IMAGING MARKER FOR COGNITIVE IMPAIRMENT DUE TO CEREBRAL WHITE MATTER LESIONS BASED ON SKELETONIZATION OF WHITE MATTER TRACTS AND DIFFUSION HISTOGRAMS
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".