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Background: MammaPrint assigns chemotherapeutic benefits to patients with estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative, and 1 to 3 node-positive invasive breast cancer. However, its cost and time-consuming nature limit its use in certain clinical settings. We aimed to develop and validate the prediction models for the low MammaPrint risk group using clinicopathologic and MRI features., Patients and Methods: Overall, 352 women with ER-positive, HER2-negative, and 1 to 3 node-positive invasive breast cancer were retrospectively reviewed and assigned to development (n = 235) and validation sets (n = 117). Univariate and multivariate analyses identified features associated with the low MammaPrint risk group. The area under the receiver operating characteristic curves (AUROCs) of models based on clinicopathologic, MRI, and combined features were evaluated., Results: Development set multivariate analysis showed that clinicopathologic features including low histologic grade (odds ratio [OR], 5.29; P = .02), progesterone receptor-positivity (OR, 3.23; P = .01), and low Ki-67 (OR, 6.05; P < .001) and MRI features, including peritumoral edema absence (OR, 2.24; P = .04) and a high proportion of persistent components (OR, 1.15; P = .004) were significantly associated with the low MammaPrint risk group. The AUROCs of models based on clinicopathologic, MRI, and combined features were 0.77, 0.64, and 0.80 in the development and 0.66, 0.60, and 0.70 in the validation sets, respectively., Conclusion: The combined model incorporating clinicopathologic and MRI features showed potential in predicting the low MammaPrint risk group, and may support decision-making in clinical settings with limited access to MammaPrint., Competing Interests: Disclosure The authors have stated that they have no conflicts of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Purpose: To examine correlations between shear-wave elastography (SWE) parameters with molecular subtype and axillary lymph node (LN) status of breast cancer., Methods: We retrospectively analyzed 545 consecutive women (mean age, 52.7 ± 10.7 years; range, 26-83) with breast cancer who underwent preoperative breast ultrasound with SWE between December 2019 and January 2021. SWE parameters (E max , E mean , and E ratio ) and the histopathologic information from surgical specimens including histologic type, histologic grade, size of invasive cancer, hormone receptor and HER2 status, Ki-67 proliferation index, and axillary LN status were analyzed. The relationships between SWE parameters and histopathologic findings were analyzed using an independent sample t-test, one-way ANOVA test with Tukey's post hoc test, and logistic regression analyses., Results: Higher stiffness values of SWE were associated with larger lesion size (>20 mm) on ultrasound, high histologic grade, larger invasive cancer size (>20 mm), high Ki-67, and axillary LN metastasis. E max and E mean were the lowest in the luminal A-like subtype, and all three parameters were the highest in the triple-negative subtype. Lower value of E max was independently associated with the luminal A-like subtype (P = 0.04). Higher value of E mean was independently associated with axillary LN metastasis for tumors ≤ 20 mm (P = 0.03)., Conclusion: Increases in the tumor stiffness values on SWE were significantly associated with aggressive histopathologic features of breast cancer. Lower stiffness values were associated with the luminal A-like subtype, and tumors with higher stiffness values were associated with axillary LN metastasis in small breast cancers., Competing Interests: Declaration of competing interest All other authors of the present study declare no competing interests., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Introduction: The purpose of this study is to investigate the differences in clinical outcomes between microinvasive carcinoma (mIC) and ductal carcinoma in situ (DCIS) and compare the imaging features of both using mammography, US and MRI., Materials and Methods: This retrospective study was approved by our institutional review board. Between January 2011 and December 2013, 516 women with mIC or DCIS confirmed by surgery were included. Patients were matched with propensity score matching to compare recurrence-free survival (RFS). RFS was compared using a Cox proportional hazards model. Imaging features were also compared between the two groups., Results: Among 516 women, 219 mIC and 297 DCIS tumors were identified. After matching, 132 women were allocated to each group. The mean follow-up duration was 80.2 months. In the matched cohort, no statistically significant association was observed between the DCIS and mIC groups in terms of total recurrence (hazard ratio [HR]: 1.7; 95% confidence interval [CI]: 0.8-4.0; P = 0.19), local-regional recurrence (HR: 3.4; 95% CI: 0.9-12.3, P = 0.07), or contralateral recurrence (HR: 0.9; 95% CI: 0.3-2.8, P = 0.89). Non-mass lesions at US (P = 0.004), moderate or marked background parenchymal enhancement (P = 0.04), and higher peak enhancement (P = 0.02) at MRI were more commonly seen in the mIC group than in the DCIS group., Conclusion: Microinvasive carcinomas are distinct from DCIS in terms of imaging features, but no statistically significant association in recurrence survival., Competing Interests: Declaration of competing interest The authors have stated that they have no conflicts of interest., (Copyright © 2023. Published by Elsevier Inc.)

Background: 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., Methods: 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., Results: 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)., Conclusion: 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., (Copyright © 2022 Elsevier Inc. All rights reserved.)

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., Competing Interests: Disclosure The authors have stated that they have no conflicts of interest., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Oncotype DX is a multigene assay used in breast cancer, and the result provided as a 'recurrence score (RS)' corresponds to the risk of a cancer recurrence and the chemotherapeutic benefit in estrogen receptor (ER)-positive human epidermal growth factor receptor (HER)2-negative invasive breast cancer. However, its accessibility is limited., Purpose: To evaluate whether magnetic resonance imaging (MRI) could be used to predict Oncotype DX RS in patients with ER-positive HER2-negative invasive breast cancer., Material and Methods: We enrolled 473 patients with ER-positive HER2-negative invasive breast cancer who underwent a preoperative MRI and Oncotype DX assay between January 2015 and December 2018. The MRI was reviewed and associations between Oncotype DX RS values were evaluated. Logistic regression analysis was used to identify independent predictors of high and low RS., Results: Of the 485 cancers, 288 (59.4%) had low (<18), 155 (31.9%) had intermediate (18-30), and 42 (8.7%) had high (≥31) RS. Multiple logistic regression analysis revealed that a round shape (odds ratio [OR] = 2.554, P = 0.089) and low proportion of washout component (OR = 1.011, P = 0.014) were associated with low RS and that heterogeneously dense (OR = 3.205, P = 0.007) or scattered fibroglandular (OR = 3.776, P = 0.005) breast tissue, a non-spiculated margin (OR = 5.435, P = 0.007), and low proportion of persistent component (OR = 1.012, P = 0.036) were associated with high RS., Conclusion: MRI features showed the potential for the discrimination of Oncotype DX RS in patients with ER-positive HER2-negative invasive breast cancer., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objective: The purpose of this study was to evaluate the feasibility of image fusion between US and supine MRI in breast cancer patients, and to evaluate differences in tumor location between prone and supine positions., Methods: This prospective study included 88 patients who underwent an additional supine MRI (MRsup) sequence following routine prone MRI (MRpro) for breast cancer between May 2016 and December 2017. The location of the tumor and discrepancies in the distances from nipple to lesion (NLD), skin to lesion (SLD), and chest wall to lesion (CLD) were evaluated between MRpro and MRsup (MRpro-sup), MRpro and MRsup-navigated US (MRpro-USnav), and MRsup and USnav (MRsup-USnav). Associations between breast thickness and measurement discrepancies were analyzed., Results: Total 91 index lesions were evaluated. The intraclass correlation coefficients (ICCs) for the location of MRpro and MRsup compared with USnav were 0.994 (range: 0.990-0.996) and 0.998 (range: 0.996-0.999), respectively. The mean MRpro-sup and MRpro-USnav measurement discrepancies were greater than those of MRsup-USnav, significantly. Most outer locations showed greater mean measurement discrepancies than inner locations, and each NLD, SLD, and CLD mean measurement discrepancy showed different tendencies according to location (upper or lower) and lesion depth (superficial, middle, or deep). High breast thickness showed significantly greater mean measurement discrepancies than low breast thickness., Conclusion: Image fusion between US and supine MRI is feasible in breast cancer patients, although there is a considerable difference in tumor location measurements between prone and supine positions, especially with thicker breasts., Competing Interests: Declaration of Competing Interest None., (Copyright © 2019. Published by Elsevier Taiwan LLC.)

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., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background/objective: The purpose of this study was to perform a comprehensive analysis of the radiological and clinicopathological factors that could predict recurrence of invasive breast cancer who underwent curative surgery without neoadjuvant chemotherapy., Methods: Three hundred and sixty-four consecutive women who underwent preoperative mammography, ultrasound, and breast magnetic resonance imaging for newly diagnosed invasive breast cancers and curative surgery between January and December 2010 were included. We analyzed the radiological findings of each modality and reviewed the histopathological features. A Cox proportional hazards model was used to determine the association between the radiological and clinicopathological parameters and disease-free survival (DFS)., Results: During the median follow-up period of 5.3 years, 23 patients (6.3%) developed recurrences: locoregional recurrence in six patients, contralateral breast recurrence in three patients, and distant recurrences in 14 patients. Microcalcifications on mammography showed a tendency towards worse DFS. The multivariate Cox regression analysis showed that presence of lymphovascular invasion (LVI) (p = 0.006), negative progesterone receptor (PR) status (p < 0.001), and positive CK5/6 expression (p = 0.015) were independent significant variables predictive of worse DFS., Conclusion: Understanding the prognostic factors in patients with invasive breast cancer may provide considerable practical information about future treatment strategies., (Copyright © 2018. Published by Elsevier Taiwan LLC.)

Background: 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., Materials and Methods: 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., Results: 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)., Conclusion: 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., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Purpose: To evaluate the diagnostic performance of fused diffusion-weighted imaging (DWI) using T1-weighted imaging (T1WI) for axillary nodal staging in patients with early breast cancer (stage I or II)., Materials and Methods: We enrolled 149 axillae in 147 consecutive patients who performed preoperative breast magnetic resonance imaging (MRI) and definitive surgery. All patients underwent T2-weighted imaging (T2WI), fused DWI using T1WI, and non-fat-suppressed (non-FS) T1WI. Two radiologists scored each axillary nodal status by using a 5-point scale and independently measured the apparent diffusion coefficient (ADC) values of the most suspicious lymph node and an index tumor. Diagnostic performance was calculated on a patient-by-patient basis., Results: Macrometastasis was present in 26.2%, micrometastasis in 7.4%, and benign lymph nodes in 66.4%. Area under the receiver operating characteristic curves (AUCs) of both readers for predicting axillary lymph node metastasis were 0.676 and 0.603 for non-FS T1WI, 0.749 and 0.727 for T2WI, 0.838 and 0.790 for fused DWI, and 0.868 and 0.837 for the combined reading using ADC. AUCs of tumor ADC were 0.709 and 0.737, whereas those of lymph node ADC were 0.818 and 0.781 for both readers. With stepwise addition of tumor ADC, lymph node ADC, and lymphovascular invasion status to the fused DWI, the AUCs gradually increased from 0.838, 0.892, and 0.908 to 0.924 for reader 1 and from 0.790, 0.863, and 0.901 to 0.908 for reader 2., Conclusion: Fused DWI using T1WI showed better diagnostic performance than conventional T2WI and non-FS T1WI for the prediction of lymph node metastasis., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: 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., Patients and Methods: 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., Results: 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., Conclusion: 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., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: To assess whether perfusion and diffusion parameters were different between low-risk tumors and non-low-risk tumors., Materials and Methods: We prospectively enrolled 87 patients with 91 tumors patients (mean, 49.6 years; range, 29-74 years) who underwent definitive surgery. We defined estrogen receptor (ER)-positive tumors with low histologic grade (HG), low Ki67 (<14%), and negative lymph node metastasis as a low-risk breast cancer. We obtained quantitative and semiquantitative perfusion parameters and apparent diffusion coefficient (ADC) for all tumors. We compared perfusion parameters and ADCs between low-risk tumors (n=33; 36%) and the others (n=58; 64%) using Fisher's exact test, Chi-square test, and student t-test. We developed empirical model to predict low-risk tumor using logistic regression analysis and receiver operating characteristics (ROC) analysis., Results: On univariate analysis, wash-in and the initial area under the curve on qualitative analysis (iAUCqualitative) were significantly different according to HG, ER, HER-2, Ki67 and lymphovascular invasion (P<.05 for all variables). ADCdiff was significantly different according to HG, HER-2, and Ki67 status (P=.010, .007, and .013). On multivariate analysis, Ktrans, iAUCqualitative, and ADCdiff were the significant variables for the prediction of low-risk tumors, and the area under the ROC curve (AUC) of combined parameters was 0.78, which was higher than those of the individual parameter. ADCdiff was positively correlated with wash-in (r=0.263) and iAUCqualitative (r=0.245), respectively., Conclusion: The prediction model using Ktrans, wash in, iAUCqualitative, and ADCdiff on DCE-MRI and DWI could be helpful for identifying of low-risk breast cancer and may be used as an imaging biomarker to guide the treatment plan., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Purpose: To evaluate the diagnostic performance of an apparent diffusion coefficient (ADC) and quantitative kinetic parameters in patients with newly diagnosed breast cancer., Materials and Methods: We enrolled 169 lesions in 89 patients with breast cancer who underwent dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). Comparisons between benign and malignant lesions were performed for lesion type (mass or nonmass-like enhancement), size (≥1cm or<1cm), ADC, kinetic parameters and the presence of a US correlate., Results: There were 63 benign and 106 malignant lesions. The mean size and initial peak enhancement of the benign lesions were significantly lower than those of malignant lesions (P<0.001 for both). The ADC of the benign lesions was significantly higher than that of malignant lesions (1.42×10(-3)mm(2)/sec vs. 1.04×10(-3)mm(2)/sec; P<0.001). The area under the receiver operating characteristic curve (AUC) for predicting malignancy was 0.87 for the combined parameters of size, ADC, and initial peak enhancement, which was higher than those of each parameter., Conclusions: Combination of quantitative kinetic parameters and ADC showed higher diagnostic performance for predicting malignancy than each parameter alone for the evaluation of patients with breast cancer., (Copyright © 2014 Elsevier Inc. All rights reserved.)