Treffer: Preoperative Planning and Experimental Validation for Robot-Assisted Minimally Invasive Surgery Based on a Clinical Evaluation System.
Title:
Preoperative Planning and Experimental Validation for Robot-Assisted Minimally Invasive Surgery Based on a Clinical Evaluation System.
Authors:
Gao L; School of Mechanical Engineering, Key Lab for Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, China., Xing Y; School of Mechanical Engineering, Key Lab for Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, China.; Institute of Medical Robotics and Intelligent Systems, Tianjin University, Tianjin, China., Bian Y; School of Mechanical Engineering, Key Lab for Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, China., Zhao J; School of Aerospace Engineering, National Engineering Research Center of Neuromodulation, Tsinghua University, Beijing, China., Liu X; School of Mechanical Engineering, Key Lab for Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, China.; Institute of Medical Robotics and Intelligent Systems, Tianjin University, Tianjin, China., Wang H; Department of Gastrointestinal Surgery, Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Tianjin Hospital of ITCWM, Tianjin, China.
Source:
The international journal of medical robotics + computer assisted surgery : MRCAS [Int J Med Robot] 2025 Feb; Vol. 21 (1), pp. e70042.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Wiley Country of Publication: England NLM ID: 101250764 Publication Model: Print Cited Medium: Internet ISSN: 1478-596X (Electronic) Linking ISSN: 14785951 NLM ISO Abbreviation: Int J Med Robot Subsets: MEDLINE
Imprint Name(s):
Publication: 2006- : West Sussex, England : Wiley
Original Publication: Ilkley, UK : Robotic Publications, c2004-
Original Publication: Ilkley, UK : Robotic Publications, c2004-
MeSH Terms:
References:
L. Wenhao and Z. Taiping, “Current Status of Minimally Invasive Surgery for Pancreatic Cancer,” Laparoscopic, Endoscopic and Robotic Surgery 4, no. 3 (2021).
M. A. Laribi, M. Arsicault, T. Riviere, et al., “Toward New Minimally Invasive Surgical Robotic System,” in 2012 IEEE International Conference on Industrial Technology, (Athens, GREECE: IEEE International Conference on Industrial Technology, ICIT, 2012), 504–509.
A. L. Trejos and R. V. Patel, “Port Placement for Endoscopic Cardiac Surgery Based on Robot Dexterity Optimization,” in IEEE International Conference on Robotics and Automation (Piscataway, USA: IEEE, 2005), 912–917.
U. Kappert, J. Schneider, R. Cichon, et al., “Development of Robotic Enhanced Endoscopic Surgery for the Treatment of Coronary Artery Disease,” supplement, Circulation 104, no. S1 (2001): S102–S107, https://doi.org/10.1161/circ.104.suppl_1.i‐102.
D. Loulmet, A. Carpentier, N. d'Attellis, et al., “Endoscopic Coronary Artery Bypass Grafting With the Aid of Robotic Assisted Instruments,”Journal of Thoracic and Cardiovascular Surgery 118, no. 1 (1999): 4–10, https://doi.org/10.1016/s0022‐5223(99)70133‐9.
W. Cannon, A. Stoll, D. Selha, P. Dupont, R. Howe, D. Torchiana, “Port Placement Planning in Robot‐Assisted Coronary Artery Bypass,” IEEE Transactions on Robotics and Automation 19, no. 5 (2003): 912–917, https://doi.org/10.1109/tra.2003.817502.
A. Cestari, N. M. Buffi, E. Scapaticci, et al., “Simplifying Patient Positioning and Port Placement During Robotic‐Assisted Laparoscopic Prostatectomy,” European Urology 57, no. 3 (2010): 530–533, https://doi.org/10.1016/j.eururo.2009.11.028.
S. Park, R. D. Howe, D. F. Torchiana, “Virtual Fixtures for Robotic Cardiac Surgery,” in Lecture Notes in Computer Science, London, UK, (Utrecht: 4th International Conference on Medical Image Computing and Computer‐Assisted Intervention, MICCAI, 2001): 1419–1420.
M. Hayashibe, N. Suzuki, M. Hashizume, et al., “Preoperative Planning System for Surgical Robotics Setup With Kinematics and Haptics,” International Journal of Medical Robotics and Computer Assisted Surgery 1, no. 2 (2005): 76–85, https://doi.org/10.1581/mrcas.2005.010208.
M. Hayashibe, N. Suzuki, M. Hashizume, K. Konishi, A. Hattori, “Robotic Surgery Setup Simulation With the Integration of Inverse Kinematics Computation and Medical Imaging,” Computer Methods and Programs in Biomedicine 83, no. 1 (2006): 63–72, https://doi.org/10.1016/j.cmpb.2006.04.010.
L. W. Sun and C. K. Yeung, “Port placement and pose selection of the da Vinci surgical system for collision‐free intervention based on performance optimization,” in Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems (San Diego: lEEE/RSJ International Conference on Intelligent Robots and Systems, 2007), 1951–1956.
H. Azimian, R. V. Patel, M. D. Naish, et al., “A Framework for Preoperative Planning of Robotics‐Assisted Minimally Invasive Cardiac Surgery (RAMICS) under Geometric Uncertainty,” Proceedings – IEEE International Conference on Robotics and Automation (2011): 5018–5023.
R. Konietschke, T. Bodenmüller, C. Rink, et al., “Optimal Setup of the DLR MiroSurge Telerobotic System for Minimally Invasive Surgery,” in IEEE International Conference on Robotics and Automation (Piscataway, USA: IEEE, 2011), 3435–3436.
K. Liang, S. X. Wang, R. D. Liu, et al., “Preoperative Planning Method for Robot‐Assisted Minimally Invasive Surgery,” Journal of Tianjin University52, no. 9 (2019): 889–899.
Y. Bo, G. Wang, J. Li, et al., “The First Clinical Use of Domestically Produced Chinese Minimally Invasive Surgical Robot System ‘Micro Hand S’,” Surgical Endoscopy 30, no. 6 (2016): 2649–2655, https://doi.org/10.1007/s00464‐015‐4506‐1.
Y. Bo, W. Guohui, L. Zheng, et al., “The Future of Robotic Surgery in Safe Hands,” Nature & Resources. (2020), https://ifbfgdd05cbc5aacc4e82sq66xwbufn5qn6qo0fgcc.eds.tju.edu.cn/collections/ThirdXiangyaHospital.
Y. Yuanbing, L. Yong, L. Zheng, Y. Bo, W. Guohui, Z. Shaihong, “Chinese Surgical Robot Micro Hand S: A Consecutive Case Series in General Surgery,” International Journal of Surgery 75, (2020): 55–59, https://doi.org/10.1016/j.ijsu.2020.01.013.
Y. Lei, J. Jiang, S. Zhu, B. Yi, J. Li, “Comparison of the Short‐Term Efficacy of Two Types of Robotic Total Mesorectal Excision for Rectal Cancer,” Techniques in Coloproctology 26, no. 1 (2022): 19–28, https://doi.org/10.1007/s10151‐021‐02546‐0.
Y. Yang, S. Han, H. Q. Sang, F. Liu, “Preoperative Planning Method Based on a MOPSO Algorithm for Robot‐Assisted Cholecystectomy,” International Journal of Computer Assisted Radiology and Surgery 17, no. 4 (2022): 731–744, https://doi.org/10.1007/s11548‐021‐02547‐2.
Z. Y. Wu, Y. N. Zhao, P. Zhou, et al., “Development and Application of Weighted TOPSIS Software Package for Drug Utilization Evaluation,” China Digital Medicine 18, no. 1 (2023): 67–71.
J. Kennedy and R. Eberhart, “Particle Swarm Optimization,” IEEE International Conference on Neural Networks 4, no. 8 (2002): 1942–1948.
Y. B. Tang, M. Chen, Y. Xing, Y. Wang, H. Wang, Y. Ji, “Validation of a Training System for Laparoscopic Longitudinal Suturing in Lesion,” International Journal of Medical Robotics and Computer Assisted Surgery 20, no. 1 (2024): e2594, https://doi.org/10.1002/rcs.2594.
L. M. Zhang, H. Cui, “Reliability of MUSE 2 and Tobii Pro Nano at Capturing Mobile Application Users' Real‐Time Cognitive Workload Changes,” Front Neurosci‐Switz 16 (2022): 1011475, https://doi.org/10.3389/fnins.2022.1011475.
Y. Ji, Z. Y. Kong, Y. Y. Deng, J. Chen, Y. Liu, L. Zhao, “The Role of Eye Tracker in Teaching Video‐Assisted Thoracoscopic Surgery: The Differences in Visual Strategies Between Novice and Expert Surgeons in Thoracoscopic Surgery,” Annals of Translational Medicine 10, no. 10 (2022): 592, https://doi.org/10.21037/atm‐22‐2145.
M. A. Laribi, M. Arsicault, T. Riviere, et al., “Toward New Minimally Invasive Surgical Robotic System,” in 2012 IEEE International Conference on Industrial Technology, (Athens, GREECE: IEEE International Conference on Industrial Technology, ICIT, 2012), 504–509.
A. L. Trejos and R. V. Patel, “Port Placement for Endoscopic Cardiac Surgery Based on Robot Dexterity Optimization,” in IEEE International Conference on Robotics and Automation (Piscataway, USA: IEEE, 2005), 912–917.
U. Kappert, J. Schneider, R. Cichon, et al., “Development of Robotic Enhanced Endoscopic Surgery for the Treatment of Coronary Artery Disease,” supplement, Circulation 104, no. S1 (2001): S102–S107, https://doi.org/10.1161/circ.104.suppl_1.i‐102.
D. Loulmet, A. Carpentier, N. d'Attellis, et al., “Endoscopic Coronary Artery Bypass Grafting With the Aid of Robotic Assisted Instruments,”Journal of Thoracic and Cardiovascular Surgery 118, no. 1 (1999): 4–10, https://doi.org/10.1016/s0022‐5223(99)70133‐9.
W. Cannon, A. Stoll, D. Selha, P. Dupont, R. Howe, D. Torchiana, “Port Placement Planning in Robot‐Assisted Coronary Artery Bypass,” IEEE Transactions on Robotics and Automation 19, no. 5 (2003): 912–917, https://doi.org/10.1109/tra.2003.817502.
A. Cestari, N. M. Buffi, E. Scapaticci, et al., “Simplifying Patient Positioning and Port Placement During Robotic‐Assisted Laparoscopic Prostatectomy,” European Urology 57, no. 3 (2010): 530–533, https://doi.org/10.1016/j.eururo.2009.11.028.
S. Park, R. D. Howe, D. F. Torchiana, “Virtual Fixtures for Robotic Cardiac Surgery,” in Lecture Notes in Computer Science, London, UK, (Utrecht: 4th International Conference on Medical Image Computing and Computer‐Assisted Intervention, MICCAI, 2001): 1419–1420.
M. Hayashibe, N. Suzuki, M. Hashizume, et al., “Preoperative Planning System for Surgical Robotics Setup With Kinematics and Haptics,” International Journal of Medical Robotics and Computer Assisted Surgery 1, no. 2 (2005): 76–85, https://doi.org/10.1581/mrcas.2005.010208.
M. Hayashibe, N. Suzuki, M. Hashizume, K. Konishi, A. Hattori, “Robotic Surgery Setup Simulation With the Integration of Inverse Kinematics Computation and Medical Imaging,” Computer Methods and Programs in Biomedicine 83, no. 1 (2006): 63–72, https://doi.org/10.1016/j.cmpb.2006.04.010.
L. W. Sun and C. K. Yeung, “Port placement and pose selection of the da Vinci surgical system for collision‐free intervention based on performance optimization,” in Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems (San Diego: lEEE/RSJ International Conference on Intelligent Robots and Systems, 2007), 1951–1956.
H. Azimian, R. V. Patel, M. D. Naish, et al., “A Framework for Preoperative Planning of Robotics‐Assisted Minimally Invasive Cardiac Surgery (RAMICS) under Geometric Uncertainty,” Proceedings – IEEE International Conference on Robotics and Automation (2011): 5018–5023.
R. Konietschke, T. Bodenmüller, C. Rink, et al., “Optimal Setup of the DLR MiroSurge Telerobotic System for Minimally Invasive Surgery,” in IEEE International Conference on Robotics and Automation (Piscataway, USA: IEEE, 2011), 3435–3436.
K. Liang, S. X. Wang, R. D. Liu, et al., “Preoperative Planning Method for Robot‐Assisted Minimally Invasive Surgery,” Journal of Tianjin University52, no. 9 (2019): 889–899.
Y. Bo, G. Wang, J. Li, et al., “The First Clinical Use of Domestically Produced Chinese Minimally Invasive Surgical Robot System ‘Micro Hand S’,” Surgical Endoscopy 30, no. 6 (2016): 2649–2655, https://doi.org/10.1007/s00464‐015‐4506‐1.
Y. Bo, W. Guohui, L. Zheng, et al., “The Future of Robotic Surgery in Safe Hands,” Nature & Resources. (2020), https://ifbfgdd05cbc5aacc4e82sq66xwbufn5qn6qo0fgcc.eds.tju.edu.cn/collections/ThirdXiangyaHospital.
Y. Yuanbing, L. Yong, L. Zheng, Y. Bo, W. Guohui, Z. Shaihong, “Chinese Surgical Robot Micro Hand S: A Consecutive Case Series in General Surgery,” International Journal of Surgery 75, (2020): 55–59, https://doi.org/10.1016/j.ijsu.2020.01.013.
Y. Lei, J. Jiang, S. Zhu, B. Yi, J. Li, “Comparison of the Short‐Term Efficacy of Two Types of Robotic Total Mesorectal Excision for Rectal Cancer,” Techniques in Coloproctology 26, no. 1 (2022): 19–28, https://doi.org/10.1007/s10151‐021‐02546‐0.
Y. Yang, S. Han, H. Q. Sang, F. Liu, “Preoperative Planning Method Based on a MOPSO Algorithm for Robot‐Assisted Cholecystectomy,” International Journal of Computer Assisted Radiology and Surgery 17, no. 4 (2022): 731–744, https://doi.org/10.1007/s11548‐021‐02547‐2.
Z. Y. Wu, Y. N. Zhao, P. Zhou, et al., “Development and Application of Weighted TOPSIS Software Package for Drug Utilization Evaluation,” China Digital Medicine 18, no. 1 (2023): 67–71.
J. Kennedy and R. Eberhart, “Particle Swarm Optimization,” IEEE International Conference on Neural Networks 4, no. 8 (2002): 1942–1948.
Y. B. Tang, M. Chen, Y. Xing, Y. Wang, H. Wang, Y. Ji, “Validation of a Training System for Laparoscopic Longitudinal Suturing in Lesion,” International Journal of Medical Robotics and Computer Assisted Surgery 20, no. 1 (2024): e2594, https://doi.org/10.1002/rcs.2594.
L. M. Zhang, H. Cui, “Reliability of MUSE 2 and Tobii Pro Nano at Capturing Mobile Application Users' Real‐Time Cognitive Workload Changes,” Front Neurosci‐Switz 16 (2022): 1011475, https://doi.org/10.3389/fnins.2022.1011475.
Y. Ji, Z. Y. Kong, Y. Y. Deng, J. Chen, Y. Liu, L. Zhao, “The Role of Eye Tracker in Teaching Video‐Assisted Thoracoscopic Surgery: The Differences in Visual Strategies Between Novice and Expert Surgeons in Thoracoscopic Surgery,” Annals of Translational Medicine 10, no. 10 (2022): 592, https://doi.org/10.21037/atm‐22‐2145.
Grant Information:
2022YFC2409603 National Key Research and Development Program of China
Contributed Indexing:
Keywords: clinical evaluation system; esophageal hiatal hernia repair; particle swarm optimisation; preoperative planning; robot‐assisted minimally invasive surgery
Entry Date(s):
Date Created: 20250217 Date Completed: 20250217 Latest Revision: 20250507
Update Code:
20250508
DOI:
10.1002/rcs.70042
PMID:
39960022
Database:
MEDLINE
Weitere Informationen
Background: Robot-assisted minimally invasive surgery has effectively addressed the challenges faced by traditional minimally invasive surgery. Well-designed preoperative planning is crucial for robot-assisted minimally invasive surgery.
Methods: This paper proposes a preoperative planning method based on a clinical evaluation system. The particle swarm optimisation algorithm and the evaluation indices including accessibility, visibility, operability, and hand-eye coordination are adopted.
Results: The simulation validation and the experimental verification were conducted to compare the pre-operative planning scheme and the clinical scheme, taking the oesophageal hiatal hernia repair as an example. The preoperative planning scheme demonstrated superior accessibility and hand-eye coordination, achieving shorter surgical time and reduced task load.
Conclusion: The proposed preoperative planning method is feasible and effective through simulation and experimentation. This method has potential applications in various surgical robot systems and procedures, which can provide surgical guidance for surgeons in different departments.
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