Visualization of bone details in a novel photon-counting dual-source CT scanner—comparison with energy-integrating CT

Objectives Photon-counting detector CT (PCD-CT) promises a leap in spatial resolution due to smaller detector pixel sizes than implemented in energy-integrating detector CTs (EID-CT). Our objective was to compare the visualization of smallest bone details between PCD-CT and EID-CT using a mouse as a specimen. Materials and methods Two euthanized mice were scanned at a 20-slice EID-CT and a dual-source PCD-CT in single-pixel mode at various CTDIVol values. Image noise and signal-to-noise ratio (SNR) were evaluated using repeated ROI measurements. Edge sharpness of bones was compared by the maximal slope within CT value plots along sampling lines intersecting predefined bones of the spine. Two readers evaluated bone detail visualization at four regions of the spine on a three-point Likert scale at various CTDIVol’s. Two radiologists selected the series with better detail visualization among each of 20 SNR-matched pairs of EID-CT and PCD-CT series. Results In CTDIVol-matched scans, PCD-CT series showed significantly lower image noise (NoiseCTDI=5 mGy: 16.27 ± 1.39 vs. 23.46 ± 0.96 HU, p < 0.01), higher SNR (SNRCTDI=5 mGy: 20.57 ± 1.89 vs. 14.00 ± 0.66, p < 0.01), and higher edge sharpness (Edge Slopelumbar spine: 981 ± 160 vs. 608 ± 146 HU/mm, p < 0.01) than EID-CT series. Two radiologists considered the delineation of bone details as feasible at consistently lower CTDIVol values at PCD-CT than at EID-CT. In comparison of SNR-matched reconstructions, PCD-CT series were still considered superior in almost all cases. Conclusions In this head-to-head comparison, PCD-CT showed superior objective and subjective image quality characteristics over EID-CT for the delineation of tiniest bone details. Even in SNR-matched pairs (acquired at different CTDIVol’s), PCD-CT was strongly preferred by radiologists. Key Points • In dose-matched scans, photon-counting detector CT series showed significantly less image noise, higher signal-to-noise ratio, and higher edge sharpness than energy-integrating detector CT series. • Human observers considered the delineation of tiny bone details as feasible at much lower dose levels in photon-counting detector CT than in energy-integrating detector CT. • In direct comparison of series matched for signal-to-noise ratio, photon-counting detector CT series were considered superior in almost all cases.

Free-breathing contrast-enhanced multiphase MRI of the liver in patients with a high risk of breath-holding failure: comparison of compressed sensing-accelerated radial and Cartesian acquisition techniques

Background Knowing the advantages and disadvantages of each magnetic resonance (MR) technique, would allow us to choose a sequence better suited in patients with a high risk of breath-holding failure. Purpose To compare the image quality of free-breathing contrast-enhanced multiphase MR imaging (MRI) using incoherent Cartesian k-space sampling combined with a motion-resolved compressed sensing reconstruction (XD-VIBE) and Golden-Angle Radial Sparse Parallel MRI (GRASP). Material and Methods A total of 67 patients were included. Overall image quality, motion artifacts, and liver edge sharpness on arterial and portal-venous phase were evaluated by two radiologists. We evaluated the signal intensity ratio between liver in the late arterial phase to aorta at peak enhancement and the detection rate of hypervascular lesions. Results Overall image quality, artifact, and liver edge sharpness scores of XD-VIBE and GRASP were not significantly different ( P = 0.070–0.397). Four (reviewer 1, 12.1%) and seven patients (reviewer 2, 21.2%) received non-diagnostic quality in the XD-VIBE group whereas one patient (reviewer 2, 2.9%) received non-diagnostic quality in the GRASP group. The ratio between the aorta and liver signal for GRASP was significantly higher than that of XD-VIBE (0.32 ± 0.10 vs. 0.47 ± 0.13; P < 0.001). The hypervascular lesion detection rate of XD-VIBE (86.7%) was higher than that of GRASP (57.1%) in the arterial phase without a statistically significant difference ( P = 0.081). Conclusion Overall image quality of XD-VIBE and GRASP were not significantly different. More XD-VIBE examinations were rated non-diagnostic. On the other hand, the relative liver parenchymal enhancement to the aorta in the late arterial phase of GRASP was higher than that of XD-VIBE, which potentially leads to lower detectability of hypervascular lesions on arterial phase images.

An Improved Adaptive Spatial Preprocessing Method for Remote Sensing Images

Since remote sensing images are one of the main sources for people to obtain required information, the quality of the image becomes particularly important. Nevertheless, noise often inevitably exists in the image, and the targets are usually blurred by the acquisition of the imaging system, resulting in the degradation of quality of the images. In this paper, a novel preprocessing algorithm is proposed to simultaneously smooth noise and to enhance the edges, which can improve the visual quality of remote sensing images. It consists of an improved adaptive spatial filter, which is a weighted filter integrating functions of both noise removal and edge sharpness. Its processing parameters are flexible and adjustable relative to different images. The experimental results confirm that the proposed method outperforms the existing spatial algorithms both visually and quantitatively. It can play an important role in the remote sensing field in order to achieve more information of interested targets.

Feasibility and Implementation of a Deep Learning MR Reconstruction for TSE Sequences in Musculoskeletal Imaging

Magnetic Resonance Imaging (MRI) of the musculoskeletal system is one of the most common examinations in clinical routine. The application of Deep Learning (DL) reconstruction for MRI is increasingly gaining attention due to its potential to improve the image quality and reduce the acquisition time simultaneously. However, the technology has not yet been implemented in clinical routine for turbo spin echo (TSE) sequences in musculoskeletal imaging. The aim of this study was therefore to assess the technical feasibility and evaluate the image quality. Sixty examinations of knee, hip, ankle, shoulder, hand, and lumbar spine in healthy volunteers at 3 T were included in this prospective, internal-review-board-approved study. Conventional (TSES) and DL-based TSE sequences (TSEDL) were compared regarding image quality, anatomical structures, and diagnostic confidence. Overall image quality was rated to be excellent, with a significant improvement in edge sharpness and reduced noise compared to TSES (p < 0.001). No difference was found concerning the extent of artifacts, the delineation of anatomical structures, and the diagnostic confidence comparing TSES and TSEDL (p > 0.05). Therefore, DL image reconstruction for TSE sequences in MSK imaging is feasible, enabling a remarkable time saving (up to 75%), whilst maintaining excellent image quality and diagnostic confidence.

Compressed Sensing Real-Time Cine Reduces CMR Arrhythmia-Related Artifacts

Background and objective: Cardiac magnetic resonance (CMR) is a key tool for cardiac work-up. However, arrhythmia can be responsible for arrhythmia-related artifacts (ARA) and increased scan time using segmented sequences. The aim of this study is to evaluate the effect of cardiac arrhythmia on image quality in a comparison of a compressed sensing real-time (CSrt) cine sequence with the reference prospectively gated segmented balanced steady-state free precession (Cineref) technique regarding ARA. Methods: A total of 71 consecutive adult patients (41 males; mean age = 59.5 ± 20.1 years (95% CI: 54.7–64.2 years)) referred for CMR examination with concomitant irregular heart rate (defined by an RR interval coefficient of variation >10%) during scanning were prospectively enrolled. For each patient, two cine sequences were systematically acquired: first, the reference prospectively triggered multi-breath-hold Cineref sequence including a short-axis stack, one four-chamber slice, and a couple of two-chamber slices; second, an additional single breath-hold CSrt sequence providing the same slices as the reference technique. Two radiologists independently assessed ARA and image quality (overall, acquisition, and edge sharpness) for both techniques. Results: The mean heart rate was 71.8 ± 19.0 (SD) beat per minute (bpm) (95% CI: 67.4–76.3 bpm) and its coefficient of variation was 25.0 ± 9.4 (SD) % (95% CI: 22.8–27.2%). Acquisition was significantly faster with CSrt than with Cineref (Cineref: 556.7 ± 145.4 (SD) s (95% CI: 496.7–616.7 s); CSrt: 23.9 ± 7.9 (SD) s (95% CI: 20.6–27.1 s); p < 0.0001). A total of 599 pairs of cine slices were evaluated (median: 8 (range: 6–14) slices per patient). The mean proportion of ARA-impaired slices per patient was 85.9 ± 22.7 (SD) % using Cineref, but this was figure was zero using CSrt (p < 0.0001). The European CMR registry artifact score was lower with CSrt (median: 1 (range: 0–5)) than with Cineref (median: 3 (range: 0–3); p < 0.0001). Subjective image quality was higher in CSrt than in Cineref (median: 3 (range: 1–3) versus 2 (range: 1–4), respectively; p < 0.0001). In line, edge sharpness was higher on CSrt cine than on Cineref images (0.054 ± 0.016 pixel−1 (95% CI: 0.050–0.057 pixel−1) versus 0.042 ± 0.022 pixel−1 (95% CI: 0.037–0.047 pixel−1), respectively; p = 0.0001). Conclusion: Compressed sensing real-time cine drastically reduces arrhythmia-related artifacts and thus improves cine image quality in patients with arrhythmia.

A Novel Nodule Edge Sharpness Radiomic Biomarker Improves Performance of Lung-RADS for Distinguishing Adenocarcinomas from Granulomas on Non-Contrast CT Scans

The aim of this study is to evaluate whether NIS radiomics can distinguish lung adenocarcinomas from granulomas on non-contrast CT scans, and also to improve the performance of Lung-RADS by reclassifying benign nodules that were initially assessed as suspicious. The screening or standard diagnostic non-contrast CT scans of 362 patients was divided into training (St, N = 145), validation (Sv, N = 145), and independent validation (Siv, N = 62) sets from different institutions. Nodules were identified and manually segmented on CT images by a radiologist. A series of 264 features relating to the edge sharpness transition from the inside to the outside of the nodule were extracted. The top 10 features were used to train a linear discriminant analysis (LDA) machine learning classifier on St. In conjunction with the LDA classifier, NIS radiomics classified nodules with an AUC of 0.82 ± 0.04, 0.77, and 0.71 respectively on St, Sv, and Siv. We evaluated the ability of the NIS classifier to determine the proportion of the patients in Sv that were identified initially as suspicious by Lung-RADS but were reclassified as benign by applying the NIS scores. The NIS classifier was able to correctly reclassify 46% of those lesions that were actually benign but deemed suspicious by Lung-RADS alone on Sv.

60-S Retrogated Compressed Sensing 2D Cine of the Heart: Sharper Borders and Accurate Quantification

Background and objective: Real-time compressed sensing cine (CSrt) provides reliable quantification for both ventricles but may alter image quality. The aim of this study was to assess image quality and the accuracy of left (LV) and right ventricular (RV) volumes, ejection fraction and mass quantifications based on a retrogated segmented compressed sensing 2D cine sequence (CSrg). Methods: Thirty patients were enrolled. Each patient underwent the reference retrogated segmented steady-state free precession cine sequence (SSFPref), the real-time CSrt cine and the segmented retrogated prototype CSrg sequence providing the same slices. Functional parameters quantification and image quality rating were performed on SSFPref and CSrg images sets. The edge sharpness, which is an estimate of the edge spread function, was assessed for the three sequences. Results: The mean scan time was: SSFPref = 485.4 ± 83.3 (SD) s (95% CI: 454.3–516.5) and CSrg = 58.3 ± 15.1 (SD) s (95% CI: 53.7–64.2) (p < 0.0001). CSrg subjective image quality score (median: 4; range: 2–4) was higher than the one provided by CSrt (median: 3; range: 2–4; p = 0.0008) and not different from SSFPref overall quality score (median: 4; range: 2–4; p = 0.31). CSrg provided similar LV and RV functional parameters to those assessed with SSFPref (p > 0.05). Edge sharpness was significantly better with CSrg (0.083 ± 0.013 (SD) pixel−1; 95% CI: 0.078–0.087) than with CSrt (0.070 ± 0.011 (SD) pixel−1; 95% CI: 0.066–0.074; p = 0.0004) and not different from the reference technique (0.075 ± 0.016 (SD) pixel−1; 95% CI: 0.069–0.081; p = 0.0516). Conclusions: CSrg cine provides in one minute an accurate quantification of LV and RV functional parameters without compromising subjective and objective image quality.

Retrogated compressed sensing cine in one minute

Funding Acknowledgements Type of funding sources: None. PURPOSE Real-time compressed sensing cine (CSrt) provides reliable quantifications for both ventricles but impairs image quality . This aim of this study was to assess the accuracy of left (LV) and right ventricular (RV) volumes, ejection fraction and mass quantifications based on a retrogated segmented compressed sensing-fashioned accelerated 2D cine sequence (CSrg). Image quality was also evaluated. METHOD AND MATERIALS Thirty patients were enrolled. Each patient underwent the reference retrogated segmented steady-state free precession cine sequence (SSFPref), the first generation real-time CSrt cine and the segmented retrogated prototype CSrg sequence providing the same numbers and positions of slices. Functional parameters quantification was performed on SSFPref and CSrg images sets. Image quality was assessed for the three sequences by using edge sharpness which is an estimate of the edge spread function. RESULTS Mean scan times were SSFPref = 512 ± 15 s, CSrt = 24 ± 5 s and CSrg = 58 ± 15 s. CSrg provided LV and RV functional parameters (end-systolic, end-diastolic, ejection fraction and LV mass) which were not significantly different from the one assessed with SSFPref (p &gt; 0.05). Edge sharpness was significantly better with CSrg (0.083 ± 0.013 pixel-1) than with CSrt (0.070 ± 0.011 pixel-1; p = 0.0004) and not different from the reference techniques (0.075 ± 0.016 pixel-1; p = 0.0516). Inter and intrarater variabilities demonstrated intraclass correlation coefficients over 0.96. CONCLUSION CSrg cine provides in one minute an accurate quantification of LV and RV functional parameters without compromising the sharpness of myocardial boarders which was impaired by the first-generation real-time compressed sensing sequence. Abstract Figure. Image quality and volumes assessment