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The precise preoperative evaluation of radiologic tumor size with extensive intraductal component (EIC) is important. This study compared the accuracy of mammography, ultrasound (US), and magnetic resonance imaging (MRI) to measure invasive breast cancer with EIC.Between 2007 and 2012, we collected data from 6816 patients who underwent surgery for invasive breast cancer at our institution. We reviewed the postoperative surgical reports of the tumors, in which the invasive tumor size and EIC were measured separately. Finally, we included 370 women who underwent preoperative mammography, US, and MRI. Each modality was retrospectively reviewed to measure the size of invasive breast cancer with EIC. The reference standard was surgical pathologic size and the accuracies of the image were evaluated.Spearman's correlation coefficient for the size of invasive cancer with EIC was good between MRI (r = 0.741) and pathology, and moderate between mammography (r = 0.661) or US (r = 0.514) and pathology. Both mass and nonmass lesions showed good correlations (intraclass correlation coefficient [ICC] = 0.672 and 0.612, respectively) in MRI. Furthermore, the subgroup of tumors without microcalcifications showed a higher correlation with MRI (ICC = 0.796) than with mammography (ICC = 0.620). However, the subgroup with microcalcifications showed a good correlation with mammography (ICC = 0.702) compared to MRI (ICC = 0.680) and US (ICC = 0.532).The lesion on mammography, US, and MRI reflected preoperative size of invasive cancer with EIC. MRI shows a higher correlation than mammography and US. However, cancer with calcifications of mammography shows a more accurate size than MRI or US.

Background To assess the performance of contrast-enhanced spectral mammography (CESM) for the prediction of DCIS underestimation in comparison with mammography, breast US, and breast MRI. Patients and Methods We prospectively enrolled patients diagnosed with DCIS on preoperative core biopsy. Visibility, lesion type, and extent on each imaging modality, CESM gray values (CGV) were evaluated. Pathologic features of core biopsy and surgery were recorded. Chi-square or Fisher's exact test were used for univariate analysis. Multivariate logistic regression analysis was used to find independent predictors for DCIS underestimation and receiver operating characteristic (ROC) curve analysis was performed. Results A total of 113 lesions in 108 patients were analyzed (50 pure DCIS; 63 underestimated DCIS). Visibility on mammography, breast US, CESM, and breast MRI were 44%, 76%, 58%, and 80% for pure DCIS, and 73%, 81%, 86%, and 92% for underestimated DCIS. Tumor extents on surgical pathology of pure and underestimated DCIS were 1.11 ± 1.35 cm and 2.61 ± 2.09 cm. On multivariate analysis, nuclear grade and suspected invasion on core biopsy, visibility on mammography, and extent on breast MRI were independent factors for the model 1, whereas nuclear grade on core biopsy, extent on CESM, and mean CGV on MLO-recombined image were independent factors for the model 2. Area under ROC curve (AUC) was 0.843 for model 1 including breast MRI, whereas AUC was 0.823 for model 2 including CESM, which didn't show a significant difference (P = .968). Conclusion For detecting underestimated DCIS, CESM was superior to mammography and breast US, and comparable to breast MRI.

We evaluated the tumor response after neoadjuvant chemotherapy (NAC) in breast cancer patients using dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging parameters assessed using a commercially available computer-aided system. We also analyzed their correlation with pathologic tumor cellularity.We retrospectively reviewed the data from 130 patients with breast cancer who had undergone NAC followed by surgery from January to October 2013. Maximum diameter, volume, peak enhancement, and persistent, plateau, and washout-enhancing components were measured using a computer-aided system on DCE MR images and correlated with the Miller-Payne grading system. Patients with a Miller-Payne grade of 5 were classified into the pathologic complete response (pCR) group. Patients with grades 1, 2, 3, and 4 were included in the non-pCR group. Diagnostic performance was evaluated using receiver operating characteristic curve analysis.Twenty patients were included in the pCR group and 110 patients in the non-pCR group. Of the 6 parameters, the rate of tumor volume reduction (r = 0.729, P .001) showed the strongest correlation with the Miller-Payne grading system, followed by the maximum diameter (r = 0.706, P .001) and washout component (r = 0.606, P .001). The area under the receiver operating characteristic curve (Az value) was the largest for the rate of volume reduction (Az = 0.895), followed by the maximum diameter (Az = 0.891).The tumor volume changes in breast cancers before and after NAC, measured automatically using a commercially available computer-aided system and a clinical DCE MR imaging protocol might be the most accurate tool for evaluation of the pathologic response after NAC.

Background In human epidermal growth factor receptor 2-positive (HER2+) breast cancer, the incorporation of a dual HER2 blockade into neoadjuvant chemotherapy (NAC) has been shown to induce a higher rate of pathologic complete response (pCR). The purpose of this study was to investigate whether pretreatment imaging and clinicopathologic features show any association with pCR in HER2+ breast cancer receiving NAC plus dual blockade. Materials and Methods This retrospective study evaluated 94 consecutive patients (mean age, 49.8 ± 9.9 years) with HER2+ breast cancer who underwent NAC plus dual blockade with trastuzumab and pertuzumab between April 2016 and June 2018. All patients underwent mammography, ultrasound, and magnetic resonance imaging prior to NAC. Clinicopathologic and imaging features acquired before NAC were evaluated for their ability to predict the pathologic response after surgery. Multivariate analysis was used to identify independent predictors of pCR. Results Fifty patients (53.2%) showed pCR and 44 (46.8%) did not. According to a univariate analysis, fine pleomorphic/fine linear or linear-branching calcification morphology on mammography, parallel orientation on ultrasound, intratumoral high signal intensity on T2-weighted magnetic resonance imaging, progesterone receptor negativity, and high levels of tumor-infiltrating lymphocytes were associated with pCR. On multivariate analysis, fine pleomorphic/fine linear or linear-branching calcification morphology on mammography (odds ratio [OR], 7.23), progesterone receptor negativity (OR, 6.76), and a high tumor-infiltrating lymphocyte level (OR, 5.92) remained significant independent factors associated with pCR. Conclusion Several pretreatment imaging and clinicopathologic features were shown to be independent variables predicting pCR in patients with HER2+ breast cancer receiving NAC with dual blockade.

The objective of the study was to compare the accuracy of different magnetic resonance (MR) sequences for measuring tumor size and to evaluate whether the imaging and histopathologic features affect the accuracy of the tumor size estimation on the MR sequence.Eight hundred women were included. The maximum diameter of the tumor was measured on T2-weighted (T2W) sequences, early-subtracted dynamic contrast-enhanced (DCE) T1-weighted (T1W) sequences, and maximal intensity projection (MIP) reconstructions. Agreement between the MR imaging and pathology-determined size were analyzed. Using the best MR sequence to measure the tumor size, the relationship between the accuracy and the imaging and histopathologic features were evaluated.Tumor measurement showed a good agreement with the pathology-determined size, and with the best results using MIP (k = 0.805) compared with the early-subtracted DCE T1W sequence (k = 0.802) and the T2W sequence (k = 0.779). On MIP, the tumors of patients with minimal or mild background parenchymal enhancement, a mass, invasive ductal carcinoma (IDC), pathology-determined size 2 cm, positive estrogen receptor, negative HER2, luminal A type, nuclear and histologic grade 1, negative nodal status, negative lymphovascular invasion, and negative extensive intraductal component were significantly more accurately estimated. The independent factors associated with the accuracy of tumor measurement were a mass, IDC, and the pathology-determined size 2 cm.Our study showed that tumor size is most accurately measured on MIP, especially for IDC appearing as a mass on MR imaging and with the pathology-determined size 2 cm.