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Hi ChatGPT, I am a Radiologist, How can you help me?

Davide Bellini1, Riccardo Ferrari2, Simone Vicini3

  • 1Academic Diagnostic Imaging Division - I.C.O.T. Hospital, Department of Medical-Surgical Sciences and Biotechnologies, Faculty of Pharmacy and Medicine, University of Rome "Sapienza", Via F. Faggiana 1668, 04100, Latina, Italy. bellinidavide29@gmail.com.

La Radiologia Medica
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Summary
This summary is machine-generated.

ChatGPT, a generative AI, shows promise in enhancing radiologist efficiency by assisting with report structuring, research protocols, and statistical analysis. While not for direct image interpretation, it aids in post-processing and analysis of radiological data.

Keywords:
Artificial intelligenceChatGPT applicationsMedical imagingRadiology workflow

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Area of Science:

  • Radiology
  • Artificial Intelligence
  • Medical Informatics

Background:

  • Current AI in radiology primarily focuses on image acquisition, reconstruction, and interpretation, often integrated into hardware.
  • Generative AI models like ChatGPT offer a unique, accessible tool with broad functional capabilities beyond traditional AI in radiology.

Purpose of the Study:

  • To explore the integration of ChatGPT into radiological practices.
  • To assess ChatGPT's potential to enhance the operational efficiency of radiologists.
  • To test ChatGPT's utility in everyday radiological tasks through real-world examples.

Main Methods:

  • An interview-based review approach was employed.
  • ChatGPT's capabilities were tested using real-world radiological tasks and examples.
  • The review focused on practical utility rather than an exhaustive feature evaluation.

Main Results:

  • ChatGPT demonstrated strong capabilities in structuring radiology reports according to international guidelines (e.g., PI-RADS, CT reporting for diverticulitis).
  • The AI model successfully designed a complete research protocol and performed advanced statistical analysis on Excel datasets, including ROC curve generation.
  • ChatGPT provided meaningful assistance in image post-processing and interpretation when images were converted to standard formats, despite lacking direct DICOM interpretation.

Conclusions:

  • ChatGPT presents significant strengths as a supportive tool for radiologists, enhancing efficiency in administrative and analytical tasks.
  • Its limitations include the inability to directly interpret DICOM images, but it can assist in interpretation when data is converted.
  • The findings highlight ChatGPT's potential to augment radiologist workflows and operational efficiency.