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dc.contributor.authorDetmer, Felicitas J.-
dc.contributor.authorMut, Fernando-
dc.contributor.authorSlawski, Martin-
dc.contributor.authorHirsch, Sven-
dc.contributor.authorBijlenga, Philippe-
dc.contributor.authorCebral, Juan R.-
dc.date.accessioned2021-02-04T10:43:15Z-
dc.date.available2021-02-04T10:43:15Z-
dc.date.issued2020-02-01-
dc.identifier.issn0001-6268de_CH
dc.identifier.issn0942-0940de_CH
dc.identifier.urihttps://europepmc.org/article/PMC/7172014de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/21536-
dc.descriptionErworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)de_CH
dc.description.abstractBackground: Hemodynamic patterns have been associated with cerebral aneurysm instability. For patient-specific computational fluid dynamics (CFD) simulations, the inflow rates of a patient are typically not known. The aim of this study was to analyze the influence of inter- and intra-patient variations of cerebral blood flow on the computed hemodynamics through CFD simulations and to incorporate these variations into statistical models for aneurysm rupture prediction. Methods: Image data of 1820 aneurysms were used for patient-specific steady CFD simulations with nine different inflow rates per case, capturing inter- and intra-patient flow variations. Based on the computed flow fields, 17 hemodynamic parameters were calculated and compared for the different flow conditions. Next, statistical models for aneurysm rupture were trained in 1571 of the aneurysms including hemodynamic parameters capturing the flow variations either by defining hemodynamic “response variables” (model A) or repeatedly randomly selecting flow conditions by patients (model B) as well as morphological and patient-specific variables. Both models were evaluated in the remaining 249 cases. Results: All hemodynamic parameters were significantly different for the varying flow conditions (p < 0.001). Both the flow-independent “response” model A and the flow-dependent model B performed well with areas under the receiver operating characteristic curve of 0.8182 and 0.8174 ± 0.0045, respectively. Conclusions: The influence of inter- and intra-patient flow variations on computed hemodynamics can be taken into account in multivariate aneurysm rupture prediction models achieving a good predictive performance. Such models can be applied to CFD data independent of the specific inflow boundary conditions.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofActa Neurochirurgicade_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectCerebral aneurysmde_CH
dc.subjectHemodynamicsde_CH
dc.subjectComputational fluid dynamicsde_CH
dc.subjectRisk factorde_CH
dc.subjectRupturede_CH
dc.subjectPredictionde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.subject.ddc616: Innere Medizin und Krankheitende_CH
dc.titleIncorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessmentde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Computational Life Sciences (ICLS)de_CH
dc.identifier.doi10.1007/s00701-020-04234-8de_CH
dc.identifier.pmid32008209de_CH
zhaw.funding.euNode_CH
zhaw.issue3de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end566de_CH
zhaw.pages.start553de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume162de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedBiomedical Simulationde_CH
zhaw.funding.zhawAneuXde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Detmer, F. J., Mut, F., Slawski, M., Hirsch, S., Bijlenga, P., & Cebral, J. R. (2020). Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment. Acta Neurochirurgica, 162(3), 553–566. https://doi.org/10.1007/s00701-020-04234-8
Detmer, F.J. et al. (2020) ‘Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment’, Acta Neurochirurgica, 162(3), pp. 553–566. Available at: https://doi.org/10.1007/s00701-020-04234-8.
F. J. Detmer, F. Mut, M. Slawski, S. Hirsch, P. Bijlenga, and J. R. Cebral, “Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment,” Acta Neurochirurgica, vol. 162, no. 3, pp. 553–566, Feb. 2020, doi: 10.1007/s00701-020-04234-8.
DETMER, Felicitas J., Fernando MUT, Martin SLAWSKI, Sven HIRSCH, Philippe BIJLENGA und Juan R. CEBRAL, 2020. Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment. Acta Neurochirurgica [online]. 1 Februar 2020. Bd. 162, Nr. 3, S. 553–566. DOI 10.1007/s00701-020-04234-8. Verfügbar unter: https://europepmc.org/article/PMC/7172014
Detmer, Felicitas J., Fernando Mut, Martin Slawski, Sven Hirsch, Philippe Bijlenga, and Juan R. Cebral. 2020. “Incorporating Variability of Patient Inflow Conditions into Statistical Models for Aneurysm Rupture Assessment.” Acta Neurochirurgica 162 (3): 553–66. https://doi.org/10.1007/s00701-020-04234-8.
Detmer, Felicitas J., et al. “Incorporating Variability of Patient Inflow Conditions into Statistical Models for Aneurysm Rupture Assessment.” Acta Neurochirurgica, vol. 162, no. 3, Feb. 2020, pp. 553–66, https://doi.org/10.1007/s00701-020-04234-8.


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