Exploring intracranial aneurysm instability markers to improve disease modeling

Dupuy, Nicolas; Juchler, Norman; Morel, Sandrine; Kwak, Brenda R.; Hirsch, Sven; Bijlenga, Philippe

doi:10.21256/zhaw-25387

Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-25387

Full metadata record

DC Field	Value	Language
dc.contributor.author	Dupuy, Nicolas	-
dc.contributor.author	Juchler, Norman	-
dc.contributor.author	Morel, Sandrine	-
dc.contributor.author	Kwak, Brenda R.	-
dc.contributor.author	Hirsch, Sven	-
dc.contributor.author	Bijlenga, Philippe	-
dc.date.accessioned	2022-08-05T09:58:14Z	-
dc.date.available	2022-08-05T09:58:14Z	-
dc.date.issued	2022	-
dc.identifier.isbn	978-0-9562914-6-2	de_CH
dc.identifier.issn	2227-3085	de_CH
dc.identifier.issn	2227-9385	de_CH
dc.identifier.uri	https://digitalcollection.zhaw.ch/handle/11475/25387	-
dc.description	Proceedings: https://www.compbiomed.net/2021/cmbe-proceedings.htm	de_CH
dc.description.abstract	Intracranial aneurysm (IA) shape is proposed to be a predicting factor of rupture. In this study, using 3D-angiographies, surgical and histological images, we ranked 11 IAs according to different characteristics (homogeneity, aspect and thickness), and correlations between the different ranking systems were investigated. We showed positive correlations between IA morphology (normalized total Gaussian curvature, GLN) and wall aspect ranking, and between GLN and histology ranking. Correlations between increased GLN, inhomogeneity of IA wall aspect and thickness were shown. This exploratory study supports the GLN in its ability to quantify IA shape and to be used as an IA wall feature predictor.	de_CH
dc.language.iso	en	de_CH
dc.publisher	Computational and Mathematical Biomedical Engineering	de_CH
dc.rights	Licence according to publishing contract	de_CH
dc.subject	Intracranial aneurysm	de_CH
dc.subject	Morphology	de_CH
dc.subject	Wall aspect	de_CH
dc.subject	Wall thickness	de_CH
dc.subject.ddc	005: Computerprogrammierung, Programme und Daten	de_CH
dc.subject.ddc	616: Innere Medizin und Krankheiten	de_CH
dc.title	Exploring intracranial aneurysm instability markers to improve disease modeling	de_CH
dc.type	Konferenz: Paper	de_CH
dcterms.type	Text	de_CH
zhaw.departement	Life Sciences und Facility Management	de_CH
zhaw.organisationalunit	Institut für Computational Life Sciences (ICLS)	de_CH
dc.identifier.doi	10.21256/zhaw-25387	-
zhaw.conference.details	7th International Conference on Computational and Mathematical Biomedical Engineering (CMBE22), Milan, Italy, 27-29 June 2022	de_CH
zhaw.funding.eu	No	de_CH
zhaw.originated.zhaw	Yes	de_CH
zhaw.pages.end	17	de_CH
zhaw.pages.start	14	de_CH
zhaw.parentwork.editor	Nithiarasu, Perumal	-
zhaw.parentwork.editor	Vergara, Christian	-
zhaw.publication.status	publishedVersion	de_CH
zhaw.volume	1	de_CH
zhaw.publication.review	Peer review (Abstract)	de_CH
zhaw.title.proceedings	CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering	de_CH
zhaw.webfeed	Biomedical Simulation	de_CH
zhaw.webfeed	Medical Image Analysis & Data Modeling	de_CH
zhaw.funding.zhaw	AneuX	de_CH
zhaw.author.additional	No	de_CH
zhaw.display.portrait	Yes	de_CH
Appears in collections:	Publikationen Life Sciences und Facility Management

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Dupuy, N., Juchler, N., Morel, S., Kwak, B. R., Hirsch, S., & Bijlenga, P. (2022). Exploring intracranial aneurysm instability markers to improve disease modeling [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 1, pp. 14–17). Computational and Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-25387

Dupuy, N. et al. (2022) ‘Exploring intracranial aneurysm instability markers to improve disease modeling’, in P. Nithiarasu and C. Vergara (eds) CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering. Computational and Mathematical Biomedical Engineering, pp. 14–17. Available at: https://doi.org/10.21256/zhaw-25387.

N. Dupuy, N. Juchler, S. Morel, B. R. Kwak, S. Hirsch, and P. Bijlenga, “Exploring intracranial aneurysm instability markers to improve disease modeling,” in CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering, 2022, vol. 1, pp. 14–17. doi: 10.21256/zhaw-25387.

DUPUY, Nicolas, Norman JUCHLER, Sandrine MOREL, Brenda R. KWAK, Sven HIRSCH und Philippe BIJLENGA, 2022. Exploring intracranial aneurysm instability markers to improve disease modeling. In: Perumal NITHIARASU und Christian VERGARA (Hrsg.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering. Conference paper. Computational and Mathematical Biomedical Engineering. 2022. S. 14–17. ISBN 978-0-9562914-6-2

Dupuy, Nicolas, Norman Juchler, Sandrine Morel, Brenda R. Kwak, Sven Hirsch, and Philippe Bijlenga. 2022. “Exploring Intracranial Aneurysm Instability Markers to Improve Disease Modeling.” Conference paper. In CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering, edited by Perumal Nithiarasu and Christian Vergara, 1:14–17. Computational and Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-25387.

Dupuy, Nicolas, et al. “Exploring Intracranial Aneurysm Instability Markers to Improve Disease Modeling.” CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering, edited by Perumal Nithiarasu and Christian Vergara, vol. 1, Computational and Mathematical Biomedical Engineering, 2022, pp. 14–17, https://doi.org/10.21256/zhaw-25387.