Natural language processing-based analysis of the level of adoption by expert radiologists of the ASSR, ASNR and NASS version 2.0 of lumbar disc nomenclature: an eight-year survey.

Abstract

Background: The American Society of Spine Radiology (ASSR), American Society of Neuroradiology (ASNR), and North American Spine Society (NASS) published a consensus paper with recommendations for lumbar disc nomenclature reports in 2014. We aimed to evaluate the degree of adoption in our radiology department of the ASSR, ASNR, and NASS 2.0 lumbar spine consensus paper using natural language processing (NLP).

Methods: In March 2015 we gave in our radiology department, at HT Medica in Jaén (Spain) a lecture detailing the changes proposed in the ASSR, ASNR, and NASS consensus about lumbar disc nomenclature, version 2.0. We analyzed 34,064 lumbar spine magnetic resonance imaging (MRI) reports from three different expert radiologists (A, B, and C) performed from May 2010 to February 2015 (15,813 studies) and from March 2015 to February 2022 (18,251 studies). Using an NLP algorithm, we evaluated 29 old and new terms related to 4 different categories: disc with fissures of the annulus, degenerated disc, herniated disc, and location of the disc.

Results: A relevant decrease in the percentage of use of old terms was found for degenerated disc category (44.63% for radiologist B and 18.95% for radiologist C) and disc localization (18.86% for radiologist A and 27.73% for radiologist C). Relevant increments in the percentage of use of new lexicon were depicted for terms related to degenerated disc (32.48% for radiologist C), herniated disc (7.27% for radiologist A) and disc localization (36.53% for radiologist C).

Conclusions: NLP algorithms may help to manage large radiological report datasets to evaluate the impact and degree of adherence of radiologists to recommendations for the use of ASSR, ASNR and NASS lumbar disc nomenclature version 2.0.