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A three-dimensional color-printed system allowing complete modeling of arteriovenous malformations for surgical simulations.

Authors :
Ye, Xun
Wang, Liang
Li, Kai
Hao, Qiang
Lu, Junlin
Chen, Xiaolin
Zhao, Yuanli
Source :
Journal of Clinical Neuroscience; Jul2020, Vol. 77, p134-141, 8p
Publication Year :
2020

Abstract

• 3D printing has been rarely used to model AVMs because of their complexity, especially for the whole and colorful model. • Each AVM model included the nidus, the feeding arteries, the draining veins, the sinuses, the adjacent principal arteries, and the skull. • The models were employed to plan surgical and endovascular treatments. To develope a colored realistic AVM model using three-dimensional (3D) printing for surgical planning and research. Raw computed tomography angiography (CTA) and magnetic resonance venography (MRV) data were integrated and used for reconstruction. Each AVM model included the nidus, the feeding arteries, the draining veins, the sinuses, the adjacent principal arteries, and the skull. The models were employed to plan surgical and endovascular treatments. Surgical feedback was obtained using a survey. Five AVM cases were included. The AVMs and the models thereof did not differ significantly in terms of length, width, or height, as measured via magnetic resonance imaging (all p > 0.05). The 3D AVM models were thus accurate. The overall score on the questionnaire survey was >4 point; the model thus aided the planning of interventional surgery. All surgeons were confident that the 3D models reflected the true lesional boundaries. Our 3D-printed intracranial AVM models were accurate, and can be used for preoperative planning and training of residents. The models improved surgeons' understanding of AVM structure, reducing operative time. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09675868
Volume :
77
Database :
Supplemental Index
Journal :
Journal of Clinical Neuroscience
Publication Type :
Academic Journal
Accession number :
143824902
Full Text :
https://doi.org/10.1016/j.jocn.2020.04.123