MétaCan
Menu
Back to cohort
Record W2783237032 · doi:10.1212/nxi.0000000000000436

Quantitative spinal cord MRI in radiologically isolated syndrome

2018· article· en· W2783237032 on OpenAlexafffund
Paula Alcaide‐Leon, Kateryna Cybulsky, Stephanie Sankar, Courtney Casserly, General Leung, Marika Hohol, Daniel Selchen, Xavier Montalbán, Aditya Bharatha, Jiwon Oh

Bibliographic record

VenueNeurology Neuroimmunology & Neuroinflammation · 2018
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersMultiple Sclerosis SocietyMultiple Sclerosis Society of CanadaOryzon GenomicsTeva Pharmaceutical IndustriesBiogenSanofiEMD SeronoNational Multiple Sclerosis Society
KeywordsMedicineFractional anisotropyDiffusion MRISpinal cordMagnetic resonance imagingWhite matterAtrophyMagnetization transferNuclear medicineRadiologyInternal medicine

Abstract

fetched live from OpenAlex

<h3>Objectives</h3> To assess whether quantitative spinal cord MRI (SC-MRI) measures, including atrophy, and diffusion tensor imaging (DTI) and magnetization transfer imaging metrics were different in radiologically isolated syndrome (RIS) vs healthy controls (HCs). <h3>Methods</h3> Twenty-four participants with RIS and 14 HCs underwent cervical SC-MRI on a 3T magnet. Manually segmented regions of interest circumscribing the spinal cord cross-sectional area (SC-CSA) between C3 and C4 were used to extract SC-CSA, fractional anisotropy, mean, perpendicular, and parallel diffusivity (MD, λ<sub>⊥</sub>, and λ<sub>||</sub>) and magnetization transfer ratio (MTR). Spinal cord (SC) lesions, SC gray matter (GM), and SC white matter (WM) areas were also manually segmented. Multivariable linear regression was performed to evaluate differences in SC-MRI measures in RIS vs HCs, while controlling for age and sex. <h3>Results</h3> In this cross-sectional study of participants with RIS, 71% had lesions in the cervical SC. Of quantitative SC-MRI metrics, spinal cord MTR showed a trend toward being lower in RIS vs HCs (<i>p</i> = 0.06), and there was already evidence of brain atrophy (<i>p</i> = 0.05). There were no significant differences in SC-DTI metrics, GM, WM, or CSA between RIS and HCs. <h3>Conclusion</h3> The SC demonstrates minimal microstructural changes suggestive of demyelination and inflammation in RIS. These findings are in contrast to established MS and raise the possibility that the SC may play an important role in triggering clinical symptomatology in MS. Prospective follow-up of this cohort will provide additional insights into the role the SC plays in the complex sequence of events related to MS disease initiation and progression.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.051
GPT teacher head0.340
Teacher spread0.289 · 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 teacher head, not a consensus.

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

Citations48
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueNeurology Neuroimmunology & NeuroinflammationSame topicMultiple Sclerosis Research StudiesFrench-language works237,207