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Proceedings Paper

Advanced 3D mesh manipulation in stereolithographic files and post-print processing for the manufacturing of patient-specific vascular flow phantoms
Author(s): Ryan P. O'Hara; Arpita Chand; Sowmya Vidiyala; Stacie M. Arechavala; Dimitrios Mitsouras; Stephen Rudin; Ciprian N. Ionita
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Paper Abstract

Complex vascular anatomies can cause the failure of image-guided endovascular procedures. 3D printed patient-specific vascular phantoms provide clinicians and medical device companies the ability to preemptively plan surgical treatments, test the likelihood of device success, and determine potential operative setbacks. This research aims to present advanced mesh manipulation techniques of stereolithographic (STL) files segmented from medical imaging and post-print surface optimization to match physiological vascular flow resistance. For phantom design, we developed three mesh manipulation techniques. The first method allows outlet 3D mesh manipulations to merge superfluous vessels into a single junction, decreasing the number of flow outlets and making it feasible to include smaller vessels. Next we introduced Boolean operations to eliminate the need to manually merge mesh layers and eliminate errors of mesh self-intersections that previously occurred. Finally we optimize support addition to preserve the patient anatomical geometry. For post-print surface optimization, we investigated various solutions and methods to remove support material and smooth the inner vessel surface. Solutions of chloroform, alcohol and sodium hydroxide were used to process various phantoms and hydraulic resistance was measured and compared with values reported in literature. The newly mesh manipulation methods decrease the phantom design time by 30 - 80% and allow for rapid development of accurate vascular models. We have created 3D printed vascular models with vessel diameters less than 0.5 mm. The methods presented in this work could lead to shorter design time for patient specific phantoms and better physiological simulations.

Paper Details

Date Published: 25 March 2016
PDF: 10 pages
Proc. SPIE 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, 978909 (25 March 2016); doi: 10.1117/12.2217036
Show Author Affiliations
Ryan P. O'Hara, Toshiba Stroke and Vascular Research Ctr. (United States)
Univ. at Buffalo (United States)
Arpita Chand, Toshiba Stroke and Vascular Research Ctr. (United States)
Univ. at Buffalo (United States)
Sowmya Vidiyala, Toshiba Stroke and Vascular Research Ctr. (United States)
Univ. at Buffalo (United States)
Stacie M. Arechavala, Toshiba Stroke and Vascular Research Ctr. (United States)
Univ. of Miami (United States)
Dimitrios Mitsouras, Brigham and Women's Hospital (United States)
Stephen Rudin, Univ. at Buffalo (United States)
Ciprian N. Ionita, Toshiba Stroke and Vascular Research Ctr. (United States)
Univ. at Buffalo (United States)


Published in SPIE Proceedings Vol. 9789:
Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations
Jianguo Zhang; Tessa S. Cook, Editor(s)

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