Publikationstyp: Beitrag in wissenschaftlicher Zeitschrift
Art der Begutachtung: Peer review (Publikation)
Titel: Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment
Autor/-in: Detmer, Felicitas J.
Mut, Fernando
Slawski, Martin
Hirsch, Sven
Bijlenga, Philippe
Cebral, Juan R.
et. al: No
DOI: 10.1007/s00701-020-04234-8
Erschienen in: Acta Neurochirurgica
Band(Heft): 162
Heft: 3
Seite(n): 553
Seiten bis: 566
Erscheinungsdatum: 1-Feb-2020
Verlag / Hrsg. Institution: Springer
ISSN: 0001-6268
0942-0940
Sprache: Englisch
Schlagwörter: Cerebral aneurysm; Hemodynamics; Computational fluid dynamics; Risk factor; Rupture; Prediction
Fachgebiet (DDC): 005: Computerprogrammierung, Programme und Daten
616: Innere Medizin und Krankheiten
Zusammenfassung: Background: 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.
Weitere Angaben: Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)
URI: https://europepmc.org/article/PMC/7172014
https://digitalcollection.zhaw.ch/handle/11475/21536
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): Lizenz gemäss Verlagsvertrag
Departement: Life Sciences und Facility Management
Organisationseinheit: Institut für Computational Life Sciences (ICLS)
Publiziert im Rahmen des ZHAW-Projekts: AneuX
Enthalten in den Sammlungen:Publikationen Life Sciences und Facility Management

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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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