Work

“Fat Shadows” From DXA for the Qualitative Assessment of Lipodystrophy: When a Picture Is Worth a Thousand Numbers

Year: 2018

Type: article

Abstract: OBJECTIVE: Lipodystrophy syndromes are a heterogeneous group of disorders associated with selective absence of fat. Currently, the diagnosis is established only clinically. RESEARCH DESIGN AND METHODS: We developed a new method from DXA scans called a "fat shadow," which is a color-coded representation highlighting only the fat tissue. We conducted a blinded retrospective validation study to assess its usefulness for the diagnosis of lipodystrophy syndromes. RESULTS: We evaluated the fat shadows from 16 patients (11 female and 5 male) with generalized lipodystrophy (GL), 57 (50 female and 7 male) with familial partial lipodystrophy (FPLD), 2 (1 female and 1 male) with acquired partial lipodystrophy, and 126 (90 female and 36 male) control subjects. FPLD was differentiated from control subjects with 85% sensitivity and 96% specificity (95% CIs 72-93 and 91-99, respectively). GL was differentiated from nonobese control subjects with 100% sensitivity and specificity (95% CIs 79-100 and 92-100, respectively). CONCLUSIONS: Fat shadows provided sufficient qualitative information to infer clinical phenotype and differentiate these patients from appropriate control subjects. We propose that this method could be used to support the diagnosis.

Source: Diabetes Care

DOI: 10.2337/dc18-0978