Microstructural abnormalities in multiple system atrophy as revealed by conventional and rotating frame relaxation MRI parameters
Bibliographic record
Abstract
Rotating frame relaxation (RFR) techniques provide robust and sensitive quantitative MRI (qMRI) metrics able to detect subtle alterations of brain tissue integrity in multiple neurological disorders. We performed a cross-sectional qMRI study in 16 patients with Multiple System Atrophy (MSA) and 14 age- and sex-matched healthy controls. The MRI protocol included the acquisition of RFR metrics, namely adiabatic T1ρ and T2ρ relaxation time constants, along with the acquisition of conventional relaxation metrics, namely R1 and R2*, and a semi-quantitative metric describing magnetization transfer (MT). Between-group comparisons of voxel-based and region-based outcomes were obtained both with and without accounting for the effect of atrophy. Significant brain atrophy was observed in the MSA patients in the white matter and grey matter of the cerebellum, and frontal white matter. On the other hand, group differences of virtually all relaxation metrics were observed for both voxel-wise and ROI analyses in many brain areas. These differences were reduced in spatial extent and/or effect size when the atrophy effect was accounted for. However, T1ρ values remained significantly longer in patients' ROIs encompassing both cerebellar grey matter and white matter, while MT, and R1 values were smaller. Cerebellar gray matter ROIs of patients also exhibited longer T2ρ and smaller R2*. Other voxel-wise group differences were still present after atrophy correction in several clusters, including among others, longer T1ρ in patients' putamen, and longer T1ρ and T2ρ and smaller MT in the patients' pons. Altogether, our findings suggest multiple processes of tissue integrity loss during the course of neurodegeneration that go beyond macrostructural alterations. We conclude that adiabatic T1ρ and T2ρ are valuable MRI metrics that expand the set of multi-parametric qMRI available to characterize the brain of MSA, providing additional and specific information on the brain tissue alterations occurring in this disease.
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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 | 0.001 | 0.002 |
| 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".