Three‐ dimensional printed navigational template for localizing small pulmonary nodules: A case‐ controlled study
Autor: | Rui Fu, Xiao‐Kun Chen, Wen-Zhao Zhong, Tao Zhang, Yi-Long Wu, Yun‐Fei Chai, Mei-Ping Huang, Jia-Tao Zhang, Jian Zhuang, Song Dong, Xue-Ning Yang, Hong-Hong Yan |
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Rok vydání: | 2020 |
Předmět: |
Male
0301 basic medicine Pulmonary and Respiratory Medicine CUSUM lung neoplasms lcsh:RC254-282 Imaging data 03 medical and health sciences 0302 clinical medicine Humans Medicine Right upper lobe pulmonary nodules three‐dimensional printing Computed tomography Aged Lung Thoracic surgeon business.industry Brief Report Nodule (medicine) General Medicine Perioperative Middle Aged lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens Treatment Outcome 030104 developmental biology medicine.anatomical_structure Oncology Case-Control Studies 030220 oncology & carcinogenesis Printing Three-Dimensional Multiple Pulmonary Nodules Female Brief Reports Multiple linear regression analysis medicine.symptom business Nuclear medicine |
Zdroj: | Thoracic Cancer, Vol 11, Iss 9, Pp 2690-2697 (2020) Thoracic Cancer |
ISSN: | 1759-7714 1759-7706 |
Popis: | 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 = 0.48X2 − 0.013X − 0.454 (R2 = 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. Localization of small pulmonary nodules is an inevitable challenge for the thoracic surgeon. This study demonstrated that the 3D printing localization technique is a feasible and accessible strategy to localize non‐palpable pulmonary nodules. |
Databáze: | OpenAIRE |
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