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Table 3 Multivariate LASSO models for discriminating between malignant and benign lesions

From: Diffusion tensor imaging for characterizing tumor microstructure and improving diagnostic performance on breast MRI: a prospective observational study

  Odds ratios*
Clinical/DCE-MRI DTI only Clinical/DCE-MRI+ADC Clinical/DCE-MRI+DTI
Clinical/DCE-MRI parameters
 Age, per 1-SD increase 1.23   1.16 1.17
 Post-menopausal NS   NS NS
 MRI indication: known cancer 1.64   1.90 1.88
 Dense breasts 0.45   0.64 0.61
 BPE category, per 1-category increase 0.68   0.65 0.66
 Lesion size, per 1-SD increase 1.96   1.95 1.85
 Mass vs. NMLE/focus 2.30   2.01 1.89
 Washout on delayed phase kinetics 2.92   2.52 2.43
 BI-RADS 5 vs. 4 4.47   2.56 2.36
DTI parameters
 Mean ADC, per 1-SD increase   0.41 0.44 0.41
 Mean FA, per 1-SD increase   NS   0.88
Bootstrap-adjusted AUC 0.76 0.75 0.81 0.81
(95% CI) (0.71, 0.83) (0.68, 0.82) (0.77, 0.88) (0.78, 0.88)
  1. *For continuous variables, ORs are scaled to show change per 1-SD increase in the corresponding variable
  2. Variable was log-transformed prior to inclusion in the logistic regression model to reduce right-skewness