Rasimcan Meral1, Benjamin J Ryan2, Noemi Malandrino3, Abdelwahab Jalal1, Adam H Neidert1, Ranganath Muniyappa3,4, Barış Akıncı5, Jeffrey F Horowitz2, Rebecca J Brown3, Elif A Oral6. 1. Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI. 2. Substrate Metabolism Laboratory, School of Kinesiology, University of Michigan, Ann Arbor, MI. 3. Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD. 4. Inter-Institute Endocrinology Training Program, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD. 5. Division of Endocrinology, Dokuz Eylül University, Izmir, Turkey. 6. Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI eliforal@med.umich.edu.
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.
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.
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