Departments of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, Netherlands.
School for Mental Health & Neuroscience, Maastricht University Medical Center, Maastricht, Netherlands.
J Magn Reson Imaging. 2017 Dec;46(6):1728-1737. doi: 10.1002/jmri.25700. Epub 2017 Mar 11.
To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy.
The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated. Using a model time series consisting of multiple harmonics and nonstationary components, the wavelet entropy was compared with Shannon and spectral (Fourier-based) entropy. As an application, the wavelet entropy in 22 children with Rolandic epilepsy was compared to 22 age-matched healthy controls. The images were obtained by performing resting-state functional magnetic resonance imaging (fMRI) using a 3T system, an 8-element receive-only head coil, and an echo planar imaging pulse sequence ( T2*-weighted). The wavelet entropy was also compared to spectral entropy, regional homogeneity, and Shannon entropy.
Wavelet entropy was found to identify the nonstationary components of the model time series. In Rolandic epilepsy patients, a significantly elevated wavelet entropy was observed relative to controls for the whole cerebrum (P = 0.03). Spectral entropy (P = 0.41), regional homogeneity (P = 0.52), and Shannon entropy (P = 0.32) did not reveal significant differences.
The wavelet entropy measure appeared more sensitive to detect abnormalities in cerebral fluctuations represented by nonstationary effects in the BOLD time series than more conventional measures. This effect was observed in the model time series as well as in Rolandic epilepsy. These observations suggest that the brains of children with Rolandic epilepsy exhibit stronger nonstationary temporal signal fluctuations than controls.
2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1728-1737.
评估小波熵在描述静息状态血氧水平依赖（BOLD）信号波动时间序列固有异常时变不规则性中的作用。进一步，在罗兰氏癫痫儿童的脑内，基于体素评估时间不规则性（无序/有序）。
BOLD 时间序列采用离散小波变换进行分解，并计算小波熵。使用由多个谐波和非平稳分量组成的模型时间序列，将小波熵与香农熵和频谱（基于傅里叶变换）熵进行比较。作为应用，将 22 例罗兰氏癫痫儿童的小波熵与 22 例年龄匹配的健康对照进行比较。使用 3T 系统、8 个接收线圈和回波平面成像脉冲序列（T2*-加权）进行静息状态功能磁共振成像（fMRI）获得图像。小波熵还与频谱熵、局部一致性和香农熵进行了比较。
小波熵被发现可以识别模型时间序列的非平稳分量。与对照组相比，罗兰氏癫痫患者整个大脑的小波熵明显升高（P=0.03）。频谱熵（P=0.41）、局部一致性（P=0.52）和香农熵（P=0.32）没有发现显著差异。
与更传统的测量方法相比，小波熵测量方法在检测 BOLD 时间序列中代表非平稳效应的脑波动异常方面更为敏感。这种效应在模型时间序列以及罗兰氏癫痫中都观察到。这些观察结果表明，罗兰氏癫痫儿童的大脑表现出比对照组更强的非平稳时间信号波动。
2 技术功效：第 3 阶段 J. Magn. Reson. Imaging 2017;46:1728-1737.
