Abstract 17989: Evolution of At-risk Aortic Tissue in Patients With Bicuspid Aortic Valve After Valve or Aorta Replacement
Bibliographic record
Abstract
Objectives: Bicuspid aortic valve (BAV) is associated with increased risk of aortopathy requiring surgery. However, to date, there is no clear consensus on aortic resection extent. Our objective was to study in BAV patients the evolution of ascending aortic (AA) ‘at-risk’ tissue, as defined by elevated wall shear stress (WSS) estimated using 4D flow MRI acquired at baseline and follow up. Methods: Eighteen BAV patients (49±15yrs) were included who underwent AA repair and MRI before surgery and at follow up (mean duration: 154±250 [7-977] days). For each patient and exam, 3D aortic systolic WSS was estimated from 4D flow MRI and at-risk tissue area was defined as the treatable region with high WSS, when compared to an atlas of physiologically normal values (as previously established in healthy controls). Results: The baseline sinus of Valsava and mid-AA diameters were both 4.5±0.6cm. Eight patients had severe aortic stenosis or regurgitation. Three patients had aortic valve replacement without aortic resection, 8 had AA repair without hemiarch repair, and 7 had AA and hemiarch repair. In the 8 AA repair patients, 3D area of elevated WSS increased at baseline from 25±29% to 52±37% at follow up, when expressed in percentage of the AA tissue remaining after surgery up from graft to the first branch (Figure). Little change in at-risk tissue area was observed in hemiarch repair patients. Conclusions: Our preliminary study demonstrates feasibility of 4D flow MRI to provide data regarding at-risk aortic tissue progression in BAV patients who underwent AA repair. Larger studies in a variety of clinical conditions are warranted to further understand the implications of these findings.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".