Assessing of the glymphatic system using DTI‐ALPS MRI in patients with neurodegenerative diseases
Bibliographic record
Abstract
Abstract Background Dysfunction of the glymphatic system (GS), a recently discovered brain by‐product elimination system, is considered to be one of the pathophysiological mechanisms for common neurodegenerative diseases such as Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and Parkinson's disease (PD). In 2017 a new way to assess the GS was proposed – a diffusion tensor images analysis along perivascular spaces (DTI‐ALPS). In our work we evaluated the DTI‐ALPS index in groups of patients with AD, DLB, PD and in a comparison group of patients with normal pressure hydrocephalus (NPH). Methods We examined 32 patients diagnosed with AD [69.5±8.0 years], 15 patients with DLB [71.1±8.0 years], 31 patients with PD without dementia [64.0±6.9 years], 11 patients NPH [68.5±9.8 years] and 27 healthy controls [63.2±7.0 years]. In four patient groups cognitive impairment was rated with Montreal Cognitive Assessment scale (MоCA). The diffusion images were acquired on a SIEMENS Prisma scanner using a 2D EPI diffusion sequence. TE=82 ms, TR=5600 ms. The b‐values were 1000 and 2500 s/mm². The number of diffusion sampling directions were 64 and 64, respectively. The slice thickness was 2 mm. Post‐processing steps were performed using DSI studio software. Next, we identified ROIs corresponding to projection and associative fibers with further extraction of tensor values in the directions Dxx, Dyy, Dzz, which were entered into a table to calculate the DTI‐ALPS index using formula ALPS‐index=mean(Dxxproj+Dxxassoci)/mean(Dyyproj+Dzzassoci) for further statistical processing. Results Patients with AD, DLB and NPH had a significantly lower values of DTI‐ALPS index on both sides compared to healthy volunteers (p<0.001). The differences between PD and healthy controls turned out to be statistically insignificant. In addition, analysis of all the patients revealed a significant direct correlation between the MoCA score and DTI‐ALPS values on both sides (pL=0.002; pR=0.035). Conclusion The obtained results showed that the glymphatic dysfunction assessed by DTI‐ALPS index could be considered as a possible participant in the pathogenesis of AD and DLB as well as in NPH reflecting cognitive decline. Whereas the glymphatic dysfunction in PD was not confirmed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".