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IMAGING MARKER FOR COGNITIVE IMPAIRMENT DUE TO CEREBRAL WHITE MATTER LESIONS BASED ON SKELETONIZATION OF WHITE MATTER TRACTS AND DIFFUSION HISTOGRAMS

2017· other· en· W6946061051 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsHyperintensityCognitionWhite matterNeuropsychologyDiffusion MRISkeletonizationMontreal Cognitive AssessmentCognitive impairmentCognitive declineMagnetic resonance imaging

Abstract

fetched live from OpenAlex

IntroduceCerebral white matter lesions are indicators of cerebral small vessel disease. WMLs are closely correlated with cognitive impairments in attention, executive function, and information processing speed. DTI is a sensitive technique that allows the quantification of microstructural tissue alterations, which can be invisible on conventional MRI. The peak width of skeletonized mean diffusivity (PSMD) is a new, fully automated, and robust imaging marker for cerebral small vessel disease (SVD). It is considered to be strongly associated with processing speed. However, it has not been applied to cerebral white matter lesions (WMLs) yet.PurposeOur study aimed to investigate the correlation between PSMD and cognition, particularly executive function, which has emerged as the most prominently affected cognitive domain in patients with WMLs.MethodsA total of 111 WML patients and 50 healthy controls (HCs) were enrolled, and their demographic information and cardiovascular disease risk factors were recorded. Subjects were divided into three groups: WMLs with normal cognition (WMLs-NC), WMLs with vascular cognitive impairment (WMLs-VCI), and HCs. They underwent conventional head MRI and DTI scans followed by neuropsychological and psychological examinations, including tests of Montreal Cognitive Assessment (MoCA) and executive function. We compared the difference in executive function and PSMD among the three groups and analyzed the correlation between PSMD and cognitive function in all subjects.Results: There were no significant differences in demographic characteristics (age, gender, level of education, and cardiovascular disease risk factors) among the three groups (Puff1e0.05). However, there were significant differences in global cognition (P<0.0001), executive function (P<0.0001), and PSMD (P<0.0001) among the three groups. The averaged PSMD value (u00d710-4mm2/s) was 2.40u00b10.23, 2.68u00b10.30, and 4.51u00b10.39 in the HC, the WMLs-NC, and the WMLs-VCI groups, respectively. There was no correlation between PSMD and cognition in the HC group. PSMD was significantly correlated with MoCA scores (r=-0.3785, P<0.0001) and executive function (r=-0.4744uff0cP<0.0001) in the WMLs-NC group and in the WMLs-VCI group (r=-0.4448, P<0.0001 and r=-0.6279, P<0.0001, respectively).Conclusions: WML patients have higher PSMD and worse cognitive performance than do healthy controls. PSMD is strongly associated with global cognition and executive functions in WML patients. This result provides new insights into the pathophysiology of cognitive impairment in WML patients. PSMD could be a surrogate marker for disease progression and can thus be used in therapeutic trials involving WML patients.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.137
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0230.007
Science and technology studies0.0010.001
Scholarly communication0.0040.009
Open science0.0040.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.004

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 head0.037
GPT teacher head0.322
Teacher spread0.285 · 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