Ascending aortic aneurysm haemodynamics are associated with aortic wall biomechanical properties
Bibliographic record
Abstract
OBJECTIVES: The effect of aortic haemodynamics on arterial wall properties in ascending thoracic aortic aneurysms (ATAAs) is not well understood. We aim to delineate the relationship between shear forces along the aortic wall and loco-regional biomechanical properties associated with the risk of aortic dissection. METHODS: Five patients with ATAA underwent preoperative magnetic resonance angiogram and four-dimensional magnetic resonance imaging. From these scans, haemodynamic models were constructed to estimate maximum wall shear stress (WSS), maximum time-averaged WSS, average oscillating shear index and average relative residence time. Fourteen resected aortic samples from these patients underwent bi-axial tensile testing to determine energy loss (ΔUL) and elastic modulus (E10) in the longitudinal (ΔULlong, E10long) and circumferential (ΔULcirc, E10circ) directions and the anisotropic index (AI) for each parameter. Nine resected aortic samples underwent peel testing to determine the delamination strength (Sd). Haemodynamic indices were then correlated to the biomechanical properties. RESULTS: A positive correlation was found between maximum WSS and ΔULlong rs=0.75, P = 0.002 and AIΔUL (rs=0.68, P=0.01). Increasing maximum time-averaged WSS was found to be associated with increasing ΔULlong (rs=0.73, P = 0.003) and AIΔUL (rs=0.62, P=0.02). Average oscillating shear index positively correlated with Sd (rs=0.73,P=0.04). No significant relationship was found between any haemodynamic index and E10, or between relative residence time and any biomechanical property. CONCLUSIONS: Shear forces at the wall of ATAAs are associated with local degradation of arterial wall viscoelastic hysteresis (ΔUL) and delamination strength, a surrogate for aortic dissection. Haemodynamic indices may provide insights into aortic wall integrity, ultimately leading to novel metrics for assessing risks associated with ATAAs.
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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 | 0.002 |
| 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".