Brain Magnetic Resonance Imaging (MRI) in Spinal Muscular Atrophy: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: 5q Spinal Muscular Atrophy (SMA) is a prototypical lower motor neuron disorder. However, the characteristic early motor impairment raises the question on the scope of brain involvement with implications for further investigations on the brain as a potential therapeutic target. OBJECTIVE: To review changes across the SMA clinical spectrum reported on brain magnetic resonance imaging (MRI). METHODS: We conducted a scoping review of existing literature on PubMed and EMBASE. Two reviewers searched and retrieved relevant articles on magnetic resonance brain imaging in individuals with SMA censoring to April 2022. Full-text articles published in peer-reviewed journals or abstracts accepted to conferences in English and French were included. RESULTS: Twelve articles were identified describing a total of 39 patients [age range: 11 days to 41 years old, type 0 (n = 5), type 1 (n = 4), type 2 (n = 2), type 3 (n = 22), type 4 (n = 6)]. All reported structural changes and did not explore other MRI modalities. In individuals with infantile onset SMA, cortical and subcortical brain abnormalities in white matter, basal ganglia, thalamus, hippocampus, and high intensity areas around lateral ventricles and thalami were reported over time. In individuals with later-onset SMA, reduced cerebellar and lobular volume were observed as well as increased grey matter density in motor areas. CONCLUSIONS: Limited data on brain imaging in SMA highlights both cortical and subcortical involvement in SMA, supporting the hypothesis that changes are not restricted to lower motor neuron pathways. Further studies are needed to determine the extent and prevalence of structural and functional brain changes across SMA types.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".