Deciphering CT texture features of human visceral fat to evaluate metabolic disorders and surgery-induced weight loss effects.

ABSTRACT:

Background

Metabolic syndrome (MetS) is highly related to the excessive accumulation of visceral adipose tissue (VAT). Quantitative measurements of VAT are commonly applied in clinical practice for measurement of metabolic risks; however, it remains largely unknown whether the texture of VAT can evaluate visceral adiposity, stratify MetS and predict surgery-induced weight loss effects.

Methods

675 Chinese adult volunteers and 63 obese patients (with bariatric surgery) were enrolled. Texture features were extracted from VATs of the computed tomography (CT) scans and machine learning was applied to identify significant imaging biomarkers associated with metabolic-related traits.

Findings

Combined with sex, ten VAT texture features achieved areas under the curve (AUCs) o

SUBMITTER: Shi J 

PROVIDER: S-EPMC8264112 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature