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Metal artifacts notoriously pose significant challenge in computed tomography (CT), leading to inaccuracies in image formation and interpretation. Artifact reduction tools have been designed to improve cone beam computed tomography (CBCT) image quality by reducing artifacts caused by certain high-density materials. Metal artifact reduction (MAR) tools are specific algorithms that are applied during image reconstruction to minimize or eliminate artifacts degrading CBCT images. The purpose of the study is to evaluate the effect of a MAR algorithm on image quality in CBCT performed for evaluating patients before transarterial radioembolization (TARE). We retrospectively included 40 consecutive patients (aged 65 ± 13 years; 23 males) who underwent 45 CBCT examinations (Allura FD 20, XperCT Roll protocol, Philips Healthcare, Best, The Netherlands) in the setting of evaluation for TARE between January 2017 and December 2018. Artifacts caused by coils, catheters, and surgical clips were scored subjectively by four readers on a 5-point scale (1 = artifacts affecting diagnostic information to 5 = no artifacts) using a side-by-side display of uncorrected and MAR-corrected images. In addition, readers scored tumor visibility and vessel discrimination. MAR-corrected images were assigned higher scores, indicating better image quality. The differences between the measurements with and without MAR were most impressive for coils with a mean improvement of 1.6 points (95%CI [1.5 1.8]) on the 5-point likert scale, followed by catheters 1.4 points (95%CI [1.3 1.5]) and clips 0.7 points (95%CI [0.3 1.1]). Improvements for other artifact sources were consistent but relatively small (below 0.25 points on average). Interrater agreement was good to perfect (Kendall's W coefficient = 0.68–0.95) and was higher for MAR-corrected images, indicating that MAR improves diagnostic accuracy. A metal artifact reduction algorithm can improve diagnostic and interventional accuracy of cone beam CT in patients undergoing radioembolization by reducing artifacts caused by diagnostic catheters and coils, lowering interference of metal artifacts with adjacent major structures, and improving tumor visibility. [ABSTRACT FROM AUTHOR]

The feasibility of full-scan, offset-detector geometry cone-beam CT has been demonstrated for several clinical applications. For full-scan acquisition with offset-detector geometry, data redundancy from complementary views can be exploited during image reconstruction. Envisioning an upright breast CT system, we propose to acquire short-scan data in conjunction with offset-detector geometry. To tackle the resulting incomplete data, we have developed a self-supervised attenuation field network (AFN). AFN leverages the inherent redundancy of cone-beam CT data through coordinate-based representation and known imaging physics. A trained AFN can query attenuation coefficients using their respective coordinates or synthesize projection data including the missing projections. The AFN was evaluated using clinical cone-beam breast CT datasets (n = 50). While conventional analytical and iterative reconstruction methods failed to reconstruct the incomplete data, AFN reconstruction was not statistically different from the reference reconstruction obtained using full-scan, full-detector data in terms of image noise, image contrast, and the full width at half maximum of calcifications. This study indicates the feasibility of a simultaneous short-scan and offset-detector geometry for dedicated breast CT imaging. The proposed AFN technique can potentially be expanded to other cone-beam CT applications. [ABSTRACT FROM AUTHOR]

The process of creating virtual models of dentomaxillofacial structures through three-dimensional segmentation is a crucial component of most digital dental workflows. This process is typically performed using manual or semi-automated approaches, which can be time-consuming and subject to observer bias. The aim of this study was to train and assess the performance of a convolutional neural network (CNN)-based online cloud platform for automated segmentation of maxillary impacted canine on CBCT image. A total of 100 CBCT images with maxillary canine impactions were randomly allocated into two groups: a training set (n = 50) and a testing set (n = 50). The training set was used to train the CNN model and the testing set was employed to evaluate the model performance. Both tasks were performed on an online cloud-based platform, 'Virtual patient creator' (Relu, Leuven, Belgium). The performance was assessed using voxel- and surface-based comparison between automated and semi-automated ground truth segmentations. In addition, the time required for segmentation was also calculated. The automated tool showed high performance for segmenting impacted canines with a dice similarity coefficient of 0.99 ± 0.02. Moreover, it was 24 times faster than semi-automated approach. The proposed CNN model achieved fast, consistent, and precise segmentation of maxillary impacted canines. [ABSTRACT FROM AUTHOR]

Computed tomography (CT) has been developed as a nondestructive technique for observing minute internal images in samples. It has been difficult to obtain photorealistic (clean or clear) CT images due to various unwanted artifacts generated during the CT scanning process, along with the limitations of back-projection algorithms. Recently, an iterative optimization algorithm has been developed that uses an entire sinogram to reduce errors caused by artifacts. In this paper, we introduce a new quantum algorithm for reconstructing CT images. This algorithm can be used with any type of light source as long as the projection is defined. Assuming an experimental sinogram produced by a Radon transform, to find the CT image of this sinogram, we express the CT image as a combination of qubits. After acquiring the Radon transform of the undetermined CT image, we combine the actual sinogram and the optimized qubits. The global energy optimization value used here can determine the value of qubits through a gate model quantum computer or quantum annealer. In particular, the new algorithm can also be used for cone-beam CT image reconstruction and for medical imaging. [ABSTRACT FROM AUTHOR]

Cone-beam computed tomography (CBCT) has been shown to be a powerful tool for 3D imaging of the appendicular skeleton, allowing for detailed visualization of bone microarchitecture. This study was designed to compare artifacts in the presence of osteosynthetic implants between CBCT and multidetector computed tomography (MDCT) in cadaveric wrist scans. A total of 32 scan protocols with varying tube potential and current were employed: both conventional CBCT and MDCT studies were included with tube voltage ranging from 60 to 140 kVp as well as additional MDCT protocols with dedicated spectral shaping via tin prefiltration. Irrespective of scanner type, all examinations were conducted in ultra-high-resolution (UHR) scan mode. For reconstruction of UHR-CBCT scans an additional iterative metal artifact reduction algorithm was employed, an image correction tool which cannot be used in combination with UHR-MDCT. To compare applied radiation doses between both scanners, the volume computed tomography dose index for a 16 cm phantom (CTDIvol) was evaluated. Images were assessed regarding subjective and objective image quality. Without automatic tube current modulation or tube potential control, radiation doses ranged between 1.3 mGy (with 70 kVp and 50.0 effective mAs) and 75.2 mGy (with 140 kVp and 383.0 effective mAs) in UHR-MDCT. Using the pulsed image acquisition method of the CBCT scanner, CTDIvol ranged between 2.3 mGy (with 60 kVp and 0.6 mean mAs per pulse) and 61.0 mGy (with 133 kVp and 2.5 mean mAs per pulse). In essence, all UHR-CBCT protocols employing a tube potential of 80 kVp or more were found to provide superior overall image quality and artifact reduction compared to UHR-MDCT (all p <.050). Interrater reliability of seven radiologists regarding image quality was substantial for tissue assessment and moderate for artifact assessment with Fleiss kappa of 0.652 (95% confidence interval 0.618–0.686; p < 0.001) and 0.570 (95% confidence interval 0.535–0.606; p < 0.001), respectively. Our results demonstrate that the UHR-CBCT scan mode of a twin robotic X-ray system facilitates excellent visualization of the appendicular skeleton in the presence of metal implants. Achievable image quality and artifact reduction are superior to dose-comparable UHR-MDCT and even MDCT protocols employing spectral shaping with tin prefiltration do not achieve the same level of artifact reduction in adjacent soft tissue. [ABSTRACT FROM AUTHOR]

Modern cone-beam CT systems are capable of ultra-high-resolution 3D imaging in addition to conventional radiography and fluoroscopy. The combination of various imaging functions in a multi-use setup is particularly appealing for musculoskeletal interventions, such as CBCT arthrography (CBCTA). With this study, we aimed to investigate the feasibility of CBCTA of the wrist in a "one-stop-shop" approach with a gantry-free twin robotic scanner that does not require repositioning of subjects. Additionally, the image quality of CBCTA was compared to subsequent arthrograms on a high-end multidetector CT (MDCTA). Fourteen cadaveric wrists received CBCTA with four acquisition protocols. Specimens were then transferred to the CT suite for additional MDCTA. Dose indices ranged between 14.3 mGy (120 kVp/100 effective mAs; full-dose) and 1.0 mGy (70 kVp/41 effective mAs; ultra-low-dose) for MDCTA and between 17.4 mGy (80 kVp/2.5 mAs per pulse; full-dose) and 1.2 mGy (60 kVp/0.5 mAs per pulse; ultra-low-dose) for CBCTA. Subjective image quality assessment for bone, cartilage and ligamentous tissue was performed by seven radiologists. The interrater reliability was assessed by calculation of the intraclass correlation coefficient (ICC) based on a two-way random effects model. Overall image quality of most CBCTA was deemed suitable for diagnostic use in contrast to a considerable amount of non-diagnostic MDCTA examinations (38.8%). The depiction of bone, cartilage and ligaments in MDCTA with any form of dose reduction was inferior to any CBCTA scan with at least 0.6 mAs per pulse (all p < 0.001). Full-dose MDCTA and low-dose CBCTA were of equal quality for bone tissue visualization (p = 0.326), whereas CBCTA allowed for better depiction of ligaments and cartilage (both p < 0.001), despite merely one third of radiation exposure (MDCTA–14.3 mGy vs. CBCTA–4.5 mGy). Moderate to good interrater reliability was ascertained for the assessment all tissues (ICC 0.689–0.756). Overall median examination time for CBCTA was 5.4 min (4.8–7.2 min). This work demonstrates that substantial dose reduction can be achieved in CT arthrography of the wrist while maintaining diagnostic image quality by employing the cone-beam CT mode of a twin robotic X-ray system. The ability of the multi-use X-ray system to switch between fluoroscopy mode and 3D imaging allows for "one-stop-shop" CBCTA in minimal examination time without the need for repositioning. [ABSTRACT FROM AUTHOR]

Cone-beam computed tomography is a powerful tool for 3D imaging of the appendicular skeleton, facilitating detailed visualization of bone microarchitecture. This study evaluated various combinations of acquisition and reconstruction parameters for the cone-beam CT mode of a twin robotic x-ray system in cadaveric wrist and elbow scans, aiming to define the best possible trade-off between image quality and radiation dose. Images were acquired with different combinations of tube voltage and tube current–time product, resulting in five scan protocols with varying volume CT dose indices: full-dose (FD; 17.4 mGy), low-dose (LD; 4.5 mGy), ultra-low-dose (ULD; 1.15 mGy), modulated low-dose (mLD; 0.6 mGy) and modulated ultra-low-dose (mULD; 0.29 mGy). Each set of projection data was reconstructed with three convolution kernels (very sharp [Ur77], sharp [Br69], intermediate [Br62]). Five radiologists subjectively assessed the image quality of cortical bone, cancellous bone and soft tissue using seven-point scales. Irrespective of the reconstruction kernel, overall image quality of every FD, LD and ULD scan was deemed suitable for diagnostic use in contrast to mLD (very sharp/sharp/intermediate: 60/55/70%) and mULD (0/3/5%). Superior depiction of cortical and cancellous bone was achieved in FDUr77 and LDUr77 examinations (p < 0.001) with LDUr77 scans also providing favorable bone visualization compared to FDBr69 and FDBr62 (p < 0.001). Fleiss' kappa was 0.618 (0.594–0.641; p < 0.001), indicating substantial interrater reliability. In this study, we demonstrate that considerable dose reduction can be realized while maintaining diagnostic image quality in upper extremity joint scans with the cone-beam CT mode of a twin robotic x-ray system. Application of sharper convolution kernels for image reconstruction facilitates superior display of bone microarchitecture. [ABSTRACT FROM AUTHOR]