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Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): Phase I: Segmentation

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Abstract

Purpose

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.

Methods

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.

Results

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%.

Conclusions

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.

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Acknowledgments

The authors acknowledge Thomas Hoffmann and Dr. Axel Boese (University of Magdeburg, Germany) for their assistance regarding the challenge design.

Funding

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.

Ethical Approval

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.

Author information

Authors and Affiliations

  1. Department of Fluid Dynamics and Technical Flows, University of Magdeburg, Magdeburg, Germany

    Philipp Berg, Samuel Voß & Gábor Janiga

  2. Department of Simulation and Graphics, University of Magdeburg, Magdeburg, Germany

    Sylvia Saalfeld & Georg Hille

  3. Institute of Neuroradiology, University Hospital Magdeburg, Magdeburg, Germany

    Oliver Beuing

  4. Forschungscampus STIMULATE, Magdeburg, Germany

    Philipp Berg, Samuel Voß, Sylvia Saalfeld, Gábor Janiga & Oliver Beuing

  5. Department of Computational Physiology, Simula Research Laboratory, Lysaker, Norway

    Aslak W. Bergersen & Kristian Valen-Sendstad

  6. Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité – Universitätsmedizin Berlin, Berlin, Germany

    Jan Bruening & Leonid Goubergrits

  7. Neurosurgery Department, Helios Hospital Berlin Buch, Berlin, Germany

    Andreas Spuler

  8. Division of Neuroradiology, Joint Department of Medical Imaging, Toronto Western Hospital, University Health Network, Toronto, ON, Canada

    Nicole M. Cancelliere & Vitor M. Pereira

  9. Biomedical Simulation Laboratory, Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada

    David A. Steinman

  10. Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University Health Network, Toronto, ON, Canada

    Vitor M. Pereira

  11. Department of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong

    Tin Lok Chiu

  12. Division of Neurosurgery, Department of Surgery, The University of Hong Kong, Pokfulam, Hong Kong

    Anderson Chun On Tsang

  13. Bioengineering Department, Volgenau School of Engineering, George Mason University, Fairfax, VA, USA

    Bong Jae Chung & Juan R. Cebral

  14. Departament d’Enginyeria Mecànica, Universitat Rovira i Virgili, Tarragona, Spain

    Salvatore Cito & Jordi Pallarès

  15. Department of Industrial Engineering, University of Parma, Parma, Italy

    Gabriele Copelli

  16. Department of Hydrodynamic Systems, Budapest University of Technology and Economics, Budapest, Hungary

    Benjamin Csippa & György Paál

  17. Graduate School of Mechanical Engineering, Tokyo University of Science, Katsushika-ku, Tokyo, Japan

    Soichiro Fujimura & Hiroyuki Takao

  18. Department of Innovation for Medical Information Technology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan

    Soichiro Fujimura & Hiroyuki Takao

  19. Department of Neurosurgery, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan

    Hiroyuki Takao

  20. Department of Mathematics, Texas A&M University, Kingsville, USA

    Simona Hodis

  21. MRI Core, Houston Methodist Research Institute, Houston, TX, USA

    Christof Karmonik & Saba Elias

  22. Dornheim Medical Images GmbH, Magdeburg, Germany

    Kerstin Kellermann

  23. Stanford University, Stanford, CA, USA

    Muhammad Owais Khan & Alison L. Marsden

  24. Philips Research, Paris, France

    Hernán G. Morales

  25. Centro de Investigación en Fisiología del Ejercicio, Facultad de Ciencias, Universidad Mayor, Santiago de Chile, Chile

    Hernán G. Morales

  26. Department of Mechanical Engineering, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX, 78249, USA

    Senol Piskin & Ender A. Finol

  27. Department of Mechanical Engineering, Koc University, Rumelifeneri Kampusu, 34450, Istanbul, Turkey

    Senol Piskin

  28. Department of Radiology and Neuroradiology, University Medical Center Schleswig-Holstein UKSH, Kiel, Germany

    Mariya Pravdivtseva

  29. Department of Mechanical and Aerospace Engineering, University at Buffalo, State University of New York, Buffalo, NY, USA

    Hamidreza Rajabzadeh-Oghaz, Nikhil Paliwal & Hui Meng

  30. Canon Stroke and Vascular Research Center, University at Buffalo, State University of New York, Buffalo, NY, USA

    Hamidreza Rajabzadeh-Oghaz, Nikhil Paliwal & Hui Meng

  31. Medtronic Engineering Innovation Centre, Hyderabad, India

    Santhosh Seshadhri

  32. Synopsys Inc., San Diego, CA, USA

    Matthew Howard

  33. Saitama Medical University General Hospital, 1981 Kamoda, Kawagoe, Saitama, 350-8655, Japan

    Masaaki Shojima

  34. Department of Neurosurgery, Tohoku University Graduate of Medicine, Sendai, Japan

    Shin-ichiro Sugiyama & Kuniyasu Niizuma

  35. Department of Biomedical Engineering, Tambov State Technical University, Tambov, Russia

    Sergey Sindeev & Sergey Frolov

  36. University Hospital Regensburg, Regensburg, Germany

    Thomas Wagner & Alexander Brawanski

  37. University of Applied Sciences Regensburg, Regensburg, Germany

    Thomas Wagner

  38. Macquarie University, Sydney, Australia

    Yi Qian

  39. Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA

    Yu-An Wu, Kent D. Carlson & Dan Dragomir-Daescu

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  1. Philipp Berg
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  39. Matthew Howard
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  51. Oliver Beuing
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Corresponding author

Correspondence to Philipp Berg.

Additional information

Associate Editors Francesco Migliavacca and Ajit P. Yoganathan oversaw the review of this article.

Electronic supplementary material

Below is the link to the electronic supplementary material.

13239_2018_376_MOESM1_ESM.png

Supplementary material 1 (PNG 2485 kb) Fig. A1 Segmentation results of each group for aneurysms A and B (right MCA) from one perspective. Notice the inconsistencies with respect to surface smoothness, aneurysm neck representation and number of side branches considered.

13239_2018_376_MOESM2_ESM.png

Supplementary material 2 (PNG 2760 kb) Fig. A2 Segmentation results of each group for aneurysm C and D (left MCA) from one perspective. Notice the inconsistencies with respect to surface smoothness, aneurysm neck representation and number of side branches considered.

13239_2018_376_MOESM3_ESM.xlsx

Supplementary material 3 (XLSX 40 kb) Table S3 Cross-sectional areas of the in- and outflow vessels (mm2) for all three datasets. Empty fields indicate the absence of the corresponding vessel.

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Berg, P., Voß, S., Saalfeld, S. et al. Multiple Aneurysms AnaTomy CHallenge 2018 (MATCH): Phase I: Segmentation. Cardiovasc Eng Tech 9, 565–581 (2018). https://doi.org/10.1007/s13239-018-00376-0

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