MR-directed ultrasound of MRI-detected lesions was useful for decision making as part of the diagnostic workup. Malignant lesions were likely to have an ultrasound correlate, especially when they presented as masses on MRI. However, the sonographic findings of these lesions were often subtle, and careful scanning technique was needed for successful MRI-ultrasound correlation.
• Tumour ADC was significantly lower in LVI-positive than LVI-negative breast cancer. • Peritumoral maximum-ADC was significantly higher in LVI-positive than LVI-negative breast cancer. • Peritumour-tumour ADC ratio was significantly higher in LVI-positive breast cancer. • Diagnostic performance of the peritumour-tumour ADC ratio was highest for positive LVI. • Peritumour-tumour ADC ratio showed higher diagnostic ability in postmenopausal than premenopausal patients.
A multi-parametric computer-aided diagnosis (CADx) scheme that combines information from T1-weighted DCE-MRI and T2-weighted MRI was investigated using a database of 110 malignant and 86 benign breast lesions. Automatic lesion segmentation was performed, and three categories of lesion features (geometric, T1-weighted DCE, and T2-weighted) were automatically extracted. Stepwise feature selection was performed considering only geometric features, only T1-weighted DCE features, only T2-weighted features, and all features. Features were merged with Bayesian artificial neural networks, and diagnostic performance was evaluated by ROC analysis. With leave-one-lesion-out cross-validation, an AUC value of 0.77 ± 0.03 was achieved with T2-weighted-only features, indicating high diagnostic value of information in T2-weighted images. AUC values of 0.79 ± 0.03 and 0.80 ± 0.03 were obtained for geometric-only features and T1-weighted DCE-only features, respectively. When all features were considered, an AUC value of 0.85 ± 0.03 was achieved. We observed p-values of 0.0006, 0.023, and 0.0014 between the {geometric-only, T1-weighted DCE-only, and T2-weighted-only features} and all features conditions, respectively. When ranked, the p-values satisfied the Holm-Bonferroni multiple-comparison test; thus, the improvement of multi-parametric CADx was statistically significant. A CADx scheme that combines information from T1-weighted DCE and T2-weighted MRI may be advantageous over conventional T1-weighted DCE-MRI CADx.
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