Rajamani Allwyn S, Rammohan Ashwin, Mohan Sasikala, Srinivasan Poonguzhali, Arthanari Shanmugam, Muthusamy Umamaheshwaran, Sivasubramanian Vijayanand, Ravichandran Palaniappan
Centre for Medical Electronics, College of Engineering Guindy, Anna University, Chennai, India.
The Institute of Surgical Gastroenterology & Liver Transplantation, Centre for GI Bleed, Division of HPB Diseases, Stanley Medical College Hospital, Old Jail Road, Chennai, India.
World J Surg. 2016 Apr;40(4):773-8. doi: 10.1007/s00268-015-3315-y.
Suturing is an integral part of all surgeries. In minimal access surgery, the force exerted is based only on visual perception (tautness of the thread and degree of tissue deformation). An unbalanced suture force can cause tissue rupture or cut-through resulting in avoidable morbidity and mortality. There is a need to find ways of improving surgical dexterity and finesse without adversely affecting patient outcomes.
We aimed to calculate the knot-tying force in minimal access pancreatic surgery (MAPS) performed by experienced surgeons (ES) and use this information to develop a surgical suturing model to train the surgical trainees. We have developed a firmware for force sensor calibration and post-data analysis, using which we aimed to compare the differences in forces applied by a trainee as compared to ES.
Our technology showed that, as compared to the ES, the trainee's (TS) knot was unbalanced with significant differences in force applied per knot for each of the knots (P < 0.01). The shape of the Force curve for each suture was also different for the TS as compared to the ES. After using the training tool, the forces applied by the TS and the Force curve for the whole suture were similar to those of the ES.
Our firmware promises to be an excellent training tool for organ anastomosis. Considering the complexity and likely complications of MAPS, it is a sine qua non that the surgeon be highly experienced and skilled. Surgical simulation is attractive because it avoids the use of patients for skills practice and provides relevant technical training for trainees before they can safely operate on humans.
缝合是所有手术不可或缺的一部分。在微创手术中，施加的力仅基于视觉感知（线的拉紧程度和组织变形程度）。缝合力不均衡可能导致组织破裂或穿透，从而造成可避免的发病率和死亡率。需要找到在不影响患者预后的情况下提高手术灵活性和精细度的方法。
我们旨在计算经验丰富的外科医生（ES）在微创胰腺手术（MAPS）中打结的力，并利用这些信息开发一个手术缝合模型来培训外科实习生。我们开发了一种用于力传感器校准和数据后分析的固件，旨在比较实习生与经验丰富的外科医生施加力的差异。
我们的技术表明，与经验丰富的外科医生相比，实习生（TS）打的结不均衡，每个结施加的力存在显著差异（P < 0.01）。与经验丰富的外科医生相比，实习生每针缝合的力曲线形状也不同。使用培训工具后，实习生施加的力以及整个缝合过程的力曲线与经验丰富的外科医生相似。
我们的固件有望成为器官吻合的优秀培训工具。考虑到微创胰腺手术的复杂性和可能出现的并发症，外科医生必须经验丰富且技术娴熟。手术模拟很有吸引力，因为它避免了使用患者进行技能练习，并在实习生能够安全地对人体进行手术之前为他们提供相关技术培训。
