Download PDF
J Neurol Surg B Skull Base 2017; 78(03): 222-226
DOI: 10.1055/s-0036-1597136
Original Article
Georg Thieme Verlag KG Stuttgart · New York

An Automated Methodology for Assessing Anatomy-Specific Instrument Motion during Endoscopic Endonasal Skull Base Surgery

R. Alex Harbison
1   Department of Otolaryngology - Head and Neck Surgery, University of Washington School of Medicine, Seattle, Washington, United States
,
Yangming Li
2   Department of Electrical Engineering, University of Washington, Seattle, Washington, United States
,
Angelique M. Berens
1   Department of Otolaryngology - Head and Neck Surgery, University of Washington School of Medicine, Seattle, Washington, United States
,
Randall A. Bly
3   Seattle Children's Hospital, Department of Otolaryngology - Head and Neck Surgery, University of Washington School of Medicine, Seattle, Washington, United States
,
Blake Hannaford
2   Department of Electrical Engineering, University of Washington, Seattle, Washington, United States
,
Kris S. Moe
1   Department of Otolaryngology - Head and Neck Surgery, University of Washington School of Medicine, Seattle, Washington, United States
› Author Affiliations
Further Information

Publication History

21 June 2016

24 October 2016

Publication Date:
20 December 2016 (online)

Also available at
   Permissions and Reprints

Abstract

Objectives Describe instrument motion during live endoscopic skull base surgery (ESBS) and evaluate kinematics within anatomic regions.

Design Case series.

Setting Tertiary academic center.

Participants A single skull base surgeon performed six anterior skull base approaches to the pituitary.

Main Outcomes and Measures Time-stamped instrument coordinates were recorded using an optical tracking system. Kinematics (i.e., mean cumulative instrument travel, velocity, acceleration, and angular velocity) was calculated by anatomic region including nasal vestibule, anterior and posterior ethmoid, sphenoid, and lateral opticocarotid recess (lOCR) regions.

Results We observed mean (standard deviation, SD) velocities of 6.14 cm/s (1.55) in the nasal vestibule versus 1.65 cm/s (0.34) near the lOCR. Mean (SD) acceleration was 7,480 cm/s2 (5790) in the vestibule versus 928 cm/s2 (662) near the lOCR. Mean (SD) angular velocity was 17.2 degrees/s (8.31) in the vestibule and 5.37 degrees/s (1.09) near the lOCR. We observed a decreasing trend in the geometric mean velocity, acceleration, and angular velocity when approaching the pituitary (p < 0.001).

Conclusion Using a novel method for analyzing instrument motion during live ESBS, we observed a decreasing trend in kinematics with proximity to the pituitary. Additional characterization of surgical instrument motion is paramount for optimizing patient safety and training.

Keywords

surgical instrument motion - surgical kinematics - endoscopic skull base surgery - surgical safety - surgical training

Supplementary Material

 

  • References

  • 1 Chin OY, Ghosh R, Fang CH, Baredes S, Liu JK, Eloy JA. Internal carotid artery injury in endoscopic endonasal surgery: A systematic review. Laryngoscope 2016; 126 (03) 582-590
    CrossrefPubMedSearch in Google Scholar
  • 2 Birkmeyer JD, Finks JF, O'Reilly A. , et al; Michigan Bariatric Surgery Collaborative. Surgical skill and complication rates after bariatric surgery. N Engl J Med 2013; 369 (15) 1434-1442
    CrossrefPubMedSearch in Google Scholar
  • 3 Datta V, Mackay S, Mandalia M, Darzi A. The use of electromagnetic motion tracking analysis to objectively measure open surgical skill in the laboratory-based model. J Am Coll Surg 2001; 193 (05) 479-485
    CrossrefPubMedSearch in Google Scholar
  • 4 Datta V, Mandalia M, Mackay S, Chang A, Cheshire N, Darzi A. Relationship between skill and outcome in the laboratory-based model. Surgery 2002; 131 (03) 318-323
    CrossrefPubMedSearch in Google Scholar
  • 5 Bann SD, Khan MS, Darzi AW. Measurement of surgical dexterity using motion analysis of simple bench tasks. World J Surg 2003; 27 (04) 390-394
    CrossrefPubMedSearch in Google Scholar
  • 6 Dosis A, Aggarwal R, Bello F. , et al. Synchronized video and motion analysis for the assessment of procedures in the operating theater. Arch Surg 2005; 140 (03) 293-299
    CrossrefPubMedSearch in Google Scholar
  • 7 Aggarwal R, Grantcharov T, Moorthy K. , et al. An evaluation of the feasibility, validity, and reliability of laparoscopic skills assessment in the operating room. Ann Surg 2007; 245 (06) 992-999
    CrossrefPubMedSearch in Google Scholar
  • 8 Verner L, Oleynikov D, Holtmann S, Haider H, Zhukov L. Measurements of the level of surgical expertise using flight path analysis from da Vinci robotic surgical system. Stud Health Technol Inform 2003; 94: 373-378
    PubMedSearch in Google Scholar
  • 9 Lin HC, Shafran I, Yuh D, Hager GD. Towards automatic skill evaluation: detection and segmentation of robot-assisted surgical motions. Comput Aided Surg 2006; 11 (05) 220-230
    CrossrefPubMedSearch in Google Scholar
  • 10 Rosen J, Solazzo M, Hannaford B, Sinanan M. Objective laparoscopic skills assessments of surgical residents using Hidden Markov models based on haptic information and tool/tissue interactions. Stud Health Technol Inform 2001; 81: 417-423
    PubMedSearch in Google Scholar
  • 11 Rosen J, Solazzo M, Hannaford B, Sinanan M. Task decomposition of laparoscopic surgery for objective evaluation of surgical residents' learning curve using hidden Markov model. Comput Aided Surg 2002; 7 (01) 49-61
    CrossrefPubMedSearch in Google Scholar
  • 12 Ahmidi N, Hager GD, Ishii L, Gallia GL, Ishii M. Robotic path planning for surgeon skill evaluation in minimally-invasive sinus surgery. Med Image Comput Comput Assist Interv 2012; 15 (Pt 1): 471-478
    PubMedSearch in Google Scholar
  • 13 Ahmidi N, Ishii M, Fichtinger G, Gallia GL, Hager GD. An objective and automated method for assessing surgical skill in endoscopic sinus surgery using eye-tracking and tool-motion data. Int Forum Allergy Rhinol 2012; 2 (06) 507-515
    CrossrefPubMedSearch in Google Scholar
  • 14 Ahmidi N, Poddar P, Jones JD. , et al. Automated objective surgical skill assessment in the operating room from unstructured tool motion in septoplasty. Int J CARS 2015; 10 (06) 981-991
    CrossrefPubMedSearch in Google Scholar
  • 15 Fedorov A, Beichel R, Kalpathy-Cramer J. , et al. 3D slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 2012; 30 (09) 1323-1341
    CrossrefPubMedSearch in Google Scholar
  • 16 Kassam AB, Prevedello DM, Carrau RL. , et al. Endoscopic endonasal skull base surgery: analysis of complications in the authors' initial 800 patients. J Neurosurg 2011; 114 (06) 1544-1568
    CrossrefPubMedSearch in Google Scholar
  • 17 Trudeau MO, Nasr A, Carrillo B, Gerstle JT, Azzie G. Construct validity and educational role for motion analysis in a laparoscopic trainer. Surg Endosc 2015; 29 (09) 2491-2495
    CrossrefPubMedSearch in Google Scholar
  • 18 Watson RA. Computer-aided feedback of surgical knot tying using optical tracking. J Surg Educ 2012; 69 (03) 306-310
    CrossrefPubMedSearch in Google Scholar
  • 19 Uemura M, Tomikawa M, Kumashiro R. , et al. Analysis of hand motion differentiates expert and novice surgeons. J Surg Res 2014; 188 (01) 8-13
    CrossrefPubMedSearch in Google Scholar