Simulating radiotherapy effect in high-grade glioma by using diffusive modeling and brain atlases

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.

Figure 1

(a) the 99th slice of the patient dataset after registration and interpolation, (b) the 99th slice of normal brain atlas, (c) the 99th image after skull stripping and segmentation of tumor, (d) the 99th image of white matter, (e) gray matter proportion, and (f) the one dominant eigenvector images extracted from SRI24 atlas.

Figure 2

The curves depict the total number of GBM cells for one patient for eight values of a ranging from 0 (no effect of radiotherapy) to 0.021 Gy⁻¹ after applying the diffusive model. The same plot shows the three different points of real cell numbers, estimated after segmenting the tumors on three MRI datasets on the respective days. The optimal value of a lies around 0.006 Gy⁻¹.

Figure 3

The simulated cell concentration (hot areas) projected on the real patient data on the 100th day after diagnosis and 21 days after the last fraction of radiotherapy.

Figure 4

The graph presents the tumor cell concentration for the initial day (diagnosis day) and the 100th day after diagnosis (21th day after the last fraction of radiotherapy). These values have been calculated along the yellow line shown on the left MRI slice, which comes across the point with the maximum concentration value.

Figure 5

Scatter plot of JC, DS, and VS (%) for six cases where the proportional, the discrete, and the uniform growth models have been applied.

Figure 6

The temporal change of the number of glioma cells for the 4th patient for 100 days. The last radiotherapy session was carried on day 79.