Evaluation of suturing performance in general surgery and ocular microsurgery by combining computer vision-based software and distributed fiber optic strain sensors: a proof-of-concept

Purpose Improper suturing may cause an inadequate wound healing process and wound dehiscence as well as infection and even graft rejection in case of corneal transplantation. Hence, training surgeons in correct suturing procedures and objectively assessing their surgical skills is desirable. Methods Two complementary methods for assessment of suturing skills in two medical fields (general surgery and ocular microsurgery) were demonstrated. Suturing quality is assessed by computer vision software. Evaluation of stitching flow of operation is based on measuring strain induced in an optical fiber that is placed in proximity to the wound and parallel thereto and is pressed and passed by wound stitches. Results Our software generated a score for suturing outcome in both general surgery and ocular microsurgery when the stitching was done on a patch. Every trainee received a score in the range 0–100 that describes his/her performance. Strain values were recognized when using a patch in general surgery and a rubber patch in ocular microsurgery, but were less distinct in (disqualified) human cornea. Conclusions We proved a concept of an objective scoring method (based on various image processing algorithms) for assessment of suturing performance. It was also shown that fiber optic strain sensors are sensitive to the flow of stitching operation on a patch but are less sensitive to the flow of stitching operation on a human cornea. By combining these two methods, we can comprehensively evaluate the suturing performance objectively.

[1]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[2]  E. Verdaasdonk,et al.  Objective assessment of technical surgical skills , 2010, The British journal of surgery.

[3]  Liang Ren,et al.  Mechanical Property and Strain Transferring Mechanism in Optical Fiber Sensors , 2012 .

[4]  Keat Ghee Ong,et al.  A Wireless Sensor for Real-Time Monitoring of Tensile Force on Sutured Wound Sites , 2016, IEEE Transactions on Biomedical Engineering.

[5]  Luca Schenato,et al.  Distributed Optical Fiber Sensing Based on Rayleigh Scattering , 2013 .

[6]  R Brent Gillespie,et al.  The Objective Assessment of Experts’ and Novices’ Suturing Skills Using An Image Analysis Program , 2013, Academic medicine : journal of the Association of American Medical Colleges.

[7]  Philippe Zanne,et al.  Stitching Planning in Laparoscopic Surgery: Towards Robot-assisted Suturing , 2009, Int. J. Robotics Res..

[8]  A. Darzi,et al.  Assessing operative skill , 1999, BMJ.

[9]  Atsuo Takanishi,et al.  Development of the suture/ligature training system WKS-2 designed to provide more detailed information of the task performance , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Saeed Alwadani Cataract surgery training using surgical simulators and wet-labs: Course description and literature review , 2018, Saudi journal of ophthalmology : official journal of the Saudi Ophthalmological Society.

[11]  Jenny Dankelman,et al.  Force Sensing in Surgical Sutures , 2013, PloS one.

[12]  W. Hop,et al.  Abdominal Wound Dehiscence in Adults: Development and Validation of a Risk Model , 2009, World Journal of Surgery.

[13]  Jenny Dankelman,et al.  Visual force feedback improves knot-tying security. , 2014, Journal of surgical education.

[14]  Anand Jagannathan,et al.  Development of computer vision algorithm towards assessment of suturing skill , 2017, 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

[15]  Ajit K. Sachdeva,et al.  American College of Surgeons/Association for Surgical Education medical student simulation-based surgical skills curriculum needs assessment. , 2014, American journal of surgery.

[16]  Makoto Hashizume,et al.  Objective assessment of the suture ligature method for the laparoscopic intestinal anastomosis model using a new computerized system , 2015, Surgical Endoscopy.

[17]  Robert G. Radwin,et al.  Modeling Surgical Technical Skill Using Expert Assessment for Automated Computer Rating , 2017, Annals of surgery.

[18]  Zhi Zhou,et al.  Advances of strain transfer analysis of optical fibre sensors , 2014 .

[19]  David C. Pye,et al.  Young’s Modulus in Normal Corneas and the Effect on Applanation Tonometry , 2008, Optometry and vision science : official publication of the American Academy of Optometry.

[20]  M. Macsai Ophthalmic microsurgical suturing techniques , 2007 .

[21]  A Cuschieri,et al.  Objective assessment of endoscopic knot quality. , 1997, American journal of surgery.

[22]  Ara Darzi,et al.  The surgical efficiency score: a feasible, reliable, and valid method of skills assessment. , 2006, American journal of surgery.

[23]  Carla M. Pugh,et al.  A Simulator for Measuring Forces During Surgical Knots , 2016, MMVR.