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Table 2 Univariate analysis of patient and lesion characteristics (DCE+DTI) 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

  Pathology status*    Univariate model
Malignant (N = 95) Benign (N = 143) AUC (95% CI) OR† (95% CI) p value
Clinical/DCE-MRI parameters
 Age, years 54.7 ± 11.3 49.3 ± 11.8 0.63 (0.56–0.71) 1.60 (1.19, 2.16) 0.002
 Post-menopausal 61 (64.2) 67 (46.9) 0.59 (0.52–0.66) 2.04 (1.14, 3.62) 0.016
 MRI indication: known cancer 77 (81.1) 84 (58.7) 0.61 (0.55–0.67) 3.00 (1.54, 5.85) 0.001
 Dense breasts 57 (60.0) 117 (81.8) 0.61 (0.55–0.67) 0.33 (0.18, 0.62) 0.001
 BPE category (1–4) 1.9 ± 1.0 2.3 ± 0.9 0.62 (0.54–0.70) 0.65 (0.47, 0.88) 0.006
 Lesion size, cm‡ 26.9 ± 27.1 16.3 ± 17.7 0.64 (0.57–0.71) 1.66 (1.27, 2.16) < 0.001
 Mass vs. NMLE/focus 54 (56.8) 81 (56.6) 0.50 (0.43–0.57) 1.01 (0.58, 1.76) 0.98
 Washout on delayed phase kinetics 87 (91.6) 111 (77.6) 0.57 (0.53–0.61) 3.14 (1.41, 7.00) 0.005
 BI-RADS 5 vs. 4 17 (17.9) 3 (2.1) 0.58 (0.53–0.62) 10.17 (2.11, 49.10) 0.004
DTI parameters
 Mean ADC, 10−3 mm2/s 1.26 ± 0.32 1.55 ± 0.30 0.75 (0.68–0.82) 0.37 (0.25, 0.54) < 0.001
 Mean axial diffusivity, 10−3 mm2/s 1.62 ± 0.41 1.91 ± 0.36 0.73 (0.66–0.80) 0.42 (0.28, 0.64) < 0.001
 Mean radial diffusivity, 10−3 mm2/s 1.08 ± 0.35 1.37 ± 0.33 0.74 (0.67–0.81) 0.40 (0.28, 0.59) < 0.001
 Mean FA‡ 0.28 ± 0.15 0.23 ± 0.13 0.61 (0.53–0.68) 1.45 (1.11, 1.91) 0.007
 Mean λ1 − λ3‡, 10−3 mm2/s 0.69 ± 0.46 0.69 ± 0.40 0.52 (0.44–0.60) 0.96 (0.74, 1.25) 0.77
  1. AUC area under the ROC curve, ROC receiver operating characteristic curve, OR odds ratio for malignancy, CI confidence interval
  2. *Values are no. (%) or mean ± SD
  3. †For continuous variables, ORs are scaled to show change per 1-SD increase in the corresponding variable
  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; A blank cell indicates that the corresponding variable was not included as a candidate predictor in the model
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