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Chat GPT-4 shows high agreement in MRI protocol selection compared to board-certified neuroradiologists

Objectives - The aim of this study was to determine whether ChatGPT-4 can correctly suggest MRI protocols and additional MRI sequences based on real-world Radiology Request Forms (RRFs) as well as to investigate the ability of ChatGPT-4 to suggest time saving protocols. - Material & methods - Re...

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Main Authors: Bendella, Zeynep (Author) , Wichtmann, Barbara (Author) , Clauberg, Ralf (Author) , Keil, Vera Catharina Wilma (Author) , Lehnen, Nils Christian (Author) , Haase, Robert (Author) , Sáez, Laura C. (Author) , Wiest, Isabella (Author) , Kather, Jakob Nikolas (Author) , Endler, Christoph Hans-Jürgen (Author) , Radbruch, Alexander (Author) , Paech, Daniel (Author) , Deike-Hofmann, Katerina (Author)
Format: Article (Journal)
Language:English
Published: December 2025
In: European journal of radiology
Year: 2025, Volume: 193, Pages: 1-7
ISSN:1872-7727
DOI:10.1016/j.ejrad.2025.112416
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.ejrad.2025.112416
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S0720048X25005029
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Author Notes:Zeynep Bendella, Barbara Daria Wichtmann, Ralf Clauberg, Vera C. Keil, Nils C. Lehnen, Robert Haase, Laura C. Sáez, Isabella C. Wiest, Jakob Nikolas Kather, Christoph Endler, Alexander Radbruch, Daniel Paech, Katerina Deike
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Summary:Objectives - The aim of this study was to determine whether ChatGPT-4 can correctly suggest MRI protocols and additional MRI sequences based on real-world Radiology Request Forms (RRFs) as well as to investigate the ability of ChatGPT-4 to suggest time saving protocols. - Material & methods - Retrospectively, 1,001 RRFs of our Department of Neuroradiology (in-house dataset), 200 RRFs of an independent Department of General Radiology (independent dataset) and 300 RRFs from an external, foreign Department of Neuroradiology (external dataset) were included. Patients’ age, sex, and clinical information were extracted from the RRFs and used to prompt ChatGPT- 4 to choose an adequate MRI protocol from predefined institutional lists. Four independent raters then assessed its performance. Additionally, ChatGPT-4 was tasked with creating case-specific protocols aimed at saving time. - Results - Two and 7 of 1,001 protocol suggestions of ChatGPT-4 were rated “unacceptable” in the in-house dataset for reader 1 and 2, respectively. No protocol suggestions were rated “unacceptable” in both the independent and external dataset. When assessing the inter-reader agreement, Coheńs weighted ĸ ranged from 0.88 to 0.98 (each p < 0.001). ChatGPT-4′s freely composed protocols were approved in 766/1,001 (76.5 %) and 140/300 (46.67 %) cases of the in-house and external dataset with mean time savings (standard deviation) of 3:51 (minutes:seconds) (±2:40) minutes and 2:59 (±3:42) minutes per adopted in-house and external MRI protocol. - Conclusion - ChatGPT-4 demonstrated a very high agreement with board-certified (neuro-)radiologists in selecting MRI protocols and was able to suggest approved time saving protocols from the set of available sequences.
Item Description:Online verfügbar: 13. September 2025, Artikelversion: 16. September 2025
Gesehen am 10.11.2025
Physical Description:Online Resource
ISSN:1872-7727
DOI:10.1016/j.ejrad.2025.112416

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