Evaluation of muscle diseases using artificial neural network analysis of ³¹P MR spectroscopy data

Dermatomyositis is an autoimmune disease characterized by an erythematous rash and severe muscle weakness. ³¹P Magnetic resonance spectroscopy (MRS) provides quantitative data for longitudinal monitoring of disease status and responses to immunosuppressive therapy. A disease variant, amyopathic dermatomyositis, presents with a typical rash but no clinical muscle weakness. However, metabolic abnormalities in the oxidative capacity of muscles of amyopathic patients during exercise were detected with ³¹P MRS. Because MRS provided the best quantitative data for evaluating dermatomyositis, the ³¹P metabolic parameters derived from the MR spectra were further processed using an artificial neural network (XERION). The neural network analyses provided additional clinical information from the weighted correlations of multiple ³¹P parameters, namely, inorganic phosphate, phos‐phocreatine, ATP, phosphodiesters, and selected ratios. This investigation analyzes the relative importance of the various metabolic parameters for accurate patient characterization and provides insights into the pathogenesis of the disease.