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Including the mechanisms, leading to these changes, in a computational model is expected to improve the accuracy of predictions of the long-term complications and optimal treatment timing of dissection patients. An idealized dissected wall was modeled to represent the elastin and collagen production and\/or degradation imposed by stress- and inflammation-mediated growth and remodeling, using the homogenized constrained mixture theory. As no optimal growth and remodeling parameters have been defined for aortic dissections, a Latin hypercube sampling with 1000 parameter combinations was assessed for four inflammation patterns, with a varying spatial extent (full\/local) and temporal evolution (permanent\/transient). The dissected membrane thickening and microstructure was considered together with the diameter expansion over a period of 90 days. The highest success rate was found for the transient inflammation patterns, with about 15% of the samples leading to converged solutions after 90 days. Clinically observed thickening rates were found for 2\u20134% of the transient inflammation samples, which represented median total diameter expansion rates of about 5 mm\/year. The dissected membrane microstructure showed an elastin decrease and, in most cases, a collagen increase. In conclusion, the model with the transient inflammation pattern allowed the reproduction of clinically observed dissected membrane thickening rates, diameter expansion rates and adaptations in microstructure, thus providing guidance in reducing the parameter space in growth and remodeling models of aortic dissections.<\/jats:p>","DOI":"10.1007\/s10237-023-01782-7","type":"journal-article","created":{"date-parts":[[2023,11,9]],"date-time":"2023-11-09T22:01:26Z","timestamp":1699567286000},"page":"413-431","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Growth and remodeling of the dissected membrane in an idealized dissected aorta model"],"prefix":"10.1007","volume":"23","author":[{"given":"Lise","family":"Gheysen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lauranne","family":"Maes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nele","family":"Famaey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick","family":"Segers","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,11,10]]},"reference":[{"key":"1782_CR1","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1098\/rsif.2018.0616","volume":"15","author":"H Ahmadzadeh","year":"2018","unstructured":"Ahmadzadeh H, Rausch MK, Humphrey JD (2018) Particle-based computational modelling of arterial disease. 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