3-D image guidance for minimally invasive robotic coronary artery bypass.
Bibliographic record
Abstract
BACKGROUND: The introduction of a robot-assisted microsurgical system has made endoscopic coronary artery bypass grafting (ECABG) possible. Despite the success of this approach, surgeons still require better visualization tools for pre-surgical planning and intra-operative image guidance. Such visualization tools could, for example, assist in the placement of thoracic ports to acquire optimum access to the target vessels. In this paper we discuss the essential steps toward image-guided completely endoscopic coronary bypass surgery with robot assistance, and we present our preliminary efforts toward the development of a three-dimensional (3-D) virtual cardiac surgical planning platform (VCSP) for ECABG. METHODS: Preoperative 3-D images of the thorax acquired with computed tomography and electrocardiogram-gated magnetic resonance imaging are imported into VCSP. Using VCSP, a user may interactively visualize and manipulate the simulated thoracic ports in 3-D within the reconstructed thoracic region. We have also implemented a virtual endoscope to simulate the endoscopic view observed by the surgeon during the operation. Once the port placements for optimal access to the target vessels are determined, the positions of the simulated tools can be recorded and marked on the patient to specify the positions for port incisions. RESULTS: A static thorax phantom was used to verify the port placements obtained from VCSP simulations. The angles and the distances between the ports, the endoscope and the markers that were placed on the surface of the phantom were measured, and the results were compared with those obtained from simulation. The physical measured distances and angles agreed with the simulated results with average errors of 4 mm and 2 degrees, respectively. CONCLUSIONS: The VCSP image-guided surgical system allows a surgeon to visualize a patient's thorax in a 3-D interactive environment for planning surgical procedures, and to determine the optimum port placement based on preoperative 3-D images. However, during an operation, the positions and orientation of the heart and the coronary arteries are changed from their corresponding locations in the preoperative images due to carbon-dioxide insufflation, lung deflation, and dynamic motions of the beating heart. One of our future goals of this project is the use of mathematical models that correct for these changes so that our system could be applied to intra-operative image guidance.
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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 | 0.001 |
| 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 | 0.001 | 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".