MétaCan
Menu
← Back to cohort
Record W2262750511 · doi:10.1161/str.43.suppl_1.a4033

Abstract 4033: Structural Integrity of the Corticospinal Tract Correlated with the Degree of Hand Recovery in Pediatric Patients Following Stroke

2012· article· en· W2262750511 on OpenAlexaff
Trish Domi, David J. Mikulis, Mary Pat McAndrews, Gabrielle deVeber

Bibliographic record

VenueStroke · 2012
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsCerebral peduncleCorticospinal tractDiffusion MRIMedicineFractional anisotropyTractographyStroke (engine)Pyramidal tractsRegion of interestPediatric strokeNuclear medicineInternal capsuleIschemic strokeMagnetic resonance imagingRadiologyAnatomyWhite matterCardiologyIschemia

Abstract

fetched live from OpenAlex

Introduction: The objective was to investigate association of the corticospinal tract (CST) and the association with neurological outcome using Diffusion Tensor Imaging (DTI) to measure the structural integrity of the CST at the level of the cerebral peduncles and the descending CST (DCST) using a tractography based approach (Diffusion Tensor Tractography - DTT) in children with a range of recovery in hand function following arterial ischemic stroke. Methods: Structural integrity of the CST supplying the hand (DTI) and neurological outcome was evaluated in 11 patients and 8 controls. DTI: sequences were performed with 2 dimensional DW EPI, 25 directions, 1000 0b value, TR 8300 msec, TE ∼ 79msc, scan time: 5 minutes. CST integrity at the level of the peduncles was measured by drawing a region-of-interest (ROI) on the anterior cerebral peduncles (Kirton, 2007) and calculating Fractional Anisotropy ([FA], range 0=isotropic, 1=anisotropic) (FSL v4.1). Tract-based spatial statistics (TBSS) were used for CST reconstruction by drawing an ROI on single axial T1-weighted image in which the hand knob region was most noticeable as the initial seed point, and the second ROI on the single axial T1 weighted image in which the cerebral peduncle was most prominent. T-tests with Welch correction (for unequal variance) were used to compare the difference in the mean FA values of the ROIs between peduncles and the DCST in normal controls, and the stroke and non-stroke affected peduncles in patients. The correlation of the mean FA of the DCST and neurological outcome assessed with the sensori-motor subscale of the Pediatric Stroke Outcome Measure. Results: Patients and controls did not differ in age at acquisition (mean=9.61 vs 12.29). DTI: The mean FA values of the peduncles between patients and controls were found to differ between hemispheres (p= .006). The mean FA of the stroke affected (ipsilesional) (mean=.3912) peduncles were significantly lower than the non-affected peduncle (contralesional) (mean =.4336, p=.001). DTT: The tract based analyses also showed FA values (mean=.3197) in the stroke affected DCST were significantly lower than the unaffected (contralesional) DCST (mean=.4441). Correlation analysis a revealed a significant negative correlation between motor outcome and mean FA of the stroke affected DCST (P < 0.05) and the unaffected DCST (P < 0.05). Conclusions: Integrity of the fibers in the DCST shows an association with motor outcome of the hand in pediatric stroke patients. Greater damage to the DCST was associated with a greater motor deficit. The results of this study suggest that the level of motor skill recovery achieved in pediatric stroke patients relates to microstructural status of the DCST.

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 score0.004
Threshold uncertainty score0.012

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)0.0040.000

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 head0.050
GPT teacher head0.308
Teacher spread0.258 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueStroke→Same topicAdvanced Neuroimaging Techniques and Applications→French-language works237,207→