Hemodynamic Assessment in Bicuspid Aortic Valve Disease and Aortic Dilation: New Insights From Voxel-By-Voxel Analysis of Reverse Flow, Stasis, and Energetics
Bibliographic record
Abstract
Objectives: Clinical management decisions surrounding ascending aorta (AAo) dilation in bicuspid aortic valve (BAV) disease benefit from personalized predictive tools. 4D-flow MRI may provide patient-specific markers reflective of BAV-associated aortopathy. This study aims to explore novel 4D-flow MRI parametric voxel-by-voxel forward flow, reverse flow, kinetic energy and stasis in BAV disease. We hypothesize that novel parametric voxel-by-voxel markers will be associated with aortic dilation and referral for surgery and can enhance our understanding of BAV hemodynamics beyond standard metrics. Methods: A total of 96 subjects (73 BAV patients, 23 healthy controls) underwent MRI scan. Healthy controls had no known cardiovascular disease. Patients were clinically referred for AAo dilation assessment. Indexed diameters were obtained by dividing the aortic diameter by the patient’s body surface area. Patients were followed for the occurrence of aortic surgery. 4D-flow analysis was performed by a single observer in five regions: left ventricular outflow tract (LVOT), AAo, arch, proximal descending aorta (PDAo), and distal descending aorta (DDAo). In each region peak velocity, kinetic energy (KE), forward flow (FF), reverse flow (RF), and stasis were measured on a voxel-by-voxel basis. T-tests (or non-parametric equivalent) compared flow parameters between cohorts. Univariate and multivariate analyses explored associations between diameter and parametric voxel-by-voxel parameters. Results: Compared to controls, BAV patients showed reduced stasis ( p < 0.01) and increased RF and FF ( p < 0.01) throughout the aorta, and KE remained similar. In the AAo, indexed diameter correlated with age (R = 0.326, p = 0.01), FF (R = −0.648, p < 0.001), RF (R = −0.441, p < 0.001), and stasis (R = −0.288, p < 0.05). In multivariate analysis, FF showed a significant inverse association with AAo indexed diameter, independent of age. During a median 179 ± 180 days of follow-up, 23 patients (32%) required aortic surgery. Compared to patients not requiring surgery, they showed increased KE and peak velocity in the proximal aorta ( p < 0.01), accompanied by increased RF and reduced stasis throughout the entire aorta ( p < 0.01). Conclusion: Novel voxel-by-voxel reverse flow and stasis were altered in BAV patients and are associated with aortic dilation and surgical treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".