Cerebral Atrophy in Amyotrophic Lateral Sclerosis Parallels the Pathological Distribution of TDP43
Bibliographic record
Abstract
Abstract Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by a preferential involvement of both upper and lower motor neurons. Evidence from neuroimaging and post-mortem studies confirms additional involvement of brain regions extending beyond the motor cortex. The aim of this study was to assess the extent of cerebral disease in ALS cross-sectionally and longitudinally, and to compare the findings with a recently proposed disease-staging model of ALS pathology. Deformation-based morphometry (DBM) was used to identify the patterns of brain atrophy associated with ALS and to assess their relationship with clinical symptoms. Longitudinal T1-weighted MRI data and clinical measures were acquired at baseline, 4 months, and 8 months, from 66 ALS patients and 43 age-matched controls who participated in the Canadian ALS Neuroimaging Consortium (CALSNIC) study. Whole brain voxel-wise mixed-effects modelling analysis showed extensive atrophy patterns differentiating ALS patients from the normal controls. Cerebral atrophy was present in the motor cortex and corticospinal tract, involving both GM and WM, and to a lesser extent in non-motor regions. More specifically, the results showed significant bilateral atrophy in the motor cortex, the corticospinal tract including the internal capsule and brainstem, with an overall pattern of ventricular enlargement; along with significant progressive longitudinal atrophy in the precentral gyrus, frontal and parietal white matter, accompanied by ventricular and sulcal enlargement. Atrophy in the precentral gyrus was significantly associated with greater disability as quantified with the ALS Functional Rating Scale-Revised (ALSFRS-R) (p<0.0001). The pattern of atrophy observed using DBM was consistent with the Brettschneider’s four stage pathological model of the disease. Deformation based morphometry provides a sensitive indicator of atrophy in ALS, and has potential as a biomarker of disease burden, in both gray and white matter.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".