Rapid Prototyping of cardiac models: current utilization and future directions
Bibliographic record
Abstract
Rapid 3D-Prototyping is an established technique that converts digital image data of any 3D structure to a physical 3D model. It has been used for a long time in industry for making prototypes of any new products. The state-of-the-art medical imaging facilities such as computed tomography and magnetic resonance imaging (and possibly echocardiography in the future) provide precise digital information of the cardiovascular structures of the human body. The digital information can be used for production of multiple replicas of the human body parts with solid or flexible materials. We have experienced the utility of 3D plastic models in preoperative assessment of the cases with double outlet right ventricle in the last two years,and are convinced that this technology should be further expanded for the following purposes: 1)To produce heart models for simulations of surgical procedures in patients with complex surgical anatomy. 2)To produce simulated phantoms of various surgical pathways such as Fontan circuit and right ventricle-to-pulmonary artery conduit for assessment of flow through complicated surgical pathways. 3)To produce a collection of teaching models for normal and pathological cardiovascular anatomy. 4)To develop a technique of image fusion for complete prototyping by using data from multiple imaging modalities. Virtual visualization of 3D information in the computer screen has revolutionized medical imaging in the last 10-20 years. Although virtual visualization facilitates understanding, it does not allow direct contact or manipulation on the physical model. 3D prototyping of the replicas certainly allows direct visual access to the physical structures and more importantly direct physical manipulation such as practice surgery on the replica of the structure to be operated. Cast model of normal heart. Cavity model of the right ventricle showing stenotic right ventricle to pulmonary artery conduit.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".