Comparison of peritumoral stromal tissue stiffness obtained by shear wave elastography between benign and malignant breast lesions.

Background Aggressive breast cancers produce abnormal peritumoral stiff areas, which can differ between benign and malignant lesions and between different subtypes of breast cancer. Purpose To compare the tissue stiffness of the inner tumor, tumor border, and peritumoral stroma (PS) between benign and malignant breast masses by shear wave elastography (SWE). Material and Methods We enrolled 133 consecutive patients who underwent preoperative SWE. Using OsiriX commercial software, we generated multiple 2-mm regions of interest (ROIs) in a linear arrangement on the inner tumor, tumor border, and PS. We obtained the mean elasticity value (Emean) of each ROI, and compared the Emean between benign and malignant tumors. Odds ratios (ORs) for prediction of malignancy were calculated. Subgroup analyses were performed among tumor subtypes. Results There were 85 malignant and 48 benign masses. The Emean of the tumor border and PS were significantly different between benign and malignant masses ( P < 0.05 for all). ORs for malignancy were 1.06, 1.08, 1.05, and 1.04 for stiffness of the tumor border, proximal PS, middle PS, and distal PS, respectively ( P < 0.05 for all). Malignant masses with a stiff rim were significantly larger than malignant masses without a stiff rim, and were more commonly associated with the luminal B and triple negative subtypes. Conclusion Stiffness of the tumor border and PS obtained by SWE were significantly different between benign and malignant masses. Malignant masses with a stiff rim were larger in size and associated with more aggressive pathologic subtypes.

Unenhanced magnetic resonance screening using fused diffusion-weighted imaging and maximum-intensity projection in patients with a personal history of breast cancer: role of fused DWI for postoperative screening.

PURPOSE: To assess the diagnostic performance of unenhanced abbreviated protocol (AP) comprising fused diffusion-weighted imaging (DWI) using T1-weighted imaging (T1WI) with DWI maximum-intensity projections (DWI MIPs) for screening patients with a personal history of breast cancer (PHBC). METHODS: This institutional review board-approved retrospective observational study included 343 patients with PHBC who underwent 3T breast magnetic resonance imaging (MRI) between November 2013 and September 2015. Three breast radiologists reviewed the DWI MIPs of the AP to identify lesions, and the remaining axial AP images to characterize the detected lesions and establish the breast imaging reporting and data system final assessment. The conventional protocol (CP) images were also evaluated in the same way. The decision-making times were recorded. RESULTS: MRI acquisition time was approximately 5 min for AP. The mean times to read MIPs and remaining images were shorter in AP than in CP (5.5 and 22.1 s vs. 7.8 and 29.6 s). On DWI MIPs, the readers detected 9, 8, and 9 of 9 pathologically proven cancers, with negative predictive values (NPVs) of 100.0, 99.6, and 100.0%. Complete AP showed sensitivities of 88.9, 100.0, and 88.9% and specificities of 94.8, 93.4, and 95.1%. Complete CP showed sensitivities of 100.0, 100.0, and 88.9% and specificities of 93.4, 94.0, and 96.3%. CONCLUSIONS: An unenhanced AP had a short acquisition time of 5 min, and DWI MIPs showed NPVs greater than 99% across readers. The diagnostic performance of complete AP was equivalent to that of CP for screening patients with PHBC.

Diagnostic Performance of Fused Diffusion-Weighted Imaging Using T1-Weighted Imaging for Axillary Nodal Staging in Patients With Early Breast Cancer.

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.

Characterization of tumor and adjacent peritumoral stroma in patients with breast cancer using high-resolution diffusion-weighted imaging: Correlation with pathologic biomarkers.

PURPOSE: To assess whether ADC values of tumor and peritumoral stroma (PS) obtained on high-resolution diffusion-weighted imaging (HR DWI) were different according to pathologic biomarkers in patients with breast cancer. METHODS: We retrospectively enrolled 96 patients (age range, 30-75 years; mean, 52 years) with breast cancer who underwent HR DWI at 3T MR scanner. We obtained the apparent diffusion coefficient (ADC) and ADC range of tumor and PS by drawing the region of interest (ROI) of entire tumor. We assessed histopathological features of tumors. ADC values of tumor and PS were compared according to pathologic biomarkers using student t-test and Mann-Whitney U test. RESULTS: Mean ADC of tumor boundary was significantly higher in ER-negative tumors than in ER-positive tumors (P=0.005). The ADC ranges of tumor boundary and proximal PS were significantly higher in tumors with high nuclear grade, negative ER, positive HER2, positive Ki67, and lymph node metastasis than those with low nuclear grade, positive ER, negative HER2, negative Ki67, and without lymph node metastasis (P<0.05 for all). ADC range of tumor boundary and proximal PS was significantly lower in low risk tumor than in the others (P=0.004 and 0.002). Mean ADC of whole tumor was significantly higher in low-risk tumor than in non-low-risk tumor (P=0.030). CONCLUSION: On HR DWI, ADC ranges of tumor boundary and adjacent proximal PS were significantly lower in low-risk tumor than in non-low-risk tumors.

Diagnostic Performance of Fused Diffusion-Weighted Imaging Using Unenhanced or Postcontrast T1-Weighted MR Imaging in Patients With Breast Cancer.

To evaluate the diagnostic performance of fused diffusion-weighted imaging (DWI) using either unenhanced (UFMR) or early postcontrast T1-weighted imaging (PCFMR) to detect and characterize breast lesions in patients with breast cancer.This retrospective observational study was approved by institutional review board in our hospital and informed consents were waived. We retrospectively selected 87 consecutive patients who underwent preoperative breast magnetic resonance imaging, including DWI and definitive surgery. Both UFMR and PCFMR were reviewed by 5 radiologists for detection, lesion size, Breast Imaging Reporting and Data System final assessment, the probability of malignancy, lesion conspicuity, and apparent diffusion coefficients.A total of 129 lesions were identified by at least 2 readers on UFMR or PCFMR. Of 645 potentially detected lesions, there were 528 (82%) with UFMR and 554 (86%) with PCFMR. Malignant lesions or index cancers showed significantly higher detection rates than benign or additional lesions on both UFMR and PCFMR (P < 0.05). Area under the characteristic curves (AUCs) for predicting malignancy ranged 0.927 to 0.986 for UFMR, and 0.936 to 0.993 for PCFMR, which was not significantly different. Lesion conspicuity was significantly higher on PCFMR than UFMR (8.59 ±â€Š1.67 vs 9.19 ±â€Š1.36, respectively; P < 0.05) across 5 readers. Mean intraclass correlation coefficients for lesion size on UFMR and PCFMR were 0.89 and 0.92, respectively.Detection rates of index malignant lesions were similar for UFMR and PCFMR. Interobserver agreement for final assessments was reliable across 5 readers. Diagnostic accuracy for predicting malignancy with UFMR versus PCFMR was similar, although lesion conspicuity was significantly greater with the latter.

Prediction of low-risk breast cancer using perfusion parameters and apparent diffusion coefficient.

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.

Comparison of readout segmented echo planar imaging (EPI) and EPI with reduced field-of-VIew diffusion-weighted imaging at 3t in patients with breast cancer.

PURPOSE: To qualitatively and quantitatively compare the diagnostic performance of rs-EPI (readout segmented echo planar imaging) and reduced FOV (field-of-view) EPI in patients with biopsy-proven breast cancer at 3T. MATERIALS AND METHODS: Between November 2013 and July 2014, 96 patients (age range, 30-75 years: mean, 52 years) with breast cancer were retrospectively enrolled in this study. In all patients, rs-EPI and rFOV EPI were performed using a 3T MR scanner. Differences between two sequences were compared quantitatively by measuring the tumor apparent diffusion coefficient (ADC), signal-to-noise ratio (SNR), contrast, and contrast-to-noise ratio (CNR). Two independent readers visually assessed overall image quality, lesion conspicuity, and reader preference. The regions of interest (ROIs) were drawn in the whole tumor and in the normal breast parenchyma. Comparisons of quantitative and qualitative parameters between two sequences were performed using the Mann-Whitney and the paired t-test. RESULTS: SNR was significantly higher in rFOV EPI than in rs-EPI (51.88 ± 27.68 vs. 76.46 ± 50.20, P < 0.001). Mean tumor ADC value and normal tissue ADC were significantly lower in rFOV EPI (P < 0.001). Absolute tumor mean and minimum ADCs of rFOV EPI were significantly lower than those of rs-EPI (P < 0.001 for both). However, normalized ADC did not show a significant difference between the two sequences (P = 0.737). Lesion conspicuity and overall image quality of rFOV EPI were significantly higher than those of rs-EPI for both readers (P = 0.025 and < 0.001). CONCLUSION: In breast cancer, rFOV EPI provided significantly higher image quality, lesion conspicuity, and SNR than rs-EPI.