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Table 5 Multivariate Clinical/DCE-MRI+DTI LASSO model with type- and size-specific DTI parameters

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

  Odds ratios*
Model without interactions Model with interactions
Clinical/DCE-MRI parameters
 Age, per 1-SD increase 1.17 1.20
 Post-menopausal NS NS
 MRI indication: known cancer 1.88 1.84
 Dense breasts 0.61 0.50
 BPE category, per 1-category increase 0.66 0.59
 Lesion size, per 1-SD increase 1.85 2.18
 Mass vs. NMLE/focus 1.89 2.28
 Washout on delayed phase kinetics 2.43 3.07
 BI-RADS 5 vs. 4 2.36 2.97
DTI parameters
 Mean ADC, per 1-SD increase
  Small non-masses 0.41 1.00
  Large non-masses 0.41 0.35
  Small masses 0.41 0.36
  Large masses 0.41 0.13
 Mean FA, per 1-SD increase
  Small non-masses 0.88 0.47
  Large non-masses 0.88 0.41
  Small masses 0.88 1.17
  Large masses 0.88 1.02
Bootstrap-adjusted AUC 0.81 0.85
(95% CI) (0.78, 0.88) (0.82, 0.90)
  1. Small lesion, < 1 cm; large lesion, ≥ 1 cm
  2. *For continuous variables, ORs are scaled to show change per 1-SD increase in the corresponding variable
  3. The model with interactions included addition terms corresponding to type × ADC, size × ADC, type × FA, and size × ADC, allowing all 4 subgroups (type × size) to have different ORs for ADC and different ORs for FA; the model without interactions contains 12 regression parameters (including the intercept), and the model with interactions contains 16 regression parameters
  4. Variable was log-transformed prior to inclusion in the logistic regression model to reduce right-skewness
  5. NS = variable was included as a candidate predictor but was not selected by the LASSO