Planning thoracoscopic segmentectomies with 3-dimensional reconstruction software improves outcomes.

Abstract

Objectives: We investigated whether preoperatively generated models of the anatomy of the lung using 3-dimensional (3D) reconstruction software based on high-resolution computed tomography scans improve surgical and postoperative outcomes after video-assisted thoracoscopic surgery (VATS) segmentectomies.

Methods: We retrospectively collected data from 100 consecutive patients who signed the general research consent form and underwent VATS segmentectomies between 2018 and 2023. The outcomes and complications of the operations planned with the 3D models were compared to the results of those performed without the models. We used propensity modelling and inverse probability of treatment weighting (IPTW) to analyse the data.

Results: Thirty-seven of the 100 patients included underwent surgery planned using the 3D models. In the 3D group, complex segmentectomies were performed more frequently (89% vs 38%, P < 0.001), and there were markedly fewer conversions to thoracotomy (P = 0.003). The IPTW analysis showed fewer severe complications (Clavien-Dindo grade III or IV) [post-IPTW odds ratio 0.10 (95% confidence interval 0.01-0.87), P = 0.037], and no Clavien-Dindo grade V complications occurred. Additionally, operative planning using models generated from 3D reconstruction software may influence procedural and postoperative parameters, such as the number of segments removed (1.9 ± 1.0 vs 1.7 ± 0.8, P = 0.40), duration of chest tube placement (3.0 days, interquartile range 2.0-4.0 vs 2.0 days, interquartile range 1.0-3.0, P = 0.060), and stay in the intensive/intermediate care unit.

Conclusions: The planning of complex anatomical VATS segmentectomies using 3D models constructed from 3D reconstruction software significantly reduces the need for conversions to thoracotomy and postoperative complications rates. In addition, complex operations are thereby performed safely.