Differentiation of solid and cystic small renal masses: the role of multiphase CT markers in predicting malignant histology, subtype, and grade DOI Open Access
Yulian Mytsyk

Polish Journal of Radiology, Journal Year: 2025, Volume and Issue: 90, P. 239 - 252

Published: May 21, 2025

Purpose This study aimed to assess the diagnostic performance of multiphase contrast-enhanced computed tomography (MCECT) in differentiating benign and malignant solid cystic small renal masses (SRMs), predicting histologic subtypes, grading, using signal intensity (SI) tumour-to-cortex (TCSI) ratio. Material methods A retrospective analysis was conducted on 181 patients with SRMs (≤ 4 cm). MCECT imaging across phases (non-contrast, corticomedullary, nephrographic, excretory) performed. SI TCSI values were measured, their evaluated receiver operating charac­teristic (ROC) analysis. Solid, Bosniak IIF, III, IV underwent histopathological confirmation. Results Among SRMs, excretory phase achieved an area under curve (AUC) 0.848 for RCC from other 100% sensitivity 61.3% specificity. For distinguishing cell carcinoma (RCC) most effective parameter ratio obtained (88.6% sensitivity, 52.4% specificity, 0.763 AUC). IIF cysts, corticomedullary provided AUC 0.902, 93% 87.5% subtyping showed distinct characteristics phases, particularly clear RCC. Nephrographic differentiated low- versus high-grade RCC, 0.901, 90.2% 86.4% Conclusions MCECT-derived biomarkers, TCSI, are non-invasive tools characterising aiding differentiation lesions, histological tumour grades. Their integration advanced radiomics could further enhance accuracy.

Language: Английский

Diagnostic performance of artificial intelligence in detection of renal cell carcinoma: a systematic review and meta-analysis DOI Creative Commons
Mahdi Gouravani, Mohammad Shahrabi Farahani, Mohammad Amin Salehi

et al.

BMC Cancer, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 27, 2025

The detection of renal cell carcinoma (RCC) tumors in the earlier stages is great importance for more effective treatment. Encouraged by key role imaging management RCC, we conducted a systematic review and meta-analysis studies that made use artificial intelligence (AI) RCC to quantitatively determine performance AI distinguishing related lesions. PubMed, Scopus, CENTRAL, Embase electronic databases were systematically searched November 2024 identify applied or classification RCC. We evaluate diagnostic utilized algorithms. Moreover, meta-regression was over suspected covariates potential sources inter-study heterogeneity. Publication bias quality assessment also done included studies. Sixty-four this review, which 31 selected meta-analysis. assessing algorithms' on internal validation showed pooled sensitivity specificity 85% (95% confidence interval [CI], 82 87) 76% CI, 70 80), respectively. externally validated Al algorithms had 80% 73 84) 90% 84 93), Studies performed clinician 79% 72 85) 60% 49 70). findings present study validate acceptable when contrasted with medical professionals identification categorization Nevertheless, presence heterogeneity between absence coherence results underscore necessity cautious interpretation these additional prospective

Language: Английский

Citations

1
Differentiation of solid and cystic small renal masses: the role of multiphase CT markers in predicting malignant histology, subtype, and grade DOI Open Access
Yulian Mytsyk

Polish Journal of Radiology, Journal Year: 2025, Volume and Issue: 90, P. 239 - 252

Published: May 21, 2025

Purpose This study aimed to assess the diagnostic performance of multiphase contrast-enhanced computed tomography (MCECT) in differentiating benign and malignant solid cystic small renal masses (SRMs), predicting histologic subtypes, grading, using signal intensity (SI) tumour-to-cortex (TCSI) ratio. Material methods A retrospective analysis was conducted on 181 patients with SRMs (≤ 4 cm). MCECT imaging across phases (non-contrast, corticomedullary, nephrographic, excretory) performed. SI TCSI values were measured, their evaluated receiver operating charac­teristic (ROC) analysis. Solid, Bosniak IIF, III, IV underwent histopathological confirmation. Results Among SRMs, excretory phase achieved an area under curve (AUC) 0.848 for RCC from other 100% sensitivity 61.3% specificity. For distinguishing cell carcinoma (RCC) most effective parameter ratio obtained (88.6% sensitivity, 52.4% specificity, 0.763 AUC). IIF cysts, corticomedullary provided AUC 0.902, 93% 87.5% subtyping showed distinct characteristics phases, particularly clear RCC. Nephrographic differentiated low- versus high-grade RCC, 0.901, 90.2% 86.4% Conclusions MCECT-derived biomarkers, TCSI, are non-invasive tools characterising aiding differentiation lesions, histological tumour grades. Their integration advanced radiomics could further enhance accuracy.

Language: Английский

Citations

0