RADS ALPHABET: news and tips for young and general radiologists

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Authors: Roberto Cannella, Carolina Lanza, Giuseppe Pellegrino, Domenico Albano, Alessandra Bruno, Giuditta Chiti, Caterina Giannitto, Elisabetta Giannotti, Cristiano Michele Girlando, Francesca Grassi, Carmelo Messina, Rebecca Mura
+8 more Giuseppe Petralia, Arnaldo Stanzione, Federica Vernuccio, Fabio Zugni, Antonio Barile, Nicoletta G. Gandolfo, Gianpaolo Carrafiello, Serena Carriero
Cited by: 0
References: 125

Abstract

Reporting and Data Systems (RADS) aim at standardizing imaging acquisition, interpretation, lexicon, and reporting standards in specific patient populations, facilitating the communication between radiologists and clinicians. While the adoption of RADS has been supported by several studies and guidelines, with some of them endorsed by the American College of Radiology, the clinical adoption of the RADS algorithm remains heterogeneous among general practice radiologists worldwide, being lower in non-academic and young radiologists. This article aims to provide an updated review, aimed at young and general radiologists, of the RADS alphabet, discussing the main applications and imaging criteria with tips for their correct use in clinical practice. The following RADS will be discussed: BI-RADS, Bone-RADS, C-RADS, CAD-RADS, LI-RADS, Lung-RADS, MET-RADS-P, MY-RADS, NI-RADS, Node-RADS, O-RADS, ONCO-RADS, PI-RADS, ST-RADS, TI-RADS, and VI-RADS. CRITICAL RELEVANCE STATEMENT: A comprehensive guide aimed at young and general radiologists featuring all of the major RADS with the objective to foster their implementation in clinical practice, which could be beneficial in a further standardization of the medical reports and in the communication between radiologists and clinicians. KEY POINTS: RADS are outlined to enhance communication efficacy between radiologists and clinicians. Updated overview of RADS frameworks, detailing applications, imaging criteria, and advancements. RADS' implementation remains a challenge, but can be addressed.

Fields of Study & Subjects

Radiology practices and education Radiomics and Machine Learning in Medical Imaging Clinical practice guidelines implementation

Publication details

Journal / source
Insights into Imaging
Volume
17
Issue
1
Pages
9–9
Publication date
12 January 2026
Language
EN