ArticleThoracic cancer2020
Three-dimensional printed navigational template for localizing small pulmonary nodules: A case-controlled study.
Article in Thoracic cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of three-dimensional technology in video-assisted thoracoscopic surgery sublobectomy.Frontiers in oncology · 2024Pooled it
- Application of three-dimensional printed models with near-infrared fluorescence technology in video-assisted thoracoscopic surgery segmentectomy: a single-center propensity-score matching analysis.Journal of thoracic disease · 2024Article
- Advances in the localization of pulmonary nodules: a comprehensive review.Journal of cardiothoracic surgery · 2024Review
- Intraoperative identification of pulmonary nodules during minimally invasive thoracic surgery: a narrative review.Quantitative imaging in medicine and surgery · 2022Review
- Artificial intelligence assisted display in thoracic surgery: development and possibilities.Journal of thoracic disease · 2021Review
- A three-dimensional printing navigational template combined with mixed reality technique for localizing pulmonary nodules.Interactive cardiovascular and thoracic surgery · 2021Article
- A novel technique for preoperative localization of pulmonary nodules using a mixture of tissue adhesive and iohexol under computed tomography guidance: A 140 patient single-center study.Thoracic cancer · 2021Article
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Authors and funding
12 authors.
Funding
Abstract
backgroundLocalization 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).
methodsThis 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.
resultsIn 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
conclusions3D 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.
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