Ultrafast Dynamic Contrast-Enhanced MRI of the Breast: From Theory to Practice.

The development of ultrafast dynamic contrast-enhanced (UF-DCE) MRI has occurred in tandem with fast MRI scan techniques, particularly view-sharing and compressed sensing. Understanding the strengths of each technique and optimizing the relevant parameters are essential to their implementation. UF-DCE MRI has now shifted from research protocols to becoming a part of clinical scan protocols for breast cancer. UF-DCE MRI is expected to compensate for the low specificity of abbreviated MRI by adding kinetic information from the upslope of the time-intensity curve. Because kinetic information from UF-DCE MRI is obtained from the shape and timing of the initial upslope, various new kinetic parameters have been proposed. These parameters may be associated with receptor status or prognostic markers for breast cancer. In addition to the diagnosis of malignant lesions, more emphasis has been placed on predicting and evaluating treatment response because hyper-vascularity is linked to the aggressiveness of breast cancers. In clinical practice, it is important to note that breast lesion images obtained from UF-DCE MRI are slightly different from those obtained by conventional DCE MRI in terms of morphology. A major benefit of using UF-DCE MRI is avoidance of the marked or moderate background parenchymal enhancement (BPE) that can obscure the target enhancing lesions. BPE is less prominent in the earlier phases of UF-DCE MRI, which offers better lesion-to-noise contrast. The excellent contrast of early-enhancing vessels provides a key to understanding the detailed pathological structure of tumor-associated vessels. UF-DCE MRI is normally accompanied by a large volume of image data for which automated/artificial intelligence-based processing is expected to be useful. In this review, both the theoretical and practical aspects of UF-DCE MRI are summarized. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Distribution pattern of FDG uptake using ring-type dedicated breast PET in comparison to whole-body PET/CT scanning in invasive breast cancer.

PURPOSE: This study aimed to investigate the incidence of rim uptake (RU) or multifocal uptake (MU) by invasive breast cancers on a ring-type dedicated breast positron emission tomography (dbPET) scanner compared with whole-body PET (wbPET) scanner imaging and to correlate uptake patterns with pathological features and prognosis. METHODS: Between 2009 and 2011, 76 lesions in 74 patients with primary invasive breast cancers were included. Each patient underwent dbPET and wbPET scanning on the same day after administration of 18F-fluorodeoxyglucose (FDG). The images were evaluated to identify specific uptake patterns (RU and MU). Their association with pathological characteristics and prognosis was analyzed. RESULTS: On dbPET, RU and MU patterns were observed in 18 lesions (24%) and 28 lesions (37%), respectively. On wbPET, RU and MU patterns were observed in six lesions (8%) and 17 lesions (22%), respectively. Lesions with RU on dbPET were of higher grade than lesions without RU (P = 0.024) and a higher Ki-67 index (mean; 31% vs. 18%, P = 0.015). They tended to be triple-negative (33% vs. 12%, P = 0.046) and less likely to be luminal A subtype (17% vs. 47%, P = 0.020). On wbPET, however, no significant differences in these markers were seen between RU and non-RU. The MU pattern did not correlate with pathological characteristics in either scanner. Lesions with RU or MU were not significantly associated with disease-free survival. CONCLUSIONS: DbPET can identify detailed FDG distribution patterns of breast cancer better than wbPET. Breast cancer with RU on dbPET was associated with higher grade and triple-negative subtype.

Intravoxel incoherent motion (IVIM) and non-Gaussian diffusion MRI of the lactating breast.

PURPOSE: To investigate the effect of breastfeeding on IVIM and non-Gaussian diffusion MRI in the breast. MATERIALS AND METHODS: An IRB approved prospective study enrolled seventeen volunteers (12 in lactation and 5 with post-weaning, range 31-43 years; mean 35.4 years). IVIM (fIVIM and D*) and non-Gaussian diffusion (ADC0 and K) parameters using 16 b values, plus synthetic apparent diffusion coefficients (sADCs) from 2 key b values (b = 200 and 1500 s/mm2) were calculated using regions of interest. ADC0 maps of the whole breast were generated and their contrast patterns were evaluated by two independent readers using retroareolar and segmental semi-quantitative scores. To compare the diffusion and IVIM parameters, Wilcoxon signed rank tests were used between pre- and post-breastfeeding and Mann-Whitney tests were used between post-weaning and pre- or post-breastfeeding. RESULTS: ADC0 and sADC values significantly decreased post-breastfeeding (1.90 vs. 1.72 × 10-3 mm2/s, P < 0.001 and 1.39 vs. 1.25 × 10-3 mm2/s, P < 0.001) while K values significantly increased (0.33 vs. 0.44, P < 0.05). fIVIM values significantly increased after breastfeeding (1.97 vs. 2.97%, P < 0.01). No significant difference was found in D* values. There was significant heterogeneity in ADC0 maps post-breastfeeding, both in retroareolar and segmental scores (P < 0.0001 and =0.0001). CONCLUSION: IVIM and non-Gaussian diffusion parameters significantly changed between pre- and post-breastfeeding status, and care needs to be taken in interpreting diffusion-weighted imaging (DWI) data in lactating breasts.

Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast.

We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0-2500 s/mm2 with one number of excitations [NEX]) and five b-values (0-2500 s/mm2, 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC0, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions.

The Value of Lesion Size as an Adjunct to the BI-RADS-MRI 2013 Descriptors in the Diagnosis of Solitary Breast Masses.

PURPOSE: This study aimed to evaluate the MRI findings of breast solitary masses in diagnostic procedures to decide the appropriate category based on American College of Radiology (ACR) BI-RADS-MRI 2013, with the focus on lesion size. METHODS: A retrospective review of 2,603 consecutive breast MRI reports identified 250 pathologically-proven solitary breast masses. Dynamic-contrast enhanced images and diffusion-weighted images were performed on a 3.0/1.5 Tesla Scanner with a 16/4 channel dedicated breast coil. MRI findings were re-evaluated according to ACR BI-RADS-MRI 2013. BI-RADS-MRI descriptors, lesion size and minimum apparent diffusion coefficient (ADC) value were statistically analyzed using univariate/multivariate logistic regression analysis and receiver operator characteristic (ROC) analysis. Based on the results, a diagnostic decision tree was constructed. RESULTS: Of the 250 lesions, 152 (61%) were malignant and 98 (39%) were benign. In univariate logistic regression analysis, most of the BI-RADS descriptors, lesion size, and ADC value were significant. Lesion size and ADC value were binarized with optimal cut-off values of 12 mm and 1.1 × 10-3 mm2/s, respectively. Multivariate logistic regression analysis showed that lesion size (≥12 mm or not), margin (circumscribed or not), kinetics (washout or not) and internal enhancement characteristics (IEC) (rim enhancement present or absent) significantly contributed to the diagnosis (P < 0.05). Using these four significant parameters, a decision tree was constructed to categorize lesions into detailed assessment categories/subcategories (Category 4A, 4B, 4C and 5). CONCLUSION: Lesion size is an independent contributor in diagnosing solitary breast masses. Adding the information of lesion size to BI-RADS-MRI 2013 descriptors will allow more detailed categorizations.

Intravoxel Incoherent Motion and Quantitative Non-Gaussian Diffusion MR Imaging: Evaluation of the Diagnostic and Prognostic Value of Several Markers of Malignant and Benign Breast Lesions.

Purpose To investigate the performance of integrated approaches that combined intravoxel incoherent motion (IVIM) and non-Gaussian diffusion parameters compared with the Breast Imaging and Reporting Data System (BI-RADS) to establish multiparameter thresholds scores or probabilities by using Bayesian analysis to distinguish malignant from benign breast lesions and their correlation with molecular prognostic factors. Materials and Methods Between May 2013 and March 2015, 411 patients were prospectively enrolled and 199 patients (allocated to training [n = 99] and validation [n = 100] sets) were included in this study. IVIM parameters (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion parameters (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm2 [ADC0] and kurtosis [K]) by using IVIM and kurtosis models were estimated from diffusion-weighted image series (16 b values up to 2500 sec/mm2), as well as a synthetic ADC (sADC) calculated by using b values of 200 and 1500 (sADC200-1500) and a standard ADC calculated by using b values of 0 and 800 sec/mm2 (ADC0-800). The performance of two diagnostic approaches (combined parameter thresholds and Bayesian analysis) combining IVIM and diffusion parameters was evaluated and compared with BI-RADS performance. The Mann-Whitney U test and a nonparametric multiple comparison test were used to compare their performance to determine benignity or malignancy and as molecular prognostic biomarkers and subtypes of breast cancer. Results Significant differences were found between malignant and benign breast lesions for IVIM and non-Gaussian diffusion parameters (ADC0, K, fIVIM, fIVIM · D*, sADC200-1500, and ADC0-800; P < .05). Sensitivity and specificity for the validation set by radiologists A and B were as follows: sensitivity, 94.7% and 89.5%, and specificity, 75.0% and 79.2% for sADC200-1500, respectively; sensitivity, 94.7% and 96.1%, and specificity, 75.0% and 66.7%, for the combined thresholds approach, respectively; sensitivity, 92.1% and 92.1%, and specificity, 83.3% and 66.7%, for Bayesian analysis, respectively; and sensitivity and specificity, 100% and 79.2%, for BI-RADS, respectively. The significant difference in values of sADC200-1500 in progesterone receptor status (P = .002) was noted. sADC200-1500 was significantly different between histologic subtypes (P = .006). Conclusion Approaches that combined various IVIM and non-Gaussian diffusion MR imaging parameters may provide BI-RADS-equivalent scores almost comparable to BI-RADS categories without the use of contrast agents. Non-Gaussian diffusion parameters also differed by biologic prognostic factors. © RSNA, 2017 Online supplemental material is available for this article.

Apparent diffusion coefficient as a potential surrogate marker for Ki-67 index in mucinous breast carcinoma.

PURPOSE: To examine the association between apparent diffusion coefficient (ADC), cellularity, and Ki-67 index in mucinous breast carcinoma (MBC) compared with invasive carcinoma of no special type (NST). ADC's ability to identify lesions with highly proliferating MBC was also examined. MATERIALS AND METHODS: Pathologically confirmed MBCs (mucinous group, n = 18) and NSTs (control group, n = 18) were retrospectively analyzed. ADC was calculated from signal intensity of diffusion-weighted imaging at b values of 0 and 1000 sec/mm(2) . The Ki-67 index and cellularity were histopathologically evaluated. The mucinous group was classified into high Ki-67 mucinous group (Ki-67 index ≥14%, highly proliferating) and low Ki-67 mucinous group. RESULTS: In the mucinous group, minimum ADC (ADCmin) showed an inverse correlation with cellularity (r = -0.802, P < 0.0001) and Ki-67 index (r = -0.825, P < 0.0001). In the control group, ADCmin showed inverse correlation with cellularity (r = -0.537 P = 0.022), but no correlation with Ki-67 index (r = 0.035, P = 0.892). ADCmin of high Ki-67 mucinous group was significantly lower than that of low Ki-67 mucinous group (P = 0.005). CONCLUSION: This study demonstrates an inverse correlation between ADC and Ki-67 index in MBC and the ability of ADC to identify highly proliferating MBC. Considering that ADC can evaluate whole lesions noninvasively, ADC may be a promising noninvasive surrogate marker for Ki-67 index in the risk stratification of MBC.