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http://dx.doi.org/10.3340/jkns.2021.0016

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)
Publication Information
Journal of Korean Neurosurgical Society / v.64, no.6, 2021 , pp. 882-890 More about this Journal
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
Intracranial arteriovenous malformations; Three-dimensional printing; Spetzler-Martin grade;
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