DTI‐ALPS Mapping: A Novel Voxel‐based Method for Analyzing the Glymphatic System in the Brain
Bibliographic record
Abstract
BACKGROUND: The glymphatic system is increasingly recognized as a critical factor in the pathogenesis of dementia, which can be assessed using the conventional diffusion tensor image analysis along the perivascular space (DTI-ALPS) based on regions of interest (ROIs). We proposed a novel voxel-based method to analyze the whole cerebral white matter DTI-ALPS and named it DTI-ALPS mapping. The goal of DTI-ALPS mapping is to characterize changes in whole cerebral white matter DTI-ALPS patterns in cognitive impairment and to provide a full-scale, voxel-basedapproach for assessing glymphatic system activity. METHOD: We included 304 participants from the Shenzhen Multimodal Aging Research (STAR) Cohort recruited at Peking University Shenzhen Hospital, including 182 cognitively unimpaired (CU) participants, 93 participants with mild cognitive impairment, and 29 patients with dementia. All participants underwent 3.0T MRI scans with 3D T1-weighted imaging and DTI sequences. We used DTI-ALPS mapping to visualize the entire cerebral white matter fibers of 30 regions. We calculated the DTI-ALPS values using both the conventional ROI-based method and the voxel-based DTI-ALPS mapping we developed. To compare ALPS values among the three groups, we conducted an analysis of variance (ANOVA), followed by post-hoc tests to identify intergroup differences in both the conventional method and DTI-ALPS mapping, respectively. We analyzed the correlations between DTI-ALPS mapping and Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and White Matter Hypointensities (WMH) derived from 3D T1-weighted imaging. RESULT: Using the DTI-ALPS mapping, we revealed whole cerebral white matter ALPS pattern. Over 13 out of 30 regions exhibited significant differences (p < 0.05) in the intergroup analyses, providing additional insights beyond those identified with conventional ROI-based ALPS. Twenty-six of 30 regions in the DTI-ALPS mapping showed a positive correlation with MoCA, and 11 of these regions were also positively correlated with MMSE (Spearman, p < 0.05) Moreover, 26 of 30 regions showed a negative correlation with WMH (Spearman, p < 0.05). CONCLUSION: The DTI-ALPS mapping provides a robust, intuitive, and comprehensive approach to evaluating the changing pattern of the glymphatic system, overcoming the limitations of conventional ROI-based ALPS methods and revealing the changing pattern associated with cognition and WMH.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".