The Utility of White Matter Hyperintensities as A Prognostic Biomarker in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Abstract Background While sclerosis of the corticospinal and corticobulbar white matter tracts is a key pathological feature of Amyotrophic Lateral Sclerosis (ALS) and previous work in the context of other neurodegenerative diseases has established the link between white matter hyperintensities (WMHs) as magnetic resonance imaging (MRI) markers of white matter damage and disease progression, WMHs remain unexplored in ALS. The present work investigates the relationship between presence and progression of WMHs and disease severity and survival in ALS patients. Method We included longitudinal MRI and clinical data of 232 ALS patients and 207 matched controls from the Canadian ALS Neuroimaging Consortium (CALSNIC) (Kalra et al. 2019). T1‐weighted and FLAIR MRIs were used to perform WMH segmentation using BISON pipeline (Figure 1) (Dadar et al. 2021). Patients with survival data ( N = 110) were categorized as “short” ( N = 45) or “long” ( N = 65) survivors based on their time‐to‐outcome from the baseline MRI with a 24‐month cut‐off threshold. Linear mixed effect modeling was employed to investigate the differences in WMH burden and longitudinal progression between the ALS patients as well as survival groups and matched controls, and to assess the relationship between WMH progression and disease severity as measured by ALSFRS‐R. Age and sex were considered as covariates and participant IDs as random effects. Result Compared to healthy controls, ALS patients had significantly greater longitudinal WMH progression (911.5 mm3/year, p < 0.0001) (Figure 2A). Furthermore, patients in the short survival group experienced greater WMH progression than those in the long survival group (1006 mm3/year, p < 0.0001) (Figure 2B). Finally, for every 500 mm3 increase in WMH volume, the ALSFRS‐R scores decreased by a full point ( p < 0.001) (Figure 3A). While both survival groups experienced increased disease severity with increased WMH volume ( p < 0.001), their rates of change did not significantly differ (Figure 3B). Conclusion This study has shown, for the first time, that ALS patients present with greater WMH progression, and that WMH progression is linked to disease severity and survival in patients, highlighting the utility of WMH as a biomarker of disease progression and prognosis in ALS.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".