Accepted for/Published in: JMIR AI
Date Submitted: Oct 29, 2024
Date Accepted: May 18, 2025
Date Submitted to PubMed: May 19, 2025
ChatGPT-4-Driven Liver Ultrasound Radiomics Analysis: Advantages and Drawbacks Compared to Traditional Techniques
ABSTRACT
Background:
The integration of artificial intelligence (AI) into medical imaging, particularly with large language models like ChatGPT-4, has the potential to advance diagnostic workflows by enabling automated and rapid analysis. ChatGPT-4's intuitive interface and ability to interpret complex queries position it as a transformative tool for medical image analysis. .
Objective:
This study aims to evaluate ChatGPT-4's performance in liver ultrasound radiomics, assessing its ability to differentiate liver conditions—specifically fibrosis, steatosis, and normal liver tissue—compared to traditional analysis software.
Methods:
Seventy grayscale ultrasound images from a preclinical liver disease model—including groups with fibrosis, fatty liver, and normal liver—were analyzed. Key texture features were extracted using ChatGPT-4 and compared with those obtained from conventional image analysis software (Interactive Data Language, IDL). Statistical significance of texture features distinguishing between liver conditions was assessed using one-way ANOVA. Logistic regression models were fit to evaluate the diagnostic performance of both individual and combined features.
Results:
ChatGPT-4 demonstrated robust diagnostic capabilities, achieving 76% accuracy and 83% sensitivity in distinguishing liver pathologies. Several texture features significantly differentiated between liver conditions. Although the IDL software achieved a slightly higher sensitivity of 89%, ChatGPT-4 offered the added benefit of concurrent processing of multiple images, enhancing analysis efficiency.
Conclusions:
While ChatGPT-4 exhibited slightly lower sensitivity and lacked manual control over region-of-interest selection, it showed promise as a viable tool for ultrasound image analysis, effectively differentiating liver pathologies. Its capability to process multiple images simultaneously could streamline diagnostic workflows and alleviate radiologist workload. With further refinement, ChatGPT-4 has the potential to enhance patient outcomes in medical imaging
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