Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Anesthesiology Department of Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Thorac Cancer. 2020 Sep;11(9):2690-2697. doi: 10.1111/1759-7714.13550. Epub 2020 Jul 19.
Localization of small pulmonary nodules is an inevitable challenge for the thoracic surgeon. This study aimed to investigate the accuracy of three-dimensional (3D) printing technology for localizing small pulmonary nodules, especially ground-glass nodules (GGNs).
This study enrolled patients with peripheral small pulmonary nodules (≤ 2 cm) who required preoperative localization. In the comparison period, patients underwent both computed tomography-guided (CT-G) and 3D-printing template guided (3D-G) localization to compare the accuracies of the two methods. In the testing period, the 3D-printing technique was implemented alone. The 3D-printing physical navigational template was designed based on data from perioperative CT images. Clinical data, imaging data, surgical data, and evaluation index were collected for further analysis. The learning curve of the 3D-printing localization technique was assessed using cumulative sum (CUSUM) analysis and multiple linear regression analysis.
In the comparison period (n = 14), the success rates of CT-G and 3D-G were 100% and 92.9% (P = 0.31), respectively; in the testing period (n = 23), the success rate of 3D-G was 95.6%. The localization times of CT-G, 3D-G (comparison), and 3D-G (testing) were 23.6 ± 5.3, 19.3 ± 6.8, and 9.8 ± 4.6 minutes, respectively. The CUSUM learning curve was modeled using the equation: Y = 0.48X - 0.013X - 0.454 (R = 0.89). The learning curve was composed of two phases, phase 1 (the initial 20 patients) and phase 2 (the remaining 17 patients).
3D printing localization has adequate accuracy and is a feasible and accessible strategy for use in localizing small pulmonary nodules, especially in right upper lobe. The use of this technique could facilitate lung nodule localization prior to surgery.
小的肺结节定位是胸外科医生面临的必然挑战。本研究旨在探讨三维(3D)打印技术定位小的肺结节,尤其是磨玻璃结节(GGN)的准确性。
本研究纳入了需要术前定位的外周性小肺结节(≤2cm)患者。在对照期,患者同时接受 CT 引导(CT-G)和 3D 打印模板引导(3D-G)定位,比较两种方法的准确性。在测试期,单独使用 3D 打印技术。根据围手术期 CT 图像的数据设计 3D 打印物理导航模板。收集临床数据、影像学数据、手术数据和评估指标进行进一步分析。使用累积和(CUSUM)分析和多元线性回归分析评估 3D 打印定位技术的学习曲线。
在对照期(n=14),CT-G 和 3D-G 的成功率分别为 100%和 92.9%(P=0.31);在测试期(n=23),3D-G 的成功率为 95.6%。CT-G、3D-G(对照)和 3D-G(测试)的定位时间分别为 23.6±5.3、19.3±6.8 和 9.8±4.6 分钟。CUSUM 学习曲线采用以下方程建模:Y=0.48X-0.013X-0.454(R=0.89)。学习曲线由两个阶段组成,第一阶段(前 20 例患者)和第二阶段(其余 17 例患者)。
3D 打印定位具有足够的准确性,是一种可行且易于实施的策略,可用于定位小的肺结节,特别是右肺上叶。该技术的使用可以促进术前肺结节的定位。