Carotid pulse wave velocity measured using a fast single‐slice oblique‐sagittal phase‐contrast MRI is associated with cognitive impairment
Bibliographic record
Abstract
Abstract Background Arterial stiffness is one of the earliest markers of vascular dysfunction1. Elevated arterial stiffness leads to the transmission of excessive pulsations into the downstream microvasculature, which may be linked to cognitive impairment in aged individuals. Pulse wave velocity (PWV) is an established surrogate of arterial stiffness. To date, PWV measurement at carotid arteries or above has been still limited. Previous work has introduced a fast MRI method to measure carotid PWV (cPWV) using single‐slice oblique‐sagittal phase‐contrast MRI (OS PC‐MRI)3. In this study, we evaluated the association between cPWV and cognitive impairment in an aged group. Method The MRI experiments were conducted on Siemens Prisma 3T MRI scanner. A 2min TOF MRI was performed to localize carotid arteries including CCA and ICA. The 3D MR angiogram was reformatted to determine an oblique slice to maximally cover both CCA and ICA (Figure 1a). A single‐slice retrospectively gated 2D OS PC‐MRI with a single in‐plane velocity encoding (CCA to ICA) (Venc = 80cm/s, temporal resolution = 14.22ms) was performed to simultaneously acquire blood velocity waveforms at each location along the CCA‐ICA segment. cPWV was calculated as the inverse slope of the line fitted to the transit time versus distance along the vessel (Figure 1b). 15 elderly participants (age: 71.4 ± 8.5 years) were enrolled in this study. Each participant underwent cognitive assessments including CDR and 13 out of 15 were conducted the MoCA. Result There was a significant difference (p = 0.0496) in cPWV between the participants with normal cognition (CDR = 0) and cognition impairment (CDR> = 0.5). Figure 3 shows the scatter plot of cPWV vs. MoCA. Overall, cPWV increased with lower MoCA. However, there was no significance (r = ‐0.5294, p = 0.0767) obtained between cPWV and MoCA given a small sample size and the presence of a suspicious data point indicated by a green circle in Figure 3. After excluding this potential outlier, a significant negative correlation between cPWV and MoCA was obtained (r = ‐0.8113, p = 0.0014). Conclusion The pilot study demonstrates that increased cPWV is associated with cognitive impairment, suggesting cPWV measured using 2D OS PC‐MRI could be an imaging marker for cognitive impairment.
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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 | 0.001 |
| 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) | 0.001 | 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".