Evidence map›Paper›PMID 40606346›Full record

ArticleQuantitative imaging in medicine and surgery2025

CT-guided needle insertion with an optical navigation robot-assisted puncture system:

Wei Cui, Yi Deng, Jingjing Chen, Yanqing Le, Huaying Shi, Suyi Ye, Bingding Huang, Xiaoming Chen, Jing Li, Rongde Xu

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Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Wei Cui *Department of Interventional Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Yi Deng *Medical School, Kunming University of Science and Technology, Department of Pulmonary and Critical Care Medicine, The First People's Hospital of Yunnan Province, Kunming, China.
Jingjing ChenDepartment of Pulmonary and Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Yanqing LeDepartment of Pulmonary and Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Huaying ShiDepartment of Pulmonary and Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Suyi YeMedical School, Kunming University of Science and Technology, Department of Pulmonary and Critical Care Medicine, The First People's Hospital of Yunnan Province, Kunming, China.
Bingding HuangCollege of Big Data and Internet, Shenzhen Technology University, Shenzhen, China.
Xiaoming ChenDepartment of Interventional Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Jing LiMedical School, Kunming University of Science and Technology, Department of Pulmonary and Critical Care Medicine, The First People's Hospital of Yunnan Province, Kunming, China.
Rongde XuDepartment of Interventional Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Robotic technologies have promising applications in computed tomography (CT)-guided puncture. However, nodule-surrogate models can be difficult to develop for relevant studies, and thus the accuracy of optical navigation robot-assisted puncture remains unclear. This study aims to evaluate a starch mixture (the starch group) and a copper particle nodule-surrogate model (the particle group) and to compare the accuracy of optical navigation robot-assisted puncture (the robot group) with traditional CT-guided manual puncture (the manual group) using swine liver and kidneys. Methods: The study was approved by the institutional animal care and use committee. Results: In the first experiment, all nodule surrogates were easily visible on the CT images. However, other aspects of the starch group (one starch overflow, one starch dispersion event, and one air embolism) were inferior to those of the particle group. In experiment 2, the accuracy of needle insertion in the robot group (3.71±1.34 mm) was higher than in the manual group (11.89±9.59 mm) (P<0.001). The needle insertion time and level of radiation exposure were superior in the robot group compared to the manual group. Complications were similar between the two groups. Conclusions: The particle method may be superior to the starch method. The robot group was more accurate than the manual group, and the occurrence of complications was similar.

Indexed as

kidneylivernodule modelpunctureRobot-enhanced procedures

Identifiers

PMID40606346
PMCPMC12209681

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