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Three-Dimensional Printing Assisted Preoperative Surgical Planning for Cerebral Arteriovenous Malformation

  • Uzunoglu, Inan (Department of Neurosurgery, Katip Celebi University Ataturk Training and Research Hospital) ;
  • Kizmazoglu, Ceren (Department of Neurosurgery, Dokuz Eylul University School of Medicine) ;
  • Husemoglu, Resit Bugra (Department of Biomechanic, Dokuz Eylul University School of Medicine) ;
  • Gurkan, Gokhan (Department of Neurosurgery, Katip Celebi University Ataturk Training and Research Hospital) ;
  • Uzunoglu, Cansu (Department of Neurological Intensive Care, Ege University School of Medicine) ;
  • Atar, Murat (Department of Neurosurgery, Sultan Abdulhamid Han Training and Research Hospital) ;
  • Cakir, Volkan (Department of Interventional Radiology, Tinaztepe University Galen Hospital) ;
  • Aydin, Hasan Emre (Department of Neurosurgery, Dumlupinar University Kutahya Evliya Celebi Training and Research Hospital) ;
  • Sayin, Murat (Department of Neurosurgery, Katip Celebi University Ataturk Training and Research Hospital) ;
  • Yuceer, Nurullah (Department of Neurosurgery, Katip Celebi University Ataturk Training and Research Hospital)
  • Received : 2021.01.20
  • Accepted : 2021.03.19
  • Published : 2021.11.01

Abstract

Objective : The aim of this study to investigate the benefits of patient-based 3-dimensional (3D) cerebral arteriovenous malformation (AVM) models for preoperative surgical planning and education. Methods : Fifteen patients were operated on for AVMs between 2015 and 2019 with patient-based 3D models. Ten patients' preoperative cranial angiogram screenings were evaluated preoperatively or perioperatively via patient-based 3D models. Two patients needed emergent surgical intervention; their models were solely designed based on their AVMs and used during the operation. However, the other patients who underwent elective surgery had the modeling starting from the skull base. These models were used both preoperatively and perioperatively. The benefits of patients arising from treatment with these models were evaluated via patient files and radiological data. Results : Fifteen patients (10 males and five females) between 16 and 66 years underwent surgery. The mean age of the patients was 40.0±14.72. The most frequent symptom patients observed were headaches. Four patients had intracranial bleeding; the symptom of admission was a loss of consciousness. Two patients (13.3%) belonged to Spetzler-Martin (SM) grade I, four (26.7%) belonged to SM grade II, eight (53.3%) belonged to SM grade III, and one (6.7%) belonged to SM grade IV. The mean operation duration was 3.44±0.47 hours. Three patients (20%) developed transient neurologic deficits postoperatively, whereas three other patients died (20%). Conclusion : Several technological innovations have emerged in recent years to reduce undesired outcomes and support the surgical team. For example, 3D models have been employed in various surgical procedures in the last decade. The routine usage of patient-based 3D models will not only support better surgical planning and practice, but it will also be useful in educating assistants and explaining the situation to the patient as well.

Keywords

References

  1. Bervini D, Morgan MK, Ritson EA, Heller G : Surgery for unruptured arteriovenous malformations of the brain is better than conservative management for selected cases: a prospective cohort study. J Neurosurg 121 : 878-890, 2014 https://doi.org/10.3171/2014.7.JNS132691
  2. Burlakoti A, Kumaratilake J, Taylor J, Massy-Westropp N, Henneberg M : The cerebral basal arterial network: morphometry of inflow and outflow components. J Anat 230 : 833-841, 2017 https://doi.org/10.1111/joa.12604
  3. Davies JM, Yanamadala V, Lawton MT : Comparative effectiveness of treatments for cerebral arteriovenous malformations: trends in nationwide outcomes from 2000 to 2009. Neurosurg Focus 33 : E11, 2012
  4. Gruter BE, Mendelowitsch I, Diepers M, Remonda L, Fandino J, Marbacher S : Combined endovascular and microsurgical treatment of arteriovenous malformations in the hybrid operating room. World Neurosurg 117 : e204-e214, 2018 https://doi.org/10.1016/j.wneu.2018.05.241
  5. Gunnal S, Farooqui M, Wabale R : Anatomical variability in the termination of the basilar artery in the human cadaveric brain. Turk Neurosurg 25 : 586-594, 2015
  6. Heros RC, Tu YK : Unruptured arteriovenous malformations: a dilemma in surgical decision making. Clin Neurosurg 33 : 187-236, 1986
  7. Jean WC, Huynh T, Tai AX, Felbaum DR, Syed HR, Ngo HM : Outcome of microsurgery for arteriovenous malformations in a resource-restricted environment: single-surgeon series from vietnam. World Neurosurg 132 : e66-e75, 2019 https://doi.org/10.1016/j.wneu.2019.08.256
  8. Lawton MT, Du R, Tran MN, Achrol AS, McCulloch CE, Johnston SC, et al. : Effect of presenting hemorrhage on outcome after microsurgical resection of brain arteriovenous malformations. Neurosurgery 56 : 485-493; discussion 485-493, 2005 https://doi.org/10.1227/01.NEU.0000153924.67360.EA
  9. Molyneux AJ, Kerr RS, Yu LM, Clarke M, Sneade M, Yarnold JA, et al. : International subarachnoid aneurysm trial (ISAT) of neurosurgical clipping versus endovascular coiling in 2143 patients with ruptured intracranial aneurysms: a randomised comparison of effects on survival, dependency, seizures, rebleeding, subgroups, and aneurysm occlusion. Lancet 366 : 809-817, 2005 https://doi.org/10.1016/S0140-6736(05)67214-5
  10. Potts MB, Lau D, Abla AA, Kim H, Young WL, Lawton MT, et al. : Current surgical results with low-grade brain arteriovenous malformations. J Neurosurg 122 : 912-920, 2015 https://doi.org/10.3171/2014.12.JNS14938
  11. Rhoton AL Jr : The supratentorial cranial space: microsurgical anatomy and surgical approaches. Neurosurgery 51 : S1-iii-S1-vi, 2002
  12. Schramm J, Schaller K, Esche J, Bostrom A : Microsurgery for cerebral arteriovenous malformations: subgroup outcomes in a consecutive series of 288 cases. J Neurosurg 126 : 1056-1063, 2017 https://doi.org/10.3171/2016.4.JNS153017
  13. Spetzler RF, Martin NA : A proposed grading system for arteriovenous malformations. J Neurosurg 65 : 476-483, 1986 https://doi.org/10.3171/jns.1986.65.4.0476
  14. Starke RM, Komotar RJ, Hwang BY, Fischer LE, Garrett MC, Otten ML, et al. : Treatment guidelines for cerebral arteriovenous malformation microsurgery. Br J Neurosurg 23 : 376-386, 2009 https://doi.org/10.1080/02688690902977662
  15. Thawani JP, Pisapia JM, Singh N, Petrov D, Schuster JM, Hurst RW, et al. : Three-dimensional printed modeling of an arteriovenous malformation including blood flow. World Neurosurg 90 : 675-683.e2, 2016 https://doi.org/10.1016/j.wneu.2016.03.095
  16. Theofanis T, Chalouhi N, Dalyai R, Starke RM, Jabbour P, Rosenwasser RH, et al. : Microsurgery for cerebral arteriovenous malformations: postoperative outcomes and predictors of complications in 264 cases. Neurosurg Focus 37 : E10, 2014
  17. Tong X, Wu J, Cao Y, Zhao Y, Wang S, Zhao J : Microsurgical outcome of unruptured brain arteriovenous malformations: a single-center experience. World Neurosurg 99 : 644-655, 2017 https://doi.org/10.1016/j.wneu.2016.12.088
  18. von der Brelie C, Simon M, Esche J, Schramm J, Bostrom A : Seizure outcomes in patients with surgically treated cerebral arteriovenous malformations. Neurosurgery 77 : 762-768, 2015 https://doi.org/10.1227/NEU.0000000000000919
  19. Weinstock P, Prabhu SP, Flynn K, Orbach DB, Smith E : Optimizing cerebrovascular surgical and endovascular procedures in children via personalized 3D printing. J Neurosurg Pediatr 16 : 584-589, 2015 https://doi.org/10.3171/2015.3.PEDS14677
  20. Wong J, Slomovic A, Ibrahim G, Radovanovic I, Tymianski M : Microsurgery for ARUBA trial (a randomized trial of unruptured brain arteriovenous malformation)-eligible unruptured brain arteriovenous malformations. Stroke 48 : 136-144, 2017 https://doi.org/10.1161/STROKEAHA.116.014660