Simulation of semilunar valve function: computer-aided design, 3D printing and flow assessment with MR
Bibliographic record
Abstract
BACKGROUND: The structure of the valve leaflets and sinuses are crucial in supporting the proper function of the semilunar valve and ensuring leaflet durability. Therefore, an enhanced understanding of the structural characteristics of the semilunar valves is fundamental to the evaluation and staging of semilunar valve pathology, as well as the development of prosthetic or bioprosthetic valves. This paper illustrates the process of combining computer-aided design (CAD), 3D printing and flow assessment with 4-dimensional flow magnetic resonance imaging (MRI) to provide detailed assessment of the structural and hemodynamic characteristics of the normal semilunar valve. METHODS: Previously published geometric data on the aortic valve was used to model the 'normal' tricuspid aortic valve with a CAD software package and 3D printed. An MRI compatible flow pump with the capacity to mimic physiological flows was connected to the phantom. A peak flow rate of 100 mL/s and heart rate of 60 beats per minute were used. MRI measurements included cine imaging, 2D and 4D phase-contrast imaging to assess valve motion, flow velocity and complex flow patterns. RESULTS: Cine MRI data showed normal valve function and competency throughout the cardiac cycle in the 3D-printed phantom. Quantitative analysis of 4D Flow data showed net flow through 2D planes proximal and distal to the valve were very consistent (26.03 mL/s and 26.09 mL/s, respectively). Measurements of net flow value agreed closely with the flow waveform provided to the pump (27.74 mL/s), confirming 4D flow acquisition in relation to the pump output. Peak flow values proximal and distal to the valve were 78.4 mL/s and 63.3 mL/s, respectively. Particle traces of flow from 4D-phase contrast MRI data demonstrated flow through the valve into the ascending aorta and vortices within the aortic sinuses, which are expected during ventricular diastole. CONCLUSION: In this proof of concept study, we have demonstrated the ability to generate physiological 3D-printed aortic valve phantoms and evaluate their function with cine- and 4D Flow MRI. This technology can work synergistically with promising tissue engineering research to develop optimal aortic valve replacements, which closely reproduces the complex function of the normal aortic valve.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".