ABSTRACT
Objective The histological grade of breast cancer is closely related with the treatment and prognosis of the malignancy, and radiomics plays a valuable role in the identification of its grade. This article aimed to investigate the values of the conventional parameters of breast MRI and breast MRI-based imaging features in the histological grading of breast invasive ductal carcinoma (IDC).Methods This retrospective study included 71 cases of breast cancer treated in our hospital from June 2015 to June 2016. We obtained the traditional quantitative parameters of MRI, including the apparent diffusion coefficient (ADC) and initial enhancement rate (IER), performed manual segmentation of the ADC and DCE maps, extracted the radiomic features and analyzed the differences in the radiomic signatures between low- and high-grade IDC. Using logistic regression analysis, we assessed the values of ADC and IER and the radiomic signatures of the ADC and DCE images in differentiating low-grade from high-grade IDC.Results The values of ADC, B_sum_variance, L_SRE and R_RP were significantly lower (P0.05). In differentiating high-grade from low-grade IDC, the ADC image-based radiomic signature model achieved a significantly higher AUC (0.858 [0.774-0.924]) than the ADC (0.709 [0.588-0.830]) and DCE model (0.691 [0.565-0.818]), and the former also manifested markedly higher accuracy, specificity, and rates of positive and negative prediction than the latter two.Conclusion ADC- and MRI-based radiomic features play a valuable role in differentiating high-grade from low-grade IDC, particularly the former, which could provide even more clinical information, while IER is of little value in this aspect.
ABSTRACT
<p><b>OBJECTIVE</b>To evaluate the diagnostic value of mammography, computed tomography (CT), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for axillary lymph node staging in breast cancer patients.</p><p><b>METHODS</b>From February, 2014 to October, 2015, 109 women with breast cancer received examinations with preoperative mamography, CT, and DCE-MRI. The diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the 3 modalities were evaluated using histopathologic assessments as the gold standard.</p><p><b>RESULTS</b>In total, 39.4% (43/109) of the patients had axillary lymph node metastasis. The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of mamography for determining lymph node metastasis were 14.0%, 84.8%, 56.9%, 37.5% and 60.0%, respectively; those of CT were 93.0%, 57.6%, 71.6%,58.8% and 92.7%, and those of DCE-MRI were 95.3%, 65.2%, 77.1%, 64.1% and 95.6%, respectively. Compared with the histopathologic result, the Kappa coefficients of mamography, CT, and DCE-MRI were -0.13, 0.459 and 0.558, respectively. The specificity of mamography was significantly higher (P<0.05), but its sensitivity, accuracy, positive predictive value, and negative predictive value were significantly lower than those of CT and DCE-MRI (P<0.05). Compared with CT, DCE-MRI had significantly higher sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for diagnosis of lymph node metastasis (P<0.05).</p><p><b>CONCLUSION</b>DCE-MRI has a greater diagnostic power than CT and mammography, and CT has a greater diagnostic power than mammography for axillary lymph node metastasis in breast cancer patients. Mamography alone should be used cautiously for the diagnosis of lymph node metastasis.</p>