Three-dimensional printing technology for localised thoracoscopic segmental resection for lung cancer: a quasi-randomised clinical trial

Lung Cancer
25/08/2020

World J Surg Oncol. 2020 Aug 24;18(1):223. doi: 10.1186/s12957-020-01998-2.

ABSTRACT

BACKGROUND: Three-dimensional (3D) computed tomography (CT) reconstruction technology has gained attention owing to its potential in locating ground glass nodules in the lung. The 3D printing technology additionally allows the visualisation of the surrounding anatomical structure and variations. However, the clinical utility of these techniques is unknown. This study aimed to establish a lung tumour and an anatomical lung model using 3D printing and 3D chest 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 classified into the following groups: group A, lung models for pre-positioning and simulated surgery that were performed with 3D chest CT reconstruction and 3D printing, and 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 two groups.

RESULTS: Between groups A and B, there were significant differences in the approach transfer rate (0% vs.10.5%, p = 0.030), operative time (2.07 ± 0.24 h vs. 2.55 ± 0.41 h, p < 0.001), intraoperative blood loss volume (43.25 ± 13.63 mL vs. 96.68 ± 32.82 mL, p < 0.001) and the rate of surgical method conversion to lobectomy (0% vs. 10.5%, p < 0.030). In contrast, there was an insignificant difference in the postoperative complication rate between groups A and B (3.9% vs. 13.2%, p = 0.132).

CONCLUSIONS: 3D printing technology facilitates a more accurate location of nodules by surgeons, as it is based on two-dimensional and 3D image-based findings, and therefore, it can improve surgical accuracy and safety. This technique is worth applying in clinical practice.