TAO Shaolin , KANG Poming , QI Dongdong , SUN Tianyu , ZHANG Zuwang , LIU Xun , LUO Yi , CHEN Mingdan , LI Yangyun , XU Li , YANG Xianyun , TAN Qunyou
  • Department of Thoracic Surgery, University-Town Hospital of Chongqing Medical University, Chongqing, 401331, P. R. China;
TAN Qunyou, Email: tanqy001@163.com
Early-stage lung cancer; minimally invasive surgery; precise localization; digital lung model; three-dimensional-printed guide; artificial intelligence
10.7507/1007-4848.202604065
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Objective To evaluate the localization accuracy and perioperative safety of three-dimensional (3D)-printed guide plate localization based on digital lung models in minimally invasive surgery for pulmonary nodules, and to provide an optimized strategy for precise localization of early-stage lung cancer. Methods Patients with pulmonary nodules who underwent minimally invasive sublobar resection between January 2025 and January 2026 were enrolled. They were randomly allocated to a CT-guided group, a territory analysis group, and an intelligent guide plate group in a 1:1:1 ratio using a computer-generated random sequence. The intelligent guide plate group utilized dual-phase CT data to construct individualized digital lung models and design 3D-printed puncture guide plates for preoperative localization. The three groups were then compared in terms of localization accuracy (evaluated by 3D spatial linear distance grading for the CT-guided and intelligent guide plate groups, and by resection margin distance concordance grading for the territory analysis group), perioperative indicators, and complications. Results A total of 75 patients were enrolled, including 26 males and 49 females, with a median age of 56 years (range, 24-81 years). There were 26 patients in the CT-guided group, 26 in the territory analysis group, and 23 in the intelligent guide plate group. The high-precision rate was 60.87% (14/23) in the intelligent guide plate group and 61.54% (16/26) in the CT-guided group, with no statistically significant difference (P=0.944). In the territory analysis group, the resection margin distance concordance was graded as high in 17 patients (65.38%), moderate in 6 (23.08%), low in 2 (7.69%), and absent in 1 (3.85%). Defining high/moderate precision for the CT-guided and intelligent guide plate groups and high/moderate concordance for the territory analysis group as the ideal localization criteria, the qualification rates were 92.31% (24/26), 91.30% (21/23), and 88.46% (23/26), respectively, with no statistically significant difference among the three groups (P=0.886). There were no statistically significant differences in operative time, blood loss, drainage volume, pain score, or postoperative hospitalization costs among the three groups (all P>0.05). The overall complication rate also did not differ significantly among the three groups (P=0.847), and the complications were predominantly mild, including pulmonary air leakage, intermuscular venous thrombosis, pulmonary infection, hepatic insufficiency, etc. All patients improved after symptomatic treatment, with no severe complications encountered. After a median follow-up of 7 months, there were no patients of recurrence, metastasis, or death. Conclusion 3D-printed guide plate localization based on digital lung models can effectively restore pulmonary physiological motion and eliminate the "displacement error" of traditional guide plates. It is comparable to CT-guided and territory analysis localization in terms of accuracy and safety, representing a safe and feasible novel precise localization strategy for minimally invasive surgery of early-stage lung cancer.

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