Skip to Main content Skip to Navigation
Journal articles

Radiotherapy planning for glioblastoma based on a tumor growth model: improving target volume delineation

Abstract : Glioblastoma di ffer from many other tumors in the sense that they grow in filtratively into the brain tissue instead of forming a solid tumor mass with a de fined boundary. Only the part of the tumor with high tumor cell density can be localized through imaging directly. In contrast, brain tissue in filtrated by tumor cells at low density appears normal on current imaging modalities. In current clinical practice, a uniform margin, typically two centimeters, is applied to account for microscopic spread of disease that is not directly assessable through imaging. The current treatment planning procedure can potentially be improved by accounting for the anisotropy of tumor growth, which arises from di erent factors: Anatomical barriers such as the falx cerebri represent boundaries for migrating tumor cells. In addition, tumor cells primarily spread in white matter and in ltrate gray matter at lower rate. We investigate the use of a phenomenological tumor growth model for treatment planning. The model is based on the Fisher-Kolmogorov equation, which formalizes these growth characteristics and estimates the spatial distribution of tumor cells in normal appearing regions of the brain. The target volume for radiotherapy planning can be de fined as an isoline of the simulated tumor cell density. This paper analyzes the model with respect to implications for target volume de finition and identi fies its most critical components. A retrospective study involving 10 glioblastoma patients treated at our institution has been performed. To illustrate the main findings of the study, a detailed case study is presented for a glioblastoma located close to the falx. In this situation, the falx represents a boundary for migrating tumor cells, whereas the corpus callosum provides a route for the tumor to spread to the contralateral hemisphere. We further discuss the sensitivity of the model with respect to the input parameters. Correct segmentation of the brain appears to be the most crucial model input. We conclude that the tumor growth model provides a method to account for anisotropic growth patterns of glioma, and may therefore provide a tool to make target delineation more objective and automated.
Document type :
Journal articles
Complete list of metadatas

Cited literature [36 references]  Display  Hide  Download

https://hal.inria.fr/hal-00917869
Contributor : Project-Team Asclepios <>
Submitted on : Friday, December 20, 2013 - 5:24:43 PM
Last modification on : Friday, August 2, 2019 - 4:32:07 PM
Document(s) archivé(s) le : Friday, March 21, 2014 - 9:25:56 AM

File

Unkelbach-Physics-v2.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Jan Unkelbach, Bjoern Menze, Ender Konukoglu, Florian Dittmann, Matthieu Le, et al.. Radiotherapy planning for glioblastoma based on a tumor growth model: improving target volume delineation. Physics in Medicine and Biology, IOP Publishing, 2013, ⟨10.1088/0031-9155/59/3/747⟩. ⟨hal-00917869v2⟩

Share

Metrics

Record views

563

Files downloads

930