Radiomics-based histological grading of pancreatic ductal adenocarcinoma using 18F-FDG PET/CT: A two-center study

European Journal of Radiology, Journal Year: 2025, Volume and Issue: unknown, P. 112070 - 112070

Published: March 1, 2025

Language: Английский

Performance of deep learning models for automatic histopathological grading of meningiomas: a systematic review and meta-analysis

Frontiers in Neurology, Journal Year: 2025, Volume and Issue: 16

Published: May 13, 2025

Accurate preoperative grading of meningiomas is crucial for selecting the most suitable treatment strategies and predicting patient outcomes. Traditional MRI-based assessments are often insufficient to distinguish between low- high-grade reliably. Deep learning (DL) models have emerged as promising tools automated histopathological using imaging data. This systematic review meta-analysis aimed comprehensively evaluate diagnostic performance deep meningioma grading. study was conducted in accordance with PRISMA-DTA guidelines prospectively registered on Open Science Framework. A search PubMed, Scopus, Web performed up March 2025. Studies DL classify based data were included. random-effects used pool sensitivity, specificity, accuracy, area under receiver operating characteristic curve (AUC). bivariate model fit summary (SROC) curve. Study quality assessed Newcastle-Ottawa Scale, publication bias evaluated Egger's test. Twenty-seven studies involving 13,130 patients The pooled sensitivity 92.31% (95% CI: 92.1-92.52%), specificity 95.3% 95.11-95.48%), accuracy 97.97% 97.35-97.98%), an AUC 0.97 0.96-0.98). SROC demonstrated excellent performance, characterized by a relatively narrow 95% confidence interval despite moderate high heterogeneity (I2 = 79.7%, p < 0.001). demonstrate automatic could serve valuable clinical decision-support tools. DOI: 10.17605/OSF.IO/RXEBM.

Language: Английский

MRI-based radiomics for differentiating high-grade from low-grade clear cell renal cell carcinoma: a systematic review and meta-analysis

Abdominal Radiology, Journal Year: 2025, Volume and Issue: unknown

Published: May 17, 2025

Language: Английский