Simulation of tumor induced angiogenesis using an analytical adaptive modeling including dynamic sprouting and blood flow modeling
In this paper, an adaptive model for tumor induced angiogenesis is developed that integrates generation and diffusion of a growth factor originated from hypoxic cells, adaptive sprouting from a parent vessel, blood flow and structural adaptation. The proposed adaptive sprout spacing model (ASS) dete...
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Veröffentlicht in: | Microvascular research 2016-09, Vol.107, p.51-64 |
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description | In this paper, an adaptive model for tumor induced angiogenesis is developed that integrates generation and diffusion of a growth factor originated from hypoxic cells, adaptive sprouting from a parent vessel, blood flow and structural adaptation. The proposed adaptive sprout spacing model (ASS) determines position, time and number of sprouts which are activated from a parent vessel and also the developed vascular network is modified by a novel sprout branching prediction algorithm. This algorithm couples local vascular endothelial growth factor (VEGF) concentrations, stresses due to the blood flow and stochastic branching to the structural reactions of each vessel segment in response to mechanical and biochemical stimuli. The results provide predictions for the time-dependent development of the network structure, including the position and diameters of each segment and the resulting distributions of blood flow and VEGF. Considering time delays between sprout progressions and number of sprouts activated at different time durations provides information about micro-vessel density in the network. Resulting insights could be useful for motivating experimental investigations of vascular pattern in tumor induced angiogenesis and development of therapies targeting angiogenesis.
•An adaptive model of tumor induced angiogenesis process considering dynamic sprouting and blood flow is developed.•An adaptive sprout spacing model (ASS) determines position, time and number of sprouts activated from the parent vessel.•The developed vascular network is modified by a novel sprout branching prediction algorithm.•The model considers time delays between sprout progressions and the number of sprouts activated at different time.•The model provides information about micro-vessel density in the network and could be useful in drug delivery and treatment. |
doi_str_mv | 10.1016/j.mvr.2016.05.002 |
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•An adaptive model of tumor induced angiogenesis process considering dynamic sprouting and blood flow is developed.•An adaptive sprout spacing model (ASS) determines position, time and number of sprouts activated from the parent vessel.•The developed vascular network is modified by a novel sprout branching prediction algorithm.•The model considers time delays between sprout progressions and the number of sprouts activated at different time.•The model provides information about micro-vessel density in the network and could be useful in drug delivery and treatment.</description><identifier>ISSN: 0026-2862</identifier><identifier>EISSN: 1095-9319</identifier><identifier>DOI: 10.1016/j.mvr.2016.05.002</identifier><identifier>PMID: 27179697</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adaptation, Physiological ; Animals ; Blood flow ; Blood Flow Velocity ; Computer Simulation ; Feedback inhibition ; Humans ; Microvessels - metabolism ; Microvessels - pathology ; Microvessels - physiopathology ; Models, Cardiovascular ; Neoplasms - blood supply ; Neoplasms - metabolism ; Neovascularization, Pathologic ; Regional Blood Flow ; Sprout spacing ; Stochastic Processes ; Time adaptive vessel branching ; Time Factors ; Tumor angiogenesis ; Tumor Hypoxia ; Tumor Microenvironment ; Vascular Endothelial Growth Factor A - metabolism</subject><ispartof>Microvascular research, 2016-09, Vol.107, p.51-64</ispartof><rights>2016 Elsevier Inc.</rights><rights>Copyright © 2016 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-b155d480e44301c9bb5058af3827f5b248dfcede7c9a5da792efe6da5033c9a23</citedby><cites>FETCH-LOGICAL-c353t-b155d480e44301c9bb5058af3827f5b248dfcede7c9a5da792efe6da5033c9a23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.mvr.2016.05.002$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27179697$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Naghavi, Nadia</creatorcontrib><creatorcontrib>Hosseini, Farideh.S.</creatorcontrib><creatorcontrib>Sardarabadi, Mohammad</creatorcontrib><creatorcontrib>Kalani, Hadi</creatorcontrib><title>Simulation of tumor induced angiogenesis using an analytical adaptive modeling including dynamic sprouting and blood flow modeling</title><title>Microvascular research</title><addtitle>Microvasc Res</addtitle><description>In this paper, an adaptive model for tumor induced angiogenesis is developed that integrates generation and diffusion of a growth factor originated from hypoxic cells, adaptive sprouting from a parent vessel, blood flow and structural adaptation. The proposed adaptive sprout spacing model (ASS) determines position, time and number of sprouts which are activated from a parent vessel and also the developed vascular network is modified by a novel sprout branching prediction algorithm. This algorithm couples local vascular endothelial growth factor (VEGF) concentrations, stresses due to the blood flow and stochastic branching to the structural reactions of each vessel segment in response to mechanical and biochemical stimuli. The results provide predictions for the time-dependent development of the network structure, including the position and diameters of each segment and the resulting distributions of blood flow and VEGF. Considering time delays between sprout progressions and number of sprouts activated at different time durations provides information about micro-vessel density in the network. Resulting insights could be useful for motivating experimental investigations of vascular pattern in tumor induced angiogenesis and development of therapies targeting angiogenesis.
•An adaptive model of tumor induced angiogenesis process considering dynamic sprouting and blood flow is developed.•An adaptive sprout spacing model (ASS) determines position, time and number of sprouts activated from the parent vessel.•The developed vascular network is modified by a novel sprout branching prediction algorithm.•The model considers time delays between sprout progressions and the number of sprouts activated at different time.•The model provides information about micro-vessel density in the network and could be useful in drug delivery and treatment.</description><subject>Adaptation, Physiological</subject><subject>Animals</subject><subject>Blood flow</subject><subject>Blood Flow Velocity</subject><subject>Computer Simulation</subject><subject>Feedback inhibition</subject><subject>Humans</subject><subject>Microvessels - metabolism</subject><subject>Microvessels - pathology</subject><subject>Microvessels - physiopathology</subject><subject>Models, Cardiovascular</subject><subject>Neoplasms - blood supply</subject><subject>Neoplasms - metabolism</subject><subject>Neovascularization, Pathologic</subject><subject>Regional Blood Flow</subject><subject>Sprout spacing</subject><subject>Stochastic Processes</subject><subject>Time adaptive vessel branching</subject><subject>Time Factors</subject><subject>Tumor angiogenesis</subject><subject>Tumor Hypoxia</subject><subject>Tumor Microenvironment</subject><subject>Vascular Endothelial Growth Factor A - metabolism</subject><issn>0026-2862</issn><issn>1095-9319</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9UE1r3DAUFKGl2Sb9AbkEHXOxq4-VbdFTCU1aCPSQ5ixk6XnRIksbydqw1_zyatk0x8KD9xjNDKNB6IqSlhLafd228z61rJ4tES0h7AytKJGikZzKD2hVka5hQ8fO0eect4RQKiT7hM5ZT3vZyX6FXh_dXLxeXAw4Tngpc0zYBVsMWKzDxsUNBMgu45Jd2FSojvaHxRntsbZ6t7g94Dla8Md3F4wv9njZQ9CzMzjvUizLSWvx6GO0ePLx5V1ziT5O2mf48rYv0NPdjz-3P5uH3_e_br8_NIYLvjQjFcKuBwLrNSfUyHEURAx64gPrJzGy9WCnGhp6I7WwupcMJuisFoTzCjF-gW5OvjXQc4G8qNllA97rALFkRQfCei4545VKT1STYs4JJrVLbtbpoChRx-rVVtXq1bF6RYSqRVfN9Zt9GWew74p_XVfCtxMB6if3DpLKxkGomV0Csygb3X_s_wL50JgU</recordid><startdate>201609</startdate><enddate>201609</enddate><creator>Naghavi, Nadia</creator><creator>Hosseini, Farideh.S.</creator><creator>Sardarabadi, Mohammad</creator><creator>Kalani, Hadi</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>201609</creationdate><title>Simulation of tumor induced angiogenesis using an analytical adaptive modeling including dynamic sprouting and blood flow modeling</title><author>Naghavi, Nadia ; Hosseini, Farideh.S. ; Sardarabadi, Mohammad ; Kalani, Hadi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-b155d480e44301c9bb5058af3827f5b248dfcede7c9a5da792efe6da5033c9a23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adaptation, Physiological</topic><topic>Animals</topic><topic>Blood flow</topic><topic>Blood Flow Velocity</topic><topic>Computer Simulation</topic><topic>Feedback inhibition</topic><topic>Humans</topic><topic>Microvessels - metabolism</topic><topic>Microvessels - pathology</topic><topic>Microvessels - physiopathology</topic><topic>Models, Cardiovascular</topic><topic>Neoplasms - blood supply</topic><topic>Neoplasms - metabolism</topic><topic>Neovascularization, Pathologic</topic><topic>Regional Blood Flow</topic><topic>Sprout spacing</topic><topic>Stochastic Processes</topic><topic>Time adaptive vessel branching</topic><topic>Time Factors</topic><topic>Tumor angiogenesis</topic><topic>Tumor Hypoxia</topic><topic>Tumor Microenvironment</topic><topic>Vascular Endothelial Growth Factor A - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Naghavi, Nadia</creatorcontrib><creatorcontrib>Hosseini, Farideh.S.</creatorcontrib><creatorcontrib>Sardarabadi, Mohammad</creatorcontrib><creatorcontrib>Kalani, Hadi</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Microvascular research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Naghavi, Nadia</au><au>Hosseini, Farideh.S.</au><au>Sardarabadi, Mohammad</au><au>Kalani, Hadi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulation of tumor induced angiogenesis using an analytical adaptive modeling including dynamic sprouting and blood flow modeling</atitle><jtitle>Microvascular research</jtitle><addtitle>Microvasc Res</addtitle><date>2016-09</date><risdate>2016</risdate><volume>107</volume><spage>51</spage><epage>64</epage><pages>51-64</pages><issn>0026-2862</issn><eissn>1095-9319</eissn><abstract>In this paper, an adaptive model for tumor induced angiogenesis is developed that integrates generation and diffusion of a growth factor originated from hypoxic cells, adaptive sprouting from a parent vessel, blood flow and structural adaptation. The proposed adaptive sprout spacing model (ASS) determines position, time and number of sprouts which are activated from a parent vessel and also the developed vascular network is modified by a novel sprout branching prediction algorithm. This algorithm couples local vascular endothelial growth factor (VEGF) concentrations, stresses due to the blood flow and stochastic branching to the structural reactions of each vessel segment in response to mechanical and biochemical stimuli. The results provide predictions for the time-dependent development of the network structure, including the position and diameters of each segment and the resulting distributions of blood flow and VEGF. Considering time delays between sprout progressions and number of sprouts activated at different time durations provides information about micro-vessel density in the network. Resulting insights could be useful for motivating experimental investigations of vascular pattern in tumor induced angiogenesis and development of therapies targeting angiogenesis.
•An adaptive model of tumor induced angiogenesis process considering dynamic sprouting and blood flow is developed.•An adaptive sprout spacing model (ASS) determines position, time and number of sprouts activated from the parent vessel.•The developed vascular network is modified by a novel sprout branching prediction algorithm.•The model considers time delays between sprout progressions and the number of sprouts activated at different time.•The model provides information about micro-vessel density in the network and could be useful in drug delivery and treatment.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>27179697</pmid><doi>10.1016/j.mvr.2016.05.002</doi><tpages>14</tpages></addata></record> |
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subjects | Adaptation, Physiological Animals Blood flow Blood Flow Velocity Computer Simulation Feedback inhibition Humans Microvessels - metabolism Microvessels - pathology Microvessels - physiopathology Models, Cardiovascular Neoplasms - blood supply Neoplasms - metabolism Neovascularization, Pathologic Regional Blood Flow Sprout spacing Stochastic Processes Time adaptive vessel branching Time Factors Tumor angiogenesis Tumor Hypoxia Tumor Microenvironment Vascular Endothelial Growth Factor A - metabolism |
title | Simulation of tumor induced angiogenesis using an analytical adaptive modeling including dynamic sprouting and blood flow modeling |
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