医学
荟萃分析
组织学
置信区间
肾细胞癌
放射科
肾透明细胞癌
诊断准确性
研究异质性
人口
核医学
内科学
环境卫生
作者
Robert Frank,Haben Dawit,Patrick M. Bossuyt,Mariska Leeflang,Trevor A. Flood,Rodney H. Breau,Matthew D. F. McInnes,Nicola Schieda
摘要
Background Biparametric (bp)‐MRI and multiparametric (mp)‐MRI may improve the diagnostic accuracy of renal mass histology. Purpose To evaluate the available evidence on the diagnostic accuracy of bp‐MRI and mp‐MRI for solid renal masses in differentiating malignant from benign, aggressive from indolent, and clear cell renal cell carcinoma (ccRCC) from other histology. Study Type Systematic review. Population MEDLINE, EMBASE, and CENTRAL up to January 11, 2022 were searched. Field Strength/Sequence 1.5 or 3 Tesla. Assessment Eligible studies evaluated the accuracy of MRI (with at least two sequences: T2, T1, dynamic contrast and diffusion‐weighted imaging) for diagnosis of solid renal masses in adult patients, using histology as reference standard. Risk of bias and applicability were assessed using QUADAS‐2. Statistical Tests Meta‐analysis using a bivariate logitnormal random effects model. Results We included 10 studies (1239 masses from approximately 1200 patients). The risk of bias was high in three studies, unclear in five studies and low in two studies. The diagnostic accuracy of malignant (vs. benign) masses was assessed in five studies (64% [179/281] malignant). The summary estimate of sensitivity was 95% (95% confidence interval [CI]: 77%–99%), and specificity was 63% (95% CI: 46%–77%). No study assessed aggressive (vs. indolent) masses. The diagnostic accuracy of ccRCC (vs. other subtypes) was evaluated in six studies (47% [455/971] ccRCC): the summary estimate of sensitivity was 85% (95% CI: 77%–90%) and specificity was 77% (95% CI: 73%–81%). Data Conclusion Our study reveals deficits in the available evidence on MRI for diagnosis of renal mass histology. The number of studies was limited, at unclear/high risk of bias, with heterogeneous definitions of solid masses, imaging techniques, diagnostic criteria, and outcome measures. Evidence Level 3 Technical Efficacy Stage 2
科研通智能强力驱动
Strongly Powered by AbleSci AI