Innovative Integration of 4D Cardiovascular Reconstruction and Hologram: Framework Development of a New Visualization Tool for Coronary Artery Bypass Grafting Planning
Bibliographic record
Abstract
Background: Planning for coronary artery bypass grafting (CABG) necessitates advanced spatial visualization skills and consideration of multiple factors, including the depth of coronary arteries within the subepicardium, calcification levels, and pericardial adhesions. Objective: This study aimed to address these requirements by reconstructing a dynamic cardiovascular model, displaying it as a naked-eye hologram, and evaluating the clinical utility of this innovative visualization tool for preoperative CABG planning. Methods: We used preoperative 4D cardiac computed tomography angiography (4D-CCTA) data from 14 patients scheduled for CABG to develop a semiautomated workflow. This workflow enabled time-resolved segmentation of the heart chambers, epicardial adipose tissue (EAT), and coronary arteries, complete with calcium scoring. Methods for segmenting cardiac structures, quantifying coronary calcification, visualizing coronary depth within EAT, and assessing pericardial adhesions via motion analysis were incorporated. These dynamic reconstructions captured spatial relationships, coronary stenosis, calcification, and depth in EAT, as well as pericardial adhesions. Dynamic cardiovascular holograms were then generated and displayed using the Looking Glass platform (Looking Glass Factory Inc). Thirteen cardiac surgeons assessed the utility of the holographic visualization tool on a Likert scale. In addition, a surgeon visually scored pericardial adhesions using the holograms of all 21 patients (including 7 undergoing secondary cardiac surgeries) and compared these scores with actual intraoperative findings. Results: Cardiac surgeons highly rated the visualization tool for its utility in preoperative planning, with a mean Likert score of 4.57/5.0 (SD 0.5). The hologram-based scoring of pericardial adhesions showed a strong correlation with intraoperative findings (correlation coefficient r=0.786; P<.001). Conclusions: This study delineates the structural framework of a visualization tool specifically designed for preoperative CABG planning. It produces high-quality, clinically relevant, dynamic holograms from patient-specific volumetric data, with clinical feedback confirming its practicality and effectiveness for preoperative surgical planning.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".