Suguru Yokosawa^{1,2}, Toru Shirai^{1}, Hisaaki Ochi^{1}, and Yoshitaka Bito^{3}

^{1}Research & Development Group, Hitachi, Ltd., Tokyo, Japan, ^{2}Graduate School of Engineering, Chiba University, Chiba, Japan, ^{3}Healthcare Business Unit, Hitachi, Ltd., Tokyo, Japan

In this study, we proposed a method for characterizing intravoxel spatial distribution of diffusion by using texture analysis with GLCM (gray level cooccurrence matrix) from single-shell diffusion MRI data, which can be acquired in practical scan time. Since the method does not assume a diffusion distribution model, unstable calculation such as fitting process is not required. The method could provide novel diagnostic indices of diffusion MRI without additional acquisition.

In this study, we proposed a method for characterizing intravoxel spatial distribution of diffusion by using texture analysis with GLCM (gray level cooccurrence matrix) from single-shell diffusion MRI data, which can be acquired in practical scan time. Since the method does not assume a diffusion distribution model, unstable calculation such as fitting process is not required.

$$ASM=\sum_i^M\sum_j^M(p(i,j))^{2}\quad\quad(1)\\ $$

$$IDM=\sum_i^M\sum_j^M\frac{1}{1+|i-j|}p(i,j)\quad\quad(2)\\ $$

$$Contrast=\sum_i^M\sum_j^M(i-j)^{2}p(i,j)\quad\quad(3)\\ $$

$$Entropy=\sum_i^M\sum_j^Mp(i,j)\log[p(i,j)]\quad\quad(4)\\ $$

$$Correlation=\sum_i^M\sum_j^M\frac{(i-\mu)(j-\mu)}{\sigma^{2}}p(i,j)\quad\quad(5)\\ $$

where,

For evaluation of the proposed method, two-dimensional spin-echo diffusion-weighted echo planner imaging (DW-EPI) was performed on six healthy volunteers using a 3 T MRI system (Hitachi, Ltd.). Images of 24 gradient directions and b-values (0 and 1000 s/mm2) were obtained. The study was approved by the ethics committee of Hitachi group headquarters. We compared conventional DTI-derived indices (MD and FA) with proposed indices (ASM, IDM, Contrast, Entropy, and Correlation).

1. Alexander AL1, Lee JE, Lazar M, et al. Diffusion tensor imaging of the brain, Neurotherapeutics. 2007;4(3):316-326.

2. Descoteaux M, Angelino E, Fitzgibbons S, et al. Regularized, Fast, and Robust Analytical Q-Ball Imaging, Magn Reson Med. 2007;58(3):497-510.

3. Zhang H, Schneider T, Wheeler-Kingshott CA, et al. NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage 2012;61(4):1000-1016.

Figure 1
Processing flow of the proposed method

Figure 2
Diagrammatic illustration of GLCM in the proposed method

Figure
3 MD, FA, ASM, IDM, Contrast, Entropy,
and Correlation images

Figure 4
Correlation between conventional indices (MD and FA) and texture features (ASM, IDM, Contrast, Entropy, and
Correlation)

Table
1 Correlation coefficient between conventional
indices (MD and FA) and texture features (ASM, IDM, Contrast, Entropy, and
Correlation)