Physical Simulation of Transcatheter Edge-to-Edge Repair Using Image-Derived 3D Printed Heart Models
Bibliographic record
Abstract
Background: Transcatheter edge-to-edge valve repair (TEER) is a complex procedure requiring delivery and alignment of the device to the target valve, which can be challenging in atypical or surgically palliated anatomy. We demonstrate application of virtual and physical simulation to plan optimal TEER access and catheter path in normal and congenitally abnormal cardiac anatomy. Methods: Three heart models were created from three-dimensional (3D) images and 3D printed, including two with congenital heart disease. TEER catheter course was simulated both virtually and physically using a commercial TEER system. Results: We demonstrate application of modeling in three patients, including two with congenital heart disease and a Fontan circulation. Access site and pathway to device delivery was simulated by members of a multidisciplinary valve team. Virtual and physical simulation were compared. Conclusions: Virtual and physical simulation of TEER using 3D printed heart models is feasible and may be beneficial for planning and simulation, particularly in patients with complex anatomy. Future work is required to demonstrate application in the clinical setting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".