Biphasic modeling of brain tumor biomechanics and response to radiation treatment. Issue 9 (14th June 2016)

• Record Type: Journal Article
• Authors: Angeli, Stelios; Stylianopoulos, Triantafyllos
• Is Part Of: Journal of biomechanics. Volume 49:Issue 9(2016)
• Page Start: 1524
• Page End: 1531
• Publication Date: 2016-06-14
• Subjects: Mathematical modeling -- Image reconstruction -- Interstitial fluid pressure -- Solid stress -- Poro-elasticity; Animal mechanics -- Periodicals; Biomechanics -- Periodicals; Biomechanics -- Periodicals; Mécanique animale -- Périodiques; Biomécanique -- Périodiques; Electronic journals; 571.4305
• DOI: 10.1016/j.jbiomech.2016.03.029
• Languages: English
• ISSNs: 0021-9290

Abstract

Abstract: Biomechanical forces are central in tumor progression and response to treatment. This becomes more important in brain cancers where tumors are surrounded by tissues with different mechanical properties. Existing mathematical models ignore direct mechanical interactions of the tumor with the normal brain. Here, we developed a clinically relevant model, which predicts tumor growth accounting directly for mechanical interactions. A three-dimensional model of the gray and white matter and the cerebrospinal fluid was constructed from magnetic resonance images of a normal brain. Subsequently, a biphasic tissue growth theory for an initial tumor seed was employed, incorporating the effects of radiotherapy. Additionally, three different sets of brain tissue properties taken from the literature were used to investigate their effect on tumor growth. Results show the evolution of solid stress and interstitial fluid pressure within the tumor and the normal brain. Heterogeneous distribution of the solid stress exerted on the tumor resulted in a 35% spatial variation in cancer cell proliferation. Interestingly, the model predicted that distant from the tumor, normal tissues still undergo significant deformations while it was found that intratumoral fluid pressure is elevated. Our predictions relate to clinical symptoms of brain cancers and present useful tools for therapy planning.