An Investigation of Corticospinal Tract Microstructural Integrity in ARSACS Using a Profilometry MRI Analysis: Results From the PROSPAX Study
Bibliographic record
Abstract
BACKGROUND: Spasticity represents a core clinical feature of Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS) patients. Nonetheless, its pathophysiological substrate is poorly investigated. We assessed the microstructural integrity of the corticospinal tract (CST) using diffusion MRI (dMRI) via profilometry analysis to understand its possible role in the development of spasticity in ARSACS. MATERIALS AND METHODS: In this multi-center prospective study, data of 37 ARSACS (M/F = 21/16; 33.4 ± 12.4 years) and 29 controls (M/F = 13/16; 42.1 ± 17.2 years) acquired within the PROSPAX consortium were collected from January 2021 to October 2022 and analyzed. Differences in terms of global CST microstructural integrity were probed, as well as a possible spatial distribution of the damage along the tract via profilometry analysis. Possible correlations between clinical severity, including the Spastic Paraplegia Rating Scale (SPRS), were also tested. RESULTS: A significant global involvement of the CST was found in ARSACS compared to controls (all tests with p < 0.001), with a spatially defined pattern of more pronounced microstructural integrity loss occurring right below and above the pons, a structure that was also confirmed to be thickened in these patients (p < 0.001). A bilateral negative correlation emerged between the microstructural integrity of the CST and clinical indices of spasticity expressed via SPRS (p = 0.02 for both CSTs). CONCLUSION: A clinically meaningful microstructural involvement of CST is present in ARSACS patients, with a spatially defined pattern of damage occurring right below and above a thickened pons. An evaluation of the microstructure of this bundle might serve as a possible biomarker in this condition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".