Hui Li1,2, Miguel Castro3,4, Pascal Haigron1,2, Jean-Philippe Verhoye1,2,5, Vito Giovanni Ruggieri2,5. 1. INSERM, UMR 1099, 35000, Rennes, France. 2. Université de Rennes 1, LTSI, 35000, Rennes, France. 3. INSERM, UMR 1099, 35000, Rennes, France. miguel.castro@univ-rennes1.fr. 4. Université de Rennes 1, LTSI, 35000, Rennes, France. miguel.castro@univ-rennes1.fr. 5. CHU Rennes, Service de Chirurgie Thoracique el de Chirurgie Vasculaire, 35000, Rennes, France.
Abstract
PURPOSE: Minimally invasive aortic valve replacement (MIAVR) procedures remain more complex and technically challenging compared to conventional full sternotomy surgery. This technique involves a restricted surgical field and a limited workspace, which is, at present, strictly reserved for the most experienced surgeons. The MIAVR clinical outcomes are strongly dependent on the appropriate choice of the thoracic incision. This work presents a decision support system to optimize, through an interactive visualization interface, the exposure of the target structure in a limited field of view. METHODS: Our approach is based on the computation of relevant anatomical measurements from preoperative CT images, and it takes into account the surgical guidelines in order to propose the surgical access that best fits the patient's morphology. RESULTS: The proposed planning system was applied and tested on 30 datasets from patients affected by severe aortic stenosis for validation purposes. We evaluated the accuracy of the automatic detections and the measurements calculated by the system with those chosen manually by the expert. CONCLUSIONS: In 87% of thirty cases, the surgical strategy proposed by the decision support system was correct. For the remaining cases, the graphical user interface (GUI) allowed the user to manually adjust the anatomical features.
PURPOSE: Minimally invasive aortic valve replacement (MIAVR) procedures remain more complex and technically challenging compared to conventional full sternotomy surgery. This technique involves a restricted surgical field and a limited workspace, which is, at present, strictly reserved for the most experienced surgeons. The MIAVR clinical outcomes are strongly dependent on the appropriate choice of the thoracic incision. This work presents a decision support system to optimize, through an interactive visualization interface, the exposure of the target structure in a limited field of view. METHODS: Our approach is based on the computation of relevant anatomical measurements from preoperative CT images, and it takes into account the surgical guidelines in order to propose the surgical access that best fits the patient's morphology. RESULTS: The proposed planning system was applied and tested on 30 datasets from patients affected by severe aortic stenosis for validation purposes. We evaluated the accuracy of the automatic detections and the measurements calculated by the system with those chosen manually by the expert. CONCLUSIONS: In 87% of thirty cases, the surgical strategy proposed by the decision support system was correct. For the remaining cases, the graphical user interface (GUI) allowed the user to manually adjust the anatomical features.
Entities:
Keywords:
3D visualization; Aortic valve; Computer-assisted medical intervention application; Decision support system; MIAVR; Minimally invasive surgery