Soft Robots with Cy5: An “Intake and Work” Imaging Technique for Intraoperative Navigation of Gastric Lesion

Locating tumors during laparoscopic surgery for early gastric cancers poses an important challenge because they lack involvement with the serosal layer and remain invisible within the peritoneal cavity. To address this issue, various techniques such as preoperative dye injection and magnetic clip detection systems have been introduced to aid in intraoperative tumor localization. However, these existing techniques are often intricate and lack intuition and endurance. In this study, we propose a novel approach utilizing fluorescent soft robots to accurately locate tumors within the stomach. The methodology involved placing a metal clip at the tumor site, followed by administering several soft robots labeled with Cy5. These soft robots were designed to autonomously converge around the metal clip. To validate their efficacy, we conducted animal experiments by implanting clips into the stomachs of rats and subsequently administering capsules containing the soft robots. By detecting the resulting fluorescence, we successfully identified the location of the clips within the stomach. Our findings indicate that these soft robots hold great promise as a viable alternative for localizing gastric lesions during laparoscopic surgery, which has better persistence and intuitiveness than other markup methods. Their implementation could significantly enhance the accuracy and efficiency of tumor identification in a technologically advanced and clinically accessible manner.

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Publication Details

Journal
Cyborg and Bionic Systems
Published
2024-12-27
DOI
https://doi.org/10.34133/cbsystems.0212
Citations
4
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
1.24
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article

Soft Robots with Cy5: An “Intake and Work” Imaging Technique for Intraoperative Navigation of Gastric Lesion

Songmei Lou, Weiqi Jin, Qin Fang, Pingyu Xiang et al.
4 citations
Cyborg and Bionic Systems
Micro and Nano Robotics
1.24
article

Soft Robots with Cy5: An “Intake and Work” Imaging Technique for Intraoperative Navigation of Gastric Lesion

Songmei Lou, Weiqi Jin, Qin Fang, Pingyu Xiang, Yanan Xue, Haojian Lu, Danying Sun, Jingyu Zhang, Pan Yu, Lifeng He, Rong Tan, Rong Xiong, Yue Wang
article en
4 citations

Abstract

Locating tumors during laparoscopic surgery for early gastric cancers poses an important challenge because they lack involvement with the serosal layer and remain invisible within the peritoneal cavity. To address this issue, various techniques such as preoperative dye injection and magnetic clip detection systems have been introduced to aid in intraoperative tumor localization. However, these existing techniques are often intricate and lack intuition and endurance. In this study, we propose a novel approach utilizing fluorescent soft robots to accurately locate tumors within the stomach. The methodology involved placing a metal clip at the tumor site, followed by administering several soft robots labeled with Cy5. These soft robots were designed to autonomously converge around the metal clip. To validate their efficacy, we conducted animal experiments by implanting clips into the stomachs of rats and subsequently administering capsules containing the soft robots. By detecting the resulting fluorescence, we successfully identified the location of the clips within the stomach. Our findings indicate that these soft robots hold great promise as a viable alternative for localizing gastric lesions during laparoscopic surgery, which has better persistence and intuitiveness than other markup methods. Their implementation could significantly enhance the accuracy and efficiency of tumor identification in a technologically advanced and clinically accessible manner.

Cyborg and Bionic SystemsVol. 6
Applied Science and Technology Research Institute (CN), Sir Run Run Shaw Hospital (CN), Zhejiang Cancer Hospital (CN), Stomatology Hospital (CN), ZheJiang Institute For Food and Drug Control (CN), Zhejiang University of Technology (CN), University of Hong Kong (HK)
Openalex Percentile: Top 20%
Micro and Nano Robotics
1.24
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