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Record W2765761054 · doi:10.3174/ajnr.a5410

Spatial Correlation of Pathology and Perfusion Changes within the Cortex and White Matter in Multiple Sclerosis

2017· article· en· W2765761054 on OpenAlexafffund
Alannah Mulholland, Rita Vitorino, Seyed‐Parsa Hojjat, Aidong Ma, Liying Zhang, L. Lee, Timothy Carroll, Charles G. Cantrell, Chase R. Figley, Richard I. Aviv

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2017
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook HospitalUniversity of ManitobaSunnybrook Health Science Centre
FundersNational Institutes of HealthCanadian Institutes of Health ResearchBiogenNational Institute of Biomedical Imaging and BioengineeringAmerican Heart Association
KeywordsMedicineMultiple sclerosisWhite matterPerfusionPathologyGrey matterExpanded Disability Status ScaleMagnetic resonance imagingBrain sizeCortex (anatomy)Nuclear medicineCardiologyRadiologyNeurosciencePsychology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The spatial correlation between WM and cortical GM disease in multiple sclerosis is controversial and has not been previously assessed with perfusion MR imaging. We sought to determine the nature of association between lobar WM, cortical GM, volume and perfusion. MATERIALS AND METHODS: Nineteen individuals with secondary-progressive multiple sclerosis, 19 with relapsing-remitting multiple sclerosis, and 19 age-matched healthy controls were recruited. Quantitative MR perfusion imaging was used to derive CBF, CBV, and MTT within cortical GM, WM, and T2-hyperintense lesions. A 2-step multivariate linear regression (corrected for age, disease duration, and Expanded Disability Status Scale) was used to assess correlations between perfusion and volume measures in global and lobar normal-appearing WM, cortical GM, and T2-hyperintense lesions. The Bonferroni adjustment was applied as appropriate. RESULTS: Global cortical GM and WM volume was significantly reduced for each group comparison, except cortical GM volume of those with relapsing-remitting multiple sclerosis versus controls. Global and lobar cortical GM CBF and CBV were reduced in secondary-progressive multiple sclerosis compared with other groups but not for relapsing-remitting multiple sclerosis versus controls. Global and lobar WM CBF and CBV were not significantly different across groups. The distribution of lobar cortical GM and WM volume reduction was disparate, except for the occipital lobes in patients with secondary-progressive multiple sclerosis versus those with relapsing-remitting multiple sclerosis. Moderate associations were identified between lobar cortical GM and lobar normal-appearing WM volume in controls and in the left temporal lobe in relapsing-remitting multiple sclerosis. No significant associations occurred between cortical GM and WM perfusion or volume. Strong correlations were observed between cortical-GM perfusion, normal appearing WM and lesional perfusion, with respect to each global and lobar region within HC, and RRMS and SPMS patients (R2 ≤ 0.96, P < .006 and R2 ≤ 0.738, P < .006). CONCLUSIONS: The weak correlation between lobar WM and cortical GM volume loss and perfusion reduction suggests the independent pathophysiology of WM and cortical GM disease.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.049
GPT teacher head0.293
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2017
Admission routes2
Has abstractyes

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