Adiposis dolorosa (Dercum's disease): MRI and ultrasound appearances

To describe ultrasound and magnetic resonance imaging (MRI) features of adiposis dolorosa, Dercum's disease, and to evaluate the MRI features prospectively against a large number of MRI examinations.

Institutional review board approval for this study was obtained. The imaging features at MRI and ultrasound of 13 cases of adiposis dolorosa (nine female, four male; age range 32-72 years) were reviewed. MRI findings typical for adiposis dolorosa were proposed and prospectively evaluated on 6247 MRI examinations performed over a period of 8 months.

Adiposis dolorosa demonstrates multiple, oblong, fatty lesions in the superficial subcutaneous fatty tissue. They are mostly <2 cm in long axis diameter. They demonstrate nodular ("blush-like") increased fluid signal at unenhanced MRI and are markedly hyperechoic at ultrasound. There is no contrast medium enhancement at MRI and no increased Doppler signal at ultrasound. Most lesions were clinically asymptomatic, some were painful/tender. There was no imaging evidence of oedema or inflammation. During prospective validation of these MRI features on 6247 MRI examinations, two cases with typical imaging features were encountered; both were diagnosed as adiposis dolorosa on clinical review. All cases of adiposis dolorosa showed these imaging findings. This results in a very low likelihood that a nodular, blush-like appearance of subcutaneous fat on MRI is not due to adiposis dolorosa.

Adiposis dolorosa, Dercum's disease, should be suggested in the presence of multiple (many) small, oblong, fatty lesions in the subcutaneous fatty tissue in adult patients if they are hyperechoic on ultrasound imaging or blush-like at unenhanced MRI; typically a small number of these lesions are tender/painful. Imaging does not demonstrate inflammation or oedema in relation to these lesions. These MRI features should suggest the diagnosis and are likely to be pathognomonic. The radiologist is often the first to suggest the diagnosis based on the imaging features.