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REVIEW   

Journal of Radiological Review 2022 June;9(2):93-9

DOI: 10.23736/S2723-9284.22.00189-1

Copyright © 2022 EDIZIONI MINERVA MEDICA

lingua: Inglese

Current knowledge of radiological structured reporting

Salvatore C. FANNI , Leonardo COLLIGIANI, Nicola SPINA, Giuseppe COLASANTI, Michela GABELLONI, Dania CIONI, Emanuele NERI

Division of Academic Radiology, Department of Translational Research, University of Pisa, Pisa, Italy



Since the beginning of radiology, radiologists have been using free-text reporting (FTR), which leaves them a virtually unlimited freedom of describing imaging findings and diagnostic impressions but can have downsides such as language heterogeneity and excessive variability in style and length, potentially resulting in reduced report clarity and poor communication with referring clinicians. A structured report can be defined as a digital document composed of hierarchically ordered items, which a radiologist can input using a standardized lexicon based on a predefined template for a given radiological procedure. Owing to its properties, structured reporting (SR) can overcome the limitations of FTR, yet some issues remain to be addressed for a more widespread adoption of SR in radiological practice. This narrative review aims to explore the clinical potential of SR, discussing its benefits and drawbacks compared to FTR (also in light of current guidelines from relevant scientific societies), the clinicians’ and radiologists’ attitude towards it, and the SIRM approach to the development of SR templates. A brief overview about the future perspectives of SR and its relationship with artificial intelligence will also be provided.


KEY WORDS: Research report; Radiology; Artificial intelligence; Review

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