Objective: The aims of this study were to optimize the scanning technique of first-pass 64-detector-row perfusion volume computed tomography imaging, to evaluate the effectiveness and stability of this scan protocol, and lastly to evaluate the differential diagnosis ability of perfusion imaging in solitary pulmonary nodules (SPNs).
Methods: A total of 144 patients with SPNs underwent perfusion scan with 64-slice spiral CT scanner. The CT perfusion imaging was analyzed for time-density curve, perfusion parametric maps, and the respective perfusion parameters. We then analyzed the main factors concerning the imaging quality and evaluated the effectiveness of scan protocol by determining the receiver operating characteristic (ROC) curve, diagnostic efficacy, and odds ratio as well as the stability of scan protocol by consistency analysis. Immunohistochemical findings of microvessel density measurement and vascular endothelial growth factor expression were evaluated.
Results: The total sensitivity, specificity, accuracy, positive predictive value, negative predictive value, likelihood ratio, and the area under ROC curve during 5-45-s scan period were 78.95%, 82.4%, 80.6%, 83.3%, 77.8%, 4.620, 0.280, and 0.840, respectively, and Kappa value was 0.894. The diagnostic efficacy of CT pulmonary perfusion was significantly higher than during 0-40-s scan period. The parameter values in different nodules were different.
Conclusion: The optimized 5-45-s scan period of CT pulmonary perfusion imaging is effective in pathologic diagnosis and has good stability, worthy of being popularized. Lung perfusion CT could be a promising and feasible method for differentiation of SPNs.
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http://dx.doi.org/10.1016/j.clinimag.2012.05.004 | DOI Listing |
Eur Radiol
January 2025
Department of Radiology, Geneva University Hospitals, Geneva, Switzerland.
Objectives: Evaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on procedure errors and scan times compared to manual planning alone.
Material And Methods: Consecutive patients undergoing non-stress CMR were prospectively enrolled at a single center (August 2023-February 2024) and randomized into manual, or automated scan execution using prototype software. Patients with pacemakers, targeted indications, or inability to consent were excluded.
Radiol Artif Intell
January 2025
https://www.procancer-i.eu/.
Purpose To assess the impact of scanner manufacturer and scan protocol on the performance of deep learning models to classify prostate cancer (PCa) aggressiveness on biparametric MRI (bpMRI). Materials and Methods In this retrospective study, 5,478 cases from ProstateNet, a PCa bpMRI dataset with examinations from 13 centers, were used to develop five deep learning (DL) models to predict PCa aggressiveness with minimal lesion information and test how using data from different subgroups-scanner manufacturers and endorectal coil (ERC) use (Siemens, Philips, GE with and without ERC and the full dataset)-impacts model performance. Performance was assessed using the area under the receiver operating characteristic curve (AUC).
View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
Department of Neurology, Faculty of Medicine, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu, Oita, 879-5593, Japan.
Background: Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in the pathological process of Alzheimer's disease (AD). Efficient screening for amyloid pathology is critical for identifying patients for early treatment. This study developed machine learning models to classify positron emission tomography (PET) Aβ-positivity in participants with preclinical and prodromal AD using data accessible to primary care physicians.
View Article and Find Full Text PDFBJOG
January 2025
National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Objective: To assess the cost-effectiveness of modifying current antenatal screening by adding first trimester structural anomaly screening to standard of care second trimester anomaly screening.
Design: Health economic decision model.
Setting: National Health Service (NHS) in England and Wales.
J Neuroimaging
January 2025
Department of Radiology, Division of Neuroradiology, Johns Hopkins Medical Center, Baltimore, Maryland, USA.
Background And Purpose: Prolonged length of stay (LOS) following a stroke is associated with unfavorable clinical outcomes. Factors predicting LOS in medium vessel occlusion (MeVO), impacting up to 40% of acute ischemic stroke (AIS) cases, remain underexplored. This study aims to investigate the predictors of LOS in AIS-MeVO.
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