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dc.contributor.authorDetmer, Felicitas J.-
dc.contributor.authorFajardo-Jiménez, Daniel-
dc.contributor.authorMut, Fernando-
dc.contributor.authorJuchler, Norman-
dc.contributor.authorHirsch, Sven-
dc.contributor.authorPereira, Vitor Mendes-
dc.contributor.authorBijlenga, Philippe-
dc.contributor.authorCebral, Juan R.-
dc.date.accessioned2018-11-09T09:15:25Z-
dc.date.available2018-11-09T09:15:25Z-
dc.date.issued2018-10-30-
dc.identifier.issn0001-6268de_CH
dc.identifier.issn0942-0940de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/12682-
dc.description.abstractBackground: For a treatment decision of unruptured cerebral aneurysms, physicians and patients need to weigh the risk of treatment against the risk of hemorrhagic stroke caused by aneurysm rupture. The aim of this study was to externally evaluate a recently developed statistical aneurysm rupture probability model, which could potentially support such treatment decisions. Methods: Segmented image data and patient information obtained from two patient cohorts including 203 patients with 249 aneurysms were used for patient-specific computational fluid dynamics simulations and subsequent evaluation of the statistical model in terms of accuracy, discrimination, and goodness of fit. The model’s performance was further compared to a similarity-based approach for rupture assessment by identifying aneurysms in the training cohort that were similar in terms of hemodynamics and shape compared to a given aneurysm from the external cohorts. Results: When applied to the external data, the model achieved a good discrimination and goodness of fit (area under the receiver operating characteristic curve AUC = 0.82), which was only slightly reduced compared to the optimism-corrected AUC in the training population (AUC = 0.84). The accuracy metrics indicated a small decrease in accuracy compared to the training data (misclassification error of 0.24 vs. 0.21). The model’s prediction accuracy was improved when combined with the similarity approach (misclassification error of 0.14). Conclusions: The model’s performance measures indicated a good generalizability for data acquired at different clinical institutions. Combining the model-based and similarity-based approach could further improve the assessment and interpretation of new cases, demonstrating its potential use for clinical risk assessment.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.subjectPredictionde_CH
dc.subjectRisk factorsde_CH
dc.subjectRupturede_CH
dc.subjectShapede_CH
dc.subject.ddc616.8: Neurologie und Krankheiten des Nervensystemsde_CH
dc.titleExternal validation of cerebral aneurysm rupture probability model with data from two patient cohortsde_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/s00701-018-3712-8de_CH
dc.identifier.pmid30374656de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.webfeedBiomedical Simulationde_CH
zhaw.webfeedMedical Image Analysis & Data Modelingde_CH
zhaw.funding.zhawAneuXde_CH
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Detmer, F. J., Fajardo-Jiménez, D., Mut, F., Juchler, N., Hirsch, S., Pereira, V. M., Bijlenga, P., & Cebral, J. R. (2018). External validation of cerebral aneurysm rupture probability model with data from two patient cohorts. Acta Neurochirurgica. https://doi.org/10.1007/s00701-018-3712-8
Detmer, F.J. et al. (2018) ‘External validation of cerebral aneurysm rupture probability model with data from two patient cohorts’, Acta Neurochirurgica [Preprint]. Available at: https://doi.org/10.1007/s00701-018-3712-8.
F. J. Detmer et al., “External validation of cerebral aneurysm rupture probability model with data from two patient cohorts,” Acta Neurochirurgica, Oct. 2018, doi: 10.1007/s00701-018-3712-8.
DETMER, Felicitas J., Daniel FAJARDO-JIMÉNEZ, Fernando MUT, Norman JUCHLER, Sven HIRSCH, Vitor Mendes PEREIRA, Philippe BIJLENGA und Juan R. CEBRAL, 2018. External validation of cerebral aneurysm rupture probability model with data from two patient cohorts. Acta Neurochirurgica. 30 Oktober 2018. DOI 10.1007/s00701-018-3712-8
Detmer, Felicitas J., Daniel Fajardo-Jiménez, Fernando Mut, Norman Juchler, Sven Hirsch, Vitor Mendes Pereira, Philippe Bijlenga, and Juan R. Cebral. 2018. “External Validation of Cerebral Aneurysm Rupture Probability Model with Data from Two Patient Cohorts.” Acta Neurochirurgica, October. https://doi.org/10.1007/s00701-018-3712-8.
Detmer, Felicitas J., et al. “External Validation of Cerebral Aneurysm Rupture Probability Model with Data from Two Patient Cohorts.” Acta Neurochirurgica, Oct. 2018, https://doi.org/10.1007/s00701-018-3712-8.


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