Breast Dynamic Contrast-enhanced Magnetic Resonance Research Articles

A new algorithm for automatic vascular mapping of DCE-MRI of the breast: Clinical application of a potential new biomarker

Background and objectiveVascularity evaluation on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a potential diagnostic value, but it represents a time consuming procedure, affected by intra- and inter-observer variability. This study tests the application of a recently published method to reproducibly quantify breast vascularity, and evaluates if the vascular volume of cancer-bearing breast, calculated from automatic vascular maps (AVMs), may correlate with pathologic tumor response after neoadjuvant chemotherapy (NAC). MethodsTwenty-four patients with unilateral locally advanced breast cancer underwent DCE-MRI before and after NAC, 8 responders and 16 non-responders. A validated algorithm, based on multiscale 3D Hessian matrix analysis, provided AVMs and allowed the calculation of vessel volume before the initiation and after the last NAC cycle for each breast. For cancer bearing breast, the difference in vascular volume before and after NAC was compared in responders and non-responders using the Wilcoxon two-sample test. A radiologist evaluated the vascularity on the subtracted images (first enhanced minus unenhanced), before and after treatment, assigning a vascular score for each breast, according to the number of vessels with length ≥30mm and maximal transverse diameter ≥2mm. The same evaluation was repeated with the support of the simultaneous visualization of the AVMs. The two evaluations were compared in terms of mean number of vessels and mean vascular score per breast, in responders and non-responders, by use of Wilcoxon two sample test. For all the analysis, the statistical significance level was set at 0.05. ResultsFor breasts harboring the cancer, evidence of a difference in vascular volume before and after NAC for responders (median=1.71cc) and non-responders (median=0.41cc) was found (p=0.003). A significant difference was also found in the number of vessels (p=0.03) and vascular score (p=0.02) before or after NAC, according to the evaluation supported by the AVMs. ConclusionsThe encouraging, although preliminary, results of this study suggest the use of AVMs as new biomarker to evaluate the pathologic response after NAC, but also support their application in other breast DCE-MRI vessel analysis that are waiting for a reliable quantification method.

Breast DCE-MRI: Influence of Postcontrast Timing on Automated Lesion Kinetics Assessments and Discrimination of Benign and Malignant Lesions

Breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) scanning protocols vary widely. The purpose of this study was to determine the effects of postcontrast timing on delayed-phase lesion kinetics assessment and ability to discriminate malignant from benign lesions. Following institutional review board approval, we retrospectively reviewed all lesions assessed on magnetic resonance examinations from April 2005 to June 2006. DCE-MRI was performed with 90-second temporal resolution. Delayed-phase kinetic parameters including percentages of persistent, plateau, and washout, and categorizations of predominant and worst curve type were compared between 4.5 and 7.5 minutes postcontrast. Ability to discriminate benign and malignant lesions based on delayed-phase kinetic parameters was compared between postcontrast timings by receiver operating characteristic (ROC) analysis. Two hundred eighty consecutive breast lesions (206 malignant and 74 benign) were evaluated in 228 women. Comparing kinetics assessments at 7.5 versus 4.5 minutes: volume percentage of washout increased in malignancies by a mean of 9.4% (P<.0001) and increased slightly in benign lesions (mean 3.2%, P=.007); predominant curve type categorizations changed significantly only for malignancies (P<.0001); and worst curve categorizations did not change significantly for either benign or malignant lesions (P>.05). There were no significant differences between timings in area under ROC curves for delayed-phase kinetic parameters. The choice of delayed postcontrast timing more strongly affects the kinetics assessments for malignancies than benign breast lesions, but our results suggest that a shortened breast DCE-MRI protocol may not significantly impact diagnostic accuracy. Furthermore, worst curve type classifications are least affected by postcontrast timing and may provide reliable assessment of delayed-phase kinetics across protocols.

Comparison of Gadoteric Acid and Gadobutrol for Detection as Well as Morphologic and Dynamic Characterization of Lesions on Breast Dynamic Contrast-Enhanced Magnetic Resonance Imaging

In contrast to conventional breast imaging techniques, one major diagnostic benefit of breast magnetic resonance imaging (MRI) is the simultaneous acquisition of morphologic and dynamic enhancement characteristics, which are based on angiogenesis and therefore provide insights into tumor pathophysiology. The aim of this investigation was to intraindividually compare 2 macrocyclic MRI contrast agents, with low risk for nephrogenic systemic fibrosis, in the morphologic and dynamic characterization of histologically verified mass breast lesions, analyzed by blinded human evaluation and a fully automatic computer-assisted diagnosis (CAD) technique. Institutional review board approval and patient informed consent were obtained. In this prospective, single-center study, 45 women with 51 histopathologically verified (41 malignant, 10 benign) mass lesions underwent 2 identical examinations at 1.5 T (mean time interval, 2.1 days) with 0.1-mmol kg doses of gadoteric acid and gadobutrol. All magnetic resonance images were visually evaluated by 2 experienced, blinded breast radiologists in consensus and by an automatic CAD system, whereas the morphologic and dynamic characterization as well as the final human classification of lesions were performed based on the categories of the Breast imaging reporting and data system MRI atlas. Lesions were also classified by defining their probability of malignancy (morpho-dynamic index; 0%-100%) by the CAD system. Imaging results were correlated with histopathology as gold standard. The CAD system coded 49 of 51 lesions with gadoteric acid and gadobutrol (detection rate, 96.1%); initial signal increase was significantly higher for gadobutrol than for gadoteric acid for all and the malignant coded lesions (P < 0.05). Gadoteric acid resulted in more postinitial washout curves and fewer continuous increases of all and the malignant lesions compared with gadobutrol (CAD hot spot regions, P < 0.05). Morphologically, the margins of the malignancies were different between the 2 agents, whereas gadobutrol demonstrated more spiculated and fewer smooth margins (P < 0.05). Lesion classifications by the human observers and by the morpho-dynamic index compared with the histopathologic results did not significantly differ between gadoteric acid and gadobutrol. Macrocyclic contrast media can be reliably used for breast dynamic contrast-enhanced MRI. However, gadoteric acid and gadobutrol differed in some dynamic and morphologic characterization of histologically verified breast lesions in an intraindividual, comparison. Besides the standardization of technical parameters and imaging evaluation of breast MRI, the standardization of the applied contrast medium seems to be important to receive best comparable MRI interpretation.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging of Breast Tumors at 3 and 7 T

The objective of this study was to compare the image quality, contrast enhancement behavior, and diagnostic value of bilateral 3-dimensional dynamic contrast-enhanced breast magnetic resonance imaging (MRI), with high spatial and temporal resolution, at 3 and 7 T, in the same patient group. Twenty-four consecutive patients (mean [SD] age, 57 [17] years) were included in this prospective institutional review board-approved study. Written informed consent was obtained from all patients. T1-weighted 3-dimensional sequences (time-resolved angiography with stochastic trajectories) were optimized at 3 and 7 T, with high temporal (both 14 seconds) and spatial resolution (1.1 × 1.1 × 1.1 mm [3 T], 0.7 × 0.7 × 0.7 mm [7 T]): echo time/repetition time, 2.84/6.01 milliseconds (3 T) and 2.5/4.75 milliseconds (7 T); acquisition time, 9 minutes (3 T/7 T). Dotarem (gadoterate meglumine, Guerbet, Roissy CdG, France) contrast agent was injected intravenously as a bolus (0.2 mL/kg of body weight) after 3 baseline images. The images were rated according to breast imaging-reporting and data system by 2 radiologists in consensus. Signal-to-noise ratio and average enhancement ratios were measured quantitatively by means of region of interest analysis. In addition, B1 mapping was done in the same 5 healthy subjects at both field strengths. Twenty-eight enhancing lesions were detected in the 24 patients at both field strengths (16 malignant, 12 benign). At 7 T, higher contrast than that at 3 T and good image quality were achieved. With the high spatial isotropic resolution of 0.7 mm at 7 T, images with more detailed information could be acquired when compared with those acquired at 3 T. Sensitivity was 93.75% and 100%, at 3 and 7 T, respectively. Specificity was 91.67% at both field strengths. The signal-to-noise ratio at both field strengths was comparable, but at 7 T, the spatial resolution was 3.2-times higher than that at 3 T. A signal-to-noise ratio decrease toward prepectoral breast regions due to B1 inhomogeneities was observed at both field strengths but was stronger at 7 T (51%) than at 3 T (19%)(P = 0.0002). At 7 T, B1+ dropped by 20.7% and 32.8% in the prepectoral and lateral region of the breast in healthy subjects. Our comparison study shows that 7-T DCE-MRI provides simultaneous high temporal and spatial resolution that is significantly improved compared with lower field strengths, but further technical improvements are necessary to overcome B1 inhomogeneity problems at 7 T to fully unfold the potential of breast MRI at 7 T.

Effects of Tamoxifen and Aromatase Inhibitors on Breast Tissue Enhancement in Dynamic Contrast–enhanced Breast MR Imaging: A Longitudinal Intraindividual Cohort Study

To prospectively investigate the effects of two antihormonal medications, tamoxifen and aromatase inhibitor (AI), on the degree of background enhancement in breast magnetic resonance (MR) imaging. This institutional review board-approved study was performed in 40 postmenopausal women (mean age, 63 years; range, 49-78 years) with unilateral breast cancer between January 2005 and December 2010. Informed consent was obtained from all participants. All patients underwent breast MR imaging before starting any medication, under tamoxifen, and after switching to an AI. Qualitative and quantitative degrees of benign parenchymal enhancement were investigated before treatment, under tamoxifen, and under AI. Data were analyzed by using the Wilcoxon singed-rank test and Student t test for matched pairs. Before treatment, the distribution of background enhancement MR-American College of Radiology (ACR) categories 1, 2, 3, and 4 was 20%, 35%, 33%, and 13%, respectively. With tamoxifen, background enhancement was suppressed, with a distribution of 80%, 15%, 5%, and 0% for MR-ACR categories 1, 2, 3, and 4, respectively. With AI, background enhancement recovered in part, with a distribution of 25%, 53%, 23%, and 0% for categories 1, 2, 3, and 4, respectively. In all 40 women, background enhancement rates were highest before treatment (mean, 51.3% ± 33.3 [standard deviation]). By using tamoxifen, background enhancement rates were significantly reduced (mean, 8.4% ± 9.2), and rose again after the switch to an AI (mean, 22.9% ± 19.1 [P < .001]). Prevalence of benign enhancing foci was 65% (26 of 40) at baseline, 12.5% (five of 40) with tamoxifen, and 40% (16 of 40) with AI. The effects of tamoxifen and AI on benign parenchymal enhancement differ. Whereas tamoxifen leads to a virtually complete suppression of enhancement, the effects of AI are less pronounced. Accordingly, whereas enhancement is unusual and deserves a more careful work-up in a patient in whom tamoxifen is used, this is not necessarily true for women in whom AIs are used. Online supplemental material is available for this article.

Computer-aided diagnosis for diagnostically challenging breast lesions in DCE-MRI based on image registration and integration of morphologic and dynamic characteristics

Abstract Diagnostically challenging lesions comprise both foci (small lesions) and non-mass-like enhancing lesions and pose a challenge to current computer-aided diagnosis systems. Motion-based artifacts lead in dynamic contrast-enhanced breast magnetic resonance to diagnostic misinterpretation; therefore, motion compensation represents an important prerequisite to automatic lesion detection and diagnosis. In addition, the extraction of pertinent kinetic and morphologic features as lesion descriptors is an equally important task. In the present paper, we evaluate the performance of a computer-aided diagnosis system consisting of motion correction, lesion segmentation, and feature extraction and classification. We develop a new feature extractor, the radial Krawtchouk moment, which guarantees rotation invariance. Many novel feature extraction techniques are proposed and tested in conjunction with lesion detection. Our simulation results have shown that motion compensation combined with Minkowski functionals and Bayesian classifier can improve lesion detection and classification.

The application of breast DCE-MRI combined with time signal curve in diagnosing early breast cancer

Objective The aim of this study was to investigate the application value of breast dynamic contrast-enhanced magnetic resonance imaging combined with time signal curve in diagnosis of early breast cancer.

Location constrained approximate message passing for compressed sensing MRI

Iterative thresholding methods have been extensively studied as faster alternatives to convex optimization methods for solving large-sized problems in compressed sensing. A novel iterative thresholding method called LCAMP (Location Constrained Approximate Message Passing) is presented for reducing computational complexity and improving reconstruction accuracy when a nonzero location (or sparse support) constraint can be obtained from view shared images. LCAMP modifies the existing approximate message passing algorithm by replacing the thresholding stage with a location constraint, which avoids adjusting regularization parameters or thresholding levels. This work is first compared with other conventional reconstruction methods using random one-dimention signals and then applied to dynamic contrast-enhanced breast magnetic resonance imaging to demonstrate the excellent reconstruction accuracy (less than 2% absolute difference) and low computation time (5-10 s using Matlab) with highly undersampled three-dimentional data (244 × 128 × 48; overall reduction factor = 10).

Improving suspicious breast lesion characterization using semi‐automatic lesion fractional volume washout kinetic analysis

Although breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) demonstrates high sensitivity for malignant tumor detection, a major limitation is the relative low specificity, resulting in many false-positive diagnoses of suspicious lesions (BI-RADS assessment of 4 or 5) in clinical practice and consequently producing a relatively low positive predictive value (PPV) for biopsies. The most enhanced areas in the malignant tumors show a typical washout (WO) kinetic feature for the postcontrast signal intensity time courses and also correlate with microvessel density. Benign proliferative breast diseases can also produce the WO curve, yielding an equivocal kinetic behavior for the benign lesions and rendering their diagnoses as suspicious lesions in clinical practice. Considering that tumor angiogenesis is essential to an aggressive cancer tumor growth, the authors hypothesize that the WO volume fraction, i.e., the total volume of the WO voxels that demonstrate the WO curve within the tumor, is relatively large for malignant tumors in comparison to that for benign lesions. In this study, the authors present a lesion fractional volume WO kinetic analysis for improving the characterization of suspicious breast lesions. A method to automatically detect the boundary of a manually selected contrast-enhanced lesion was introduced and tested, utilizing the signal intensity difference between the contrast-enhanced lesion and its surrounding tissues. The kinetic features of the postcontrast signal intensity time courses were quantitatively analyzed voxel-by-voxel with emphasis on the examination of the WO behavior. The WO volume fraction relative to the whole lesion volume was introduced and tested as a biomarker for improving the characterization of suspicious breast lesions. The sample for this test consisted of 28 suspicious lesions with correlative histopathology reports available. The lesions included 10 malignant tumors and 18 benign lesions, yielding a 35.7% PPV of the biopsies. The semi-automatic method produced an objective volume of interest for each lesion with voxelwise-quantified kinetic features. With an optimal choice of kinetic analysis, the mean and standard deviation of the WO volume fraction were 59.1 ± 13.1 (%) with the range from 41.0% to 80.7% for the malignant tumors and 31.4 ± 20.5 (%) with the range between 3.3% and 71.6% for the benign lesions, respectively. The WO volume fraction was significantly larger (p < 0.0004) for the malignant tumors than for the benign lesions. While maintaining the same sensitivity for malignant tumors, using the WO volume fraction as an additional biomarker would characterize 14 out of the 18 benign lesions as benign, potentially resulting in an 100% improvement rate in the PPV of the biopsies (from 35.7% to 71.4%) and consequently a 77.8% reduction rate in potentially unnecessary biopsies (from 18 to 4). The significantly larger WO volume fraction for the malignant tumors was probably related to the increased vascularity associated with tumor angiogenesis. The results suggest that the WO volume fraction biomarker has potential to improve the computer-based assessment of breast MRI by greatly increasing the PPV of breast biopsies and potentially significantly reducing the number of unnecessary biopsies without compromising sensitivity.

ENTROPY TOLERANT FUZZY C-MEANS IN MEDICAL IMAGES

Segmenting the Dynamic Contrast-Enhanced Breast Magnetic Resonance Images (DCE-BMRI) is an extremely important task to diagnose the disease because it has the highest specificity when acquired with high temporal and spatial resolution and is also corrupted by heavy noise, outliers, and other imaging artifacts. In this paper, we intend to develop efficient robust segmentation algorithms based on fuzzy clustering approach for segmenting the DCE-BMRs. Our proposed segmentation algorithms have been amalgamated with effective kernel-induced distance measure on standard fuzzy c-means algorithm along with the spatial neighborhood information, entropy term, and tolerance vector into a fuzzy clustering structure for segmenting the DCE-BMRI. The significant feature of our proposed algorithms is its capability to find the optimal membership grades and obtain effective cluster centers automatically by minimizing the proposed robust objective functions. Also, this article demonstrates the superiority of the proposed algorithms for segmenting DCE-BMRI in comparison with other recent kernel-based fuzzy c-means techniques. Finally the clustering accuracies of the proposed algorithms are validated by using silhouette method in comparison with existed fuzzy clustering algorithms.

Resolving arterial phase and temporal enhancement characteristics in DCE MRM at high spatial resolution with TWIST acquisition

To investigate the potential of a view-sharing 3D fast gradient-echo sequence using pseudo random trajectories (TWIST) to achieve very short acquisition times with high in-plane resolution and good volume coverage and its application to dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI). Two versions of a 3D fast gradient echo TWIST sequence were implemented and applied to patients: First, an ultrafast TWIST acquisition (TA = 5.7 sec) in combination with a routine DCE MRM protocol to allow the extraction of arterial input functions and to resolve the first pass of the contrast agent. Second, a dynamic full coverage TWIST DCE acquisition (TA = 10.6 sec) in a repeat examination, replacing the routine DCE MRM sequence. The ultrafast acquisition enabled extraction of arterial input functions and the monitoring of the contrast agent's first pass through vessels and lesions. The dynamic full coverage TWIST acquisition captured the initial dynamic slope of the signal time curve of lesions accurately, in contrast to the routine protocol. TWIST acquisitions proved very robust and offer high flexibility in protocol timing. The ultrafast protocol achieved 5.7 seconds time resolution with good image quality and can be combined with any established routine protocol. The full dynamics TWIST DCE protocol offers improved time resolution of the CE dynamic time-course and closely matches the image quality of the routine protocol.

Optimization of Time-to-peak Analysis for Differentiating Malignant and Benign Breast Lesions with Dynamic Contrast-Enhanced MRI

The aim of this study was to investigate the feasibility of applying measures sensitive to time-to-peak (T(peak)) heterogeneity as indicators for malignancy on breast dynamic contrast-enhanced magnetic resonance imaging. The study included 39 benign and 97 malignant breast lesions from 103 patients. Lesions were automatically segmented by k-means clustering. Voxel-by-voxel T(peak) values were extracted using an empirical model. The pth percentile values (p = 10, 20…) of the T(peak) distribution within each lesion and the fractional and absolute hot spot volumes were determined, where the hot spot volume is the volume of tissue with T(peak) less than a threshold value. Using the area under the receiver-operating characteristic curve (AUC), these measures were tested as indicators for differentiating fibroadenomas from invasive lesions and from ductal carcinoma in situ, as well as for differentiating nonfibroadenoma benign lesions from these malignant lesions. Region of interest-based T(peak) measurements were also tested. Finally, the relationship between hot spot volume and lesion volume was investigated. For differentiating fibroadenomas from malignant lesions, AUC values increased with decreasing values of p. At the optimal threshold (3 minutes), the hot spot volume provided high diagnostic performance (AUC ≥0.96 ± 0.02 for absolute hot spot volume). However, for differentiating nonfibroadenoma benign lesions from malignant lesions, AUC values were low. A significant correlation between absolute hot spot volume and lesion volume was found for malignant lesions and nonfibroadenoma benign lesions. Quantitative analysis of the T(peak) distribution can be optimized for diagnostic performance, providing indicators sensitive to intralesion T(peak) heterogeneity.

Accuracy of magnetic resonance in suspicious breast lesions: a systematic quantitative review and meta-analysis

Dynamic contrast-enhanced breast magnetic resonance (MR) is a promising emerging technique for evaluating breast lesions. A quantitative systematic review was performed to estimate the accuracy of breast MR in the diagnosis of high-risk breast lesions and breast cancer. A comprehensive search of the Cochrane Library, MEDLINE, CANCERLIT, LILACS, and EMBASE databases was performed from January 1985 to August 2010. The medical subjects heading (MeSH) and text words for the terms "breast neoplasm", "breast lesions", "breast cancer" and "magnetic resonance" were combined with the MeSH term diagnosis ("sensitivity and specificity"). Studies that compared breast MR with paraffin-embedded sections parameters for the diagnosis of breast lesions (benign, high-risk borderline, and breast cancer) were included. Sixty-nine studies were analyzed, which included 9,298 women with 9,884 breast lesions. Interrater overall agreement between breast MR and paraffin section diagnosis was 79% (κ = 0.55), indicating moderate agreement. Pooled sensitivity and specificity were 90% [95% CI 88-92%] and 75% [95% CI 70-79%], respectively. The pooled likelihood positive ratio was 3.64 (95% CI 3.0-4.2) and the negative ratio was 0.12 (95% CI 0.09-0.15). For breast cancer or high-risk lesions versus benign lesions, the AUC was 0.91 for breast MR and the point Q* was 0.84. In summary, breast MR is a useful pre-operative test for predicting the diagnosis of breast lesions.

Dynamic Contrast-Enhanced Breast MRI at 7 Tesla Utilizing a Single-loop Coil: A Feasibility Trial

The aim of this study was to assess the feasibility of dynamic contrast-enhanced ultra-high-field breast imaging at 7 Tesla. A total of 15 subjects, including 5 patients with histologically proven breast cancer, were examined on a 7 Tesla whole-body magnetic resonance imaging system using a unilateral linearly polarized single-loop coil. Subjects were placed in prone position on a biopsy support system, with the coil placed directly below the region of interest. The examination protocol included the following sequences: 1) T2-weighted turbo spin echo sequence; 2) six dynamic T1-weighted spoiled gradient-echo sequences; and 3) subtraction imaging. Contrast-enhanced T1-weighted imaging at 7 Tesla could be obtained at high spatial resolution with short acquisition times, providing good image accuracy and a conclusively good delineation of small anatomical and pathological structures. T2-weighted imaging could be obtained with high spatial resolution at adequate acquisition times. Because of coil limitations, four high-field magnetic resonance examinations showed decreased diagnostic value. This first scientific approach of dynamic contrast-enhanced breast magnetic resonance imaging at 7 Tesla demonstrates the complexity of ultra-high-field breast magnetic resonance imaging and countenances the implementation of further advanced bilateral coil concepts to circumvent current limitations from the coil and ultra-high-field magnetic strength.

Principal component analysis of breast DCE‐MRI adjusted with a model‐based method

To investigate a fast, objective, and standardized method for analyzing breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) applying principal component analysis (PCA) adjusted with a model-based method. 3D gradient-echo DCE breast images of 31 malignant and 38 benign lesions, recorded on a 1.5T scanner, were retrospectively analyzed by PCA and by the model-based three-timepoints (3TP) method. Intensity-scaled (IS) and enhancement-scaled (ES) datasets were reduced by PCA yielding a first IS-eigenvector that captured the signal variation between fat and fibroglandular tissue; two IS-eigenvectors and the two first ES-eigenvectors captured contrast-enhanced changes, whereas the remaining eigenvectors captured predominantly noise changes. Rotation of the two contrast-related eigenvectors led to a high congruence between the projection coefficients and the 3TP parameters. The ES-eigenvectors and the rotation angle were highly reproducible across malignant lesions, enabling calculation of a general rotated eigenvector base. Receiver operating characteristic (ROC) curve analysis of the projection coefficients of the two eigenvectors indicated high sensitivity of the first rotated eigenvector to detect lesions (area under the curve [AUC] > 0.97) and of the second rotated eigenvector to differentiate malignancy from benignancy (AUC = 0.87). PCA adjusted with a model-based method provided a fast and objective computer-aided diagnostic tool for breast DCE-MRI.

Algorithm‐based method for detection of blood vessels in breast MRI for development of computer‐aided diagnosis

To develop a computer-based algorithm for detecting blood vessels that appear in breast dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and to evaluate the improvement in reducing the number of vascular pixels that are labeled by computer-aided diagnosis (CAD) systems as being suspicious of malignancy. The analysis was performed in 34 cases. The algorithm applied a filter bank based on wavelet transform and the Hessian matrix to detect linear structures as blood vessels on a two-dimensional maximum intensity projection (MIP). The vessels running perpendicular to the MIP plane were then detected based on the connectivity of enhanced pixels above a threshold. The nonvessel enhancements were determined and excluded based on their morphological properties, including those showing scattered small segment enhancements or nodular or planar clusters. The detected vessels were first converted to a vasculature skeleton by thinning and subsequently compared to the vascular track manually drawn by a radiologist. When evaluating the performance of the algorithm in identifying vascular tissue, the correct-detection rate refers to pixels identified by both the algorithm and radiologist, while the incorrect-detection rate refers to pixels identified by only the algorithm, and the missed-detection rate refers to pixels identified only by the radiologist. From 34 analyzed cases the median correct-detection rate was 85.6% (mean 84.9% +/- 7.8%), the incorrect-detection rate was 13.1% (mean 15.1% +/- 7.8%), and the missed-detection rate was 19.2% (mean 21.3% +/- 12.8%). When detected vessels were excluded in the hot-spot color-coding of the CAD system, they could reduce the labeling of vascular vessels in 2.6%-68.6% of hot-spot pixels (mean 16.6% +/- 15.9%). The computer algorithm-based method can detect most large vessels and provide an effective means in reducing the labeling of vascular pixels as suspicious on a DCE-MRI CAD system. This algorithm may improve the workflow of radiologists using CAD for image display, but will be particularly useful for development of automated CAD that gives diagnostic impression.

Metabolic and Vascular Features of Dynamic Contrast-enhanced Breast Magnetic Resonance Imaging and 15O-Water Positron Emission Tomography Blood Flow in Breast Cancer

We sought to (1) describe associations between measures of tumor perfusion by dynamic contrast-enhanced breast magnetic resonance imaging (DCE-MRI), blood flow by (15)O-water positron emission tomography (PET) and metabolism by (18)F-fluorodeoxyglucose ((18)F)-FDG PET and (2) improve our understanding of tumor enhancement on MRI through independent measures of tumor metabolism and blood flow. We performed a retrospective analysis of the existing PET and MRI databases from the Departments of Nuclear Medicine and Radiology. We identified patients with locally advanced breast cancer who underwent (15)O-water/(18)F-FDG PET within 1 month of clinical DCE-MRI between February 2004 and August 2006. The (15)O-water PET blood flow and (18)F-FDG metabolic rate and tissue transport constant (K(1)) in the primary malignancy were calculated. DCE-MRI peak percent enhancement and peak signal enhancement ratio (SER) were measured for each tumor. Correlations and regression analysis of these variables were performed. Fifteen patients with complete PET and DCE-MRI data were included in the analysis cohort. Peak SER correlated significantly with blood flow (r = 0.73, P = .002) and K(1) (r = 0.76, P = .001). However, peak SER did not correlate significantly with FDG metabolic rate (r = 0.44, P = .101). There were no significant correlations between peak percent enhancement and any of the PET parameters. Our findings suggest that tumor perfusion, represented by (15)O-water PET blood flow, is an important factor in the MRI enhancement of locally advanced breast cancer. A lack of correlation of FDG metabolic rate with blood flow and DCE-MRI kinetics suggests that (18)F-FDG PET provides complementary metabolic information independent of vascular factors.

Dynamic contrast-enhanced MR imaging in screening detected microcalcification lesions of the breast: is there any value?

To prospectively evaluate whether dynamic contrast-enhanced magnetic resonance (MR) imaging findings can help predict the presence of malignancy when screening detected microcalcification lesions, and its contribution to patient management of stereotactic vacuum-assisted breast biopsy (SVAB). Dynamic contrast-enhanced breast MR imaging was performed when screening 100 detected microcalcification lesions not visualized by ultrasonography with 11-gauge SVAB. Definitive surgery was performed on all patients with the biopsy resulting in the diagnosis of breast cancer or atypical ductal hyperplasia (ADH). Positive predictive values (PPVs) and negative predictive values (NPVs) were calculated on the basis of a BI-RADS (Breast Imaging Reporting and Data System) category and the absence or presence of contrast uptake in the area of microcalcification. The BI-RADS mammography category correlated with the diagnosis of breast cancer (ADH excluded): category 3 = 7% (4/55); category 4 = 48% (13/27); category 5 = 94% (17/18). After dynamic contrast-enhanced MR imaging, three of four malignancies with BI-RADS mammography category 3 were diagnosed as true positive. Therefore, the PPV of BI-RADS mammography category 3 with MR imaging was 1.8% (1/55). The PPV of contrast uptake of MR imaging was 86% (32/37), significantly higher than the 67% (30/45) PPV of BI-RADS mammography 4 and 5 (P = 0.033). The NPV of BI-RADS mammography 3 was 93% (51/55) versus 97% (61/63) NPV of MR imaging (P = 0.167). In the evaluation of screening detected microcalcification lesions, dynamic contrast-enhanced breast MR imaging provides additional information with high PPV and NPV, and may therefore offer an alternative to SVAB for women who do not want to undergo SVAB with equivocal findings following full diagnostic mammographic assessment, but breast MR imaging with imperfect PPV and NPV cannot replace SVAB. Dynamic contrast-enhanced breast MR imaging can demonstrate malignant microcalcifications detected by screening mammography and can be recommended in the evaluation of equivocal microcalcifications prior to SVAB.

Dynamic Contrast-enhanced Breast MR Imaging in Men: Preliminary Results

To prospectively evaluate whether the descriptors of lesion features and the diagnostic criteria that have been established for breast magnetic resonance (MR) imaging in female patients may be used for differential diagnosis with breast MR imaging in male patients as well. The study design was approved by the institutional review board; all patients gave informed consent. The Institutional Review Board and informed consent information applied to the prospective and any retrospective component of the study. Seventeen consecutive male patients (mean age, 53 years +/- 14) were referred for imaging of a palpable breast mass. In addition to mammography and high-frequency breast ultrasonography, patients underwent dynamic breast MR imaging in a prone position with a dedicated double-breast surface coil. The standardized protocol consisted of a T2-weighted turbo spin-echo sequence followed by a dynamic series. Findings were recorded by using the terminology and descriptors and by evaluating the diagnostic criteria (related to morphology and enhancement kinetics) that have been developed for breast MR imaging in female patients. Validation was achieved at biopsy (nine patients) or follow-up with clinical examination and conventional imaging (eight patients). Because of the small size of the patient cohort, statistical significance was not tested. A total of 24 breast abnormalities were diagnosed. Three patients had invasive breast cancer (five tumors), 11 had gynecomastia (six unilateral, five bilateral), two had pseudogynecomastia, and one had a benign solid tumor (angiolipoma). All malignant tumors appeared as irregular masses with heterogeneous internal architecture or rim enhancement and showed rapid initial enhancement (mean value, 137% +/- 23) followed by a washout time course (Breast Imaging Reporting and Data System [BI-RADS] category 5). Diffuse and nodular gynecomastia showed slow initial and persistent enhancement with normal-appearing parenchymal architecture (BI-RADS category 2; 15 of 16 breasts in 10 of 11 patients). In one patient with biopsy-proved bilateral gynecomastia, an area with segmental enhancement was classified as suspicious for ductal carcinoma in situ. Pseudogynecomastia did not enhance at all. The angiolipoma showed benign morphologic features and slow initial and persistent enhancement (BI-RADS category 2). In the small study cohort, the MR imaging features of benign breast diseases and breast cancers in male patients seemed to be comparable to those seen in female patients.

Independent component analysis for the examination of dynamic contrast-enhanced breast magnetic resonance imaging data: preliminary study.

An application of independent component analysis (ICA) is reported for the detection and characterization of breast lesions in dynamic contrast-enhanced MRI. The ICA technique, which uses a novel statistical algorithm to separate mixed signal sources of unknown nature, enables the extraction of spatial and temporal features of dynamic MRI data. Six patients with confirmed lesion diagnosis (three with malignancy and three with benign condition) participated in this study. T1-weighted MRI covering both breast volumes was dynamically acquired in every 90 seconds after the bolus injection of contrast media using three-dimensional fast low-angle shot sequence (3-D FLASH). With the application of the ICA, differential signal responses were delineated from benign and malignant lesions, and areas with high temporal correlations with the extracted signal components were selectively visualized. The results suggest that ICA allowed for an identification of lesion morphology and lesion-specific dynamic enhancement patterns.