Computer-Aided Biomedical Imaging of Periiliac Adipose Tissue Identifies Perivascular Fat as a Marker of Disease Complexity in Patients with Lower Limb Ischemia

Abstract

The aim of the study was to develop a semi-automated, computer-aided imaging technique to quantify the amount and distribution of perivascular fat at the level of the iliac arteries (periiliac adipose tissue—PIAT), and to investigate the association of this new computer-aided imaging biomarker with other biomedical imaging biomarkers, which characterize the pelvic adipose tissue (SAT—subcutaneous adipose tissue; VAT—visceral adipose tissue). We included 34 patients with peripheral arterial disease, in whom the volumes of PIAT, SAT and VAT were quantified using a dedicated software, at the level of right and left iliac arteries. Median value of PIAT was five milliliters. Patients with PIAT > five milliliters were in more advanced Fontaine classes, with more complex arterial lesions, compared to those with low PIAT (<5 mL) (p < 0.0001). PIAT volumes presented a gradual increase with the Trans-Atlantic Inter-Society Consensus (TASC) class (2.57 +/− 1.98 in TASC A, 4.65 +/− 1.63 in TASC B, 8.79 +/− 1.99 in TASC C and 13.77 +/− 2.74 in TASC D). The distribution of PIAT between the left and right iliac axis was quasi-uniform (correlation between right and left PIAT: r = 0.46, p = 0.005). Linear regression analysis showed that the mean PIAT volume was correlated with VAT (r = 0.38, p = 0.02), but not with the SAT at the level of iliac artery origin (r = 0.16, p = 0.34). PIAT may represent a novel biomedical imaging derived biomarker, which characterizes the distribution of adipose tissue in the pelvic area and may serve as an indicator of the severity and complexity of lower limb ischemia.