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Medical imaging diagnostic test accuracy research is strengthened by adhering to best practices for study design, data collection, data documentation, and study reporting. In this review, key elements of such research are discussed, and specific recommendations provided for optimizing diagnostic accuracy study execution to improve uniformity, minimize common sources of bias and avoid potential pitfalls. Examples are provided regarding study methodology and data collection practices based on insights gained by the liver imaging reporting and data system (LI‐RADS) individual participant data group, who have evaluated raw data from numerous MRI diagnostic accuracy studies for risk of bias and data integrity. The goal of this review is to outline strategies for investigators to improve research practices, and to help reviewers and readers better contextualize a study's findings while understanding its limitations. Level of Evidence: 5 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

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 [ABSTRACT FROM AUTHOR]