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Background: Preoperative three-dimensional (3D) lung reconstructions can reduce intraoperative blood loss, conversion rate, and operation duration. These 3D reconstructions are predominantly provided by commercial expensive products, hence we aimed to assess the usability and performance of preoperative 3D lung reconstructions created with open-source software.
Methods: Patients were invited to participate in this prospective pilot study if they were planned for uniportal video-assisted thoracoscopic surgery (VATS) lobectomy or segmentectomy between January and February 2023. Participants were excluded if a two-dimensional (2D) late-arterial-phase computed tomography (CT) scan contained motion artifacts, another surgical procedure was performed, or the surgery was canceled. After informed consent was obtained, 3D lung reconstructions were constructed using open-source 3D Slicer software. The system usability score (SUS) questionnaire assessed the usability of these reconstructions, whilst performance was evaluated based on anatomical validity compared to prior 2D CT assessment as well as operative findings. Descriptive statistics were reported.
Results: Thirteen patients were included, of whom one underwent a segmentectomy. Eighty-three percent of the 3D lung reconstructions scored above average (SUS >68). Compared to 2D CT scans, 38% of lung nodule segmental locations were detected more accurately through 3D lung reconstructions. Furthermore, 3D lung reconstructions revealed anatomical variations in 62%, which were not recognized on 2D CT scans, and provided surgeons with insights that would change the procedure and/or transection planes in 62%. One 3D lung reconstruction failed to demonstrate an intraoperative recognized segmental pulmonary artery (A6) branch.
Conclusions: Three-dimensional lung reconstructions created with open-source software were usable and effective for uniportal VATS anatomical resections.
Trial Registration: ClinicalTrials.gov/NCT06132607.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11304144 | PMC |
http://dx.doi.org/10.21037/tlcr-24-134 | DOI Listing |
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