Purpose To examine the diagnostic performance of high-spatial-resolution (HSR) CT with 0.25-mm section thickness for evaluating renal artery in-stent restenosis. Materials and Methods A 0.05-mm wire phantom and vessel phantoms with renal stents with in-stent stenotic sections of varying diameters were scanned with both an HSR CT scanner equipped with 160-section multi-detector rows (0.25-mm section thickness) and a conventional CT scanner. The wire phantom was used to analyze modulation transfer function (MTF). With the vessel phantoms, the error rates were calculated as the absolute difference between the measured diameters and true diameters divided by the true diameters at the narrowing sections. For qualitative evaluation, overall image quality and diagnostic accuracy for evaluating stenosis in three stages were assessed by two radiologists. Statistical analyses included the paired t test, Wilcoxon signed-rank test, and McNemar test. Results HSR CT achieved 24.3 line pairs per centimeter ± 0.5 (standard deviation) and 29.1 line pairs per centimeter ± 0.4 at 10% and 2% MTF, respectively; and conventional CT was 12.5 line pairs per centimeter ± 0.1 and 14.3 line pairs per centimeter ± 0.1 at 10% and 2% MTF, respectively. The mean error rate of the measured diameter at HSR CT (8.0% ± 5.8) was significantly lower than that at at conventional CT (16.9% ± 9.3; P < .001). Image quality at HSR CT was significantly better than that at conventional CT (P < .001), but HSR CT was not significantly superior to conventional CT in terms of diagnostic accuracy. Conclusion Compared with conventional CT, high-spatial-resolution CT achieved spatial resolutions of up to 29 line pairs per centimeter at 2% modulation transfer function and yielded improved measurement accuracy for the evaluation of in-stent restenosis in a phantom study of renal artery stents. Published under a CC BY 4.0 license.
Photon-counting CT has a completely different detector mechanism than conventional energy-integrating CT. In the photon-counting detector, X-rays are directly converted into electrons and received as electrical signals. Photon-counting CT provides virtual monochromatic images with a high contrast-to-noise ratio for abdominal CT imaging and may improve the ability to visualize small or low-contrast lesions. In addition, photon-counting CT may offer the possibility of reducing radiation dose. This review provides an overview of the actual clinical operation of photon-counting CT and its diagnostic utility in abdominal imaging. We also describe the clinical implications of photon-counting CT including imaging of hepatocellular carcinoma, liver metastases, hepatic steatosis, pancreatic cancer, intraductal mucinous neoplasm of the pancreas, and thrombus. Graphical Abstract
Knowledge of the MRI features of borderline epithelial ovarian tumor can aid in preoperative diagnosis; however, several benign and malignant tumors can mimic borderline tumors and pose diagnostic ... Borderline epithelial ovarian tumors are a distinct pathologic entity characterized by increased epithelial proliferation and nuclear atypia, but without frank stromal invasion. Borderline tumor (B... Created with BioRender.com
Objective: This study aimed to evaluate the effects of deep learning (DL) reconstruction and a postprocessing sharpening filter on the image quality of single-shot fast spin-echo (SSFSE) T2-weighted imaging (T2WI) of the uterus. Materials and Methods: Fifty consecutive patients who underwent pelvic magnetic resonance imaging were included. Parasagittal T2WI with a slice thickness of 4 mm was obtained with the periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) and SSFSE sequences (mean scan time, 204 and 22 seconds, respectively). The following 3 types of SSFSE images were reconstructed, and the signal-to-noise ratio (SNR) and tissue contrast were assessed: conventional reconstruction (SSFSE-C), DL reconstruction (SSFSE-DL), and DL with a sharpening filter (SSFSE-DLF). Three radiologists independently assessed image quality, and area under the visual grading characteristics curve (AUCVGC) analysis was performed to compare the SSFSE and PROPELLER images. Results: Compared with that of the PROPELLER images, the SNR of the SSFSE-C, SSFSE-DL, and SSFSE-DLF images was significantly lower (P < 0.05), significantly higher (P < 0.05), and equivalent, respectively. The SSFSE-DL images exhibited significantly lower contrast between the junctional zone and myometrium than those obtained with the other sequences (P < 0.05). In qualitative comparisons with the PROPELLER images, all 3 SSFSE sequences, SSFSE-DL, and SSFSE-DLF demonstrated significantly higher scores for artifacts, noise, and sharpness, respectively (P < 0.01). The overall image quality of SSFSE-C (mean AUCVGC, 0.03; P < 0.01) and SSFSE-DL (mean AUCVGC, 0.23; P < 0.01) was rated as significantly inferior, whereas that of SSFSE-DLF (mean AUCVGC, 0.69) was equivalent or significantly higher (P < 0.01). Conclusion: Using a combination of DL and a sharpening filter markedly increases the image quality of SSFSE of the uterus to the level of the PROPELLER sequence.