Neurovascular surgery aims to repair diseased or damaged blood vessels in the brain or spine. There are numerous procedures that fall under this category, and in all of them, the direction of blood flow through these vessels is crucial information. Current methods to determine this information intraoperatively include static pre-operative images combined with augmented reality, Doppler ultrasound, and injectable fluorescent dyes. Each of these systems has inherent limitations. This study includes the proposal and preliminary validation of a technique to identify the direction of blood flow through vessels using only video segments of a few seconds acquired from routinely used surgical microscopes. The video is enhanced to reveal subtle colour fluctuations related to blood pulsation, and these rhythmic signals are further analysed in Fourier space to reveal the direction of blood flow. The proposed method was validated using a novel physical phantom and retrospective analysis of surgical videos and demonstrated high accuracy in identifying the direction of blood flow.

References

1. 1)
  - 5. Knopman, J., Stieg, P.E.: ‘Management of unruptured brain arteriovenous malformations’, Lancet, 2014, 383, (9917), pp. 581–583 (doi: 10.1016/S0140-6736(14)60001-5).
2. 2)
  - 2. Kriss, T.C., Kriss, V.M.: ‘History of the operating microscope: from magnifying glass to microneurosurgery’, Neurosurgery, 1998, 42, (4), p. pp. 899–907 (doi: 10.1097/00006123-199804000-00116).
3. 3)
  - 10. Orrapin, S., Rerkasem, K.: ‘Carotid endarterectomy for symptomatic carotid stenosis’, Cochrane Database Syst. Rev., 2017, 6, (6), p. 281.
4. 4)
  - 21. Farid, H., Woodward, J.B.: ‘Video stabilization and enhancement’, Dartmouth College, 2007, TR2007-605, p. 12.
5. 5)
  - 18. McLeod, A.J., Baxter, J.S.H., Ribaupierre, S.D., et al: ‘Motion magnification for endoscopic surgery’. Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling (Int. Society for Optics and Photonics), San Diego, CA, USA, 2014, vol. 9036, p. 90360C.
6. 6)
  - 4. Kersten-Oertel, M., Gerard, I.J., Drouin, S., et al: ‘Augmented reality in neurovascular surgery: feasibility and first uses in the operating room’, Int. J. Comput. Assist. Radiol. Surg., 2015, 10, (11), pp. 1823–1836 (doi: 10.1007/s11548-015-1163-8).
7. 7)
  - 23. Vassallo, R., Bainbridge, D., Moore, J., et al: ‘A mold design for creating low-cost patient specific models with complex anatomy’. Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, (Int. Society for Optics and Photonics), Houston, TX, USA, 2018, vol. 10576, p. 105761S.
8. 8)
  - 3. Friedlander, R.M.: ‘Arteriovenous malformations of the brain’, N. Engl. J. Med., 2007, 356, (26), pp. 2704–2712 (doi: 10.1056/NEJMcp067192).
9. 9)
  - 4. Rhoten, R.L.P., Comair, Y.G., Shedid, D., et al: ‘Specific repression of the preproendothelin-1 gene in intracranial arteriovenous malformations’, J. Neurosurg., 1997, 86, (1), pp. 101–108 (doi: 10.3171/jns.1997.86.1.0101).
10. 10)
  - 20. Xiao, Y., Rivaz, H., Kasuya, H., et al: ‘Intra-operative video characterization of carotid artery pulsation patterns in case series with post-endarterectomy hypertension and hyperperfusion syndrome’, Transl. Stroke Res., 2018, 9, (5), pp. 452–458 (doi: 10.1007/s12975-017-0605-8).
11. 11)
  - 25. McLeod, A.J., Capaldi, D.P.I., Baxter, J.S.H., et al: ‘Analysis of periodicity in video sequences through dynamic linear modeling’, In, Descoteaux, M., Maier Hein, L., Franz, A. (Eds): ‘Medical image computing and computer-assisted intervention: MICCAI 2017. Lecture notes in computer science’ (Springer International Publishing, USA, 2017, pp. 386–393).
12. 12)
  - 19. Klemm, S., Rexeisen, R., Walter Stummer, M.D., et al: ‘A video processing pipeline for intraoperative analysis of cerebral blood flow’, Comput. Methods Biomech. Biomed. Eng.: Imaging Vis., 2019, pp. 1–11, DOI: 10.1080/21681163.2018.1559771.
13. 13)
  - 12. Ng, Y.P., King, N.K.K., Wan, K.R., et al: ‘Uses and limitations of indocyanine green videoangiography for flow analysis in arteriovenous malformation surgery’, J. Clin. Neurosci., 2013, 20, (2), pp. 224–232 (doi: 10.1016/j.jocn.2011.12.038).
14. 14)
  - 19. Srinidhi, C.L., Aparna, P., Rajan, J.: ‘Recent advancements in retinal vessel segmentation’, J. Med. Syst., 2017, 41, (4), p. 70 (doi: 10.1007/s10916-017-0719-2).
15. 15)
  - 10. Verkruysse, W., Svaasand, L.O., Nelson, J.S.: ‘Remote plethysmographic imaging using ambient light’, Opt. Express, 2008, 16, (26), pp. 21434–21445 (doi: 10.1364/OE.16.021434).
16. 16)
  - 7. Spetzler, R.F., Kondziolka, D.S., Higashida, R.T., et al: ‘Comprehensive management of arteriovenous malformations of the brain and spine’ (Cambridge University Press, Cambridge, UK, 2015).
17. 17)
  - 1. Michalak, S.M., Rolston, J.D., Lawton, M.T.: ‘Incidence and predictors of complications and mortality in cerebrovascular surgery: national trends from 2007 to 2012’, Neurosurgery, 2016, 79, (2), pp. 182–193 (doi: 10.1227/NEU.0000000000001251).
18. 18)
  - 27. Mair, A.T., Vaughan, T.A., Ungi, T., et al: ‘Evaluation of an interactive ultrasound-based breast tumor contouring workflow’. Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling (Int. Society for Optics and Photonics, Orlando, FL, USA, 2017, vol. 10135, p. 101351C.
19. 19)
  - 24. Widmaier, E.P., Raff, H., Strang, K.T.: ‘Vander's human physiology: the mechanisms of body function’ (McGraw-Hill, USA, 2006).
20. 20)
  - 6. Stieg, P.E., Batjer, H.H., Samson, D.: ‘Intracranial arteriovenous malformations’ (CRC Press, Boca Raton, Florida, USA, 2006).
21. 21)
  - 6. Wong, J.M., Ziewacz, J.E., Ho, A.L., et al: ‘Patterns in neurosurgical adverse events: open cerebrovascular neurosurgery’, Neurosurg. Focus, 2012, 33, (5), p. E15 (doi: 10.3171/2012.7.FOCUS12181).
22. 22)
  - 16. Wadhwa, N., Rubinstein, M., Durand, F., et al: ‘Phase-based video motion processing’, ACM Trans. Graph., 2013, 32, (4), p. 80 (doi: 10.1145/2461912.2461966).
23. 23)
  - 11. Hope Ross, M., Yannuzzi, L.A., Gragoudas, E.S., et al: ‘Adverse reactions due to indocyanine green’, Ophthalmology, 1994, 101, (3), pp. 529–533 (doi: 10.1016/S0161-6420(94)31303-0).
24. 24)
  - 13. Vassallo, R., Kasuya, H., Lo, B.W.Y., et al: ‘Augmented reality guidance in cerebrovascular surgery using microscopic video enhancement’, Healthc. Technol. Lett., 2018, 5, (5), pp. 158–161 (doi: 10.1049/htl.2018.5069).
25. 25)
  - 8. Beijnum, J.V., Worp, H.B.V.D., Buis, D.R., et al: ‘Treatment of brain arteriovenous malformations: A systematic review and meta-analysis’, J. Am. Med. Assoc., 2011, 306, (18), pp. 2011–2019 (doi: 10.1001/jama.2011.1632).
26. 26)
  - 15. Wu, H.Y., Rubinstein, M., Shih, E., et al: ‘Eulerian video magnification for revealing subtle changes in the world’, ACM Trans. Graph., 2012, 31, (4), pp. 1–8 (doi: 10.1145/2185520.2185561).
27. 27)
  - 14. Iversen, D.H., Løvstakken, L., Unsgård, G., et al: ‘Automatic intraoperative estimation of blood flow direction during neurosurgical interventions’, Int. J. Comput. Assist. Radiol. Surg., 2018, 13, (5), pp. 693–701 (doi: 10.1007/s11548-018-1711-0).

Determining blood flow direction from short neurovascular surgical microscope videos

References

Related content