P.14.4 Diagnostic role of quantitative NMR imaging exemplified by 3 cases of juvenile dermatomyositis

Abstract

Skeletal muscle diagnostic imaging is classically based on visual inspection of T1-weighted NMR images and interpretation of patterns of fatty infiltration. The existence of oedematous/inflammatory/necrotic lesions is subjectively appreciated on T2-weighted images, typically acquired with the STIR sequence to minimize fat confounding effects. Because it relies on identification of hyperintensities between and within muscles, the interpretation risk with T2-weighted images is to miss global, homogenous increases in T2. In this report, we demonstrate this concern to be more than theoretical. Three patients aged 6, 7 and 12 were referred for further investigation of progressive muscle wasting (P1) or clinical suspicion of dermatomyositis (P2, P3). All of them had normal CK values. Whole-body T1w showed no fatty infiltration in muscles. Standard T2w imaging was normal in P1, showed discrete differences in signal intensity, particularly between anterior and posterior leg compartments in P2 and was moderately positive with hyperintense streaks in P3. Quantitative T2 maps were obtained from multi TE spin echo data after extraction of the water component by tri-exponential fitting. In the 3 patients, muscle water T2s were abnormally elevated in the scapular and pelvic girdles, the thighs and the legs: 45/51 muscles of P1, 46/60 of P2 and 47/51 of P3 had T2s higher than 39 ms, the upper normal value. Mean T2s were 42.3, 42.3 and 45.9 ms, with highest T2s measured at 50.0, 51.9 and 53.3 ms in P1, P2 and P3 respectively. Juvenile dermatomyositis was histologically confirmed in all patients. After 3 months on steroid, P1 was rescanned. In the previously inflamed muscles, T2 had on average decreased by 3.4 ms (p < 0.001) and 17 muscles had resumed normal T2 values. Quantitative T2 mapping can be required to detect unambiguously muscle lesions as shown here in juvenile dermatomyositis. It is also essential to monitor response to treatment in the absence of biological biomarkers. Skeletal muscle diagnostic imaging is classically based on visual inspection of T1-weighted NMR images and interpretation of patterns of fatty infiltration. The existence of oedematous/inflammatory/necrotic lesions is subjectively appreciated on T2-weighted images, typically acquired with the STIR sequence to minimize fat confounding effects. Because it relies on identification of hyperintensities between and within muscles, the interpretation risk with T2-weighted images is to miss global, homogenous increases in T2. In this report, we demonstrate this concern to be more than theoretical. Three patients aged 6, 7 and 12 were referred for further investigation of progressive muscle wasting (P1) or clinical suspicion of dermatomyositis (P2, P3). All of them had normal CK values. Whole-body T1w showed no fatty infiltration in muscles. Standard T2w imaging was normal in P1, showed discrete differences in signal intensity, particularly between anterior and posterior leg compartments in P2 and was moderately positive with hyperintense streaks in P3. Quantitative T2 maps were obtained from multi TE spin echo data after extraction of the water component by tri-exponential fitting. In the 3 patients, muscle water T2s were abnormally elevated in the scapular and pelvic girdles, the thighs and the legs: 45/51 muscles of P1, 46/60 of P2 and 47/51 of P3 had T2s higher than 39 ms, the upper normal value. Mean T2s were 42.3, 42.3 and 45.9 ms, with highest T2s measured at 50.0, 51.9 and 53.3 ms in P1, P2 and P3 respectively. Juvenile dermatomyositis was histologically confirmed in all patients. After 3 months on steroid, P1 was rescanned. In the previously inflamed muscles, T2 had on average decreased by 3.4 ms (p < 0.001) and 17 muscles had resumed normal T2 values. Quantitative T2 mapping can be required to detect unambiguously muscle lesions as shown here in juvenile dermatomyositis. It is also essential to monitor response to treatment in the absence of biological biomarkers.