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Record W4210244170 · doi:10.1002/alz.056596

Disintegration of anterior thalamic radiation fibers in cerebrovascular disease subjects with periventricular white matter hyperintensities leads to lower executive function performance

2021· article· en· W4210244170 on OpenAlexaffabout
Seyyed Mohammad Hassan Haddad, Christopher J.M. Scott, Miracle Ozzoude, Melissa F. Holmes, Stephen R. Arnott, Nuwan D. Nanayakkara, Donna Kwan, Brian Tan, Leanne K. Casaubon, Jennifer Mandzia, Demetrios J. Sahlas, Gustavo Saposnik, Ayman Hassan, Sandra E. Black, Dar Dowlatshahi, Stephen C. Strother, Richard H. Swartz, Sean Symons, Manuel Montero‐Odasso, Robert Bartha

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsHealth Sciences CentreThunder Bay Regional Health Sciences CentreMcMaster UniversityQueen's UniversityUniversity of TorontoUniversity of OttawaBaycrest HospitalRobarts Clinical TrialsSunnybrook Health Science CentreWestern University
Fundersnot available
KeywordsHyperintensityWhite matterDiffusion MRIFractional anisotropyCardiologyMedicineInternal medicineCognitive declineCognitionPsychologyMagnetic resonance imagingDiseaseRadiologyDementiaPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background White matter hyperintensities (WMH) are more prevalent in elder adults and those typically located in periventricular areas are known as periventricular WMHs (pWMH). Recent studies link WMHs to hypoperfusion and ischemic injuries arising from diverse cerebrovascular diseases (CVDs). Previous studies have reported strong associations between WMH burden and disintegration of normal‐appearing white matter (WM) and WM pathways evaluated using diffusion tensor imaging (DTI). This WM deterioration may be the underlying cause of cognitive dysfunction in people with WMHs. The purpose of this study is to identify major WM tracts in which there is evidence of microstructure damage associated with pWMH severity to determine whether this damage is associated with cognitive decline. Method Association between pWMH volume and fractional anisotropy (FA) in 18 major WM tracts in 100 CVD subjects (aged 55‐84 years, 29% female, evidenced by an ischemic stroke event documented by MRI or CT, with a modified Rankin score 0‐3) from the Ontario Neurodegenerative Disease Research Initiative was examined using linear regression. DTI (30 directions, b=1000 s/mm2) was acquired on eight 3T MRI scanners. Mean FA in 18 WM tracts was quantified using TRACULA in FreeSurfer in each subject. Volumes of pWMHs were obtained by semi‐automated segmentation of T1‐weighted images in each subject. Cognitive assessments were completed as part of ONDRI. Associations between cognitive scores and FA in tracts that significantly correlated with pWMH severity were also examined. Result Linear regression (adjusted by age and sex) detected significant correlation between FA in right anterior thalamic radiation (ATR) (Fig. 1) and pWMH volume after Bonferroni correction (p‐value=0.002, r=‐0.356) (Fig. 2). No other significant associations were identified. Since right ATR is part of fronto‐striato‐thalamic circuit contributing to executive function, FA in ATR predicted association with Trail Making Test‐Part B (adjusted by age, sex, and education) and a signhificant correlation was identified (p‐value=0.006, r=‐0.256) (Fig. 3). Conclusion ATR disintegration was associated with pWMH severity in participants with CVD and with executive function. This study suggests that tissue microstructure deterioration in ATR measured by DTI may contribute to decline in executive function in CVD patients with pWMHs.

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 score0.006
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)0.0030.000

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 head0.017
GPT teacher head0.258
Teacher spread0.241 · 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
Published2021
Admission routes2
Has abstractyes

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