ReviewRadiology2025
In Pursuit of KI-RADS: Toward a Single, Evidence-based Imaging Classification of Renal Masses.
Review in Radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Agreement of axial T2-MRI versus Contrast-Enhanced CT for solid renal mass active surveillance.Abdominal radiology (New York) · 2026Article
- Staging and imaging-based prognostication in renal cell carcinoma: current guidelines and practical considerations.Abdominal radiology (New York) · 2026Review
- Toward a Structured Imaging Reporting System for Kidney Masses: The Molecular Imaging Perspective on KI-RADS.Molecular imaging and biology · 2026Review
- A disease-centric vision-language foundation model for precision oncology in kidney cancer.Nature communications · 2026Article
- Evaluation, Optimization, and Validation of a Multiparametric CT Algorithm for Solid Renal Masses: CT-Score Version 2.0.Radiology. Imaging cancer · 2026Article
- Optimizing outcomes of partial nephrectomy in patients with tumors in solitary kidneys: a non-systematic review.Journal of medicine and life · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Despite the successful application of Imaging Reporting and Data Systems to improve the radiologic description and management of disease in many organs, one does not yet exist for the kidney. Instead, the radiologic approach to the kidney has focused on the Bosniak classification system, which is based on imaging characteristics for cystic renal masses, and detecting macroscopic fat within solid renal masses. Radiologically, cystic and solid renal masses are categorized and evaluated separately because of historical precedent, differences in appearance at imaging, and differences in biologic behavior. However, the World Health Organization classification of renal neoplasms does not support such separation. Further, the primary goal has been cancer diagnosis. Differentiating benign from malignant masses is important, but data show that many renal cancers, particularly when small, will not cause harm. Therefore, a critical goal of any unifying, single, imaging-based classification of kidney masses (ie, a Kidney Imaging Reporting and Data System) should be predicting the biologic behavior or aggressiveness of suspected kidney cancer. This system could inform the need for treatment or active surveillance and reduce prevalent overdiagnosis and overtreatment. This review describes the rationale for and challenges in creating such a system and the research needed for it to be developed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.