Diffusion tensor imaging in the characterization of multiple system atrophy

Abstract

Purpose: Multiple system atrophy (MSA) is a rare neurodegenerative disease that remains poorly understood, and the diagnosis of MSA continues to be challenging. We endeavored to improve the diagnostic process and understanding of in vivo characteristics of MSA by diffusion tensor imaging (DTI). Materials and methods: Twenty MSA subjects, ten parkinsonian dominant (MSA-P), ten cerebellar dominant (MSA-C), and 20 healthy volunteer subjects were recruited. Fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps were processed using tract-based spatial statistics. Diffusion data were additionally evaluated in the basal ganglia. A support vector machine was used to assess diagnostic utility, leave-one-out cross-validation in the evaluation of classification schemes, and receiver operating characteristic analyses to determine cutoff values. Results: We detected widespread changes in the brain white matter of MSA subjects; however, no group-wise differences were found between MSA-C and MSA-P subgroups. Altered DTI metrics in the putamen and middle cerebellar peduncles were associated with a positive parkinsonian and cerebellar phenotype, respectively. Concerning clinical applicability, we achieved high classification performance on mean diffusivity data in the combined bilateral putamen and middle cerebellar peduncle (accuracy 90.3%±9%, sensitivity 86.5%±11%, and specificity 99.3%±4%). Conclusion: DTI in the middle cerebellar peduncle and putamen may be used in the diagnosis of MSA with a high degree of accuracy.