Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): Phase I: Segmentation
Advanced morphology analysis and image-based hemodynamic simulations are increasingly used to assess the rupture risk of intracranial aneurysms (IAs). However, the accuracy of those results strongly depends on the quality of the vessel wall segmentation.
To evaluate state-of-the-art segmentation approaches, the Multiple Aneurysms AnaTomy CHallenge (MATCH) was announced. Participants carried out segmentation in three anonymized 3D DSA datasets (left and right anterior, posterior circulation) of a patient harboring five IAs. Qualitative and quantitative inter-group comparisons were carried out with respect to aneurysm volumes and ostia. Further, over- and undersegmentation were evaluated based on highly resolved 2D images. Finally, clinically relevant morphological parameters were calculated.
Based on the contributions of 26 participating groups, the findings reveal that no consensus regarding segmentation software or underlying algorithms exists. Qualitative similarity of the aneurysm representations was obtained. However, inter-group differences occurred regarding the luminal surface quality, number of vessel branches considered, aneurysm volumes (up to 20%) and ostium surface areas (up to 30%). Further, a systematic oversegmentation of the 3D surfaces was observed with a difference of approximately 10% to the highly resolved 2D reference image. Particularly, the neck of the ruptured aneurysm was overrepresented by all groups except for one. Finally, morphology parameters (e.g., undulation and non-sphericity) varied up to 25%.
MATCH provides an overview of segmentation methodologies for IAs and highlights the variability of surface reconstruction. Further, the study emphasizes the need for careful processing of initial segmentation results for a realistic assessment of clinically relevant morphological parameters.
KeywordsChallenge Intracranial aneurysm Morphology Segmentation
The authors acknowledge Thomas Hoffmann and Dr. Axel Boese (University of Magdeburg, Germany) for their assistance regarding the challenge design.
This study was funded by the Federal Ministry of Education and Research in Germany within the Forschungscampus STIMULATE (Grant Number 13GW0095A) and the German Research Foundation (Grant Number 399581926).
Conflict of interest
Authors Philipp Berg, Samuel Voß, Sylvia Saalfeld, Gábor Janiga, Aslak W. Bergersen, Kristian Valen-Sendstad, Jan Bruening, Leonid Goubergrits, Andreas Spuler, Nicole M. Cancelliere, David A. Steinman, Vitor M. Pereira, Tin Lok Chiu, Anderson Chun On Tsang, Bong Jae Chung, Juan R. Cebral, Salvatore Cito, Jordi Pallarès, Gabriele Copelli, Benjamin Csippa, György Paál, Soichiro Fujimura, Hiroyuki Takao, Simona Hodis, Georg Hille, Christof Karmonik, Saba Elias, Kerstin Kellermann, Muhammad Owais Khan, Alison L. Marsden, Hernán G. Morales, Senol Piskin, Ender A. Finol, Mariya Pravdivtseva, Hamidreza Rajabzadeh-Oghaz, Nikhil Paliwal, Hui Meng, Santhosh Seshadhri, Matthew Howard, Masaaki Shojima, MD, Shin-ichiro Sugiyama, Kuniyasu Niizuma, Sergey Sindeev, Sergey Frolov, Thomas Wagner, Alexander Brawanski, Yi Qian, Yu-An Wu, Kent Carlson, Dan Dragomir-Daescu, and Oliver Beuing declare that they have no conflicts of interest.
This article does not contain any studies with human participants or animals performed by any of the authors. Institutional Review Board approval was obtained from University Hospital Magdeburg for sharing of the anonymized images.
- 5.Berg, P., D. Stucht, G. Janiga, O. Beuing, O. Speck, and D. Thévenin. Cerebral blood flow in a healthy Circle of Willis and two intracranial aneurysms: computational fluid dynamics versus four-dimensional phase-contrast magnetic resonance imaging. J. Biomech. Eng. 2014. https://doi.org/10.1115/1.4026108.Google Scholar
- 20.Dhar, S., M. Tremmel, J. Mocco, et al. Morphology parameters for intracranial aneurysm rupture risk assessment. Neurosurgery 63:185–196; discussion 196–197, 2008.Google Scholar
- 21.Fiorella, D., C. Sadasivan, H. H. Woo, and B. Lieber. Regarding “Aneurysm rupture following treatment with flow-diverting stents: computational hemodynamics analysis of treatment”. Am. J. Neuroradiol. 32:E95–E97; author reply E98–E100, 2011.Google Scholar
- 23.Geers, A. J., I. Larrabide, A. G. Radaelli, et al. Reproducibility of image-based computational hemodynamics in intracranial aneurysms: comparison of CTA and 3D-RA. 2009 IEEE Int. Symp. Biomed. Imaging Nano Macro (ISBI), pp. 610–613.Google Scholar
- 37.Niemann, U., P. Berg, A. Niemann, et al. Rupture status classification of intracranial aneurysms using morphological parameters. 31st IEEE CBMS Int. Symp. Comput.-Based Med. Syst., Karlstad, Sweden, 2018.Google Scholar
- 41.Saalfeld, S., P. Berg, A. Niemann, M. Luz, B. Preim, and O. Beuing. Semi-automatic neck curve reconstruction for intracranial aneurysm rupture risk assessment based on morphological parameters. Int. J. Comput. Assist. Radiol. Surg. 2018 (accepted for publication).Google Scholar
- 45.Valen-Sendstad, K., A. W. Bergersen, Y. Shimogonya, et al. Real-world variability in the prediction of intracranial aneurysm wall shear stress: the 2015 International Aneurysm CFD Challenge. Cardiovasc. Eng. Technol. 2018 (accepted for publication).Google Scholar