A corrigendum for this article has been published. To view the corrigendum, please click here.
- Corrigendum to “Simulating Radiotherapy Effect in High-Grade Glioma by Using Diffusive Modeling and Brain Atlases”, Alexandros Roniotis, Kostas Marias, Vangelis Sakkalis, Georgios C. Manikis, and Michalis Zervakis
BioMed Research International
Corrigendum (1 page), Article ID 2712657, Volume 2018 (2018)
Published 28 February 2018
- Comment on “Simulating Radiotherapy Effect in High-Grade Glioma by Using Diffusive Modeling and Brain Atlases”, Giovanni Borasi and Alan E. Nahum
BioMed Research International
Letter to the Editor (1 page), Article ID 801057, Volume 2015 (2015)
Published 22 November 2015
Journal of Biomedicine and Biotechnology
Volume 2012, Article ID 715812, 9 pages
http://dx.doi.org/10.1155/2012/715812
Simulating Radiotherapy Effect in High-Grade Glioma by Using Diffusive Modeling and Brain Atlases
1Institute of Computer Science, Foundation For Research and Technology-Hellas, 700 13 Heraklion, Crete, Greece
2Department of Electronic & Computer Engineering, Technical University of Crete, 73100 Chania, Greece
Received 21 February 2012; Revised 18 May 2012; Accepted 21 May 2012
Academic Editor: George E. Plopper
Copyright © 2012 Alexandros Roniotis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Applying diffusive models for simulating the spatiotemporal change of concentration of tumour cells is a modern application of predictive oncology. Diffusive models are used for modelling glioblastoma, the most aggressive type of glioma. This paper presents the results of applying a linear quadratic model for simulating the effects of radiotherapy on an advanced diffusive glioma model. This diffusive model takes into consideration the heterogeneous velocity of glioma in gray and white matter and the anisotropic migration of tumor cells, which is facilitated along white fibers. This work uses normal brain atlases for extracting the proportions of white and gray matter and the diffusion tensors used for anisotropy. The paper also presents the results of applying this glioma model on real clinical datasets.