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dc.contributor.authorGosling, Rebecca
dc.contributor.authorMorris, Paul D.
dc.contributor.authorLawford, Patricia V.
dc.contributor.authorHose, David Rodney
dc.contributor.authorGunn, Julian P.
dc.date.accessioned2019-09-18T06:47:19Z
dc.date.available2019-09-18T06:47:19Z
dc.date.created2019-02-20T10:30:07Z
dc.date.issued2018
dc.identifier.citationFrontiers in Physiology. 2018, 9 .nb_NO
dc.identifier.issn1664-042X
dc.identifier.urihttp://hdl.handle.net/11250/2617325
dc.description.abstractComputational modeling has been used routinely in the pre-clinical development of medical devices such as coronary artery stents. The ability to simulate and predict physiological and structural parameters such as flow disturbance, wall shear-stress, and mechanical strain patterns is beneficial to stent manufacturers. These methods are now emerging as useful clinical tools, used by physicians in the assessment and management of patients. Computational models, which can predict the physiological response to intervention, offer clinicians the ability to evaluate a number of different treatment strategies in silico prior to treating the patient in the cardiac catheter laboratory. For the first time clinicians can perform a patient-specific assessment prior to making treatment decisions. This could be advantageous in patients with complex disease patterns where the optimal treatment strategy is not clear. This article reviews the key advances and the potential barriers to clinical adoption and translation of these virtual treatment planning models.nb_NO
dc.language.isoengnb_NO
dc.publisherFrontiers Medianb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titlePredictive Physiological Modeling of Percutaneous Coronary Intervention - Is Virtual Treatment Planning the Future?nb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber7nb_NO
dc.source.volume9nb_NO
dc.source.journalFrontiers in Physiologynb_NO
dc.identifier.doi10.3389/fphys.2018.01107
dc.identifier.cristin1679051
dc.description.localcodeCopyright © 2018 Gosling, Morris, Lawford, Hose and Gunn. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.nb_NO
cristin.unitcode194,65,25,0
cristin.unitnameInstitutt for sirkulasjon og bildediagnostikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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