Surgeon Knowledge of the Pulmonary Arterial System and Surgical Plan Confidence Is Improved by Interactive Virtual 3D-CT Models of Lung Cancer Patient Anatomies

交互式虚拟3D-CT肺癌患者解剖模型可提高外科医生对肺动脉系统的了解和手术方案的信心

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Abstract

Objective: Interactive three-dimensional virtual models of pulmonary structures (3D-CT) may improve the safety and accuracy of robotic-assisted thoracic surgery (RATS). The aim of this study was to evaluate the impact of 3D-CT models as an imaging adjunct on surgical confidence and anatomical assessment for lobectomy planning. Methods: We retrospectively analyzed the response of 10 specialist thoracic surgeons who each reviewed 10 pre-operative images of patients undergoing robotic-assisted lobectomy lung cancer cases from June to November 2018 in our institute, resulting in 100 data points. The number of arteries, veins, and bronchi entering the resected lobes were determined from the operation video recording by the operating surgeon. 3D-CT models were generated for each case and made available for online visualization and manipulation. Thoracic surgeons were invited to participate in the survey which consisted of evaluation of CT (control) and 3D-CT (intervention) models. A questionnaire regarding anatomical structures, surgical approach, and confidence was administered. Results: Ten participants were recruited. 3D-CT models led to a significant (p < 0.003) increase in the surgeons' ability to correctly identifying pulmonary arteries entering the resection lobes in 35% (CT) and 57% (3D-CT) of cases. A significant (p < 1e-13) improvement in anatomy assessment and surgical plan confidence was observed for the 3D-CT arm, with median Likert scale scores of "2-Slightly easy" (CT) and "4-Very easy" (3D-CT). Conclusion: The use of 3D-CT models for thoracic surgery planning increases the surgeon confidence in recognizing anatomical structures, largely by enhanced appreciation of anatomical variations in the segmental pulmonary arterial system. Further studies are needed to investigate if 3D-CT models can be used in providing precise information about segmental artery distribution and therefore surgical planning of sub-lobar resections.

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