Imaging Patterns Characterizing Mitochondrial Leukodystrophies

Background and purpose: Achieving a specific diagnosis in leukodystrophies is often difficult due to clinical and genetic heterogeneity. Mitochondrial defects cause 5%-10% of leukodystrophies. Our objective was to define MR imaging features commonly shared by mitochondrial leukodystrophies and to distinguish MR imaging patterns related to specific genetic defects.

Materials and methods: One hundred thirty-two patients with a mitochondrial leukodystrophy with known genetic defects were identified in the data base of the Amsterdam Leukodystrophy Center. Numerous anatomic structures were systematically assessed on brain MR imaging. Additionally, lesion characteristics were scored. Statistical group analysis was performed for 57 MR imaging features by hierarchic testing on clustered genetic subgroups.

Results: MR imaging features indicative of mitochondrial disease that were frequently found included white matter rarefaction (n = 50 patients), well-delineated cysts (n = 20 patients), T2 hyperintensity of the middle blade of the corpus callosum (n = 85 patients), and symmetric abnormalities in deep gray matter structures (n = 42 patients). Several disorders or clusters of disorders had characteristic features. The combination of T2 hyperintensity in the brain stem, middle cerebellar peduncles, and thalami was associated with complex 2 deficiency. Predominantly periventricular localization of T2 hyperintensities and cystic lesions with a distinct border was associated with defects in complexes 3 and 4. T2-hyperintense signal of the cerebellar cortex was specifically associated with variants in the gene NUBPL. T2 hyperintensities predominantly affecting the directly subcortical cerebral white matter, globus pallidus, and substantia nigra were associated with Kearns-Sayre syndrome.

Conclusions: In a large group of patients with a mitochondrial leukodystrophy, general MR imaging features suggestive of mitochondrial disease were found. Additionally, we identified several MR imaging patterns correlating with specific genotypes. Recognition of these patterns facilitates the diagnosis in future patients.