Medulla oblongata volume as a promising predictor of survival in amyotrophic lateral sclerosis

Brainstem–cortex disconnection in amyotrophic lateral sclerosis: bulbar impairment, genotype associations, asymptomatic changes and biomarker opportunities

“…Similar to the versatility of structural data, DWI/DTI data can be meaningfully interrogated by tractography, tract-based statistical approaches or in connectomic models [ 42 – 44 ]. Our data indicate that contrary to previous reports [ 45 ], vertex analyses have relatively little to offer at a brainstem level; brainstem outline alterations merely reflect overall shape deformations and may not meaningfully capture focal pathology in relevant structures such as cranial nerve nuclei or descending corticospinal tract degeneration. Similarly, the assessment of medullary volumes revealed no disease-associated or genotype-specific signatures either cross-sectionally or longitudinally.…”

Clinical Profiles and Patterns of Neurodegeneration in Amyotrophic Lateral Sclerosis: A Cluster-Based Approach Based on MR Imaging Metrics

“…In the present study, we performed a data-driven analysis to identify the radiologic clustering of newly diagnosed patients with ALS, in relation to 3 well-known neuroanatomic loci involved in ALS disease, namely the PreCT 22 and ParaCT 22 and the medulla oblongata. 20 Our data suggested that already at the time of diagnosis, patients with ALS showed specific patterns of neurodegeneration, with a prevalent impairment of the motor and extramotor cortex, cluster 3; MOv, cluster 2; or all 3 MR imaging measures, cluster 1. This latter group of patients was characterized by older age, higher female prevalence, greater disease severity expressed by lower ALSFRS-r scores, a higher progression rate, and lower median survival.…”

“…13 Specifically, disease severity (expressed as ALS Functional Rating Scale-Revised [ALSFRS-r] score) and progression rate correlated with the mean cortical thickness of the motor area, [14][15][16][17][18] extramotor areas (eg, paracentral lobules), 17,19 and medulla oblongata volume (MOv). [19][20][21] These MR imaging metrics have also been proposed as predictive biomarkers of survival. 20,22 Nonetheless, most imaging studies validated MR imaging metrics by describing phenotype-, genotype-, or stage-associated radiologic profiles [23][24][25] in a priori selected clinical categorizations (eg, spinal or bulbar onset, fast and slow progressors, prevalent upper or lower motor neuron impairment).…”

“…[19][20][21] These MR imaging metrics have also been proposed as predictive biomarkers of survival. 20,22 Nonetheless, most imaging studies validated MR imaging metrics by describing phenotype-, genotype-, or stage-associated radiologic profiles [23][24][25] in a priori selected clinical categorizations (eg, spinal or bulbar onset, fast and slow progressors, prevalent upper or lower motor neuron impairment). An alternative interesting approach was recently performed by Bede et al, 26 which used cluster analysis of pooled imaging data and subsequent analysis of cluster-associated clinical characteristics.…”

“…Different from these latter studies, we restricted our clusterbased analysis to MR imaging metrics identified as core features of disease severity and survival in ALS by previous reports, namely cortical thickness of the precentral gyrus (PreCT) 22 and paracentral gyrus (ParaCT) 22 and MOv. 20 Thus, we aimed to identify the clinical and prognostic features of the different radiologic clusters.…”