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Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations.
Kingsley, Jessica L; Costello, James R; Raghunand, Natarajan; Rejniak, Katarzyna A.
Afiliación
  • Kingsley JL; Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.
  • Costello JR; University of South Florida, Tampa, Florida, United States of America.
  • Raghunand N; Department of Radiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.
  • Rejniak KA; Department of Cancer Physiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, United States of America.
PLoS Comput Biol ; 17(7): e1009206, 2021 07.
Article en En | MEDLINE | ID: mdl-34310608
Radiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell-level) phenomena. Nevertheless, to examine the causes of frequent fast fluctuations in tissue oxygenation, models simulating individual cells' behavior are needed. Here, we provide a link between the average data values recorded for radiologic images and the cellular and vascular architecture of the corresponding tissues. Using hybrid agent-based modeling, we generate a set of tissue morphologies capable of reproducing oxygenation levels observed in radiologic images. We then use these in silico tissues to investigate whether oxygen fluctuations can be explained by changes in vascular oxygen supply or by modulations in cellular oxygen absorption. Our studies show that intravascular changes in oxygen supply reproduce the observed fluctuations in tissue oxygenation in all considered regions of interest. However, larger-magnitude fluctuations cannot be recreated by modifications in cellular absorption of oxygen in a biologically feasible manner. Additionally, we develop a procedure to identify plausible tissue morphologies for a given temporal series of average data from radiology images. In future applications, this approach can be used to generate a set of tissues comparable with radiology images and to simulate tumor responses to various anti-cancer treatments at the tissue-scale level.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Oxígeno / Modelos Biológicos / Neoplasias Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Oxígeno / Modelos Biológicos / Neoplasias Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos