Diffusion-weighted imaging of the abdomen: Impact of b-values on texture analysis features

The purpose of this work was to systematically assess the impact of the b-value on texture analysis in MR diffusion-weighted imaging (DWI) of the abdomen. In eight healthy male volunteers, echo-planar DWI sequences at 16 b-values ranging between 0 and 1000 s/mm(2) were acquired at 3 T. Three different apparent diffusion coefficient (ADC) maps were computed (0, 750/100, 390, 750 s/mm(2)/all b-values). Texture analysis of rectangular regions of interest in the liver, kidney, spleen, pancreas, paraspinal muscle and subcutaneous fat was performed on DW images and the ADC maps, applying 19 features computed from the histogram, grey-level co-occurrence matrix (GLCM) and grey-level run-length matrix (GLRLM). Correlations between b-values and texture features were tested with a linear and an exponential model; the best fit was determined by the smallest sum of squared residuals. Differences between the ADC maps were assessed with an analysis of variance. A Bonferroni-corrected p-value less than 0.008 (=0.05/6) was considered statistically significant. Most GLCM and GLRLM-derived texture features (12-18 per organ) showed significant correlations with the b-value. Four texture features correlated significantly with changing b-values in all organs (p < 0.008). Correlation coefficients varied between 0.7 and 1.0. The best fit varied across different structures, with fat exhibiting mostly exponential (17 features), muscle mostly linear (12 features) and the parenchymatous organs mixed feature alterations. Two GLCM features showed significant variability in the different ADC maps. Several texture features vary systematically in healthy tissues at different b-values, which needs to be taken into account if DWI data with different b-values are analyzed. Histogram and GLRLM-derived texture features are stable on ADC maps computed from different b-values.