171209 20260515163945.0 doi 10.1016/j.compbiomed.2026.111715 sideral 149278 ART-2026-149278 eng Caballero, Ricardo Universidad de Zaragoza A personalized mechanobiology-driven multiscale model of atherosclerosis 2026 Atherosclerosis is a chronic inflammatory and metabolic disease primarily driven by systemic lipid imbalances, with plaque localization and progression further modulated by local hemodynamic and cellular factors within the arterial wall. Here we present a validation study of a hybrid multiscale model that couples computational fluid dynamics (CFD), mass-transport-driven low-density lipoprotein (LDL) maps, and an agent-based model (ABM) of cell behavior to predict coronary plaque initiation and progression. Validation employed adult minipigs carrying a low-density lipoprotein receptor (LDLR) mutation—an established preclinical analogue of human hypercholesterolemia—using longitudinal in vivo imaging data collected within the BIOCCORA study, with 1-year follow-up capturing plaque initiation and evolution. By linking wall shear stress (WSS)-dependent LDL filtration with cytokine-guided smooth muscle cell (SMC) activity, the model mechanistically reconstructs the plaque microenvironment rather than fitting outcomes post hoc. Tested on four imaging-derived porcine coronary arteries tracked over time, the model anticipates where and how fast plaques grow and how lipid pools evolve across cross-sections, showing strong concordance with experiments. These results position hybrid multiscale in silico models as promising predictors for disease progression and could aid in future treatment decision-making. Access copy available to the general public Unrestricted nfo:eu-repo/grantAgreement/ES/AEI/PID2022-140219OB-I00 info:eu-repo/grantAgreement/ES/MICINN PRE2020-095671 info:eu-repo/semantics/openAccess by-nc-nd https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Martínez, Miguel Ángel Universidad de Zaragoza (orcid)0000-0002-8375-0354 Wentzel, Jolanda J. Akyildiz, Ali C. Peña, Estefanía Universidad de Zaragoza (orcid)0000-0002-0664-5024 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 210 (2026), 111715 [19 pp.] Comput. biol. med. Computers in biology and medicine 0010-4825 6380797 http://zaguan.unizar.es/record/171209/files/texto_completo.pdf Versión publicada 2705707 http://zaguan.unizar.es/record/171209/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:171209 articulos driver 2026-05-15-14:55:07 ARTICLE