Skip to main content
SpringerLink
Log in

Handheld robotic needle holder training: slower but better

  • Published:
Surgical Endoscopy Aims and scope Submit manuscript

Abstract

Background

Handheld robotic laparoscopic instruments fill the gap between robotic and conventional instruments, combining the advantages of degrees of freedom and low price. The difficulty and value in learning these new instruments require detailed investigation.

Methods

Forty novice surgeons with no laparoscopic experience were randomly assigned to two groups: conventional instrument group (Group Conv) and robotic instrument group (Group Rob). The same training protocol was used in both groups: after viewing a standard operation film, laparoscopic suture training was administered using the corresponding instruments. After each training period, surgeons were tested using a force-sensing test platform. Maximum force (MF) and impulse (IMP) of operators through each ring were recorded. Learning curves based on MF and IMP for both instruments were compared. Institutional review board approval is not needed for this study.

Results

MF and IMP of both groups decreased with increased training time; the learning curve of Group Conv decreased faster than that of Group Rob. When training time reached 13 h, the MF of Group Rob was significantly lower than that of Group Conv (P < 0.05), while IMP showed no significant difference between the two groups.

Conclusions

Effective training reduces operator MF and IMP, possibly decreasing damage to tissues with both conventional and handheld robotic needle holders. Group Rob took longer to reach a plateau, but subsequently had lower suture tension than did Group Conv. MF is more sensitive than IMP for measuring performance progress.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

IMP:

Impulse

MF:

Maximum force

References

  1. Bann S, Khan M, Hernandez J, Munz Y, Moorthy K, Datta V, Rockall T, Darzi A (2003) Robotics in surgery. J Am Coll Surg 196:784–795

    Article  Google Scholar 

  2. Williams RD (2002) What's new in urology. J Am Coll Surg 195:663–674

    Article  Google Scholar 

  3. Hockstein NG, Gourin CG, Faust RA, Terris DJ (2007) A history of robots: from science fiction to surgical robotics. J Robot Surg 1:113–118

    Article  CAS  Google Scholar 

  4. Kalan S, Chauhan S, Coelho RF, Orvieto MA, Camacho IR, Palmer KJ, Patel VR (2010) History of robotic surgery. J Robot Surg 4:141–147

    Article  Google Scholar 

  5. Casella DP, Fox JA, Schneck FX, Cannon GM, Ost MC (2013) Cost analysis of pediatric robot-assisted and laparoscopic pyeloplasty. J Urol 189:1083–1086

    Article  Google Scholar 

  6. Morelli L, Di Franco G, Lorenzoni V, Guadagni S, Palmeri M, Furbetta N, Gianardi D, Bianchini M, Caprili G, Mosca F, Turchetti G, Cuschieri A (2019) Structured cost analysis of robotic TME resection for rectal cancer: a comparison between the da Vinci Si and Xi in a single surgeon's experience. Surg Endosc 33:1858–1869

    Article  Google Scholar 

  7. Amodeo A, Linares QA, Joseph JV, Belgrano E, Patel HR (2009) Robotic laparoscopic surgery: cost and training. Minerva Urol Nefrol 61:121–128

    CAS  PubMed  Google Scholar 

  8. Zapardiel I, Hernandez A, De Santiago J (2015) The efficacy of robotic driven handheld instruments for the acquisition of basic laparoscopic suturing skills. Eur J Obstet Gynecol Reprod Biol 186:106–109

    Article  Google Scholar 

  9. Sanchez-Margallo JA, Sanchez-Margallo FM (2017) Initial experience using a robotic-driven laparoscopic needle holder with ergonomic handle: assessment of surgeons' task performance and ergonomics. Int J Comput Assist Radiol Surg 12:2069–2077

    Article  Google Scholar 

  10. Bensignor T, Morel G, Reversat D, Fuks D, Gayet B (2016) Evaluation of the effect of a laparoscopic robotized needle holder on ergonomics and skills. Surg Endosc 30:446–454

    Article  Google Scholar 

  11. Feng J, Yang K, Zhang Z, Li M, Chen X, Yan Z, Du Z, Wang X (2019) Handheld laparoscopic robotized instrument: progress or challenge? Surg Endosc. https://doi.org/10.1007/s00464-019-06820-z

    Article  PubMed  Google Scholar 

  12. Horeman T, Rodrigues SP, Jansen FW, Dankelman J, van den Dobbelsteen JJ (2010) Force measurement platform for training and assessment of laparoscopic skills. Surg Endosc 24:3102–3108

    Article  Google Scholar 

  13. Simon J, Finter F, Ignatius A, Meilinger M, Durselen L (2011) Maximum tensile force of different suture techniques in reconstruction of the renal remnant after nephron-sparing surgery. Surg Endosc 25:503–507

    Article  CAS  Google Scholar 

  14. Sieber MA, Fellmann-Fischer B, Mueller M (2017) Performance of Kymerax(c) precision-drive articulating surgical system compared to conventional laparoscopic instruments in a pelvitrainer model. Surg Endosc 31:4298–4308

    Article  Google Scholar 

  15. Sipahi M, Arslan E (2018) A New Needle Holder Design to Facilitate Intracorporeal Knot Tying. Surg Innov 25:199–202

    Article  Google Scholar 

  16. Chandra V, Nehra D, Parent R, Woo R, Reyes R, Hernandez-Boussard T, Dutta S (2010) A comparison of laparoscopic and robotic assisted suturing performance by experts and novices. Surgery 147:830–839

    Article  Google Scholar 

  17. Hardon SF, Horeman T, Bonjer HJ, Meijerink W (2018) Force-based learning curve tracking in fundamental laparoscopic skills training. Surg Endosc 32:3609–3621

    Article  Google Scholar 

  18. Jamshidi R, LaMasters T, Eisenberg D, Duh QY, Curet M (2009) Video self-assessment augments development of videoscopic suturing skill. J Am Coll Surg 209:622–625

    Article  Google Scholar 

  19. Yang K, Perez M, Hubert N, Hossu G, Perrenot C, Hubert J (2017) Effectiveness of an integrated video recording and replaying system in robotic surgical training. Ann Surg 265:521–526

    Article  Google Scholar 

  20. Pernar LIM, Robertson FC, Tavakkoli A, Sheu EG, Brooks DC, Smink DS (2017) An appraisal of the learning curve in robotic general surgery. Surg Endosc 31:4583–4596

    Article  Google Scholar 

  21. Stefanidis D, Hope WW, Korndorffer JR, Markley S, Scott DJ (2010) Initial laparoscopic basic skills training shortens the learning curve of laparoscopic suturing and is cost-effective. J Am Coll Surg 210:436–440

    Article  Google Scholar 

  22. Lee SY, Allen PJ, Sadot E, D’Angelica MI, DeMatteo RP, Fong Y, Jarnagin WR, Kingham TP (2015) Distal pancreatectomy: a single institution’s experience in open, laparoscopic, and robotic approaches. J Am Coll Surg 220:18–27

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank all of the volunteers in this study.

Funding

This work was supported by the youth talent project of the Health Commission of Hubei Province (Grant No. WJ2019Q050) and the Hubei provincial teaching reform research project (Grant No. 2018038).

Author information

Author notes

  1. Jing Feng and Zhiyuan Yan contributed to the work equally and should be regarded as co-first authors

  2. Zhijiang Du and Kun Yang contributed equally to this study and are co-corresponding authors.

Authors and Affiliations

  1. Department of Urology, ZhongNan Hospital, Wuhan University, No. 169 Donghu Road, Wuhan, 430071, Hubei, China

    Jing Feng, Man Li, Zhang Zhang, XiaoJia Chen & Kun Yang

  2. State Key Laboratory of Robotics and System, Harbin Institute of Technology, No. 92, Xidazhi Street, Nangang District, Harbin, 150000, China

    Zhiyuan Yan & Zhijiang Du

  3. Medicine - Remote Mapping Associated Laboratory, ZhongNan Hospital, Wuhan University, Wuhan, China

    Jing Feng, Man Li, Zhang Zhang, XiaoJia Chen & Kun Yang

Authors
  1. Jing Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhiyuan Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Man Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. XiaoJia Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Zhijiang Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Zhijiang Du or Kun Yang.

Ethics declarations

Disclosure

Jing Feng, Zhiyuan Yan, Man Li, Zhang Zhang, XiaoJia Chen, Zhi Jiang Du and Kun Yang declare that they have no conflicts of interest or financial ties to disclose.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary file1 (MP4 37815 kb)

Supplementary file2 (DOCX 451 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Feng, J., Yan, Z., Li, M. et al. Handheld robotic needle holder training: slower but better. Surg Endosc 35, 1667–1674 (2021). https://doi.org/10.1007/s00464-020-07550-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00464-020-07550-3

Keywords

Search

Navigation