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Author Spotlight: Advancements in 3D Optical Imaging for Comprehensive Body Composition Assessment in Modern Research

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Deep Learning-Derived Body Composition Analysis Predicts Long-Term Mortality After Transcatheter Aortic Valve

Chia-Hao Liu^1,2, Agata Sularz¹, Ghasaq Saleh¹

¹Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.

Mayo Clinic Proceedings. Digital Health

|April 30, 2026

Summary

This summary is machine-generated.

Reduced skeletal muscle and adipose tissue after transcatheter aortic valve replacement (TAVR) are linked to higher mortality. Body composition analysis from CT scans can improve risk assessment for TAVR patients.

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Published on: March 21, 2021

Area of Science:

Cardiovascular Imaging
Medical Physics
Geriatric Medicine

Background:

Transcatheter aortic valve replacement (TAVR) is a key treatment for aortic stenosis.
Patient outcomes after TAVR can be influenced by various factors, including body composition.
Preprocedural assessment is crucial for optimizing TAVR success.

Purpose of the Study:

To investigate the association between body composition metrics from computed tomography (CT) angiography and all-cause mortality post-TAVR.
To determine if specific body composition parameters can predict long-term survival after TAVR.

Main Methods:

Utilized CT angiography data from 2642 TAVR patients (2011-2023).
Quantified skeletal muscle (SM), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and SM index (SMI) using a deep learning model.
Assessed 3-year all-cause mortality using multivariable Cox proportional hazards models.

Main Results:

Lower SM, SAT, VAT, and SMI were independently associated with increased 3-year all-cause mortality.
Specific thresholds for these metrics indicated higher mortality risk (e.g., SM <128 cm², SMI <41 cm²/m²).
Adjusted hazard ratios indicated significant associations for all analyzed body composition parameters.

Conclusions:

Diminished skeletal muscle and adipose tissue reserves are significant independent predictors of mortality after TAVR.
Automated CT-derived body composition analysis offers a promising tool for preoperative risk stratification in TAVR candidates.
These findings can aid in refining clinical decision-making for patients undergoing TAVR.