Assessing Quantitative Parenchymal Features at Baseline Dynamic Contrast-enhanced MRI and Cancer Occurrence in Women with Extremely Dense Breasts.

Background Automated identification of quantitative breast parenchymal enhancement features on dynamic contrast-enhanced (DCE) MRI scans could provide added value in assessment of breast cancer risk in women with extremely dense breasts. Purpose To automatically identify quantitative properties of the breast parenchyma on baseline DCE MRI scans and assess their association with breast cancer occurrence in women with extremely dense breasts. Materials and Methods This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. MRI was performed in eight hospitals between December 2011 and January 2016. After segmentation of fibroglandular tissue, quantitative features (including volumetric density, volumetric morphology, and enhancement characteristics) of the parenchyma were extracted from baseline MRI scans. Principal component analysis was used to identify parenchymal measures with the greatest variance. Multivariable Cox proportional hazards regression was applied to assess the association between breast cancer occurrence and quantitative parenchymal features, followed by stratification of significant features into tertiles. Results A total of 4553 women (mean age, 55.7 years ± 6 [SD]) with extremely dense breasts were included; of these women, 122 (3%) were diagnosed with breast cancer. Five principal components representing 96% of the variance were identified, and the component explaining the greatest independent variance (42%) consisted of MRI features relating to volume of enhancing parenchyma. Multivariable analysis showed that volume of enhancing parenchyma was associated with breast cancer occurrence (hazard ratio [HR], 1.09; 95% CI: 1.01, 1.18; P = .02). Additionally, women in the high tertile of volume of enhancing parenchyma showed a breast cancer occurrence twice that of women in the low tertile (HR, 2.09; 95% CI: 1.25, 3.61; P = .005). Conclusion In women with extremely dense breasts, a high volume of enhancing parenchyma on baseline DCE MRI scans was associated with increased occurrence of breast cancer as compared with a low volume of enhancing parenchyma. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Grimm in this issue.

Long-term Survival in Breast Cancer Patients Is Associated with Contralateral Parenchymal Enhancement at MRI: Outcomes of the SELECT Study.

Background Several single-center studies found that high contralateral parenchymal enhancement (CPE) at breast MRI was associated with improved long-term survival in patients with estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer. Due to varying sample sizes, population characteristics, and follow-up times, consensus of the association is currently lacking. Purpose To confirm whether CPE is associated with long-term survival in a large multicenter retrospective cohort, and to investigate if CPE is associated with endocrine therapy effectiveness. Materials and Methods This multicenter observational cohort included women with unilateral ER-positive HER2-negative breast cancer (tumor size ≤50 mm and ≤three positive lymph nodes) who underwent MRI from January 2005 to December 2010. Overall survival (OS), recurrence-free survival (RFS), and distant RFS (DRFS) were assessed. Kaplan-Meier analysis was performed to investigate differences in absolute risk after 10 years, stratified according to CPE tertile. Multivariable Cox proportional hazards regression analysis was performed to investigate whether CPE was associated with prognosis and endocrine therapy effectiveness. Results Overall, 1432 women (median age, 54 years [IQR, 47-63 years]) were included from 10 centers. Differences in absolute OS after 10 years were stratified according to CPE tertile as follows: 88.5% (95% CI: 88.1, 89.1) in tertile 1, 85.8% (95% CI: 85.2, 86.3) in tertile 2, and 85.9% (95% CI: 85.4, 86.4) in tertile 3. CPE was independently associated with OS, with a hazard ratio (HR) of 1.17 (95% CI: 1.0, 1.36; P = .047), but was not associated with RFS (HR, 1.11; P = .16) or DRFS (HR, 1.11; P = .19). The effect of endocrine therapy on survival could not be accurately assessed; therefore, the association between endocrine therapy efficacy and CPE could not reliably be estimated. Conclusion High contralateral parenchymal enhancement was associated with a marginally decreased overall survival in patients with estrogen receptor-positive and human epidermal growth factor receptor 2-negative breast cancer, but was not associated with recurrence-free survival (RFS) or distant RFS. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Honda and Iima in this issue.

Deep Learning-Based Segmentation of Locally Advanced Breast Cancer on MRI in Relation to Residual Cancer Burden: A Multi-Institutional Cohort Study.

BACKGROUND: While several methods have been proposed for automated assessment of breast-cancer response to neoadjuvant chemotherapy on breast MRI, limited information is available about their performance across multiple institutions. PURPOSE: To assess the value and robustness of deep learning-derived volumes of locally advanced breast cancer (LABC) on MRI to infer the presence of residual disease after neoadjuvant chemotherapy. STUDY TYPE: Retrospective. SUBJECTS: Training cohort: 102 consecutive female patients with LABC scheduled for neoadjuvant chemotherapy (NAC) from a single institution (age: 25-73 years). Independent testing cohort: 55 consecutive female patients with LABC from four institutions (age: 25-72 years). FIELD STRENGTH/SEQUENCE: Training cohort: single vendor 1.5 T or 3.0 T. Testing cohort: multivendor 3.0 T. Gradient echo dynamic contrast-enhanced sequences. ASSESSMENT: A convolutional neural network (nnU-Net) was trained to segment LABC. Based on resulting tumor volumes, an extremely randomized tree model was trained to assess residual cancer burden (RCB)-0/I vs. RCB-II/III. An independent model was developed using functional tumor volume (FTV). Models were tested on an independent testing cohort and response assessment performance and robustness across multiple institutions were assessed. STATISTICAL TESTS: The receiver operating characteristic (ROC) was used to calculate the area under the ROC curve (AUC). DeLong's method was used to compare AUCs. Correlations were calculated using Pearson's method. P values <0.05 were considered significant. RESULTS: Automated segmentation resulted in a median (interquartile range [IQR]) Dice score of 0.87 (0.62-0.93), with similar volumetric measurements (R = 0.95, P < 0.05). Automated volumetric measurements were significantly correlated with FTV (R = 0.80). Tumor volume-derived from deep learning of DCE-MRI was associated with RCB, yielding an AUC of 0.76 to discriminate between RCB-0/I and RCB-II/III, performing similar to the FTV-based model (AUC = 0.77, P = 0.66). Performance was comparable across institutions (IQR AUC: 0.71-0.84). DATA CONCLUSION: Deep learning-based segmentation estimates changes in tumor load on DCE-MRI that are associated with RCB after NAC and is robust against variations between institutions. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 4.

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus, ways to triage these normal MRI examinations to reduce radiologist workload are needed. Purpose To determine the feasibility of an automated triaging method using deep learning (DL) to dismiss the highest number of MRI examinations without lesions while still identifying malignant disease. Materials and Methods This secondary analysis of data from the Dense Tissue and Early Breast Neoplasm Screening, or DENSE, trial evaluated breast MRI examinations from the first screening round performed in eight hospitals between December 2011 and January 2016. A DL model was developed to differentiate between breasts with lesions and breasts without lesions. The model was trained to dismiss breasts with normal phenotypical variation and to triage lesions (Breast Imaging Reporting and Data System [BI-RADS] categories 2-5) using eightfold internal-external validation. The model was trained on data from seven hospitals and tested on data from the eighth hospital, alternating such that each hospital was used once as an external test set. Performance was assessed using receiver operating characteristic analysis. At 100% sensitivity for malignant disease, the fraction of examinations dismissed from radiologic review was estimated. Results A total of 4581 MRI examinations of extremely dense breasts from 4581women (mean age, 54.3 years; interquartile range, 51.5-59.8 years) were included. Of the 9162 breasts, 838 had at least one lesion (BI-RADS category 2-5, of which 77 were malignant) and 8324 had no lesions. At 100% sensitivity for malignant lesions, the DL model considered 90.7% (95% CI: 86.7, 94.7) of the MRI examinations with lesions to be nonnormal and triaged them to radiologic review. The DL model dismissed 39.7% (95% CI: 30.0, 49.4) of the MRI examinations without lesions. The DL model had an average area under the receiver operating characteristic curve of 0.83 (95% CI: 0.80, 0.85) in the differentiation between normal breast MRI examinations and MRI examinations with lesions. Conclusion Automated analysis of breast MRI examinations in women with dense breasts dismissed nearly 40% of MRI scans without lesions while not missing any cancers. ClinicalTrials.gov: NCT01315015 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Joe in this issue.

Radiogenomic Analysis of Breast Cancer by Linking MRI Phenotypes with Tumor Gene Expression.

Background Better understanding of the molecular biology associated with MRI phenotypes may aid in the diagnosis and treatment of breast cancer. Purpose To discover the associations between MRI phenotypes of breast cancer and their underlying molecular biology derived from gene expression data. Materials and Methods This is a secondary analysis of the Multimodality Analysis and Radiologic Guidance in Breast-Conserving Therapy, or MARGINS, study. MARGINS included patients eligible for breast-conserving therapy between November 2000 and December 2008 for preoperative breast MRI. Tumor RNA was collected for sequencing from surgical specimen. Twenty-one computer-generated MRI features of tumors were condensed into seven MRI factors related to tumor size, shape, initial enhancement, late enhancement, smoothness of enhancement, sharpness, and sharpness variation. These factors were associated with gene expression levels from RNA sequencing by using gene set enrichment analysis. Statistical significance of these associations was evaluated by using a sample permutation test and the false discovery rate. Results Gene expression and MRI data were obtained for 295 patients (mean age, 56 years ± 10.3 [standard deviation]). Larger and more irregular tumors showed increased expression of cell cycle and DNA damage checkpoint genes (false discovery rate <0.25; normalized enrichment statistic [NES], 2.15). Enhancement and sharpness of the tumor margin were associated with expression of ribosomal proteins (false discovery rate <0.25; NES, 1.95). Smoothness of enhancement, tumor size, and tumor shape were associated with expression of genes involved in the extracellular matrix (false discovery rate <0.25; NES, 2.25). Conclusion Breast cancer MRI phenotypes were related to their underlying molecular biology revealed by using RNA sequencing. The association between enhancements and sharpness of the tumor margin with the ribosome suggests that these MRI features may be imaging biomarkers for drugs targeting the ribosome. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Cho in this issue.

Correcting time-intensity curves in dynamic contrast-enhanced breast MRI for inhomogeneous excitation fields at 7T.

PURPOSE: Inhomogeneous excitation at ultrahigh field strengths (7T and above) compromises the reliability of quantified dynamic contrast-enhanced breast MRI. This can hamper the introduction of ultrahigh field MRI into the clinic. Compensation for this non-uniformity effect can consist of both hardware improvements and post-acquisition corrections. This paper investigated the correctable radiofrequency transmit ( B1+ ) range post-acquisition in both simulations and patient data for 7T MRI. METHODS: Simulations were conducted to determine the minimum B1+ level at which corrections were still beneficial because of noise amplification. Two correction strategies leading to differences in noise amplification were tested. The effect of the corrections on a 7T patient data set (N = 38) with a wide range of B1+ levels was investigated in terms of time-intensity curve types as well as washin, washout and peak enhancement values. RESULTS: In simulations assuming a common amount of T1 saturation, the lowest B1+ level at which the SNR of the corrected images was at least that of the original precontrast image was 43% of the nominal angle. After correction, time-intensity curve types changed in 24% of included patients, and the distribution of curve types corresponded better to the distribution found in literature. Additionally, the overlap between the distributions of washin, washout, and peak enhancement values for grade 1 and grade 2 tumors was slightly reduced. CONCLUSION: Although the correctable range varies with the amount of T1 saturation, post-acquisition correction for inhomogeneous excitation was feasible down to B1+ levels of 43% of the nominal angle in vivo.

Synchronous Breast Cancer: Phenotypic Similarities on MRI.

BACKGROUND: Previous studies have shown discrepancies between index and synchronous breast cancer in histology and molecular phenotype. It is yet unknown whether this observation also applies to the MRI phenotype. PURPOSE: To investigate whether the appearance of breast cancer on MRI (i.e. phenotype) is different from that of additional breast cancer (i.e. synchronous cancer), and whether such a difference, if it exists, is associated with prognosis. STUDY TYPE: Retrospective. POPULATION: In all, 464 consecutive patients with early-stage ER+/HER2- breast cancer were included; 34/464 (7.3%) had 44 synchronous cancers in total (34 ipsilateral, 10 contralateral). SEQUENCE: 1.5T, contrast-enhanced T1 -weighted. ASSESSMENT: We assessed imaging phenotype using 50 quantitative features from each cancer and applied principal component analysis (PCA) to identify independent properties. The degree of phenotype difference was assessed. An association between phenotype differences and prognosis in terms of the Nottingham Prognostic Index (NPI) and PREDICT score were analyzed. STATISTICAL TESTS: PCA; Wilcoxon rank sum test; Benjamini-Hochberg to control the false discovery rate. RESULTS: PCA identified eight components in patients with ipsilateral synchronous cancer. Six out of eight were significantly different between index and synchronous cancer. These components represented features describing texture (three components, P < 0.001, P < 0.001, P = 0.004), size (P < 0.001), smoothness (P < 0.001), and kinetics (P = 0.004). Phenotype differences in terms of the six components were split in tertiles. Larger phenotype differences in size, kinetics, and texture were associated with significantly worse prognosis in terms of NPI (P = 0.019, P = 0.045, P = 0.014), but not for the PREDICT score (P = 0.109, P = 0.479, P = 0.109). PCA identified six components in patients with contralateral synchronous cancer. None were significantly different from the index cancer (P = 0.178, P = 0.178, P = 0.178, P = 0.326, P = 0.739, P = 0.423). DATA CONCLUSION: The MRI phenotype of ER+/HER2- breast cancer was different from that of ipsilateral synchronous cancer and a large phenotype difference was associated with worse prognosis. No significant difference was found for synchronous contralateral cancer. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2020;51:1858-1867.

Harmonization of Quantitative Parenchymal Enhancement in T1 -Weighted Breast MRI.

BACKGROUND: Differences in imaging parameters influence computer-extracted parenchymal enhancement measures from breast MRI. PURPOSE: To investigate the effect of differences in dynamic contrast-enhanced MRI acquisition parameter settings on quantitative parenchymal enhancement of the breast, and to evaluate harmonization of contrast-enhancement values with respect to flip angle and repetition time. STUDY TYPE: Retrospective. PHANTOM/POPULATIONS: We modeled parenchymal enhancement using simulations, a phantom, and two cohorts (N = 398 and N = 302) from independent cancer centers. SEQUENCE FIELD/STRENGTH: 1.5T dynamic contrast-enhanced T1 -weighted spoiled gradient echo MRI. Vendors: Philips, Siemens, General Electric Medical Systems. ASSESSMENT: We assessed harmonization of parenchymal enhancement in simulations and phantom by varying the MR parameters that influence the amount of T1 -weighting: flip angle (8°-25°) and repetition time (4-12 msec). We calculated the median and interquartile range (IQR) of the enhancement values before and after harmonization. In vivo, we assessed overlap of quantitative parenchymal enhancement in the cohorts before and after harmonization using kernel density estimations. Cohort 1 was scanned with flip angle 20° and repetition time 8 msec; cohort 2 with flip angle 10° and repetition time 6 msec. STATISTICAL TESTS: Paired Wilcoxon signed-rank-test of bootstrapped kernel density estimations. RESULTS: Before harmonization, simulated enhancement values had a median (IQR) of 0.46 (0.34-0.49). After harmonization, the IQR was reduced: median (IQR): 0.44 (0.44-0.45). In the phantom, the IQR also decreased, median (IQR): 0.96 (0.59-1.22) before harmonization, 0.96 (0.91-1.02) after harmonization. Harmonization yielded significantly (P < 0.001) better overlap in parenchymal enhancement between the cohorts: median (IQR) was 0.46 (0.37-0.58) for cohort 1 vs. 0.37 (0.30-0.44) for cohort 2 before harmonization (57% overlap); and 0.35 (0.28-0.43) vs. .0.37 (0.30-0.44) after harmonization (85% overlap). DATA CONCLUSION: The proposed practical harmonization method enables an accurate comparison between patients scanned with differences in imaging parameters. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 4.

Contralateral parenchymal enhancement on breast MRI before and during neoadjuvant endocrine therapy in relation to the preoperative endocrine prognostic index.

OBJECTIVES: To investigate whether contralateral parenchymal enhancement (CPE) on MRI during neoadjuvant endocrine therapy (NET) is associated with the preoperative endocrine prognostic index (PEPI) of ER+/HER2- breast cancer. METHODS: This retrospective observational cohort study included 40 unilateral ER+/HER2- breast cancer patients treated with NET. Patients received NET for 6 to 9 months with MRI response monitoring after 3 and/or 6 months. PEPI was used as endpoint. PEPI is based on surgery-derived pathology (pT- and pN-stage, Ki67, and ER-status) and stratifies patients in three groups with distinct prognoses. Mixed effects and ROC analysis were performed to investigate whether CPE was associated with PEPI and to assess discriminatory ability. RESULTS: The median patient age was 61 (interquartile interval: 52, 69). Twelve patients had PEPI-1 (good prognosis), 15 PEPI-2 (intermediate), and 13 PEPI-3 (poor). High pretreatment CPE was associated with PEPI-3: pretreatment CPE was 39.4% higher on average (95% CI = 1.3, 91.9%; p = .047) compared with PEPI-1. CPE decreased after 3 months in PEPI-2 and PEPI-3. The average reduction was 24.4% (95% CI = 2.6, 41.3%; p = .032) in PEPI-2 and 29.2% (95% CI = 7.8, 45.6%; p = .011) in PEPI-3 compared with baseline. Change in CPE was predictive of PEPI-1 vs PEPI-2+3 (AUC = 0.77; 95% CI = 0.57, 0.96). CONCLUSIONS: CPE during NET is associated with PEPI-group in ER+/HER2- breast cancer: a high pretreatment CPE and a decrease in CPE during NET were associated with a poor prognosis after NET on the basis of PEPI. KEY POINTS: • Change in contralateral breast parenchymal enhancement on MRI during neoadjuvant endocrine therapy distinguished between patients with a good and intermediate/poor prognosis at final pathology. • Patients with a poor prognosis at final pathology showed higher baseline parenchymal enhancement on average compared to patients with a good prognosis. • Patients with an intermediate/poor prognosis at final pathology showed a higher average reduction in parenchymal enhancement after 3 months of neoadjuvant endocrine therapy.

Reducing distortions in echo-planar breast imaging at ultrahigh field with high-resolution off-resonance maps.

PURPOSE: DWI is a promising modality in breast MRI, but its clinical acceptance is slow. Analysis of DWI is hampered by geometric distortion artifacts, which are caused by off-resonant spins in combination with the low phase-encoding bandwidth of the EPI sequence used. Existing correction methods assume smooth off-resonance fields, which we show to be invalid in the human breast, where high discontinuities arise at tissue interfaces. METHODS: We developed a distortion correction method that incorporates high-resolution off-resonance maps to better solve for severe distortions at tissue interfaces. The method was evaluated quantitatively both ex vivo in a porcine tissue phantom and in vivo in 5 healthy volunteers. The added value of high-resolution off-resonance maps was tested using a Wilcoxon signed rank test comparing the quantitative results obtained with a low-resolution off-resonance map with those obtained with a high-resolution map. RESULTS: Distortion correction using low-resolution off-resonance maps corrected most of the distortions, as expected. Still, all quantitative comparison metrics showed increased conformity between the corrected EPI images and a high-bandwidth reference scan for both the ex vivo and in vivo experiments. All metrics showed a significant improvement when a high-resolution off-resonance map was used (P < 0.05), in particular at tissue boundaries. CONCLUSION: The use of off-resonance maps of a resolution higher than EPI scans significantly improves upon existing distortion correction techniques, specifically by superior correction at glandular tissue boundaries.

Estimating B1+ in the breast at 7 T using a generic template.

Dynamic contrast-enhanced MRI is the workhorse of breast MRI, where the diagnosis of lesions is largely based on the enhancement curve shape. However, this curve shape is biased by RF transmit (B1+ ) field inhomogeneities. B1+ field information is required in order to correct these. The use of a generic, coil-specific B1+ template is proposed and tested. Finite-difference time-domain simulations for B1+ were performed for healthy female volunteers with a wide range of breast anatomies. A generic B1+ template was constructed by averaging simulations based on four volunteers. Three-dimensional B1+ maps were acquired in 15 other volunteers. Root mean square error (RMSE) metrics were calculated between individual simulations and the template, and between individual measurements and the template. The agreement between the proposed template approach and a B1+ mapping method was compared against the agreement between acquisition and reacquisition using the same mapping protocol. RMSE values (% of nominal flip angle) comparing individual simulations with the template were in the range 2.00-4.01%, with mean 2.68%. RMSE values comparing individual measurements with the template were in the range8.1-16%, with mean 11.7%. The agreement between the proposed template approach and a B1+ mapping method was only slightly worse than the agreement between two consecutive acquisitions using the same mapping protocol in one volunteer: the range of agreement increased from ±16% of the nominal angle for repeated measurement to ±22% for the B1+ template. With local RF transmit coils, intersubject differences in B1+ fields of the breast are comparable to the accuracy of B1+ mapping methods, even at 7 T. Consequently, a single generic B1+ template suits subjects over a wide range of breast anatomies, eliminating the need for a time-consuming B1+ mapping protocol.

Contralateral parenchymal enhancement on dynamic contrast-enhanced MRI reproduces as a biomarker of survival in ER-positive/HER2-negative breast cancer patients.

OBJECTIVES: To assess whether contralateral parenchymal enhancement reproduces as an independent biomarker for patient survival in an independent patient cohort from a different cancer institution. METHODS: This is a HIPAA-compliant IRB approved retrospective study. Patients with ER-positive/HER2-negative operable invasive ductal carcinoma and preoperative dynamic contrast-enhanced MRI were consecutively included between 2005 and 2009. The parenchyma of the breast contralateral to known cancer was segmented automatically on MRI and contralateral parenchymal enhancement (CPE) was calculated. CPE was split into tertiles and tested for association with invasive disease-free survival (IDFS) and overall survival (OS). Propensity score analysis with inverse probability weighting (IPW) was used to adjust CPE for patient and tumour characteristics as well as systemic therapy. RESULTS: Three hundred and two patients were included. The median age at diagnosis was 48 years (interquartile range, 42-57). Median follow-up was 88 months (interquartile range, 76-102); 15/302 (5%) patients died and 37/302 (13%) had a recurrence or died. In context of multivariable analysis, IPW-adjusted CPE was associated with IDFS [hazard ratio (HR) = 0.27, 95% confidence interval (CI) = 0.05-0.68, p = 0.004] and OS (HR = 0.22, 95% CI = 0.00-0.83, p = 0.032). CONCLUSIONS: Contralateral parenchymal enhancement on pre-treatment dynamic contrast-enhanced MRI as an independent biomarker of survival in patients with ER-positive/HER2-negative breast cancer has been upheld in this study. These findings are a promising next step towards a practical and inexpensive test for risk stratification of ER-positive/HER2-negative breast cancer. KEY POINTS: • High parenchymal-enhancement in the disease-free contralateral breast reproduces as biomarker for survival. • This is in patients with ER-positive/HER2-negative breast cancer from an independent cancer centre. • This is independent of patient and pathology parameters and systemic therapy.

Eligibility of patients for minimally invasive breast cancer therapy based on MRI analysis of tumor proximity to skin and pectoral muscle.

There is growing interest in minimally invasive breast cancer therapy. Eligibility of patients is, however, dependent on several factors related to the tumor and treatment technology. The aim of this study is to assess the proportion of patients eligible for minimally invasive breast cancer therapy for different safety and treatment margins based on breast tumor location. Patients with invasive ductal cancer were selected from the MARGINS cohort. Semiautomatic segmentation of tumor, skin, and pectoral muscle was performed in Magnetic Resonance images. Shortest distances of tumors to critical organs (ie, skin and pectoral muscle) were calculated. Proportions of eligible patients were determined for different safety and treatment margins. Three-hundred-forty-eight patients with 351 tumors were included. If a 10 mm safety margin to skin and pectoral muscle is required without treatment margin, 72.3% of patients would be eligible for minimally invasive treatment. This proportion decreases to 45.9% for an additional treatment margin of 5 mm. Shortest distances between tumors and critical organs are larger in older patients and in patients with less aggressive tumor subtypes. If a 10 mm safety margin to skin and pectoral muscle is required, more than two-thirds of patients would be eligible for minimally invasive breast cancer therapy.

Survival is associated with complete response on MRI after neoadjuvant chemotherapy in ER-positive HER2-negative breast cancer.

BACKGROUND: Pathological complete remission (pCR) of estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative breast cancer is rarely achieved after neoadjuvant chemotherapy (NAC). In addition, the prognostic value of pCR for this breast cancer subtype is limited. We explored whether response evaluation by magnetic resonance imaging (MRI) is associated with recurrence-free survival after NAC in ER-positive/HER2-negative breast cancer. METHODS: MRI examinations were performed in 272 women with ER-positive/HER2-negative breast cancer before, during and after NAC. MRI interpretation included lesion morphology at baseline, changes in morphology and size, and contrast uptake kinetics. These MRI features, clinical characteristics and final pathology were correlated with recurrence-free survival. RESULTS: The median follow up time was 41 months. There were 35 women with events, including 19 breast-cancer-related deaths. On multivariable analysis, age younger than 50 years (hazard ratio (HR) = 2.55, 95 % confidence interval (CI) 1.3, 5.02, p = 0.007), radiological complete response after NAC (HR = 14.11, CI 1.81, 1818; p = 0.006) and smaller diameters of washout/plateau enhancement at MRI after NAC (HR = 1.02, CI 1.00, 1.04, p = 0.036) were independently associated with best recurrence-free survival. Pathological response was not significant; HR = 2.12, CI 0.86, 4.64, p = 0.096. CONCLUSIONS: MRI after NAC in ER-positive/HER2-negative tumors may be predictive of recurrence-free survival. A radiological complete response at MRI after NAC is associated with an excellent prognosis.

Association between Parenchymal Enhancement of the Contralateral Breast in Dynamic Contrast-enhanced MR Imaging and Outcome of Patients with Unilateral Invasive Breast Cancer.

PURPOSE: To retrospectively investigate whether parenchymal enhancement in dynamic contrast material-enhanced magnetic resonance (MR) imaging of the contralateral breast in patients with unilateral invasive breast cancer is associated with therapy outcome. MATERIALS AND METHODS: After obtaining approval of the institutional review board and patients' written informed consent, 531 women with unilateral invasive breast cancer underwent dynamic contrast-enhanced MR imaging between 2000 and 2008. The contralateral parenchyma was segmented automatically, in which the mean of the top 10% late enhancement was calculated. Cox regression was used to test associations between parenchymal enhancement, patient and tumor characteristics, and overall survival and invasive disease-free survival. Subset analyses were performed and stratified according to immunohistochemical subtypes and type of adjuvant treatment received. RESULTS: Median follow-up was 86 months. Age (P < .001) and immunohistochemical subtype (P = .042) retained significance in multivariate analysis for overall survival. In patients with estrogen receptor-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer (n = 398), age (P < .001), largest diameter on MR images (P = .049), and parenchymal enhancement (P = .011) were significant. In patients who underwent endocrine therapy (n = 174), parenchymal enhancement was the only significant covariate for overall survival and invasive disease-free survival (P < .001). CONCLUSION: Results suggest that parenchymal enhancement in the contralateral breast of patients with invasive unilateral breast cancer is significantly associated with long-term outcome, particularly in patients with estrogen receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. Lower value of the mean top 10% enhancement of the parenchyma shows potential as a predictive biomarker for relatively poor outcome in patients who undergo endocrine therapy. These results should, however, be validated in a larger study.

Association between rim enhancement of breast cancer on dynamic contrast-enhanced MRI and patient outcome: impact of subtype.

The heterogeneous nature of breast cancer is represented by three breast cancer subtypes associated with different patient outcome. However, within subtypes, variations still exist. Additional stratification is necessary for more individualized therapy. Functional tumor characteristics on dynamic contrast-enhanced (DCE)-MRI may play a role. Rim enhancement of breast cancers has been associated with unfavorable pathology characteristics in the context of outcome. However, existence of a direct link is unknown. The purpose was to retrospectively determine the association between rim enhancement on DCE-MRI and long-term patient outcome, and whether it has complementary value to subtype. Preoperative DCE-MRI was performed in 556 consecutive female patients who were eligible for breast-conserving therapy. Presence of rim enhancement was assessed. Tumor characteristics were derived from resection specimens. Patients were stratified according to subtype. Association was assessed between rim enhancement and patient, pathology and treatment characteristics, recurrence-free interval and invasive disease-free survival. Median follow-up was 84 months. Patients were stratified into ER-positive/HER2-negative (N = 416), HER2-positive (N = 75), or triple-negative (N = 65) subtypes. Rim enhancement was seen in 29.0% (N = 161/556) of tumors and was associated with higher histologic grade, negative ER-status, and triple-negative subtype. Only within triple-negative tumors, an association was seen with outcome. Recurrence was lower in non-rim-enhancing tumors (N = 1/36; 2.8%) compared to rim-enhancing tumors (N = 9/28; 32.1%) (p = 0.001). Survival was higher in non-rim-enhancing tumors (N = 34/36; 94.4%) compared to rim-enhancing tumors (N = 18/28; 64.3%) (p = 0.001). Rim enhancement on DCE-MRI is associated with long-term outcome of patients with triple-negative breast cancer and may potentially serve as a prognostic biomarker in these patients.

Sequential (18)F-FDG PET/CT for early prediction of complete pathological response in breast and axilla during neoadjuvant chemotherapy.

PURPOSE: To investigate the value of response monitoring in both the primary tumour and axillary nodes on sequential PET/CT scans during neoadjuvant chemotherapy (NAC) for predicting complete pathological response (pCR), taking the breast cancer subtype into account. METHODS: In 107 consecutive patients 290 PET/CT scans were performed at baseline (PET/CT1, 107 patients), after 2 - 3 weeks of chemotherapy (PET/CT2, 85 patients), and after 6 - 8 weeks (PET/CT3, 98 patients). The relative changes in SUVmax (from baseline) of the tumour and the lymph nodes and in both combined (after logistic regression), and the changes in the highest SUVmax between scans (either tumour or lymph node) were determined and their associations with pCR of the tumour and lymph nodes after completion of NAC were assessed using receiver operating characteristic (ROC) analysis. RESULTS: A pCR was seen in 17 HER2-positive tumours (65 %), 1 ER-positive/HER2-negative tumour (2 %), and 16 triple-negative tumours (52 %). The areas under the ROC curves (ROC-AUC) for the prediction of pCR in HER2-positive tumours after 3 weeks were 0.61 for the relative change in tumours, 0.67 for the combined change in tumour and nodes, and 0.72 for the changes in the highest SUVmax between scans. After 8 weeks equivalent values were 0.59, 0.42 and 0.64, respectively. In triple-negative tumours the ROC-AUCs were 0.76, 0.84 and 0.76 after 2 weeks, and 0.87, 0.93 and 0.88 after 6 weeks, respectively. CONCLUSION: In triple-negative tumours a PET/CT scan after 6 weeks (three cycles) appears to be optimally predictive of pCR. In HER2-positive tumours neither a PET/CT scan after 3 weeks nor after 8 weeks seems to be useful. The changes in SUVmax of both the tumour and axillary nodes combined correlates best with pCR.

Combined use of ¹8F-FDG PET/CT and MRI for response monitoring of breast cancer during neoadjuvant chemotherapy.

PURPOSE: To explore the potential complementary value of PET/CT and dynamic contrast-enhanced MRI in predicting pathological response to neoadjuvant chemotherapy (NAC) of breast cancer and the dependency on breast cancer subtype. METHODS: We performed (18)F-FDG PET/CT and MRI examinations before and during NAC. The imaging features evaluated on both examinations included baseline and changes in (18)F-FDG maximum standardized uptake value (SUVmax) on PET/CT, and tumour morphology and contrast uptake kinetics on MRI. The outcome measure was a (near) pathological complete response ((near-)pCR) after surgery. Receiver operating characteristic curves with area under the curve (AUC) were used to evaluate the relationships between patient, tumour and imaging characteristics and tumour responses. RESULTS: Of 93 patients, 43 achieved a (near-)pCR. The responses varied among the different breast cancer subtypes. On univariate analysis the following variables were significantly associated with (near-)pCR: age (p = 0.033), breast cancer subtype (p < 0.001), relative change in SUVmax on PET/CT (p < 0.001) and relative change in largest tumour diameter on MRI (p < 0.001). The AUC for the relative reduction in SUVmax on PET/CT was 0.78 (95% CI 0.68-0.88), and for the relative reduction in tumour diameter at late enhancement on MRI was 0.79 (95% CI 0.70-0.89). The AUC increased to 0.90 (95% CI 0.83-0.96) in the final multivariate model with PET/CT, MRI and breast cancer subtype combined (p = 0.012). CONCLUSION: PET/CT and MRI showed comparable value for monitoring response during NAC. Combined use of PET/CT and MRI had complementary potential. Research with more patients is required to further elucidate the dependency on breast cancer subtype.

Current clinical indications for magnetic resonance imaging of the breast.

MRI is increasingly used in breast cancer patients. MRI has a high sensitivity compared to mammography and ultrasound. The specificity is moderate leading to an increased risk of false positive findings. Currently, a beneficial effect of breast MRI has been established in some patient groups and is debated in the general breast cancer population. The diagnostic ability of MRI and its role in various groups of breast cancer patients are discussed in this review.

Automated rating of background parenchymal enhancement in MRI of extremely dense breasts without compromising the association with breast cancer in the DENSE trial.

OBJECTIVES: Background parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI (DCE-MRI) as rated by radiologists is subject to inter- and intrareader variability. We aim to automate BPE category from DCE-MRI. METHODS: This study represents a secondary analysis of the Dense Tissue and Early Breast Neoplasm Screening trial. 4553 women with extremely dense breasts who received supplemental breast MRI screening in eight hospitals were included. Minimal, mild, moderate and marked BPE rated by radiologists were used as reference. Fifteen quantitative MRI features of the fibroglandular tissue were extracted to predict BPE using Random Forest, Naïve Bayes, and KNN classifiers. Majority voting was used to combine the predictions. Internal-external validation was used for training and validation. The inverse-variance weighted mean accuracy was used to express mean performance across the eight hospitals. Cox regression was used to verify non inferiority of the association between automated rating and breast cancer occurrence compared to the association for manual rating. RESULTS: The accuracy of majority voting ranged between 0.56 and 0.84 across the eight hospitals. The weighted mean prediction accuracy for the four BPE categories was 0.76. The hazard ratio (HR) of BPE for breast cancer occurrence was comparable between automated rating and manual rating (HR = 2.12 versus HR = 1.97, P = 0.65 for mild/moderate/marked BPE relative to minimal BPE). CONCLUSION: It is feasible to rate BPE automatically in DCE-MRI of women with extremely dense breasts without compromising the underlying association between BPE and breast cancer occurrence. The accuracy for minimal BPE is superior to that for other BPE categories.