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Optical navigation robot-assisted puncture system for accurate lung nodule biopsy: an animal study

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机构: [1]Department of Pulmonary and Critical Care Medicine, The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China [2]Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China [3]College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China [4]Wuerzburg Dynamics Inc., Shenzhen, China [5]Department of Interventional Radiology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
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关键词: Percutaneous lung biopsy (PLB) computed tomography (CT) computed tomography-guided biopsy (CT-guided biopsy) optical navigation robot-assisted puncture system

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Background: As lung cancer is one of the most significant factors seriously endangering human health, a robot-assisted puncture system with high accuracy and safety is urgently needed. The purpose of this investigation was to compare the safety and effectiveness of such a robot-assisted system to the conventional computed tomography (CT)-guided manual method for percutaneous lung biopsies (PLBs) in pigs.Methods: An optical navigation robot-assisted puncture system was developed and compared to the traditional CT-guided PLB using simulated lesions in experimental animals. A total of 30 pulmonary nodules were successfully created in 5 pigs (Wuzhishan pig, 1 male and 4 females). Of these, 15 were punctured by the optical navigation robot-assisted puncture system (robotic group), and 15 were manually punctured under CT guidance (manual group). The biopsy success rate, operation time, first needle tip-target point deviation, and needle adjustment times were compared between groups. Postoperative CT scans were performed to identify complications.Results: The single puncture success rate was higher in the robotic group (13/15; 86.7%) than in the manual group (8/15; 53.3%). The first puncture was closer to the target lesion (1.8 +/- 1.7 mm), and the operation time was shorter (7.1 +/- 3.7 minutes) in the robotic group than in the manual group (4.4 +/- 2.8 mm and 12.9 +/- 7.6 minutes, respectively). The angle deviation was smaller in the robotic group (3.26(degrees) +/- 2.48(degrees)) than in the manual group (7.71(degrees) +/- 3.86(degrees)). The robotic group displayed significant advantages (P<0.05). The primary complication in both groups was slight bleeding, with an incidence of 26.7% in the robotic group and 40.0% in the manual group. There was 1 case of pneumothorax in the manual group, and there were no deaths due to complications in either group.Conclusions: An optical navigation robot-assisted system for PLBs guided by CT images was developed and demonstrated. The experimental results indicate that the proposed system is accurate, efficient, and safe in pigs.

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出版当年[2023]版:
大类 | 2 区 医学
小类 | 3 区 核医学
最新[2023]版:
大类 | 2 区 医学
小类 | 3 区 核医学
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出版当年[2022]版:
Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
最新[2023]版:
Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子: 最新[2023版] 最新五年平均 出版当年[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

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第一作者机构: [1]Department of Pulmonary and Critical Care Medicine, The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China [2]Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
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通讯机构: [2]Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China [3]College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China [*1]Department of Pulmonary and Critical Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, 106 Zhongshan 2nd Road, Guangzhou 510080, China [*2]College of Big Data and Internet, Shenzhen Technology University, 3002 Lantian Road, Shenzhen 518118, China.
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