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Three‐dimensional printed navigational template for localizing small pulmonary nodules: A case‐controlled study

BACKGROUND: 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). METHODS: This study enro...

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Detalles Bibliográficos
Autores principales: Fu, Rui, Chai, Yun‐Fei, Zhang, Jia‐Tao, Zhang, Tao, Chen, Xiao‐Kun, Dong, Song, Yan, Hong‐Hong, Yang, Xue‐Ning, Huang, Mei‐Ping, Wu, Yi‐Long, Zhuang, Jian, Zhong, Wen‐Zhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons Australia, Ltd 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7471015/
https://www.ncbi.nlm.nih.gov/pubmed/32686309
http://dx.doi.org/10.1111/1759-7714.13550
Descripción
Sumario:BACKGROUND: 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). METHODS: 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. RESULTS: 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(2) − 0.013X − 0.454 (R(2) = 0.89). The learning curve was composed of two phases, phase 1 (the initial 20 patients) and phase 2 (the remaining 17 patients). CONCLUSIONS: 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.