Table 1.

Summary of reporting guidelines for common study types used in radiological research, and their corresponding guideline extensions where these involve artificial intelligence

Study design	Reporting guideline	Latest version	AI-related extension	Date of AI-extension published
Clinical Trial Protocol	SPIRIT	2013	SPIRIT-AI	September 2020
Diagnostic Accuracy Studies	STARD	2015	STARD-AI	Expected 2021
			CLAIM	March 2020
			MINIMAR	June 2020
Prediction models for diagnostic or prognostication purposes	TRIPOD	2015	TRIPOD –AI/ML	Expected 2021
	PROBAST	2019	PROBAST-ML	Expected 2021
Randomised Controlled Trials (Interventional Study Design)	CONSORT	2010	CONSORT-AI	September 2020
Systematic reviews and meta-analyses	PRISMA PRISMA-DTA	2009 2018	None planned or announced
Critical appraisal and data extraction of publications relating to prediction models	CHARMS	2014	Applicable to machine learning
Evaluation of human factors in early algorithm deployment	Not applicable		DECIDE-AI	Expected 2021/2022

AI, artificial intelligence; CHARMS, Checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies; CLAIM, Checklist for Artificial Intelligence in Medical Imaging; CONSORT, Consolidated Standards of Reporting Trials; DECIDE-AI, Developmental and Exploratory Clinical Investigation of Decision-support systems driven by Artificial Intelligence; DTA, Diagnostic Trials of Accuracy; MINIMAR, Minimum Information for Medical AI Reporting; ML, machine learning; PRISMA, Preferred Reporting Items for Systematic Review and Meta-analysis; PROBAST, Prediction model Risk Of Bias Assessment Tool; SPIRIT, Standard Protocol Items: Recommendations for Interventional Trials; STARD, Standards for Reporting of Diagnostic Accuracy Studies; TRIPOD, Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis.