MétaCan
Menu
Back to cohort
Record W2885904423 · doi:10.3389/fneur.2018.00575

Pathological Insights From Quantitative Susceptibility Mapping and Diffusion Tensor Imaging in Ice Hockey Players Pre and Post-concussion

2018· article· en· W2885904423 on OpenAlexafffund
Alexander Mark Weber, Anna Pukropski, Christian Kames, Michael Jarrett, Shiroy B. Dadachanji, Jack Taunton, David K.B. Li, Alexander Rauscher

Bibliographic record

VenueFrontiers in Neurology · 2018
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
FundersMultiple Sclerosis SocietyMultiple Sclerosis Society of CanadaVertex PharmaceuticalsCanadian Institutes of Health ResearchTeva Pharmaceutical IndustriesBiogenCelgeneSanofi
KeywordsMyelinDiffusion MRIWhite matterFractional anisotropyConcussionVoxelChemistryBiophysicsNeuroscienceMagnetic resonance imagingMedicinePsychologyBiologyRadiologyPoison controlCentral nervous system

Abstract

fetched live from OpenAlex

Myelin sensitive MRI techniques, such as diffusion tensor imaging and myelin water imaging, have previously been used to reveal changes in myelin after sports-related concussions. What is not clear from these studies, however, is how myelin is affected: whether it becomes degraded and possibly removed, or whether the myelin sheath loosens and becomes "decompacted". Previously, our team revealed myelin specific changes in ice hockey players 2 weeks post-concussion using myelin water imaging. In that study, 45 subjects underwent a pre-season baseline scan, 11 of which sustained a concussion during play and received follow-up scans: eight were scanned within 3 days, 10 were scanned at 14 days, and nine were scanned at 60 days. In the current retrospective analysis, we used quantitative susceptibility mapping, along with the diffusion tensor imaging measures axial diffusivity and radial diffusivity, to investigate this myelin disruption. If sports-related concussive hits lead to myelin fragmentation in regions of lowered MWF, this should result in a measurable increase in magnetic susceptibility, due to the anisotropic myelin fragmenting into isotropic myelin debris, and the diamagnetic myelin tissue being removed, while no such changes should be expected if the myelin sheath simply loosens and becomes decompacted. An increase in radial diffusivity would likewise reveal myelin fragmentation, as myelin sheaths block water diffusion out of the axon, with little to no changes expected for myelin sheath loosening. Statistical analysis of the same voxels-of-interest that were found to have reduced myelin water fraction 2 weeks post-concussion, revealed no statistically significant changes in magnetic susceptibility, axial diffusivity, or radial diffusivity at any time-point post-concussion. This suggests that myelin water fraction changes are likely due to a loosening of the myelin sheath structure, as opposed to fragmentation and removal of myelin debris.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.058
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.309
Teacher spread0.282 · 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.

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

Citations24
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in NeurologySame topicAdvanced Neuroimaging Techniques and ApplicationsFrench-language works237,207