Three-dimensional printing technology for localised thoracoscopic segmental resection for lung cancer
Abstract Background Three-dimensional (3D) CT reconstruction technology has gained increasing attention owing to its potential in locating ground glass nodules in the lung. The 3D printing technology additionally allows visualising the surrounding anatomical structure and variations. However, the clinical utility of these techniques is not known. We aimed to establish a lung tumour and an anatomical lung model using three-dimensional (3D) printing and 3D chest computed tomography (CT) reconstruction and to evaluate the clinical potential of 3D printing technology in uniportal video-assisted thoracoscopic segmentectomy. Methods Eighty-nine patients with ground glass nodules who underwent uniportal video-assisted thoracoscopic segmentectomy were divided into the following groups: Group A, lung models for pre-positioning and simulated surgery that were made with 3D chest CT reconstruction and 3D printing; Group B, patients who underwent chest CT scans with image enhancement for 3D reconstruction. The differences in the surgery approach transfer rate, surgical method conversion rate, operative time, intraoperative blood loss, and postoperative complication rate were compared between the groups. Results The surgery approach transfer rate was 0% and 10.5% for Groups A and B, respectively, showing a significant difference (p = 0.030). The operative time was 2.07 ± 0.24 hours and 2.55 ± 0.41 hours, respectively, showing a significant difference (p<༜0.001). Intraoperative blood loss volume was 43.25 ± 13.63 and 96.68 ± 32.82 ml, respectively, showing a significant difference (p<༜0.001). The postoperative complication rate was 3.9% and 13.2%, respectively, showing a non-significant difference (P = 0.132). The rate of surgical method conversion to lobectomy in Group A was 0%, which was significantly lower than that of 10.5% in group B (p < 0.030). Conclusions 3D printing technology helps surgeons to locate the nodules more accurately, as it is based on 2D and 3D imaging findings, thereby improving the accuracy and safety of surgery. This technique is worth for application in clinical practice. Trial registration: Retrospectively registered.