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Updated: Jan 15, 2026

Adipo-Clear: A Tissue Clearing Method for Three-Dimensional Imaging of Adipose Tissue
Published on: July 28, 2018
AI in Adipose Imaging: Revolutionizing Visceral Adipose Tissue, Ectopic Fat, and Cardiovascular Risk Assessment
Sneha R Kandi1,2, Rohan Khera3,4,5,6, Sanjay Rajagopalan1,2,7
1Department of Medicine, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
Purpose Of Review:
This review explores the role of artificial intelligence (AI) in visceral adipose tissue (VAT) and ectopic fat imaging. It aims to evaluate how AI may be used to enhance the efficiency and accuracy of cardiovascular disease (CVD) risk assessment. It addresses key questions regarding AI's capabilities in risk prediction, segmentation, and integration with large volume data for CVD risk assessment.
Recent Findings:
Recent studies demonstrate that AI, powered by deep learning models, significantly improve VAT and ectopic fat segmentation. AI can also be used to facilitate early detection of cardiometabolic risks and allows integration of imaging with clinical data for a more personalized approach to medicine. Emerging applications include AI-enabled telehealth and continuous monitoring through wearable technologies. AI is transforming VAT and ectopic fat imaging by enabling more precise, personalized, and scalable assessments of fat distribution and cardiovascular risk. While challenges remain, such as model interpretability, future research will likely focus on refining algorithms and expanding AI's clinical applications, potentially redefining obesity and CVD risk management.
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