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Maximum slope using ultrafast breast DCE-MRI at 1.5 Tesla: a potential tool for predicting breast lesion
Margaux Pelissier1, Khalid Ambarki2, Julia Salleron3
1Department of Radiology, Institut de Cancérologie de Lorraine, 6 avenue de Bourgogne, 54 519, Vandoeuvre-les-Nancy, France.
Objectives:
We evaluated the relationship between the maximum slope (MS) based on ultrafast breast DCE-MRI sequences, and the clinical parameters and routine prognostic factors of breast cancer.
Methods:
210 lesions were retrospectively evaluated: 150 malignant (30 each of luminal A invasive carcinoma, luminal B invasive carcinoma, HER2 overexpression (HER2), triple negative (TN), invasive lobular carcinoma (ILC)), and 60 benign. For each lesion, the MS was obtained with an ultrafast sequence and semi-quantitative curves were classified into three types with a conventional DCE sequence. The correlation between MS and age, body mass index (BMI), menopause, and routine prognostic factors were analyzed.
Results:
A MS cut-off at 6.5%/s could discriminate benign from malignant lesions, with sensitivity and specificity of 84% and 90%, respectively, whereas analysis of semi-quantitative curves showed sensitivity and specificity of 89.3% and 55%, respectively. In multivariate analysis, MS values decreased with BMI increasing (p = 0.035), postmenopausal status (p < 0.001), and positive ER status (p < 0.001) and increased with tumor size (p < 0.001). The MS was significantly lower for the pooled luminal A + ILC group than for the pooled luminal B + HER2 + TN group featuring tumors with poorer prognoses (p < 0.001). With a threshold of 11%/s, the sensitivity and specificity to identify invasive carcinoma subtypes with poorer prognoses were 71% and 68%, respectively.
Conclusion:
The MS allows better tumor characterization and identifies factors of poor prognosis for breast cancer.
Key Points:
• Maximum slope calculated from ultrafast breast DCE-MRI differentiates benign from malignant breast lesions better than semi-quantitative curves of conventional DCE-MRI. • Maximum slope calculated from ultrafast breast DCE-MRI identifies breast cancers with poor prognoses. • In the case of multiple lesions, the most aggressive may be identified and targeted by measuring the maximum slope.
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