Brain-wide pulsatility mapping with gated ultrasound localization microscopy <i>in vivo</i>
Bibliographic record
Abstract
Cardiovascular diseases are associated with cognitive impairment. Aging arteries increased stiffness leads to an increased pulsatility in downstream vessels and brain structural damage. Hence, brain-wide pulsatility maps could yield a powerful biomarker for neurodegenerative diseases. Ultrasound Localization Microscopy (ULM) can probe the rodent brain smallest vessels, but is currently limited to averaged velocities over multiple cardiac cycles. The objective here was to map the pulsatility using ULM in a rat brain in vivo using a cardiac-gated approach. Rat brains were imaged following craniotomy with a Vantage system (L22-14, Verasonics, WA). ECG-gated frames were acquired in groups of 400 (1000 fps) during 8 min following a microbubble injection. More than 20 × 106 bubbles were detected and tracked to map local velocities. Significantly distinct velocities could be measured during systole and diastole in the entire rat brain. Pulsatility indexes from 0.15 in cortical branches to 0.30 in the anterior cerebral artery could be measured, with an increase in blood velocities of 8% to 15% during systole compared to diastole. To our knowledge, this study reports for the first time the mapping of small vessels pulsatility in the entire rodent brain. [We acknowledge the support of IVADO, TransMedTech and Apogée/CFREF.]
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".