Peripheral neuropathy: detection with diffusion-tensor imaging

Abstract

Purpose: To investigate the ability of diffusion-tensor imaging (DTI) and T2 to help detect the mildest nerve lesion conceivable, that is, subclinical ulnar neuropathy at the elbow.

Materials and methods: This prospective study was approved by the institutional ethics board. Written informed consent was obtained from all participants. Magnetic resonance neurography was performed at 3.0 T by using proton density- and T2-weighted relaxometry and DTI on elbows in 30 healthy subjects without clinical evidence of neuropathy. Quantitative analysis of ulnar nerve T2 and fractional anisotropy (FA) was performed, and T2 and FA values were correlated to electrical nerve conduction velocities (NCVs) with Pearson correlation analysis. Additional qualitative assessment of T2-weighted and FA images was performed by two readers, and sensitivity and specificity were calculated.

Results: Ten of the 30 subjects (33%) had NCV slowing across the elbow segment. Compared with subjects without NCV slowing, subjects with slowing had decreased FA values (0.51 ± 0.09 vs 0.41 ± 0.07, respectively; P = .006) and increased T2 values (64.2 msec ± 10.9 vs 76.2 msec ± 13.7, respectively; P = .01) in the proximal ulnar sulcus. FA values showed a significant correlation (P = .01) with NCV slowing over the sulcus as an electrophysiologic indicator of myelin sheath damage. Qualitative assessment of FA maps and T2-weighted images helped identify subjects with conduction slowing with a sensitivity of 80% and 55%, respectively, and a specificity of 83% and 63%.

Conclusion: FA maps can accurately depict even mild peripheral neuropathy and perform better than the current standard of reference, T2-weighted images. DTI may therefore add diagnostic value as a highly sensitive technique for the detection of peripheral neuropathy.