Adaptive constrained constructive optimisation for complex vascularisation processes

Abstract Mimicking angiogenetic processes in vascular territories acquires importance in the analysis of the multi-scale circulatory cascade and the coupling between blood flow and cell function. The present work extends, in several aspects, the Constrained Constructive Optimisation (CCO) algorithm...

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Autores principales:	Gonzalo Daniel Maso Talou, Soroush Safaei, Peter John Hunter, Pablo Javier Blanco
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/65fae056cd384075b7690e7a3696184f
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spelling	oai:doaj.org-article:65fae056cd384075b7690e7a3696184f2021-12-02T16:31:07ZAdaptive constrained constructive optimisation for complex vascularisation processes10.1038/s41598-021-85434-92045-2322https://doaj.org/article/65fae056cd384075b7690e7a3696184f2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-85434-9https://doaj.org/toc/2045-2322Abstract Mimicking angiogenetic processes in vascular territories acquires importance in the analysis of the multi-scale circulatory cascade and the coupling between blood flow and cell function. The present work extends, in several aspects, the Constrained Constructive Optimisation (CCO) algorithm to tackle complex automatic vascularisation tasks. The main extensions are based on the integration of adaptive optimisation criteria and multi-staged space-filling strategies which enhance the modelling capabilities of CCO for specific vascular architectures. Moreover, this vascular outgrowth can be performed either from scratch or from an existing network of vessels. Hence, the vascular territory is defined as a partition of vascular, avascular and carriage domains (the last one contains vessels but not terminals) allowing one to model complex vascular domains. In turn, the multi-staged space-filling approach allows one to delineate a sequence of biologically-inspired stages during the vascularisation process by exploiting different constraints, optimisation strategies and domain partitions stage by stage, improving the consistency with the architectural hierarchy observed in anatomical structures. With these features, the aDaptive CCO (DCCO) algorithm proposed here aims at improving the modelled network anatomy. The capabilities of the DCCO algorithm are assessed with a number of anatomically realistic scenarios.Gonzalo Daniel Maso TalouSoroush SafaeiPeter John HunterPablo Javier BlancoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-22 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Gonzalo Daniel Maso Talou Soroush Safaei Peter John Hunter Pablo Javier Blanco Adaptive constrained constructive optimisation for complex vascularisation processes
description	Abstract Mimicking angiogenetic processes in vascular territories acquires importance in the analysis of the multi-scale circulatory cascade and the coupling between blood flow and cell function. The present work extends, in several aspects, the Constrained Constructive Optimisation (CCO) algorithm to tackle complex automatic vascularisation tasks. The main extensions are based on the integration of adaptive optimisation criteria and multi-staged space-filling strategies which enhance the modelling capabilities of CCO for specific vascular architectures. Moreover, this vascular outgrowth can be performed either from scratch or from an existing network of vessels. Hence, the vascular territory is defined as a partition of vascular, avascular and carriage domains (the last one contains vessels but not terminals) allowing one to model complex vascular domains. In turn, the multi-staged space-filling approach allows one to delineate a sequence of biologically-inspired stages during the vascularisation process by exploiting different constraints, optimisation strategies and domain partitions stage by stage, improving the consistency with the architectural hierarchy observed in anatomical structures. With these features, the aDaptive CCO (DCCO) algorithm proposed here aims at improving the modelled network anatomy. The capabilities of the DCCO algorithm are assessed with a number of anatomically realistic scenarios.
format	article
author	Gonzalo Daniel Maso Talou Soroush Safaei Peter John Hunter Pablo Javier Blanco
author_facet	Gonzalo Daniel Maso Talou Soroush Safaei Peter John Hunter Pablo Javier Blanco
author_sort	Gonzalo Daniel Maso Talou
title	Adaptive constrained constructive optimisation for complex vascularisation processes
title_short	Adaptive constrained constructive optimisation for complex vascularisation processes
title_full	Adaptive constrained constructive optimisation for complex vascularisation processes
title_fullStr	Adaptive constrained constructive optimisation for complex vascularisation processes
title_full_unstemmed	Adaptive constrained constructive optimisation for complex vascularisation processes
title_sort	adaptive constrained constructive optimisation for complex vascularisation processes
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/65fae056cd384075b7690e7a3696184f
work_keys_str_mv	AT gonzalodanielmasotalou adaptiveconstrainedconstructiveoptimisationforcomplexvascularisationprocesses AT soroushsafaei adaptiveconstrainedconstructiveoptimisationforcomplexvascularisationprocesses AT peterjohnhunter adaptiveconstrainedconstructiveoptimisationforcomplexvascularisationprocesses AT pablojavierblanco adaptiveconstrainedconstructiveoptimisationforcomplexvascularisationprocesses
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Adaptive constrained constructive optimisation for complex vascularisation processes

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