Skewness and Kurtosis of Apparent Diffusion Coefficient in Human Brain Lesions to Distinguish Benign and Malignant Using MRI

Abstract

The application of Diffusion Weighted Imaging (DWI) in cancer identification and discrimination is increase singly interest within last decade. DWI has significant advantages, as it does not require contrast medium and provides qualitative and quantitative information that can be helpful for lesion assessment. Therefore, this study presents the utility of skewness and kurtosis of Apparent Diffusion Coefficient (ADC) to distinguish between benign and malignant brain lesions. All the Magnetic Resonance Imaging (MRI) scans were performed with a 3 Tesla Siemens Skyra MR system using a head coil. The sample consists of six subjects with locally advanced brain lesion. The Echo-Planar Imaging pulse sequence was used to acquire axial DW MRI data with a flip angle = \(90^{\circ }\), Time of Echo/Time of Repetition (TE/TR) = 98/6400 ms, Field of View (FOV) = 256 mm, matrix size = 256 \(\times \) 256, slice thickness of 1 mm and two levels of diffusion sensitization (\({\text {b} = 0 \text { and } 1000\,\text {s}/\text {mm}^2}\)). MATLAB 2014 Simulink software was used for the data analysis. The Region of Interest (ROI) the brain lesion was selected. The mean values of both the skewness and kurtosis of ADC within the ROI were determined and finally, the values were compared between benign and malignant brain lesions. The mean kurtosis and skewness of malignant and benign are 3.201, 3.738 and 0.071, 0.463 respectively. The mean kurtosis of benign is significantly high whereas mean skewness is significantly low. Therefore, there is a possibility of utilizing mean skewness and kurtosis pixel values as a potential biomarker to differentiate between benign and malignant brain lesions. ...