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Objectives: This study investigated the feasibility and image quality of ultra-low-dose unenhanced abdominal CT using photon-counting detector technology and tin prefiltration.
Materials And Methods: Employing a first-generation photon-counting CT scanner, eight cadaveric specimens were examined both with tin prefiltration (Sn 100 kVp) and polychromatic (120 kVp) scan protocols matched for radiation dose at three different levels: standard-dose (3 mGy), low-dose (1 mGy) and ultra-low-dose (0.5 mGy). Image quality was evaluated quantitatively by means of contrast-to-noise-ratios (CNR) with regions of interest placed in the renal cortex and subcutaneous fat. Additionally, three independent radiologists performed subjective evaluation of image quality. The intraclass correlation coefficient was calculated as a measure of interrater reliability.
Results: Irrespective of scan mode, CNR in the renal cortex decreased with lower radiation dose. Despite similar mean energy of the applied x-ray spectrum, CNR was superior for Sn 100 kVp over 120 kVp at standard-dose (17.75 ± 3.51 vs. 14.13 ± 4.02), low-dose (13.99 ± 2.6 vs. 10.68 ± 2.17) and ultra-low-dose levels (8.88 ± 2.01 vs. 11.06 ± 1.74) (all ≤ 0.05). Subjective image quality was highest for both standard-dose protocols (score 5; interquartile range 5-5). While no difference was ascertained between Sn 100 kVp and 120 kVp examinations at standard and low-dose levels, the subjective image quality of tin-filtered scans was superior to 120 kVp with ultra-low radiation dose ( < 0.05). An intraclass correlation coefficient of 0.844 (95% confidence interval 0.763-0.906; < 0.001) indicated good interrater reliability.
Conclusions: Photon-counting detector CT permits excellent image quality in unenhanced abdominal CT with very low radiation dose. Employment of tin prefiltration at 100 kVp instead of polychromatic imaging at 120 kVp increases the image quality even further in the ultra-low-dose range of 0.5 mGy.
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http://dx.doi.org/10.3390/diagnostics13040603 | DOI Listing |
JMIR Med Inform
September 2025
Departments of Radiology, The Third Affiliated Hospital, Sun Yat-Sen University, 600 Tianhe Road, Guangzhou, Guangdong, 510630, China, 86 18922109279, 86 20852523108.
Background: Despite the Coronary Artery Reporting and Data System (CAD-RADS) providing a standardized approach, radiologists continue to favor free-text reports. This preference creates significant challenges for data extraction and analysis in longitudinal studies, potentially limiting large-scale research and quality assessment initiatives.
Objective: To evaluate the ability of the generative pre-trained transformer (GPT)-4o model to convert real-world coronary computed tomography angiography (CCTA) free-text reports into structured data and automatically identify CAD-RADS categories and P categories.
J Cataract Refract Surg
September 2025
Ophthalmology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy.
Purpose: To compare the usability and training effectiveness of a 3D-printed coaxial illumination system mounted on an off-the-shelf stereo-microscope to a professional ophthalmic surgical microscope, in cataract surgery simulation.
Setting: Ophthalmology Lab, Ophthalmology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Siena, Italy.
Design: Prospective randomized crossover study.
J Vestib Res
September 2025
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
ObjectiveTo explore the incidence, risk factors, and comorbidities of persistent postural-perceptual dizziness (PPPD) after stroke.MethodsPatients with acute stroke and vestibular symptoms were enrolled prospectively and continuously. Baseline information, risk factors, imaging materials, and diagnosis were collected.
View Article and Find Full Text PDFPLoS Negl Trop Dis
September 2025
Universitat Oberta de Catalunya, Barcelona, Spain.
Background: Originally adapted from a paper-based guide for skin-related neglected tropical diseases (NTDs), version 3.0.0 of the World Health Organization (WHO) SkinNTDs app aims to strengthen disease surveillance and frontline health worker capacity in NTD-endemic settings.
View Article and Find Full Text PDFPLoS One
September 2025
The Institute of Port Information Digitalization, China Liaoning Port Group Co. Ltd., Dalian, Liaoning, China.
Background: Underwater environments face challenges with image degradation due to light absorption and scattering, resulting in blurring, reduced contrast, and color distortion. This significantly impacts underwater exploration and environmental monitoring, necessitating advanced algorithms for effective enhancement.
Objectives: The study aims to develop an innovative underwater image enhancement algorithm that integrates physical models with deep learning to improve visual quality and surpass existing methods in performance metrics.