We present an efﬁcient numerical method to quantify the spatial variation of glioma growth based on subject-speciﬁc medical images using a mechanically-coupled tumor model. The method is illustrated in a murine model of glioma in which we consider the tumor as a growing elastic mass that continuously deforms the surrounding healthy-appearing brain tissue. As an inverse parameter identiﬁcation problem, we quantify the volumetric growth of glioma and the growth component of deformation by ﬁtting the model predicted cell density to the cell density estimated using the diffusion-weighted magnetic resonance imaging data. Numerically, we developed an adjoint-based approach to solve the optimization problem. Results on a set of experimentally measured, in vivo rat glioma data indicate good agreement between the ﬁtted and measured tumor area and suggest a wide variation of in-plane glioma growth with the growth-induced Jacobian ranging from 1.0 to 6.0. Keywords Glioma growth · Mechanically-coupled · Inverse problem · Finite element · Adjoint-state method · Mass effect 1 Introduction to the observation. However, these empirical models are nei- ther able to quantify the spatial variation of tumor growth Tumor growth is a complex phenomenon affected by a nor to provide insights into the underlying biological mech- series
Computational Mechanics – Springer Journals
Published: Jun 2, 2018
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