Synchrotron speckle-based x-ray phase-contrast imaging for mapping intra-aneurysmal blood flow without contrast agent
Bibliographic record
Abstract
Abstract Intracranial aneurysms carry risk of rupture with life threatening consequences. Hemodynamic forces are considered to be the key in cerebral aneurysm rupture. Notably, the hemodynamic analysis requires precise characterization of intra-aneurysmal blood velocity field, raising the need to develop novel measurement techniques. This study aims to assess the performance of speckle-based x-ray phase contrast particle imaging velocimetry (PIV) for velocity field mapping of a pulsatile blood flow in a patient specific aneurysm model without contrast agent. Porcine blood was used in a blood circulation loop including the aneurysm model, which was imaged using the synchrotron x-ray phase contrast imaging (PCI) at an optimum phase propagation distance. X-ray images were processed to improve speckle characteristics for PIV analysis. A computational fluid dynamic (CFD) model was developed for simulation of the blood velocity field and compared to the x-ray PCI-PIV measurements. The CFD model and x-ray PCI-PIV measurements showed similar intra-aneurysmal blood flow structures although the velocity magnitudes were generally higher in CFD model. Contrary to CFD model, x-ray PCI-PIV measurements revealed formation of blood cell stagnation at the aneurysm dome at low blood flow rate, cushioning upon the blood flow shear force. Synchrotron x-ray PCI-PIV offers potential for hemodynamic analysis in patient specific cerebral aneurysm models without contrast agent.
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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 | 0.001 |
| 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".