Augmented reality in gynecologic surgery: evaluation of potential benefits for myomectomy in an experimental uterine model



Augmented Reality (AR) is a technology that can allow a surgeon to see subsurface structures. This works by overlaying information from another modality, such as MRI and fusing it in real time with the endoscopic images. AR has never been developed for a very mobile organ like the uterus and has never been performed for gynecology. Myomas are not always easy to localize in laparoscopic surgery when they do not significantly change the surface of the uterus, or are at multiple locations.


To study the accuracy of myoma localization using a new AR system compared to MRI-only localization.


Ten residents were asked to localize six myomas (on a uterine model into a laparoscopic box) when either using AR or in conditions that simulate a standard method (only the MRI was available). Myomas were randomly divided in two groups: the control group (MRI only, AR not activated) and the AR group (AR activated). Software was used to automatically measure the distance between the point of contact on the uterine surface and the myoma. We compared these distances to the true shortest distance to obtain accuracy measures. The time taken to perform the task was measured, and an assessment of the complexity was performed.


The mean accuracy in the control group was 16.80 mm [0.1–52.2] versus 0.64 mm [0.01–4.71] with AR. In the control group, the mean time to perform the task was 18.68 [6.4–47.1] s compared to 19.6 [3.9–77.5] s with AR. The mean score of difficulty (evaluated for each myoma) was 2.36 [1–4] versus 0.87 [0–4], respectively, for the control and the AR group.


We developed an AR system for a very mobile organ. This is the first user study to quantitatively evaluate an AR system for improving a surgical task. In our model, AR improves localization accuracy.

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  1. 1.

    Trew G, Pistofidis G, Pados G, Lower A, Mettler L, Wallwiener D et al (2011) Gynaecological endoscopic evaluation of 4 % icodextrin solution: a European, multicentre, double-blind, randomized study of the efficacy and safety in the reduction of de novo adhesions after laparoscopic gynaecological surgery. Hum Reprod 26(8):2015–2027

  2. 2.

    Desai P, Patel P (2011) Fibroids, infertility and laparoscopic myomectomy. J Gynecol Endosc Surg 2(1):36–42

  3. 3.

    Marescaux J, Rubino F, Arenas M, Mutter D, Soler L (2004) Augmented-reality-assisted laparoscopic adrenalectomy. JAMA 292(18):2214–2215

  4. 4.

    Pessaux P, Diana M, Soler L, Piardi T, Mutter D, Marescaux J (2014) Towards cybernetic surgery: robotic and augmented reality-assisted liver segmentectomy. Langenbecks Arch Surg 400(3):381–385

  5. 5.

    Pessaux P, Diana M, Soler L, Piardi T, Mutter D, Marescaux J (2014) Robotic duodenopancreatectomy assisted with augmented reality and real-time fluorescence guidance. Surg Endosc 28(8):2493–2498

  6. 6.

    Nakamoto M, Nakada K, Sato Y, Konishi K, Hashizume M, Tamura S (2008) Intraoperative magnetic tracker calibration using a magneto-optic hybrid tracker for 3-D ultrasound-based navigation in laparoscopic surgery. IEEE Trans Med Imaging 27(2):255–270

  7. 7.

    Simpfendorfer T, Baumhauer M, Muller M, Gutt CN, Meinzer HP, Rassweiler JJ et al (2011) Augmented reality visualization during laparoscopic radical prostatectomy. J Endourol 25(12):1841–1845

  8. 8.

    Soler L, Nicolau S, Pessaux P, Mutter D, Marescaux J (2014) Real-time 3D image reconstruction guidance in liver resection surgery. Hepatobiliary Surg Nutr 3(2):73–81

  9. 9.

    Grimson WL, Ettinger GJ, White SJ, Lozano-Perez T, Wells WM, Kikinis R (1996) An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization. IEEE Trans Med Imaging 15(2):129–140

  10. 10.

    Collins T, Pizarro D, Bartoli A, Canis M, Bourdel N (2013) Realtime wide-baseline registration of the uterus in laparoscopic videos using multiple texture maps. In: Liao H, Linte C, Masamune K, Peters T, Zheng G (eds) Augmented reality environments for medical imaging and computer-assisted interventions. Lecture notes in computer science, 8090. Springer, Berlin, pp 162–171

  11. 11.

    Wilson MR, Poolton JM, Malhotra N, Ngo K, Bright E, Masters RS (2011) Development and validation of a surgical workload measure: the surgery task load index (SURG-TLX). World J Surg 35(9):1961–1969

  12. 12.

    Sharma N, Aggarwal LM (2010) Automated medical image segmentation techniques. J Med Phys 35(1):3–14

  13. 13.

    Rizzo S, Calareso G, De Maria F, Zanagnolo V, Lazzari R, Cecconi A et al (2013) Gynecologic tumors: how to communicate imaging results to the surgeon. Cancer Imaging 13(4):611–625

  14. 14.

    Alleemudder A, King P, Mehta S (2014) Point of technique: reducing wrong-side errors for endourology procedures. Urology 84(6):1541–1543

  15. 15.

    Neily J, Mills PD, Eldridge N, Dunn EJ, Samples C, Turner JR et al (2009) Incorrect surgical procedures within and outside of the operating room. Arch Surg 144(11):1028–1034

  16. 16.

    Irace C, Corona C (2010) How to avoid wrong-level and wrong-side errors in lumbar microdiscectomy. J Neurosurg Spine 12(6):660–665

  17. 17.

    Togashi K, Nakai A, Sugimura K (2001) Anatomy and physiology of the female pelvis: MR imaging revisited. J Magn Reson Imaging 13(6):842–849

  18. 18.

    Metwally M, Farquhar CM, Li TC (2011) Is another meta-analysis on the effects of intramural fibroids on reproductive outcomes needed? Reprod Biomed Online 23(1):2–14

  19. 19.

    Sinha R, Hegde A, Mahajan C, Dubey N, Sundaram M (2008) Laparoscopic myomectomy: do size, number, and location of the myomas form limiting factors for laparoscopic myomectomy? J Minim Invasive Gynecol 15(3):292–300

  20. 20.

    Shimanuki H, Takeuchi H, Kikuchi I, Kumakiri J, Kinoshita K (2006) Effectiveness of intraoperative ultrasound in reducing recurrent fibroids during laparoscopic myomectomy. J Reprod Med 51(9):683–688

  21. 21.

    Doridot V, Dubuisson JB, Chapron C, Fauconnier A, Babaki-Fard K (2001) Recurrence of leiomyomata after laparoscopic myomectomy. J Am Assoc Gynecol Laparosc 8(4):495–500

  22. 22.

    Nezhat FR, Roemisch M, Nezhat CH, Seidman DS, Nezhat CR (1998) Recurrence rate after laparoscopic myomectomy. J Am Assoc Gynecol Laparosc. 5(3):237–240

  23. 23.

    Hanafi M (2005) Predictors of leiomyoma recurrence after myomectomy. Obstet Gynecol 105(4):877–881

  24. 24.

    Griffin L, Feinglass J, Garrett A, Henson A, Cohen L, Chaudhari A et al (2013) Postoperative outcomes after robotic versus abdominal myomectomy. JSLS. 17(3):407–413

  25. 25.

    Khan AT, Shehmar M, Gupta JK (2014) Uterine fibroids: current perspectives. Int J Womens Health 6:95–114

  26. 26.

    Tan N, McClure TD, Tarnay C, Johnson MT, Lu DS, Raman SS (2014) Women seeking second opinion for symptomatic uterine leiomyoma: role of comprehensive fibroid center. J Ther Ultrasound 2:3

  27. 27.

    Zawin M, McCarthy S, Scoutt LM, Comite F (1990) High-field MRI and US evaluation of the pelvis in women with leiomyomas. Magn Reson Imaging 8(4):371–376

  28. 28.

    Dueholm M, Lundorf E, Hansen ES, Ledertoug S, Olesen F (2002) Accuracy of magnetic resonance imaging and transvaginal ultrasonography in the diagnosis, mapping, and measurement of uterine myomas. Am J Obstet Gynecol 186(3):409–415

  29. 29.

    Byun JY, Kim SE, Choi BG, Ko GY, Jung SE, Choi KH (1999) Diffuse and focal adenomyosis: MR imaging findings. Radiographics 19:161–170

  30. 30.

    Cohen J (1998) Statistical power analysis for the behavioral sciences, 2nd edn. Lawrence Erlbaum Associates, New Jersey

  31. 31.

    Bartoli A, Collins T, Bourdel N, Canis M (2012) Computer assisted minimally invasive surgery: is medical computer vision the answer to improving laparosurgery? Med Hypotheses 79(6):858–863

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We want to thank Rochette E. and Comptour A. (assistance in proofreading the article).

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Correspondence to Nicolas Bourdel.

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N. Bourdel, T. Collins, D. Pizarro, A. Bartoli, D. Da Ines, B. Pereira, M. Canis have no conflicts of interest or financial ties to disclose.

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Supplemental Material Figure 1

Virtual MRI of the uterus model. Top left, top right and bottom left show axial, sagittal and coronal slices, respectively. Bottom right show slices oriented in the 3D volume. (TIFF 1521 kb)

Supplementary material 2 (MOV 105773 kb)

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Bourdel, N., Collins, T., Pizarro, D. et al. Augmented reality in gynecologic surgery: evaluation of potential benefits for myomectomy in an experimental uterine model. Surg Endosc 31, 456–461 (2017) doi:10.1007/s00464-016-4932-8

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  • Gynecologic surgery
  • Laparoscopy
  • Augmented Reality
  • Myomectomy
  • MRI