Background parenchymal enhancement at breast MR imaging and breast cancer risk

The relationship of breast density in mammography and magnetic resonance imaging in high-risk women and women with breast cancer

PURPOSE

To evaluate the relationship between mammographic breast density (MBD), background parenchymal enhancement (BPE), and fibroglandular tissue (FGT) in women with breast cancer (BC) and at high risk for developing BC.

METHODS

Our institutional database was queried for patients who underwent mammography and MRI.

RESULTS

Four hundred three (85%) had BC and 72 (15%) were at high risk. MBD (P=.0005), BPE (P<.0001), and FGT (P=.02) were all higher in high-risk women compared to the BC group.

CONCLUSIONS

Higher levels of MBD, BPE and FGT are seen in women at higher risk for developing BC when compared to women with BC.

A new quantitative image analysis method for improving breast cancer diagnosis using DCE-MRI examinations

PURPOSE

To investigate the feasibility of applying a new quantitative image analysis method to improve breast cancer diagnosis performance using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) by integrating background parenchymal enhancement (BPE) features into the decision making process.

METHODS

A dataset involving 115 DCE-MRI examinations was used in this study. Each examination depicts one identified suspicious breast tumor. Among them, 75 cases were verified as malignant and 40 were benign by the biopsy results. A computer-aided detection scheme was applied to segment breast regions and the suspicious tumor depicted on the sequentially scanned MR images of each case. We then computed 18 kinetic features in which 6 were computed from the segmented breast tumor and 12 were BPE features from the background parenchymal regions (excluding the tumor). Support vector machine (SVM) based statistical learning classifiers were trained and optimized using different combinations of features that were computed either from tumor only or from both tumor and BPE. Each SVM was tested using a leave-one-case-out validation method and assessed using an area under the receiver operating characteristic curve (AUC).

RESULTS

When using kinetic features computed from tumors only, the maximum AUC is 0.865 ± 0.035. After fusing with the BPE features, AUC increased to 0.919 ± 0.029. At 90% specificity, the tumor classification sensitivity increased by 13.2%.

CONCLUSIONS

The proposed quantitative BPE features provide valuable supplementary information to the kinetic features of breast tumors in DCE-MRI. Their addition to computer-aided diagnosis methodologies could improve breast cancer diagnosis based on DCE-MRI examinations.

Comparison of contrast enhancement and diffusion-weighted magnetic resonance imaging in healthy and cancerous breast tissue

OBJECTIVE

To measure background parenchymal enhancement (BPE) and compare with other contrast enhancement values and diffusion-weighted MRI parameters in healthy and cancerous breast tissue at the clinical level.

MATERIALS AND METHODS

This HIPAA-compliant, IRB approved retrospective study enrolled 77 patients (38 patients with breast cancer - mean age 51.8 ± 10.0 years; 39 high-risk patients for screening evaluation - mean age 46.3 ± 11.7 years), who underwent contrast-enhanced 3T breast MRI. Contrast enhanced MRI and diffusion-weighted imaging were performed to quantify BPE, lesion contrast enhancement, and apparent diffusion coefficient (ADC) metrics in fibroglandular tissue (FGT) and lesions.

RESULTS

BPE did not correlate with ADC values. Mean BPE for the lesion-bearing patients was higher (43.9%) compared to that of the high-risk screening patients (28.3%, p=0.004). Significant correlation (r=0.37, p<0.05) was found between BPE and lesion contrast enhancement.

CONCLUSION

No significant association was observed between parenchymal or lesion enhancement with conventional apparent diffusion metrics, suggesting that proliferative processes are not co-regulated in cancerous and parenchymal tissue.

Effective factors to raise diagnostic performance of breast MRI for diagnosing pathologic complete response in breast cancer patients after neoadjuvant chemotherapy

BACKGROUND

Although MRI is a highly effective tool in evaluating residual disease after neoadjuvant chemotherapy (NAC), there are many reports of discordance between the response of MRI and pathology. To increase MR accuracy, additional methods, which reflect post-NAC changes, should be considered in diagnosis.

PURPOSE

To evaluate effective methods that raise the diagnostic performance of MRI for predicting pathologic complete response (pCR) in breast cancer after neoadjuvant chemotherapy (NAC).

MATERIAL AND METHODS

For 98 invasive breast carcinoma patients, chemotherapeutic response to MRI was evaluated for the following parameters: tumor size, tumor distribution pattern, kinetic curve analysis, and background parenchymal enhancement pattern (BPE). BPE was categorized as "minimal", "mild", "moderate", or "marked", according to the ACR BI-RADS criteria.

RESULTS

After NAC, the mean size of tumors decreased by 40% in non-pCR and by 59% in pCR groups, respectively. The sensitivity, specificity, false positive rate and false negative rate of MRI were 96% (78/81), 53% (9/17), 47% (8/17), and 4% (3/81), respectively. At pre-NAC MRI, the most common kinetic curve was delayed washout pattern (68%, 67/98); however, at post-NAC MRI the persistent pattern (55%, 47/86). Grouped lesion was the most common tumor distribution pattern on pre-NAC MRI (28%, 27/98), while on post-NAC solitary mass (40%, 34/86). The most common BPE at pre- and post-NAC MRI was mild and minimal enhancement, respectively.

CONCLUSION

To improve the diagnostic accuracy of MRI, we should consider additional factors including: tumor distribution pattern, BPE, kinetic curve analysis, and tumor size.

Identification of Breast Cancer Using Integrated Information from MRI and Mammography

Objectives

Integration of information from corresponding regions between the breast MRI and an X-ray mammogram could benefit the detection of breast cancer in clinical diagnosis. We aimed to provide a framework of registration from breast MRI to mammography and to evaluate the diagnosis using the combined information.

Materials and Methods

43 patients with 46 lesions underwent both MRI and mammography scans, and the interval between the two examinations was around one month. The distribution of malignant to benign lesions was 31/46 based on histological results. Maximum intensity projection and thin-plate spline methods were applied for image registration for MRI to mammography. The diagnosis using integrated information was evaluated using results of histology as the reference. The assessment of annotations and statistical analysis were performed by the two radiologists.

Results

For the cranio-caudal view, the mean post-registration error between MRI and mammography was 2.2±1.9 mm. For the medio-lateral oblique view, the proposed approach performed even better with a mean error of 3.0±2.4 mm. In the diagnosis using MRI assessment with information of mammography, the sensitivity was 91.9±2.3% (29/31, 28/31), specificity 70.0±4.7% (11/15, 10/15), accuracy 84.8±3.1% (40/46, 38/46), positive predictive value 86.4±2.1% (29/33, 28/33) and negative predictive value 80.8±5.4% (11/13, 10/13).

Conclusion

MRI with the aid of mammography shows potential improvements of sensitivity, specificity, accuracy, PPV and NPV in clinical breast cancer diagnosis compared to the use of MRI alone.

Quantitative assessment of background parenchymal enhancement in breast MRI predicts response to risk-reducing salpingo-oophorectomy: preliminary evaluation in a cohort of BRCA1/2 mutation carriers

Introduction

We present a fully automated method for deriving quantitative measures of background parenchymal enhancement (BPE) from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and perform a preliminary evaluation of these measures to assess the effect of risk-reducing salpingo-oophorectomy (RRSO) in a cohort of breast cancer susceptibility gene 1/2 (BRCA1/2) mutation carriers.

Methods

Breast DCE-MRI data from 50 BRCA1/2 carriers were retrospectively analyzed in compliance with the Health Insurance Portability and Accountability Act and with institutional review board approval. Both the absolute (| |) and relative (%) measures of BPE and fibroglandular tissue (FGT) were computed from the MRI scans acquired before and after RRSO. These pre-RRSO and post-RRSO measures were compared using paired Student’s t test. The area under the curve (AUC) of the receiver operating characteristic (ROC) was used to evaluate the performance of relative changes in the BPE and FGT measures in predicting breast cancer that developed in these women after the RRSO surgery.

Results

For the 44 women who did not develop breast cancer after RRSO, the absolute volume of BPE and FGT had a significant decrease (P < 0.05) post-RRSO, whereas for the 6 women who developed breast cancer, there were no significant changes in these measures. Higher values in all BPE and FGT measures were also observed post-RRSO for the women who developed breast cancer, compared with women who did not. Relative changes in BPE percentage were most predictive of women who developed breast cancer after RRSO (P < 0.05), whereas combining BPE percentage and |FGT| yielded an AUC of 0.80, higher than BPE percentage (AUC = 0.78) or |FGT| (AUC = 0.66) alone (both P > 0.02).

Conclusions

Quantitative measures of BPE and FGT are different before and after RRSO, and their relative changes are associated with prediction of developing breast cancer, potentially indicative of women who are more susceptible to develop breast cancer after RRSO in BRCA1/2 mutation carriers.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-015-0577-0) contains supplementary material, which is available to authorized users.

Are Qualitative Assessments of Background Parenchymal Enhancement, Amount of Fibroglandular Tissue on MR Images, and Mammographic Density Associated with Breast Cancer Risk?

PURPOSE

To investigate whether qualitative magnetic resonance (MR) imaging assessments of background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT), and mammographic density are associated with risk of developing breast cancer in women who are at high risk.

MATERIALS AND METHODS

In this institutional review board-approved HIPAA-compliant retrospective study, all screening breast MR images obtained from January 2006 to December 2011 in women aged 18 years or older and at high risk for but without a history of breast cancer were identified. Women in whom breast cancer was diagnosed after index MR imaging comprised the cancer cohort, and one-to-one matching (age and BRCA status) of each woman with breast cancer to a control subject was performed by using MR images obtained in women who did not develop breast cancer with follow-up time maximized. Amount of BPE, BPE pattern (peripheral vs central), amount of FGT at MR imaging, and mammographic density were assessed on index images. Imaging features were compared between cancer and control cohorts by using conditional logistic regression.

RESULTS

Twenty-three women at high risk (mean age, 47 years ± 10 [standard deviation]; six women had BRCA mutations) with no history of breast cancer underwent screening breast MR imaging; in these women, a diagnosis of breast cancer (invasive, n = 12; in situ, n = 11) was made during the follow-up interval. Women with mild, moderate, or marked BPE were nine times more likely to receive a diagnosis of breast cancer during the follow-up interval than were those with minimal BPE (P = .007; odds ratio = 9.0; 95% confidence interval: 1.1, 71.0). BPE pattern, MR imaging amount of FGT, and mammographic density were not significantly different between the cohorts (P = .5, P = .5, and P = .4, respectively).

CONCLUSION

Greater BPE was associated with a higher probability of developing breast cancer in women at high risk for cancer and warrants further study.

Background parenchymal uptake during molecular breast imaging and associated clinical factors

OBJECTIVE. The purposes of this study were to describe the prevalence of background parenchymal uptake categories observed at screening molecular breast imaging (MBI) and to examine the association of background parenchymal uptake with mammographic density and other clinical factors. MATERIALS AND METHODS. Adjunct MBI screening was performed for women with dense breasts on previous mammograms. Two radiologists reviewed images from the MBI examinations and subjectively categorized background parenchymal uptake into four groups: photopenic, minimal-mild, moderate, or marked. Women with breast implants or a personal history of breast cancer were excluded. The association between background parenchymal uptake categories and patient characteristics was examined with Kruskal-Wallis and chi-square tests as appropriate. RESULTS. In 1149 eligible participants, background parenchymal uptake was photopenic in 252 (22%), minimal-mild in 728 (63%), and moderate or marked in 169 (15%). The distribution of categories differed across BI-RADS density categories (p < 0.0001). In 164 participants with extremely dense breasts, background parenchymal uptake was photopenic in 72 (44%), minimal-mild in 55 (34%), and moderate or marked in 37 (22%). The moderate-marked group was younger on average, more likely to be premenopausal or perimenopausal, and more likely to be using postmenopausal hormone therapy than the photopenic or minimal-mild groups (p < 0.0001). CONCLUSION. Among women with similar-appearing mammographic density, background parenchymal uptake ranged from photopenic to marked. Background parenchymal uptake was associated with menopausal status and postmenopausal hormone therapy but not with premenopausal hormonal contraceptives, phase of menstrual cycle, or Gail model 5-year risk of breast cancer. Additional work is necessary to fully characterize the underlying cause of background parenchymal uptake and determine its utility in predicting subsequent risk of breast cancer.

BI-RADS update for breast cancer caregivers

This review will discuss changes relevant to breast cancer caregivers in the fifth edition of the Breast Imaging Reporting and Data System.

Alternative screening for dense breasts: MRI

OBJECTIVE. The purpose of this article is to review the use of MRI in breast density measurement and breast cancer risk estimation and to discuss the role of MRI as an alternative screening to mammography for screening women with dense breasts. CONCLUSION. The potential of MRI for screening women with dense breasts remains controversial because of the paucity of clinical evidence, the possibility of overdiagnosis, and the cost-effectiveness of the technique in this population. Although methods of MRI measurement require standardization and automation, future addition of MRI density to risk models may positively impact their value.

MRI-guided breast biopsy: outcomes and effect on patient management

INTRODUCTION

The purpose of this study was to correlate the pathology results of MRI-guided breast biopsies at our institution with MRI findings and patient clinical history characteristics. The effect of MRI-guided breast biopsies on surgical management in patients with a new diagnosis of breast cancer was also assessed.

PATIENTS AND METHODS

In this Health Insurance Portability and Accountability Act-compliant study we retrospectively reviewed all MRI-guided breast biopsies performed from March 2006 to May 2012. Clinical history, MRI features, and pathology outcomes were reviewed. In patients who underwent breast MRI to evaluate extent of disease, any change in surgical management resulting from the MRI-guided biopsy was recorded. Statistical analysis included binary logistic regression and independent Student t test.

RESULTS

Two-hundred fifteen lesions in 168 patients were included, of which 23 (10.7%) were malignant, 43 (20%) were high-risk, and 149 (69.3%) were benign. No clinical characteristic was associated with malignancy in our cohort. MRI features associated with malignancy were: larger size (mean 2.6 cm vs. 1.3 cm; P = .046), washout kinetics (18% malignancy rate; P = .02), and marked background parenchymal enhancement (40% malignancy rate; P < .001-.03). Nineteen (28%) of the 67 patients with a new diagnosis of breast cancer who underwent MRI-guided breast biopsy had a change in surgical management based on the biopsy result.

CONCLUSION

Malignancy rate was associated with lesion size, washout kinetics, and marked background enhancement of the breast parenchyma but was not associated with any clinical history characteristics. Preoperative MRI-guided breast biopsies changed surgical management in 28% of women with a new diagnosis of breast cancer.

Technologist-performed handheld screening breast US imaging: how is it performed and what are the outcomes to date?

Breast density-inform legislation is increasing the need for data on outcomes of tailored screening. Dense parenchyma can mask cancers, and denser tissue is also more likely to develop breast cancer than fatty tissue. Digital mammography is standard for women with dense breasts. Supplemental screening magnetic resonance imaging should be offered to women who meet high-risk criteria. Supplemental screening ultrasonographic (US) imaging may be appropriate in the much larger group of women with dense breasts. Both physician- and technologist-performed screening US imaging increases detection of node-negative invasive breast cancer. To meet anticipated demand in the United States, screening US images will most likely be acquired by trained technologists rather than physicians. While automated US offers standard documentation, there are few data on outcomes. US has been used diagnostically for decades to characterize masses seen by using mammography, but training specific to screening has been lacking. Standard approaches to training and documentation of technologist-performed handheld screening US imaging are needed. This article reviews the current status of technologist-performed handheld screening breast US imaging.

Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method

PURPOSE

Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Studies suggest that the relative amount of fibroglandular (i.e., dense) tissue in the breast as quantified in MR images can be predictive of the risk for developing breast cancer, especially for high-risk women. Automated segmentation of the fibroglandular tissue and volumetric density estimation in breast MRI could therefore be useful for breast cancer risk assessment.

METHODS

In this work the authors develop and validate a fully automated segmentation algorithm, namely, an atlas-aided fuzzy C-means (FCM-Atlas) method, to estimate the volumetric amount of fibroglandular tissue in breast MRI. The FCM-Atlas is a 2D segmentation method working on a slice-by-slice basis. FCM clustering is first applied to the intensity space of each 2D MR slice to produce an initial voxelwise likelihood map of fibroglandular tissue. Then a prior learned fibroglandular tissue likelihood atlas is incorporated to refine the initial FCM likelihood map to achieve enhanced segmentation, from which the absolute volume of the fibroglandular tissue (|FGT|) and the relative amount (i.e., percentage) of the |FGT| relative to the whole breast volume (FGT%) are computed. The authors' method is evaluated by a representative dataset of 60 3D bilateral breast MRI scans (120 breasts) that span the full breast density range of the American College of Radiology Breast Imaging Reporting and Data System. The automated segmentation is compared to manual segmentation obtained by two experienced breast imaging radiologists. Segmentation performance is assessed by linear regression, Pearson's correlation coefficients, Student's paired t-test, and Dice's similarity coefficients (DSC).

RESULTS

The inter-reader correlation is 0.97 for FGT% and 0.95 for |FGT|. When compared to the average of the two readers' manual segmentation, the proposed FCM-Atlas method achieves a correlation of r = 0.92 for FGT% and r = 0.93 for |FGT|, and the automated segmentation is not statistically significantly different (p = 0.46 for FGT% and p = 0.55 for |FGT|). The bilateral correlation between left breasts and right breasts for the FGT% is 0.94, 0.92, and 0.95 for reader 1, reader 2, and the FCM-Atlas, respectively; likewise, for the |FGT|, it is 0.92, 0.92, and 0.93, respectively. For the spatial segmentation agreement, the automated algorithm achieves a DSC of 0.69 ± 0.1 when compared to reader 1 and 0.61 ± 0.1 for reader 2, respectively, while the DSC between the two readers' manual segmentation is 0.67 ± 0.15. Additional robustness analysis shows that the segmentation performance of the authors' method is stable both with respect to selecting different cases and to varying the number of cases needed to construct the prior probability atlas. The authors' results also show that the proposed FCM-Atlas method outperforms the commonly used two-cluster FCM-alone method. The authors' method runs at ∼5 min for each 3D bilateral MR scan (56 slices) for computing the FGT% and |FGT|, compared to ∼55 min needed for manual segmentation for the same purpose.

CONCLUSIONS

The authors' method achieves robust segmentation and can serve as an efficient tool for processing large clinical datasets for quantifying the fibroglandular tissue content in breast MRI. It holds a great potential to support clinical applications in the future including breast cancer risk assessment.

Mammographic density, MRI background parenchymal enhancement and breast cancer risk

Mammographic density (MD), representing connective and epithelial tissue (fibroglandular tissue, FGT) is a major risk factor for breast cancer. In an analysis of an autopsy series (Bartow SA, Pathak DR, Mettler FA. Radiographic microcalcification and parenchymal patterns as indicators of histologic "high-risk" benign breast disease. Cancer 1990; 66: 1721-1725, Bartow SA, Pathak DR, Mettler FA et al. Breast mammographic pattern: a concatenation of confounding and breast cancer risk factors. Am J Epidemiol 1995; 142: 813-819), MD was found to be strongly correlated with the collagen and epithelial content of the breast (Li T, Sun L, Miller N et al. The association of measured breast tissue characteristics with MD and other risk factors for breast cancer. Cancer Epidemiol Biomarkers Prev 2005; 14: 343-349), and another report showed that breast epithelium was highly concentrated in the areas of collagen concentration (Hawes D, Downey S, Pearce CL et al. Dense breast stromal tissue shows greatly increased concentration of breast epithelium but no increase in its proliferative activity. Breast Cancer Res 2006; 8: R24). Collagen comprises the overwhelming majority of the FGT, occupying an area on the slides obtained from the autopsy series some 15 times the area of glandular tissue. The relationship of MD with breast cancer risk appears likely to be due to a major extent to increasing epithelial cell numbers with increasing MD. FGT is also seen in breast magnetic resonance imaging (breast MRI) and, as expected, it has been shown that this measure of FGT (MRI-FGT) is highly correlated with MD. A contrast-enhanced breast MRI shows that normal FGT 'enhances' (background parenchymal enhancement, BPE) after contrast agent is administered(Morris EA. Diagnostic breast MR imaging: current status and future directions. Radiol Clin North Am 2007; 45: 863-880, vii., Kuhl C. The current status of breast MR imaging. Part I. Choice of technique, image interpretation, diagnostic accuracy, and transfer to clinical practice. Radiology 2007; 244: 356-378), and a recent study suggests that BPE is also a major breast cancer risk factor, possibly as important as, and independent of MD (King V, Brooks JD, Bernstein JL et al. BPE at breast MR imaging and breast cancer risk. Radiology 2011; 260: 50-60). BPE is much more sensitive to the effects of menopause and tamoxifen than is FGT (King V, Gu Y, Kaplan JB et al. Impact of menopausal status on BPE and fibroglandular tissue on breast MRI. Eur Radiol 2012; 22: 2641-2647, King V, Kaplan J, Pike MC et al. Impact of tamoxifen on amount of fibroglandular tissue, BPE, and cysts on breast MRI. Breast J 2012; 18: 527-534). Changes in MD and BPE may be most useful in predicting response to chemopreventive agents aimed at blocking breast cell proliferation. More study of the biological basis of the effects of MD and BPE is needed if we are to fully exploit these factors in developing chemopreventive approaches to breast cancer.

A computerized global MR image feature analysis scheme to assist diagnosis of breast cancer: a preliminary assessment

OBJECTIVES

To develop a new computer-aided detection scheme to compute a global kinetic image feature from the dynamic contrast enhanced breast magnetic resonance imaging (DCE-MRI) and test the feasibility of using the computerized results for assisting classification between the DCE-MRI examinations associated with malignant and benign tumors.

MATERIALS AND METHODS

The scheme registers sequential images acquired from each DCE-MRI examination, segments breast areas on all images, searches for a fraction of voxels that have higher contrast enhancement values and computes an average contrast enhancement value of selected voxels. Combination of the maximum contrast enhancement values computed from two post-contrast series in one of two breasts is applied to predict the likelihood of the examination being positive for breast cancer. The scheme performance was evaluated when applying to a retrospectively collected database including 80 malignant and 50 benign cases.

RESULTS

In each of 91% of malignant cases and 66% of benign cases, the average contrast enhancement value computed from the top 0.43% of voxels is higher in the breast depicted suspicious lesions as compared to another negative (lesion-free) breast. In classifying between malignant and benign cases, using the computed image feature achieved an area under a receiver operating characteristic curve of 0.839 with 95% confidence interval of [0.762, 0.898].

CONCLUSIONS

We demonstrated that the global contrast enhancement feature of DCE-MRI can be relatively easily and robustly computed without accurate breast tumor detection and segmentation. This global feature provides supplementary information and a higher discriminatory power in assisting diagnosis of breast cancer.

Repeatability of quantitative MRI measurements in normal breast tissue

PURPOSE

To evaluate the variability and repeatability of repeated magnetic resonance imaging (MRI) measurements in normal breast tissues between and within subjects.

METHODS

Eighteen normal premenopausal subjects underwent two contrast-enhanced MRI scans within 72 hours or during the same menstrual phase in two consecutive months. A subset of nine women also completed diffusion-weighted imaging (DWI). Fibroglandular tissue (FGT) density and FGT enhancement were measured on the contrast-enhanced MRI. Apparent diffusion coefficient (ADC) values were computed from DWI. Between- and within-subject coefficients of variation (bCV and wCV, respectively) were assessed. Repeatability of all measurements was assessed by the coefficient of repeatability (CR) and Bland-Altman plots.

RESULTS

The bCV of FGT density and FGT enhancement at visit 1 and visit 2 ranged from 47% to 63%. The wCV was 13% for FGT density, 22% for FGT enhancement, and 11% for ADC. The CRs of FGT density and FGT enhancement were 0.15 and 0.19, respectively, and for ADC, it was 6.1 x 10(-4) mm(2)/s.

CONCLUSIONS

We present an estimate of the variability and repeatability of MR measurements in normal breasts. These estimates provide the basis for understanding the normal variation of healthy breast tissue in MRI and establishing thresholds for agreement between measurements.

Computer-aided diagnosis of breast DCE-MRI images using bilateral asymmetry of contrast enhancement between two breasts

Dynamic contrast material-enhanced magnetic resonance imaging (DCE-MRI) of breasts is an important imaging modality in breast cancer diagnosis with higher sensitivity but relatively lower specificity. The objective of this study is to investigate a new approach to help improve diagnostic performance of DCE-MRI examinations based on the automated detection and analysis of bilateral asymmetry of characteristic kinetic features between the left and right breast. An image dataset involving 130 DCE-MRI examinations was assembled and used in which 80 were biopsy-proved malignant and 50 were benign. A computer-aided diagnosis (CAD) scheme was developed to segment breast areas depicted on each MR image, register images acquired from the sequential MR image scan series, compute average contrast enhancement of all pixels in one breast, and a set of kinetic features related to the difference of contrast enhancement between the left and right breast, and then use a multi-feature based Bayesian belief network to classify between malignant and benign cases. A leave-one-case-out validation method was applied to test CAD performance. The computed area under a receiver operating characteristic (ROC) curve is 0.78 ± 0.04. The positive and negative predictive values are 0.77 and 0.64, respectively. The study indicates that bilateral asymmetry of kinetic features between the left and right breasts is a potentially useful image biomarker to enhance the detection of angiogenesis associated with malignancy. It also demonstrates the feasibility of applying a simple CAD approach to classify between malignant and benign DCE-MRI examinations based on this new image biomarker.

Contrast-enhanced digital mammography

Mammography is the only technology documented to reduce breast cancer mortality. Its sensitivity, however, is 75% to 80% at best and reduced to 30% to 50% in women with dense breasts. MR imaging is a sensitive modality for the detection of breast cancer but cannot be used in all patients. Its sensitivity is due in large part to its ability to detect enhancement of tumor vascularity so cancers can be detected before a mass is present. Contrast-enhanced dual-energy mammography uses the same capability of vascular enhancement and has been demonstrated to be more sensitive than routine mammography.

Automated chest wall line detection for whole-breast segmentation in sagittal breast MR images

PURPOSE

Breast magnetic resonance imaging (MRI) plays an important role in the clinical management of breast cancer. Computerized analysis is increasingly used to quantify breast MRI features in applications such as computer-aided lesion detection and fibroglandular tissue estimation for breast cancer risk assessment. Automated segmentation of the whole-breast as an organ from the other parts imaged is an important step in aiding lesion localization and fibroglandular tissue quantification. For this task, identifying the chest wall line (CWL) is most challenging due to image contrast variations, intensity discontinuity, and bias field.

METHODS

In this work, the authors develop and validate a fully automated image processing algorithm for accurate delineation of the CWL in sagittal breast MRI. The CWL detection is based on an integrated scheme of edge extraction and CWL candidate evaluation. The edge extraction consists of applying edge-enhancing filters and an edge linking algorithm. Increased accuracy is achieved by the synergistic use of multiple image inputs for edge extraction, where multiple CWL candidates are evaluated by the dynamic time warping algorithm coupled with the construction of a CWL reference. Their method is quantitatively validated by a dataset of 60 3D bilateral sagittal breast MRI scans (in total 3360 2D MR slices) that span the full American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) breast density range. Agreement with manual segmentation obtained by an experienced breast imaging radiologist is assessed by both volumetric and boundary-based metrics, including four quantitative measures.

RESULTS

In terms of breast volume agreement with manual segmentation, the overlay percentage expressed by the Dice's similarity coefficient is 95.0% and the difference percentage is 10.1%. More specifically, for the segmentation accuracy of the CWL boundary, the CWL overlay percentage is 92.7% and averaged deviation distance is 2.3 mm. Their method requires ≈ 4.5 min for segmenting each 3D breast MRI scan (56 slices) in comparison to ≈ 35 min required for manual segmentation. Further analysis indicates that the segmentation performance of their method is relatively stable across the different BI-RADS density categories and breast volume, and also robust with respect to a varying range of the major parameters of the algorithm.

CONCLUSIONS

Their fully automated method achieves high segmentation accuracy in a time-efficient manner. It could support large scale quantitative breast MRI analysis and holds the potential to become integrated into the clinical workflow for breast cancer clinical applications in the future.

Predicting local recurrence following breast-conserving treatment: parenchymal signal enhancement ratio (SER) around the tumor on preoperative MRI

BACKGROUND

The level of background parenchymal enhancement around tumor is known to be associated with breast cancer risk. However, there is no study investigating predictive power of parenchymal signal enhancement ratio (SER) around tumor for ipsilateral breast tumor recurrence (IBTR).

PURPOSE

To investigate whether the breast parenchymal SER around the tumor on preoperative dynamic contrast-enhanced magnetic resonance imaging (MRI) is associated with subsequent IBTR in breast cancer patients who had undergone breast-conserving treatment.

MATERIAL AND METHODS

Nineteen consecutive women (mean age, 44 years; range, 34-63 years) with breast cancer who developed IBTR following breast-conserving treatment and 114 control women matched for age, as well as T and N stages were included. We compared the clinicopathologic features of the two groups including nuclear grade, histologic grade, hormonal receptor status, human epidermal growth factor receptor-2 (HER-2) status, lymphovascular invasion, negative margin width, use of adjuvant therapy, and parenchymal SER around the tumor on preoperative DCE-MRI. The SER was measured on a slice showing the largest dimension of the tumor. Multivariate conditional logistic regression analysis was used to identify independent factors associated with IBTR.

RESULTS

In univariate analysis, ER negativity (odds ratio [OR] = 4.7; P = 0.040), PR negativity (OR = 4.0; P = 0.013), HER-2 positivity (OR = 3.6; P = 0.026), and a parenchymal SER greater than 0.53 (OR = 23.3; P = 0.011) were associated with IBTR. In multivariate analysis, ER negativity (OR = 3.8; P = 0.015) and a parenchymal SER greater than 0.53 (OR = 13.2; P = 0.040) on preoperative MRI were independent factors associated with IBTR.

CONCLUSION

In addition to ER negativity, a higher parenchymal SER on preoperative MRI was an independent factor associated with subsequent IBTR in patients with breast cancer who had undergone breast-conserving treatment.

Background parenchymal enhancement in the contralateral normal breast of patients undergoing neoadjuvant chemotherapy measured by DCE-MRI

The purpose of this study was to analyze background parenchymal enhancement (BPE) in the contralateral normal breast of cancer patients during the course of neoadjuvant chemotherapy (NAC). Forty-five subjects were analyzed. Each patient had three MRIs, one baseline (B/L) and two follow-up (F/U) studies. The fibroglandular tissue in the contralateral normal breast was segmented using a computer-assisted algorithm. Based on the segmented fibroglandular tissue, BPE was calculated. BPE measured in baseline (B/L) and follow-up (F/U) MR studies were compared. The baseline BPE was also correlated with age and compared between pre/peri-menopausal (<55 years old) and post-menopausal women (≥55 years old). The pre-treatment BPE measured in B/L MRI was significantly higher in women <55 years old than in women ≥55 years old (20.1%±7.4% vs. 12.1%±5.1%, p≤0.01). A trend of negative correlation between BPE and age was noted (r=-0.29). In women <55years old, BPE at F/U-1 (18.8%±6.9%) was decreased compared to B/L, and was further decreased in F/U-2 (13.3%±5.7%) which was significant compared to B/L and F/U-1. In women ≥55 years old, no significant difference was noted in any paired comparison among B/L, F/U-1 and F/U-2 MRI. A higher baseline BPE was associated with a greater reduction of BPE in F/U-2 MRI (r=0.73). Our study showed that younger women tended to have higher BPE than older women. BPE was significantly decreased in F/U-2 MRI after NAC in women <55 years old. The reduction in BPE was most likely due to the ovarian ablation induced by chemotherapeutic agents.

The impact of bilateral salpingo-oophorectomy on breast MRI background parenchymal enhancement and fibroglandular tissue

OBJECTIVE

The objective of this study was to evaluate the effect of bilateral salpingo-oophorectomy (BSO) on background parenchymal enhancement (BPE) and the amount of fibroglandular tissue (FGT) seen on breast MRI.

METHODS

Retrospective review identified 21 BRCA mutation carriers who underwent breast MRI before and after elective BSO. After exclusion of patients placed on postoperative hormone replacement therapy, there were 18 eligible patients. Blinded to surgical status, three independent readers used categorical scales to rate BPE (minimal, mild, moderate, marked) and the amount of FGT (fatty, scattered, heterogeneously dense, dense) on pre- and post-BSO MRI examinations. The sign test was used to assess for changes in the categorical ratings of BPE and FGT.

RESULTS

Significant proportions of women demonstrated decreases in BPE and in the amount of FGT following oophorectomy (P = 0.004 and 0.02, respectively.) BPE decreases were larger and seen earlier than FGT changes. There was no significant relationship between age/body mass index and changes in BPE and FGT.

CONCLUSIONS

BPE and the amount of FGT seen on breast MRI are significantly decreased by oophorectomy; BPE decreases to a greater extent and earlier than FGT.

KEY POINTS

• Background parenchymal enhancement significantly decreases at breast MRI following oophorectomy. • Fibroglandular tissue significantly decreases on breast MRI following oophorectomy. • Decrease in background parenchymal enhancement is greater than in fibroglandular tissue. • Decrease in background parenchymal enhancement occurs earlier than in fibroglandular tissue.

Clinical application of magnetic resonance imaging in management of breast cancer patients receiving neoadjuvant chemotherapy

Neoadjuvant chemotherapy (NAC), also termed primary, induction, or preoperative chemotherapy, is traditionally used to downstage inoperable breast cancer. In recent years it has been increasingly used for patients who have operable cancers in order to facilitate breast-conserving surgery, achieve better cosmetic outcome, and improve prognosis by reaching pathologic complete response (pCR). Many studies have demonstrated that magnetic resonance imaging (MRI) can assess residual tumor size after NAC, and that provides critical information for planning of the optimal surgery. NAC also allows for timely adjustment of administered drugs based on response, so ineffective regimens could be terminated early to spare patients from unnecessary toxicity while allowing other effective regimens to work sooner. This review article summarizes the clinical application of MRI during NAC. The use of different MR imaging methods, including dynamic contrast-enhanced MRI, proton MR spectroscopy, and diffusion-weighted MRI, to monitor and evaluate the NAC response, as well as how changes of parameters measured at an early time after initiation of a drug regimen can predict final treatment outcome, are reviewed. MRI has been proven a valuable tool and will continue to provide important information facilitating individualized image-guided treatment and personalized management for breast cancer patients undergoing NAC.

Evaluation of the kinetic properties of background parenchymal enhancement throughout the phases of the menstrual cycle

PURPOSE

To develop and apply a semiautomatic method of segmenting fibroglandular tissue to quantify magnetic resonance (MR) imaging contrast material-enhancement kinetics of breast background parenchyma (BP) and lesions throughout the phases of the menstrual cycle in women with benign and malignant lesions.

MATERIALS AND METHODS

The institutional review board approved this retrospective HIPAA-compliant study, and informed consent was waived. From December 2008 to August 2011, 58 premenopausal women who had undergone contrast material-enhanced MR imaging and MR imaging-guided biopsy were identified. The longest time from the start of the last known period was 34 days. One lesion per patient (37 benign and 21 malignant) was analyzed. The patient groups were stratified according to the week of the menstrual cycle when MR imaging was performed. A method based on principal component analysis (PCA) was applied for quantitative analysis of signal enhancement in the BP and lesions by using the percentage of slope and percentage of enhancement. Linear regression and the Mann-Whitney U test were used to assess the association between the kinetic parameters and the week of the menstrual cycle.

RESULTS

In the women with benign lesions, percentages of slope and enhancement for both BP and lesions during week 2 were significantly (P < .05) lower than those in week 4. Percentage of enhancement in the lesion in week 2 was lower than that in week 3 (P < .05). The MR images of women with malignant lesions showed no significant difference between the weeks for any of the parameters. There was a strong positive correlation between lesion and BP percentage of slope (r = 0.72) and between lesion and BP percentage of enhancement (r = 0.67) in the benign group. There was also a significant (P = .03) difference in lesion percentage of slope between the benign and malignant groups at week 2.

CONCLUSION

The PCA-based method can quantify contrast enhancement kinetics of BP semiautomatically, and kinetics of BP and lesions vary according to the week of the menstrual cycle in benign but not in malignant lesions.

Effect of the menstrual cycle on background parenchymal enhancement in breast MR imaging

PURPOSE

We assessed the influence of the menstrual cycle on background parenchymal enhancement (BPE) of the breast in the early and delayed phases of dynamic magnetic resonance (MR) imaging and the optimal timing of MR imaging of the breast in Japanese women.

MATERIAL AND METHODS

We reviewed dynamic MR images of 165 consecutive women with regular menstrual cycles and divided the women into 4 groups by week of the menstrual cycle: 32 in Week One (Days 1 through 4 of the menstrual cycle); 46 in Week 2 (Days 5 through 12); 49 in Week 3 (Days 13 through 20); and 38 in Week 4 (Days 21 through 30). We qualitatively evaluated BPE of the whole breast in the early and delayed phases of MR imaging; categorized enhancement as minimal, mild, moderate, or marked; and calculated the rate at which signal intensity increased (=SI post-SI pre/SI pre) in regions of interest in from the early and delayed phase to the before contrast administration phase to assess BPE quantitatively.

RESULTS

In both the early and delayed dynamic MR phases, BPE was significantly more extensive and stronger in Week 4 than Week 2 (P<0.01). Throughout the menstrual cycle, BPE was significantly stronger in the delayed phase than in the early phase in both qualitative (Week One, P=0.0002; Weeks 2 through 4, P<0.0001) and quantitative (Weeks One through 4, P<0.0001) assessments.

CONCLUSION

The optimal time to perform dynamic breast MR imaging in premenopausal Japanese women was during Days 5 through 12 of the menstrual cycle.

Atlas-based probabilistic fibroglandular tissue segmentation in breast MRI

In this paper we propose an atlas-aided probabilistic model-based segmentation method for estimating the fibroglandular tissue in breast MRI, where a novel fibroglandular tissue atlas is learned to aid the segmentation. The atlas represents a pixel-wise likelihood of being fibroglandular tissue in the breast, which is derived by combining deformable image warping, using aligned breast contour points as landmarks, with a kernel density estimation technique. A mixture multivariate model is learned to characterize the breast tissue using MR image features, and the segmentation is subsequently based on examining the posterior probability where the learned atlas is incorporated as the prior probability. In our experiments, the algorithm-generated segmentation results of 10 cases are compared to the manual segmentations, verified by an experienced breast imaging radiologist, to assess the accuracy of the algorithm, where the Dice's Similarity Coefficient (DSC) shows a 0.85 agreement. The proposed automated segmentation method could be used to estimate the volumetric amount of fibroglandular tissue in the breast for breast cancer risk estimation.

Impact of tamoxifen on amount of fibroglandular tissue, background parenchymal enhancement, and cysts on breast magnetic resonance imaging

The objective of this study was to evaluate the impact of tamoxifen treatment on amount of fibroglandular tissue (FGT), background parenchymal enhancement (BPE), and cysts on breast MRI. Retrospective search identified 96 women with breast cancer who had a breast MRI both before and during adjuvant tamoxifen therapy between 2002 and 2008. After exclusion of all irradiated breasts, 88 women were eligible. Two readers blinded to tamoxifen treatment status independently rated level of BPE, amount of FGT, and cysts using a 4-point categorical scale: BPE--Minimal, Mild, Moderate, Marked; FGT--Fatty, Scattered, Heterogeneously Dense (HD), Dense; Cysts--Minimal, Mild, Moderate, Marked. A consensus interpretation was reached in cases of disagreement. During tamoxifen, there was a significant shift from higher to lower degree BPE, cysts, and FGT compared with before tamoxifen. BPE, cysts and FGT decreased in 68% (60/88), 38% (33/88), and 40% (35/88) of women during tamoxifen (p<0.001 for all measures). After the exclusion of all cases with minimal BPE, cysts, or FGT on the pre-tamoxifen MRI, the percentage of women demonstrating a decrease in these factors increased to 81% (60/74), 77% (33/43), and 41% (35/86), respectively. Exclusion of patients treated with chemotherapy did not substantially change these results. The percentage of women with decreases in FGT and cysts increased with greater duration on tamoxifen, whereas decreases in BPE were detected early in treatment (<90 days) and did not change substantially with longer duration on tamoxifen. A significant association exists between treatment with tamoxifen and decreases in BPE, cysts, and FGT on breast MRI.

Diagnostic imaging strategy for MDCT- or MRI-detected breast lesions: use of targeted sonography

BACKGROUND

Leading-edge technology such as magnetic resonance imaging (MRI) or computed tomography (CT) often reveals mammographically and ultrasonographically occult lesions. MRI is a well-documented, effective tool to evaluate these lesions; however, the detection rate of targeted sonography varies for MRI detected lesions, and its significance is not well established in diagnostic strategy of MRI detected lesions. We assessed the utility of targeted sonography for multidetector-row CT (MDCT)- or MRI-detected lesions in practice.

METHODS

We retrospectively reviewed 695 patients with newly diagnosed breast cancer who were candidates for breast conserving surgery and underwent MDCT or MRI in our hospital between January 2004 and March 2011. Targeted sonography was performed in all MDCT- or MRI-detected lesions followed by imaging-guided biopsy. Patient background, histopathology features and the sizes of the lesions were compared among benign, malignant and follow-up groups.

RESULTS

Of the 695 patients, 61 lesions in 56 patients were detected by MDCT or MRI. The MDCT- or MRI-detected lesions were identified by targeted sonography in 58 out of 61 lesions (95.1%). Patients with pathological diagnoses were significantly older and more likely to be postmenopausal than the follow-up patients. Pathological diagnosis proved to be benign in 20 cases and malignant in 25. The remaining 16 lesions have been followed up.Lesion size and shape were not significantly different among the benign, malignant and follow-up groups.

CONCLUSIONS

Approximately 95% of MDCT- or MRI-detected lesions were identified by targeted sonography, and nearly half of these lesions were pathologically proven malignancies in this study. Targeted sonography is a useful modality for MDCT- or MRI-detected breast lesions.

Small masses on breast MR: is biopsy necessary?

RATIONALE AND OBJECTIVES

To evaluate outcome of magnetic resonance (MR)-detected biopsied breast lesions ≤5 mm by correlating imaging characteristics with pathology.

METHODS AND MATERIALS

Institutional review board-approved retrospective review of 565 lesions biopsied with MR guidance between March 2004 and February 2009 found 68 lesions ≤5 mm in 61 patients. Lesions evaluated were those prospectively recommended for biopsy based on clinical setting, suspicious lesion morphology, and kinetics. Two study radiologists, blinded to final pathology, reviewed MR exams recording patient age, exam indication (staging, surveillance, diagnostic, or follow-up), mass location, size, morphology, T2-weighted signal, and kinetics. Chart review provided final pathology.

RESULTS

Of 68 masses ≤5 mm, 14 (20.6%) were malignant. Of 32 <5 mm, 32 (28.1%) were malignant. Of 14 malignancies, 7 (50%) were in patients with recently diagnosed breast cancer, 6 in the same breast, of which 4 (66.7%) were in same quadrant. Higher likelihood of malignancy based on proximity to known cancer was statistically significant (P = .01). No significant difference in proportion of malignancies was found based on age, T2-weighted signal, morphology, or kinetics.

CONCLUSION

For MR-detected biopsied masses, the positive predictive value for malignancy of those ≤5 mm was 20.6%. The highest prevalence of cancers was in the same quadrant as a newly diagnosed breast cancer. The decision to biopsy small masses should be based on carefully assessed MR features, and in the context of exam indication, not solely on size.