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Record W3026088322 · doi:10.1161/str.51.suppl_1.tmp109

Abstract TMP109: Cortico-Ponto-Cerebellar Structural Connectivity in Perinatal Stroke

2020· article· en· W3026088322 on OpenAlexaff
Brandon T. Craig, Alicia Hilderley, Helen L. Carlson, Adam Kirton

Bibliographic record

VenueStroke · 2020
Typearticle
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineDiffusion MRIFractional anisotropyInternal capsuleTractographyStroke (engine)PopulationCerebral palsyPyramidal tractsWhite matterPhysical medicine and rehabilitationMagnetic resonance imagingAnatomyRadiology

Abstract

fetched live from OpenAlex

Introduction: Perinatal stroke (PS) causes hemiparetic cerebral palsy and lifelong disability. As an early cerebrovascular injury, typically involving injury to motor systems, PS represents an ideal model for understanding motor system development. Emerging models demonstrate widespread network alterations but the role of the cerebellum is poorly defined. We used diffusion tractography to explore the development of the cortico-ponto-cerebellar (CPC) tract in children with PS, hypothesizing an association between non-dominant CPC diffusion metrics and motor ability. Methods: Retrospective, population-based, cross-sectional, controlled study. Participants aged 6-19 years with unilateral MRI confirmed perinatal arterial ischemic stroke (AIS; n=11) or periventricular venous infarction (PVI; n=20), and typically developing controls (TDC; n=31) had a 3T MRI including T1-weighted and diffusion imaging (32 directions; b=750s/mm 2 , 3 b0 volumes). Probabilistic tensor-based tractography was performed using the posterior limb of the internal capsule and contralateral middle cerebellar peduncle as regions of interest for seeding. Tensor-based outcomes were calculated including mean diffusivity (MD) and fractional anisotropy (FA). An asymmetry index (AI) was subsequently calculated (dominant / non-dominant values). PS participants completed motor assessments [Assisting Hand Assessment (AHA), Melbourne Assessment (MA), Box and Blocks Test (BBT)]. Results: Paired-samples t-tests revealed MD was significantly higher for non-dominant versus dominant tracts across all groups (all p<0.001), while FA did not differ (all p>0.05). MD AI differed among groups (F(2,59)=10.117, p <0.001) such that MD AI was significantly lower (less symmetrical) in AIS (AI=0.912±0.04) compared to PVI (AI=0.960±0.05, p =0.01) and TDC (AI=0.977±0.03, p <0.001). FA AI did not differ between groups (F(2,59)=1.045, p =0.358). A positive association was observed between MD AI and BBT performance in the affected hand (r=0.439, p =0.019). Conclusion: CPC tractography in children with PS is feasible. Development of the CPC appears to be altered following perinatal stroke, the degree of which may relate to motor function.

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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.258
Teacher spread0.238 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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