Fat Shadows from DEXA for Documentation of Fat Distribution in Patients with Lipodystrophy

Lipodystrophy (LD) syndromes are a heterogeneous group of disorders causing atypical diabetes, associated with selective absence of fat with diagnosis mostly depending on the clinical acumen of the physician. With niche therapies either approved or under investigation, development of objective diagnostic tools for these syndromes are urgently needed. Here we describe a new method using the built-in features of the enCore software v14.10 to render out non-fat tissues from Dual Energy X-ray Absorptiometry (DEXA) scans to derive a “fat-shadow” (Figure). We evaluated fat-shadows from 58 LD (50F:8M) patients and 91 non-LD patients (51F:40M). Among the LD, 3 had Generalized LD, 2 had Acquired Partial LD, and 53 had Familial Partial LD. Controls consisted of a mixed population of lean (12F:14M) or obese patients (39F:26M) with or without metabolic disease. There was substantial overlap in % body fat between the LD and non-LD groups (interquartile range: total, 22.2-39.8% vs. 33.6-45.9%; trunk, 27.0-46.8% vs. 39.1-50.2%; legs, 16.6-30.6% vs. 27.7-42.6%). However, fat-shadows obtained from patients with LD stood out due to the paucity of fat signal either in a generalized or regional manner compared to controls. Overall, fat-shadows provided sufficient qualitative information to infer clinical phenotype. We propose that these fat-shadows could be used for accurate documentation of fat distribution in LD.