TY - GEN
T1 - Importance of patient DTI's to accurately model glioma growth using the reaction diffusion equation
AU - Stretton, E.
AU - Geremia, E.
AU - Menze, B.
AU - Delingette, H.
AU - Ayache, N.
PY - 2013
Y1 - 2013
N2 - Tumor growth models based on the Fisher Kolmogorov reaction-diffusion equation (FK) have shown convincing results in reproducing and predicting the invasion patterns of gliomas brain tumors. Diffusion tensor images (DTIs) were suggested to model the anisotropic diffusion of tumor cells in the brain white matter. However, clinical patient-DTIs are expensive and often acquired with low resolution, which compromises the accuracy of the tumor growth models. In this work, we used the traveling wave approximation model to describe the evolution of the visible boundary of the tumor modeled by the FK equation to investigate the impact of replacing the patient DTI by (i) an isotropic diffusion map or (ii) an anisotropic high-resolution DTI atlas formed by averaging DTIs of multiple patients. We quantify the impact of replacing the patient DTI using three metrics: the shape of the simulated glioma, the estimation of the tumor growth parameters, and the prediction performance on clinical cases.
AB - Tumor growth models based on the Fisher Kolmogorov reaction-diffusion equation (FK) have shown convincing results in reproducing and predicting the invasion patterns of gliomas brain tumors. Diffusion tensor images (DTIs) were suggested to model the anisotropic diffusion of tumor cells in the brain white matter. However, clinical patient-DTIs are expensive and often acquired with low resolution, which compromises the accuracy of the tumor growth models. In this work, we used the traveling wave approximation model to describe the evolution of the visible boundary of the tumor modeled by the FK equation to investigate the impact of replacing the patient DTI by (i) an isotropic diffusion map or (ii) an anisotropic high-resolution DTI atlas formed by averaging DTIs of multiple patients. We quantify the impact of replacing the patient DTI using three metrics: the shape of the simulated glioma, the estimation of the tumor growth parameters, and the prediction performance on clinical cases.
KW - DTI
KW - glioma
KW - reaction-diffusion equation
UR - http://www.scopus.com/inward/record.url?scp=84881627821&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2013.6556681
DO - 10.1109/ISBI.2013.6556681
M3 - Conference contribution
AN - SCOPUS:84881627821
SN - 9781467364546
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 1142
EP - 1145
BT - ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging
T2 - 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
Y2 - 7 April 2013 through 11 April 2013
ER -