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Table 2 Descriptive characteristics of selected computer-extracted features

From: Relationships between computer-extracted mammographic texture pattern features and BRCA1/2mutation status: a cross-sectional study

    Correlation with percent mammographic density (n = 237) Correlation with age (n = 237) Non-carriers (n = 100) UnaffectedBRCA1/2carriers (n = 137)
Feature type and number Feature1 Definition r* P-value r* P-value Mean (SD) Range Mean (SD) Range
Gray-level magnitude-based features:           
M1 AVE Average gray value within ROI; higher values correspond to denser region 0.31 <0.0001 0.01 0.89 139.6 (26.1) 69.0, 223.5 134.1 (28.9) 59.0, 242.0
M2 MinCDF Gray value corresponding to the 5% region cutoff on cumulative density function; higher values correspond to denser region -0.13 0.04 0.23 0.0005 98.0 (23.6) 35.0, 162.0 78.1 (27.3) 15.0, 210.0
M3 Balance Ratio of (95% CDF-AVE) to (AVE-5% CDF); related to skewness; values less than one correspond to having an ROI that is skewed toward relatively denser values -0.32 <0.0001 -0.04 0.49 1.07 (0.42) 0.45, 3.31 1.11 (0.40) 0.38, 2.33
Texture-based features:           
T1 Energy Measure of image homogeneity; higher values correspond to being more homogeneous -0.30 <0.0001 0.19 0.003 0.004 (0.011) 0.0, 0.109 0.003 (0.004) 0.0, 0.028
T2 MaxF (COOC) Largest number of a gray value pair in the co-occurrence matrix; measure of image homogeneity; higher values correspond to being more homogeneous -0.24 0.0002 0.15 0.02 0.012 (0.024) 0.001, 0.239 0.010 (0.017) 0.001, 0.145
  1. CDF, cumulative density function; COOC, co-occurrence; ROI, region-of-interest. *Spearman’s rank correlation coefficient. 1All features were selected using the training dataset. The Balance feature was only selected in sensitivity analyses where the training dataset was truncated at the upper age-limit of mutation carriers. P-values <0.05 are shown in bold font.