MR Imaging-based Estimation of Upper Motor Neuron Density in Patients with Amyotrophic Lateral Sclerosis: A Feasibility Study

Jacqueline Chen, Volodymyr Kostenko, Erik P. Pioro, Bruce D. Trapp

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Purpose To determine if magnetic resonance (MR) imaging metrics can estimate primary motor cortex (PMC) motor neuron (MN) density in patients with amyotrophic lateral sclerosis (ALS). Materials and Methods Between 2012 and 2014, in situ brain MR imaging was performed in 11 patients with ALS (age range, 35-81 years; seven women and four men) soon after death (mean, 5.5 hours after death; range, 3.2-9.6 hours). The brain was removed, right PMC (RPMC) was excised, and MN density was quantified. RPMC metrics (thickness, volume, and magnetization transfer ratio) were calculated from MR images. Regression modeling was used to estimate MN density by using RPMC and global MR imaging metrics (brain and tissue volumes); clinical variables were subsequently evaluated as additional estimators. Models were tested at in vivo MR imaging by using the same imaging protocol (six patients with ALS; age range, 54-66 years; three women and three men). Results RPMC mean MN density varied over a greater than threefold range across patients and was estimated by a linear function of normalized gray matter volume (adjusted R2 = 0.51; P = .008; <10% error in most patients). When considering only sporadic ALS, a linear function of normalized RPMC and white matter volumes estimated MN density (adjusted R2 = 0.98; P = .01; <10% error in all patients). In vivo data analyses detected decreases in MN density over time. Conclusion PMC mean MN density varies widely in end-stage ALS possibly because of disease heterogeneity. MN density can potentially be estimated by MR imaging metrics.

Original languageEnglish (US)
Pages (from-to)955-964
Number of pages10
JournalRadiology
Volume287
Issue number3
DOIs
StatePublished - Jun 1 2018
Externally publishedYes

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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