Journal of Shandong University (Health Sciences) ›› 2026, Vol. 64 ›› Issue (5): 74-82.doi: 10.6040/j.issn.1671-7554.0.2025.0895

• Clinical Medicine • Previous Articles     Next Articles

Application of 3D reconstruction combined with CT-guided puncture localization in minimally invasive treatment of pulmonary ground-glass nodules

LIANG Chen1, YAO Lijuan2, LYU Longfei1, TANG Ze1, QIN Da1, CUI Youbin1,YU Xiaoqi1   

  1. 1. Second Department of Thoracic Surgery, The First Hospital of Jilin University, Changchun 130021, Jilin, China;
    2. Department of Outpatient, 93175 Unit, Chinese Peoples Liberation Army, Changchun 130051, Jilin, China
  • Online:2026-05-13 Published:2026-05-13

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Abstract: Objective To compare the therapeutic outcomes of an artificial intelligence(AI)-assisted lung CT three-dimensional reconstruction combined with CT-guided lung nodule fine-needle aspiration biopsy preoperative management model versus a conventional thoracoscopic surgery preoperative management model in the treatment of ground-glass nodules(GGN)via video-assisted thoracic surgery(VATS). Methods Clinical data were collected from 114 patients with GGN undergoing VATS sublobar resection between August 2023 and April 2025. Patients were categorized into four groups based on whether they underwent AI-assisted 3D reconstruction of pulmonary CT and CT-guided lung nodule localization preoperatively: the control group(n=19), the biopsy group(n=25), the 3D reconstruction group(n=16), and the combinaton group(n=54). The control group underwent only preoperative contrast-enhanced lung CT. The biopsy group and 3D reconstruction group additionally underwent CT-guided lung nodule fine-needle aspiration localization or conventional CT 3D reconstruction, respectively. The combination group utilized both AI-assisted lung CT 3D reconstruction and preoperative CT-guided lung nodule fine-needle aspiration localization. The following clinical indicators were collected and compared across the four groups: needle localization success rate, perioperative parameters(surgical approach, surgical duration, intraoperative blood loss, postoperative chest tube retention time, total postoperative drainage volume, length of hospital stay, and hospitalization costs). Results There were no statistically significant differences in general clinical data between the combination group and the control group, the puncture group, or the 3D reconstruction group. The combination group, puncture group, and 3D reconstruction group all demonstrated superior outcomes compared to the control group in six postoperative indicators: anesthesia duration, total drainage volume, drainage tube retention time, surgical duration, intraoperative blood loss, and total surgical cost(P<0.05). The 3D reconstruction group and combination group had shorter hospital stays and smaller lesion resection volumes than the control group(P<0.05), while the combination group had shorter hospital stays and smaller lesion resection volumes than the puncture group(P<0.05). Both the puncture group and combination group had fewer days of postoperative infection than the control group(P<0.05). There was an interaction between 3D reconstruction and needle localization in six indicators: anesthesia duration, total drainage volume, drainage tube retention time, surgical duration, intraoperative blood loss, and total cost. The combination group demonstrated superiority over the puncture group in localization time and patient tolerance scores. Conclusion The preoperative management model combining AI-assisted CT three-dimensional reconstruction with CT-guided needle localization significantly improves perioperative outcomes in VATS sublobar resection, enhances patient quality of life and prognosis, and holds broad clinical application prospects.

Key words: Artificial intelligence, Three-dimensional reconstruction, Puncture positioning, Video-assisted thoracoscopic surgery, Lung ground-glass nodule

CLC Number: 

  • R615
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