DOI 10.1007/s11695-026-08942-5
Preoperative Magnetic Resonance Imaging-Derived Adiposity Profiling and Cardiometabolic Remodeling After Metabolic and Bariatric Surgery.
Аннотация
BACKGROUND
Cardiometabolic remodeling after metabolic and bariatric surgery is heterogeneous and may not be fully characterized by clinical measures. This exploratory pilot study examined whether abdominal magnetic resonance imaging (MRI)-derived adiposity profiles, combined with clinical and echocardiographic data, could identify preoperative patterns associated with 12-month cardiometabolic remodeling after laparoscopic sleeve gastrectomy (LSG).
METHODS
This prospective study included 40 adults with severe obesity who underwent LSG. Baseline clinical characteristics, MRI-derived subcutaneous adipose tissue (SAT), visceral adipose tissue, liver fat fraction, and transthoracic echocardiographic parameters were evaluated in relation to 12-month changes in body weight (BW), glycated hemoglobin (A1C), mean blood pressure (mean BP), and left ventricular mass index (LVMI). Elastic net regression with 1,000 bootstrap resamples was used to identify stable exploratory signals.
RESULTS
At 12 months, participants achieved a BMI reduction of 14.78 ± 4.52 kg/m², corresponding to 90.01 ± 24.06% excess BMI loss, with significant improvements in A1C, mean BP, and LVMI (all p < 0.001). Higher baseline BW and A1C were associated with greater weight loss and glycemic improvement, respectively. Cardiovascular remodeling showed distinct patterns: higher baseline BP and greater abdominal SAT were associated with greater BP reduction, whereas greater baseline LVMI and lower estimated filling pressure were associated with more favorable cardiac reverse remodeling. Removing MRI variables reduced model performance for mean BP reduction and LVMI regression but had little effect on weight loss or glycemic improvement.
CONCLUSIONS
MRI-derived adiposity measures may add selective information for cardiovascular remodeling after LSG, but require validation in larger independent cohorts.
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