MRI measures of brain injury in children with Multiple Sclerosis
Bibliographic record
Abstract
Multiple sclerosis (MS) is thought to be an autoimmune disease that affects the central nervous system of young adults. Although an uncommon disease in children, recent research has examined the effect of this disease upon a younger demographic group. This patient population has attracted the attention of MS researchers, as it promises a better understanding of the pathophysiology of MS at its earliest stage. Magnetic resonance imaging (MRI), a sensitive tool for detecting white matter (WM) pathology, has improved the diagnosis and appreciation of the pathogenesis of MS in adults. However, little is known about its use in children. Therefore, the main objective of this thesis is to contribute and to increase knowledge in this important new area. For this purpose, specific image processing methodologies were developed, and pathology on MRI was compared between patients with adult- and pediatric-onset MS. Comparing the spatial distribution, frequency, and volume of lesions on T2-weighted (T2w) MR images among patients with pediatric- and adult-onset MS, who had similar disease duration, showed a similar total T2w lesions between the two groups. However, children exhibited a higher T2w lesion volume and frequency in the infratentorial region, particularly in the pontine region. Persistent T1-weighted (T1w) lesions, a marker of permanent tissue damage and axonal loss, were assessed to determine whether MS lesions in children are as destructive as those in adults. To obtain a fair comparison using the scans available, normalization of intensity was essential. We showed the limitations of the currently available techniques for intensity normalization, and the need for a WM independent methodology. We proposed and developed a novel WM-independent intensity normalization method for T1w images and assessed inter-scanner, between-scanner and within subject variation before and after normalization. We also calculated the sample size required for detecting recovery of T1w intensity using our methodology and the most commonly used intensity normalization method. Then we used our methodology to assess recovery of normalized T1w intensity within new lesions in children with relapsing remitting MS (RRMS) compared to adults. We found that MS lesions recover better in children, suggesting a greater reparative capacity in younger patients. We also used our intensity normalization method to perform a quantitative comparison of T1w intensity recovery in new lesions between children with MS and children with monophasic inflammatory demyelinating syndromes (monoADS). We found that new MS lesions recover more poorly than of those in children with monoADS. This may suggest that new MS lesions are more destructive than new lesions in monophasic inflammatory demyelinating diseases.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".