Literature Review of Handheld Articulating Instruments in Minimally Invasive Surgery
Rui Mao, Lei Gao, Gang Wu, Wen Lin
- 发表年份
- 2023
- 引用次数
- 5
摘要
Background: Minimally invasive surgery (MIS) using handheld articulating instruments (HAIs) has emerged as an innovative approach, offering enhanced dexterity and accessibility compared with conventional straight tools. There has been a significant surge in market interest surrounding HAIs. However, the question about the potential benefits of these devices for surgeons and patients in clinical applications remains unclear. Methods: We thoroughly searched relevant literature about the HAIs with clinical applications. This article reviews the feasibility, safety, outcomes, ergonomics, and learning curve associated with utilizing HAIs, including notable commercial products FlexDex, ArtiSential, and HandX. This study also investigates the comparisons of the use of HAIs with traditional laparoscopy and the da Vinci robotic system in terms of surgical outcomes and operational efficiency. Results: Early clinical studies demonstrate the applicability of HAIs across gastrointestinal, urologic, cardiothoracic, and general surgery, with promising results and few complications reported. Comparisons with conventional laparoscopy reveal no significant differences in surgical outcomes. However, HAIs present a more prolonged learning curve than robotic surgery for novice users. Combining three-dimensional visualization techniques facilitate performance. Further research with larger sample sizes is warranted to establish definitive superiority in surgical efficiency and characterize optimal training methodology. Conclusions: Overall, the maneuverability and lower cost of HAIs present new possibilities in MIS, potentially expanding accessibility for smaller health care organizations and benefiting more patients.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002