lesion). Of the 17 multilocular cases, 15 (88.2%) showed tongue-shaped crests in lesions. Thirty-four cases (94.4%) showed apparent expansible change toward lip/buccal and (or) palatal/lingual sides ofjaw, with partialcortical erosion.

CONCLUSION

CBCT imaging yields accurate three-dimensional images of lesion shape and structure. Therefore, CBCT can be usedfor the clinical diagnosis and surgical assessment of ameloblastoma.

Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction

The potential for statistical image reconstruction methods such as penalized-likelihood (PL) to improve C-arm cone-beam CT (CBCT) soft-tissue visualization for intraoperative imaging over conventional filtered backprojection (FBP) is assessed in this work by making a fair comparison in relation to soft-tissue performance. A prototype mobile C-arm was used to scan anthropomorphic head and abdomen phantoms as well as a cadaveric torso at doses substantially lower than typical values in diagnostic CT, and the effects of dose reduction via tube current reduction and sparse sampling were also compared. Matched spatial resolution between PL and FBP was determined by the edge spread function of low-contrast (∼ 40-80 HU) spheres in the phantoms, which were representative of soft-tissue imaging tasks. PL using the non-quadratic Huber penalty was found to substantially reduce noise relative to FBP, especially at lower spatial resolution where PL provides a contrast-to-noise ratio increase up to 1.4-2.2 × over FBP at 50% dose reduction across all objects. Comparison of sampling strategies indicates that soft-tissue imaging benefits from fully sampled acquisitions at dose above ∼ 1.7 mGy and benefits from 50% sparsity at dose below ∼ 1.0 mGy. Therefore, an appropriate sampling strategy along with the improved low-contrast visualization offered by statistical reconstruction demonstrates the potential for extending intraoperative C-arm CBCT to applications in soft-tissue interventions in neurosurgery as well as thoracic and abdominal surgeries by overcoming conventional tradeoffs in noise, spatial resolution, and dose.

Deformable image registration for cone-beam CT guided transoral robotic base-of-tongue surgery

Transoral robotic surgery (TORS) offers a minimally invasive approach to resection of base-of-tongue tumors. However, precise localization of the surgical target and adjacent critical structures can be challenged by the highly deformed intraoperative setup. We propose a deformable registration method using intraoperative cone-beam computed tomography (CBCT) to accurately align preoperative CT or MR images with the intraoperative scene. The registration method combines a Gaussian mixture (GM) model followed by a variation of the Demons algorithm. First, following segmentation of the volume of interest (i.e. volume of the tongue extending to the hyoid), a GM model is applied to surface point clouds for rigid initialization (GM rigid) followed by nonrigid deformation (GM nonrigid). Second, the registration is refined using the Demons algorithm applied to distance map transforms of the (GM-registered) preoperative image and intraoperative CBCT. Performance was evaluated in repeat cadaver studies (25 image pairs) in terms of target registration error (TRE), entropy correlation coefficient (ECC) and normalized pointwise mutual information (NPMI). Retraction of the tongue in the TORS operative setup induced gross deformation >30 mm. The mean TRE following the GM rigid, GM nonrigid and Demons steps was 4.6, 2.1 and 1.7 mm, respectively. The respective ECC was 0.57, 0.70 and 0.73, and NPMI was 0.46, 0.57 and 0.60. Registration accuracy was best across the superior aspect of the tongue and in proximity to the hyoid (by virtue of GM registration of surface points on these structures). The Demons step refined registration primarily in deeper portions of the tongue further from the surface and hyoid bone. Since the method does not use image intensities directly, it is suitable to multi-modality registration of preoperative CT or MR with intraoperative CBCT. Extending the 3D image registration to the fusion of image and planning data in stereo-endoscopic video is anticipated to support safer, high-precision base-of-tongue robotic surgery.

Monte Carlo study of the effects of system geometry and antiscatter grids on cone-beam CT scatter distributions

PURPOSE

The proliferation of cone-beam CT (CBCT) has created interest in performance optimization, with x-ray scatter identified among the main limitations to image quality. CBCT often contends with elevated scatter, but the wide variety of imaging geometry in different CBCT configurations suggests that not all configurations are affected to the same extent. Graphics processing unit (GPU) accelerated Monte Carlo (MC) simulations are employed over a range of imaging geometries to elucidate the factors governing scatter characteristics, efficacy of antiscatter grids, guide system design, and augment development of scatter correction.

METHODS

A MC x-ray simulator implemented on GPU was accelerated by inclusion of variance reduction techniques (interaction splitting, forced scattering, and forced detection) and extended to include x-ray spectra and analytical models of antiscatter grids and flat-panel detectors. The simulator was applied to small animal (SA), musculoskeletal (MSK) extremity, otolaryngology (Head), breast, interventional C-arm, and on-board (kilovoltage) linear accelerator (Linac) imaging, with an axis-to-detector distance (ADD) of 5, 12, 22, 32, 60, and 50 cm, respectively. Each configuration was modeled with and without an antiscatter grid and with (i) an elliptical cylinder varying 70-280 mm in major axis; and (ii) digital murine and anthropomorphic models. The effects of scatter were evaluated in terms of the angular distribution of scatter incident upon the detector, scatter-to-primary ratio (SPR), artifact magnitude, contrast, contrast-to-noise ratio (CNR), and visual assessment.

RESULTS

Variance reduction yielded improvements in MC simulation efficiency ranging from ∼17-fold (for SA CBCT) to ∼35-fold (for Head and C-arm), with the most significant acceleration due to interaction splitting (∼6 to ∼10-fold increase in efficiency). The benefit of a more extended geometry was evident by virtue of a larger air gap-e.g., for a 16 cm diameter object, the SPR reduced from 1.5 for ADD = 12 cm (MSK geometry) to 1.1 for ADD = 22 cm (Head) and to 0.5 for ADD = 60 cm (C-arm). Grid efficiency was higher for configurations with shorter air gap due to a broader angular distribution of scattered photons-e.g., scatter rejection factor ∼0.8 for MSK geometry versus ∼0.65 for C-arm. Grids reduced cupping for all configurations but had limited improvement on scatter-induced streaks and resulted in a loss of CNR for the SA, Breast, and C-arm. Relative contribution of forward-directed scatter increased with a grid (e.g., Rayleigh scatter fraction increasing from ∼0.15 without a grid to ∼0.25 with a grid for the MSK configuration), resulting in scatter distributions with greater spatial variation (the form of which depended on grid orientation).

CONCLUSIONS

A fast MC simulator combining GPU acceleration with variance reduction provided a systematic examination of a range of CBCT configurations in relation to scatter, highlighting the magnitude and spatial uniformity of individual scatter components, illustrating tradeoffs in CNR and artifacts and identifying the system geometries for which grids are more beneficial (e.g., MSK) from those in which an extended geometry is the better defense (e.g., C-arm head imaging). Compact geometries with an antiscatter grid challenge assumptions of slowly varying scatter distributions due to increased contribution of Rayleigh scatter.

Accelerated barrier optimization compressed sensing (ABOCS) reconstruction for cone-beam CT: phantom studies

PURPOSE

Recent advances in compressed sensing (CS) enable accurate CT image reconstruction from highly undersampled and noisy projection measurements, due to the sparsifiable feature of most CT images using total variation (TV). These novel reconstruction methods have demonstrated advantages in clinical applications where radiation dose reduction is critical, such as onboard cone-beam CT (CBCT) imaging in radiation therapy. The image reconstruction using CS is formulated as either a constrained problem to minimize the TV objective within a small and fixed data fidelity error, or an unconstrained problem to minimize the data fidelity error with TV regularization. However, the conventional solutions to the above two formulations are either computationally inefficient or involved with inconsistent regularization parameter tuning, which significantly limit the clinical use of CS-based iterative reconstruction. In this paper, we propose an optimization algorithm for CS reconstruction which overcomes the above two drawbacks.

METHODS

The data fidelity tolerance of CS reconstruction can be well estimated based on the measured data, as most of the projection errors are from Poisson noise after effective data correction for scatter and beam-hardening effects. We therefore adopt the TV optimization framework with a data fidelity constraint. To accelerate the convergence, we first convert such a constrained optimization using a logarithmic barrier method into a form similar to that of the conventional TV regularization based reconstruction but with an automatically adjusted penalty weight. The problem is then solved efficiently by gradient projection with an adaptive Barzilai-Borwein step-size selection scheme. The proposed algorithm is referred to as accelerated barrier optimization for CS (ABOCS), and evaluated using both digital and physical phantom studies.

RESULTS

ABOCS directly estimates the data fidelity tolerance from the raw projection data. Therefore, as demonstrated in both digital Shepp-Logan and physical head phantom studies, consistent reconstruction performances are achieved using the same algorithm parameters on scans with different noise levels and∕or on different objects. On the contrary, the penalty weight in a TV regularization based method needs to be fine-tuned in a large range (up to seven times) to maintain the reconstructed image quality. The improvement of ABOCS on computational efficiency is demonstrated in the comparisons with adaptive-steepest-descent-projection-onto-convex-sets (ASD-POCS), an existing CS reconstruction algorithm also using constrained optimization. ASD-POCS alternatively minimizes the TV objective using adaptive steepest descent (ASD) and the data fidelity error using projection onto convex sets (POCS). For similar image qualities of the Shepp-Logan phantom, ABOCS requires less computation time than ASD-POCS in MATLAB by more than one order of magnitude.

CONCLUSIONS

We propose ABOCS for CBCT reconstruction. As compared to other published CS-based algorithms, our method has attractive features of fast convergence and consistent parameter settings for different datasets. These advantages have been demonstrated on phantom studies.

Cone-Beam CT with a Flat-Panel Detector: From Image Science to Image-Guided Surgery

The development of large-area flat-panel x-ray detectors (FPDs) has spurred investigation in a spectrum of advanced medical imaging applications, including tomosynthesis and cone-beam CT (CBCT). Recent research has extended image quality metrics and theoretical models to such applications, providing a quantitative foundation for the assessment of imaging performance as well as a general framework for the design, optimization, and translation of such technologies to new applications. For example, cascaded systems models of Fourier domain metrics, such as noise-equivalent quanta (NEQ), have been extended to these modalities to describe the propagation of signal and noise through the image acquisition and reconstruction chain and to quantify the factors that govern spatial resolution, image noise, and detectability. Moreover, such models have demonstrated basic agreement with human observer performance for a broad range of imaging conditions and imaging tasks. These developments in image science have formed a foundation for the knowledgeable development and translation of CBCT to new applications in image-guided interventions - for example, CBCT implemented on a mobile surgical C-arm for intraoperative 3D imaging. The ability to acquire high-quality 3D images on demand during surgical intervention overcomes conventional limitations of surgical guidance in the context of preoperative images alone. A prototype mobile C-arm developed in academic-industry partnership demonstrates CBCT with low radiation dose, sub-mm spatial resolution, and soft-tissue visibility potentially approaching that of diagnostic CT. Integration of the 3D imaging system with real-time tracking, deformable registration, endoscopic video, and 3D visualization offers a promising addition to the surgical arsenal in interventions ranging from head-and-neck / skull base surgery to spine, orthopaedic, thoracic, and abdominal surgeries. Cadaver studies show the potential for significant boosts in surgical performance under CBCT guidance, and early clinical trials demonstrate feasibility, workflow, and image quality within the surgical theatre.

Anatomical background and generalized detectability in tomosynthesis and cone-beam CT

PURPOSE

Anatomical background presents a major impediment to detectability in 2D radiography as well as 3D tomosynthesis and cone-beam CT (CBCT). This article incorporates theoretical and experimental analysis of anatomical background "noise" in cascaded systems analysis of 2D and 3D imaging performance to yield "generalized" metrics of noise-equivalent quanta (NEQ) and detectability index as a function of the orbital extent of the (circular arc) source-detector orbit.

METHODS

A physical phantom was designed based on principles of fractal self-similarity to exhibit power-law spectral density (kappa/Fbeta) comparable to various anatomical sites (e.g., breast and lung). Background power spectra [S(B)(F)] were computed as a function of source-detector orbital extent, including tomosynthesis (approximately 10 degrees -180 degrees) and CBCT (180 degrees + fan to 360 degrees) under two acquisition schemes: (1) Constant angular separation between projections (variable dose) and (2) constant total number of projections (constant dose). The resulting S(B) was incorporated in the generalized NEQ, and detectability index was computed from 3D cascaded systems analysis for a variety of imaging tasks.

RESULTS

The phantom yielded power-law spectra within the expected spatial frequency range, quantifying the dependence of clutter magnitude (kappa) and correlation (beta) with increasing tomosynthesis angle. Incorporation of S(B) in the 3D NEQ provided a useful framework for analyzing the tradeoffs among anatomical, quantum, and electronic noise with dose and orbital extent. Distinct implications are posed for breast and chest tomosynthesis imaging system design-applications varying significantly in kappa and beta, and imaging task and, therefore, in optimal selection of orbital extent, number of projections, and dose. For example, low-frequency tasks (e.g., soft-tissue masses or nodules) tend to benefit from larger orbital extent and more fully 3D tomographic imaging, whereas high-frequency tasks (e.g., microcalcifications) require careful, application-specific selection of orbital extent and number of projections to minimize negative effects of quantum and electronic noise.

CONCLUSIONS

The complex tradeoffs among anatomical background, quantum noise, and electronic noise in projection imaging, tomosynthesis, and CBCT can be described by generalized cascaded systems analysis, providing a useful framework for system design and optimization.

Characterization of scatter in cone-beam CT breast imaging: comparison of experimental measurements and Monte Carlo simulation

It is commonly understood that scattered radiation in x-ray computed tomography (CT) degrades the reconstructed image. As a precursor to developing scatter compensation methods, it is important to characterize this scatter using both empirical measurements and Monte Carlo simulations. Previous studies characterizing scatter using both experimental measurements and Monte Carlo simulations have been reported in diagnostic radiology and conventional mammography. The emerging technology of cone-beam CT breast imaging (CTBI) differs significantly from conventional mammography in the breast shape and imaging geometry, aspects that are important factors impacting the measured scatter. This study used a bench-top cone-beam CTBI system with an indirect flat-panel detector. A cylindrical phantom with equivalent composition of 50% fibroglandular and 50% adipose tissues was used, and scatter distributions were measured by beam stop and aperture methods. The GEANT4-based simulation package GATE was used to model x-ray photon interactions in the phantom and detector. Scatter to primary ratio (SPR) measurements using both the beam stop and aperture methods were consistent within 5% after subtraction of nonbreast scatter contributions and agree with the low energy electromagnetic model simulation in GATE. The validated simulation model was used to characterize the SPR in different CTBI conditions. In addition, a realistic, digital breast phantom was simulated to determine the characteristics of various scatter components that cannot be separated in measurements. The simulation showed that the scatter distribution from multiple Compton and Rayleigh scatterings, as well as from the single Compton scattering, has predominantly low-frequency characteristics. The single Rayleigh scatter was observed to be the primary contribution to the spatially variant scatter component.

An in vitro evaluation of cone-beam breast CT methods

Tomosynthesis was developed for mammography, especially breast cancer detection. However, its limited-angular range scan and resultant data incompleteness causes strong image artifacts and distortions. To address this problem, a hybrid imaging method was proposed in our previous work, which combines tomosynthesis and low-resolution CT into a single system to produce fewer artifacts and distortions at a similar dose level. The purpose of this paper is to evaluate the images reconstructed using the proposed method as compared with that using the conventional tomosynthesis method (ML-convex). For that purpose, the projection datasets are acquired in both numerical simulation and phantom experiments on our breast imaging platform. Three kinds of phantoms are used in our work, including a numerical phantom, a physical phantom and 8 in vitro phantoms made of breast specimens. In addition to visual comparison of the reconstructed images, we employ spatial resolution, image contrast, reconstruction error, and convergence rate to evaluate the results quantitatively. It is observed that the results from our method can achieve significantly higher spatial resolution, higher contrast, smaller reconstruction error and faster convergence rate. Besides, a reader study using 8 in vitro phantoms of breast specimens demonstrates the clinical potential of our method, which significantly outperforms the conventional tomosynthesis.

On-line target position localization in the presence of respiration: a comparison of two methods

PURPOSE

To compare two "four-dimensional" methods for image-guided target localization in the presence of respiration.

METHODS AND MATERIALS

Four-dimensional image guidance was performed with two methods. A respiration-correlated computed tomography (RCCT) was acquired on a CT simulator, and an average CT (AVG-CT) image was generated from the RCCT. A respiration-correlated cone-beam CT (RC-CBCT) and a free-breathing cone-beam CT (FB-CBCT) were acquired. The "RCCT method" consisted of calculating the mean target position on both the RCCT and RC-CBCT, registering the RCCT to the RC-CBCT, and determining the shift in the mean target position from the planned mean position. The "AVG-CT method" consisted of registering the AVG-CT to the FB-CBCT. The ability of each to measure the shift in the mean target position was compared, both in a respiratory phantom and in 8 patients.

RESULTS

In phantom, the RCCT and AVG-CT methods were able to measure the true mean target position to within 0.15 cm and 0.10 cm, respectively. In the patient study, the mean error between the methods was 0.13 cm (left-right), 0.14 cm (anterior-posterior), and 0.10 cm (cranio-caudal). The error was not observed to vary with tumor position or magnitude of tumor motion.

CONCLUSIONS

Respiration may impact the on-line image guidance process. The RCCT method enables localization of the mean tumor position and measurement of changes in the motion pattern, whereas the AVG-CT method is simple, fast, and easily implemented. We found the methods to be nearly equivalent in detecting shifts in the mean tumor position.

Comparison of localization performance with implanted fiducial markers and cone-beam computed tomography for on-line image-guided radiotherapy of the prostate

PURPOSE

The aim of this work was to assess the accuracy of kilovoltage (kV) cone-beam computed tomography (CBCT)-based setup corrections as compared with orthogonal megavoltage (MV) portal image-based corrections for patients undergoing external-beam radiotherapy of the prostate.

METHODS AND MATERIALS

Daily cone-beam CT volumetric images were acquired after setup for patients with three intraprostatic fiducial markers. The estimated couch shifts were compared retrospectively to patient adjustments based on two orthogonal MV portal images (the current clinical standard of care in our institution). The CBCT soft-tissue based shifts were also estimated by digitally removing the gold markers in each projection to suppress the artifacts in the reconstructed volumes. A total of 256 volumetric images for 15 patients were analyzed.

RESULTS

The Pearson coefficient of correlation for the patient position shifts using fiducial markers in MV vs. kV was (R2 = 0.95, 0.84, 0.81) in the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions, respectively. The correlation using soft-tissue matching was as follows: R2 = 0.90, 0.49, 0.51 in the LR, AP and SI directions. A Bland-Altman analysis showed no significant trends in the data. The percentage of shifts within a +/-3-mm tolerance (the clinical action level) was 99.7%, 95.5%, 91.3% for fiducial marker matching and 99.5%, 70.3%, 78.4% for soft-tissue matching.

CONCLUSIONS

Cone-beam CT is an accurate and precise tool for image guidance. It provides an equivalent means of patient setup correction for prostate patients with implanted gold fiducial markers. Use of the additional information provided by the visualization of soft-tissue structures is an active area of research.