Repaired Tetralogy of Fallot Pressure Assessment: Insights from 4D-Flow Pressure Mapping
Bibliographic record
Abstract
Tetralogy of Fallot (TOF) is the most prevalent cyanotic congenital heart defect (CHD) that alters normal blood flow through the heart and accounts for 10% of all CHD. Pulmonary stenosis and regurgitation are common in adults who have undergone TOF repair (rTOF) and can impact the load on the right ventricle, blood flow pressure, and pulmonary hemodynamics. Pressure mapping, obtained through 4D-flow magnetic resonance imaging (4D-flow MRI), has been applied to identify abnormal heart hemodynamics in CHD. Hence, the aim of this research was to compare pressure drop and relative pressures between patients with repaired TOF (rTOF) and healthy volunteers. An in vitro validation was performed, followed by an in vivo validation. We hypothesized that pressure drop is a more stable pressure mapping method than relative pressures to detect altered hemodynamics. A total of 36 subjects, 18 rTOF patients and 18 controls underwent cardiac MRI scans and 4D-flow MRI. Pressure drops and relative pressures in the MPA were higher in rTOF patients compared to the controls (p < 0.05). Following the in vitro validation, pressure drops proved to be a more stable pressure mapping method than relative pressures, as the flow loses its laminarity and becomes more turbulent. In conclusion, this study demonstrated that flow hemodynamics in rTOF can exhibit altered pressure maps. Pressure mapping can help provide further insight into rTOF patients’ hemodynamics to improve patient care and clinical decisions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".