Diffusion tensor imaging and quantitative susceptibility mapping as diagnostic tools for motor neuron disorders Academic Article uri icon

Overview

MeSH Major

  • Bile Duct Diseases
  • Liver Abscess, Amebic
  • Sepsis

abstract

  • © 2018 Purpose: Diffusion tensor imaging (DTI) and quantitative susceptibility mapping (QSM) have been proposed as methods to aid in the diagnosis of amyotrophic lateral sclerosis (ALS) and primary lateral sclerosis (PLS), both diseases affecting upper motor neurons. We test the performance of DTI and QSM alone and in combination to distinguish patients with diseases affecting upper motor neurons (ALS/PLS) from patients with other motor symptom-predominant neurologic disorders. Methods: 3.0 Tesla MRI with DTI and QSM in patients referred to a subspecialty neurology clinic for evaluation of motor symptom-predominant neurologic disorders were retrospectively reviewed. Corticospinal tract fractional anisotropy and maximum motor cortex susceptibility were measured. Subjects were categorized by diagnosis and imaging metrics were compared between groups using Student's t-tests. Receiver operating characteristic curves were generated for imaging metrics alone and in combination. Results: MRI scans for 43 patients with ALS or PLS and 15 patients with motor symptom predominant, non-upper motor neuron disease (mimics) were reviewed. Fractional anisotropy was lower (0.57 vs. 0.60, p < 0.01) and maximum motor cortex magnetic susceptibility higher (64.4 vs. 52.7, p = 0.01) in patients with ALS/PLS compared to mimics. There was no significant difference in area under the curve for these metrics alone (0.73, 0.63; p > 0.05) or in combination (0.75; p > 0.05). Conclusion: We found significant differences in DTI and QSM metrics in patients with diseases affecting upper motor neurons (ALS/PLS) compared to mimics, but no significant difference in the performance of these metrics in diagnosing ALS/PLS compared to mimics.

publication date

  • January 2019

Research

keywords

  • Academic Article

Identity

Digital Object Identifier (DOI)

  • 10.1016/j.clinimag.2018.09.015

Additional Document Info

start page

  • 6

end page

  • 11

volume

  • 53