Noninvasive vascular ultrasound elastography applied to the characterization of experimental aneurysms and follow-up after endovascular repair
Bibliographic record
Abstract
Experimental and simulation studies were conducted to noninvasively characterize abdominal aneurysms with ultrasound (US) elastography before and after endovascular treatment. Twenty three dogs having bilateral aneurysms surgically created on iliac arteries with venous patches were investigated. In a first set of experiments, the feasibility of elastography to differentiate vascular wall elastic properties between the aneurismal neck (healthy region) and the venous patch (pathological region) was evaluated on six dogs. Lower strain values were found in venous patches (p < 0.001). In a second set of experiments, 17 dogs having endovascular repair (EVAR) by stent graft (SG) insertion were examined three months after SG implantation. Angiography, color Doppler US, examination of macroscopic sections and US elastography were used. The value of elastography was validated with the following end points by considering a solid thrombus of a healed aneurysm as a structure with small deformations and a soft thrombus associated with endoleaks as a more deformable tissue: (1) the correlation between the size of healed organized thrombi estimated by elastography and by macroscopic examinations; (2) the correlation between the strain amplitude measured within vessel wall elastograms and the leak size; and (3) agreement on the presence and size of endoleaks as determined by elastography and by combined reference imaging modalities (angiography + Doppler US). Mean surfaces of solid thrombi estimated with elastography were found correlated with those measured on macroscopic sections (r = 0.88, p < 0.001). Quantitative strain values measured within the vessel wall were poorly linked with the leak size (r = 0.12, p = 0.5). However, the qualitative evaluation of leak size in the aneurismal sac was very good, with a Kappa agreement coefficient of 0.79 between elastography and combined reference imaging modalities. In summary, complementing B-scan and color Doppler, noninvasive US elastography was found to be potentially a relevant tool for aneurismal follow-up after EVAR, provided it allows geometrical and mechanical characterizations of the solid thrombus within the aneurismal sac. This elasticity imaging technique might help detecting potential complications during follows-up subsequent to EVAR.
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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".