Dynamic Contrast Material-enhanced Magnetic Resonance Imaging Research Articles

Computer-Aided Diagnosis Scheme for Distinguishing Between Benign and Malignant Masses in Breast DCE-MRI.

Our purpose in this study was to develop a computer-aided diagnosis (CAD) scheme for distinguishing between benign and malignant breast masses in dynamic contrast material-enhanced magnetic resonance imaging (DCE-MRI). Our database consisted 90 DCE-MRI examinations, each of which contained four sequential phase images; this database included 28 benign masses and 62 malignant masses. In our CAD scheme, we first determined 11 objective features of masses by taking into account the image features and the dynamic changes in signal intensity that experienced radiologists commonly use for describing masses in DCE-MRI. Quadratic discriminant analysis (QDA) was employed to distinguish between benign and malignant masses. As the input of the QDA, a combination of four objective features was determined among the 11 objective features according to a stepwise method. These objective features were as follows: (i) the change in signal intensity from 2 to 5min; (ii) the change in signal intensity from 0 to 2min; (iii) the irregularity of the shape; and (iv) the smoothness of the margin. Using this approach, the classification accuracy, sensitivity, and specificity were shown to be 85.6% (77 of 90), 87.1% (54 of 62), and 82.1% (23 of 28), respectively. Furthermore, the positive and negative predictive values were 91.5% (54 of 59) and 74.2% (23 of 31), respectively. Our CAD scheme therefore exhibits high classification accuracy and is useful in the differential diagnosis of masses in DCE-MRI images.

MR Perfusion-derived Hemodynamic Parametric Response Mapping of Bevacizumab Efficacy in Recurrent Glioblastoma.

To better understand the effect of bevacizumab therapy on tumor blood flow and oxygenation status in patients with recurrent glioblastoma. Retrospective data evaluation was approved by the local ethics committee of the University of Heidelberg (ethics approval number, S-320/2012), and informed consent was waived. A total of 71 patients who received a diagnosis of recurrent glioblastoma underwent conventional anatomic magnetic resonance (MR) imaging and dynamic susceptibility contrast material-enhanced MR imaging at baseline and at the first follow-up examination after initiation of bevacizumab therapy. Parametric response maps (PRMs) were created with multistep (nonlinear) registration of patients' post- to pretreatment images and voxel-wise subtraction between Gaussian-normalized relative cerebral blood volume (nrCBV) and Gaussian-normalized relative cerebral blood flow (nrCBF) maps. Intratumor voxels were stratified as being increased (PRM[+]) or decreased (PRM[-]) if they exceeded a threshold that represented the 95% confidence interval in the normal-appearing brain. Correlation with progression-free and overall survival was performed with Cox proportional hazards models. The risks for disease progression and death significantly increased with (a) higher baseline nrCBV (hazard ratio [HR] = 1.86, P < .01; HR = 1.52, P < .01) and nrCBF (HR = 1.78, P < .01; HR = 1.86, P < .01) values and (b) higher PRM(-) of nrCBV (HR = 1.03, P = .01; HR = 1.02, P = .03) and nrCBF (HR = 1.04, P < .01; HR = 1.03, P < .01), but not with higher PRM(+) of nrCBV and nrCBF, and not for the relative change in mean nrCBV and nrCBF, confirming the superiority of the PRM approach. The magnitude of PRM(-) for both nrCBV and nrCBF significantly increased for higher baseline values (P < .01). Pretreatment hemodynamic parameters are the principal determinant of response to bevacizumab therapy in patients with recurrent glioblastoma. Although the magnitude of PRM(-) is a function of the corresponding pretreatment parameter, the finding of higher PRM(-) and a lack of change in PRM(+) in nonresponders to bevacizumab therapy implies that tumors with a high degree of angiogenesis before bevacizumab therapy retain a higher level of angiogenesis during therapy, despite a greater antiangiogenic effect of bevacizumab, such that a reversal of the biologic behavior and relative prognosis of these tumors does not occur.

T1-weighted Dynamic Contrast-enhanced MR Imaging of the Lung in Asthma: Semiquantitative Analysis for the Assessment of Contrast Agent Kinetic Characteristics

To evaluate the contrast agent kinetics of dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging in healthy lungs and asthmatic lungs by using non-model-based semiquantitative parameters and to explore the relationships with pulmonary function testing and eosinophil level. The study was approved by the National Research Ethical Committee (reference no. 11/NW/0387), and written informed consent was obtained from all individuals. Ten healthy subjects and 30 patients with asthma underwent pulmonary function tests, blood and sputum eosinophil counts, and 1.5-T DCE MR imaging within 7 days. Semiquantitative parameters of contrast agent kinetics were calculated from the relative signal intensity-time course curves on a pixel-by-pixel basis and were summarized by using whole-lung median values. The distribution heterogeneity was assessed by using the regional coefficient of variation. DCE MR imaging readouts were compared between groups by using one-way analysis of variance, and the relationships with pulmonary function testing and eosinophil counts were assessed by using Pearson correlation analysis. Asthmatic patients showed significantly lower peak enhancement (P < .001) and initial areas under the relative signal intensity curve in the first 60 seconds (P = .002) and significantly reduced late-phase washout slope (P = .002) when compared with healthy control subjects. The distribution heterogeneity of bolus arrival time (P = .029), time to peak (P = .008), upslope of the first-pass peak (P = .011), and late-phase washout slope (P = .032), estimated by using the median coefficient of variation, were significantly higher in asthmatic patients than in healthy control subjects. These imaging readouts also showed significant linear correlations with measurements of pulmonary function testing but not with eosinophil level in patients with asthma. The contrast agent kinetic characteristics of T1-weighted DCE MR images of asthmatic lungs are different from those of healthy lungs and are related to measurements of pulmonary function testing but not to eosinophil level.

Monitoring Vascular Disrupting Therapy in a Rabbit Liver Tumor Model: Relationship between Tumor Perfusion Parameters at IVIM Diffusion-weighted MR Imaging and Those at Dynamic Contrast-enhanced MR Imaging.

To investigate whether perfusion-related intravoxel incoherent motion (IVIM) diffusion-weighted (DW) magnetic resonance (MR) imaging parameters correlate with dynamic contrast material-enhanced MR imaging parameters in between-subject and/or within-subject longitudinal settings for monitoring the therapeutic effects of a vascular disrupting agent (VDA) (CKD-516) in rabbit VX2 liver tumors. With institutional Animal Care and Use Committee approval, 21 VX2 liver tumor-bearing rabbits (treated, n = 15; control, n = 6) underwent IVIM DW imaging with 12 b values (0-800 sec/mm(2)) and dynamic contrast-enhanced MR imaging performed before (baseline) CKD-516 administration and 4 hours, 24 hours, and 7 days after administration. Perfusion-related IVIM DW imaging parameters of the tumors, including the pseudodiffusion coefficient (D*) and perfusion fraction (f), as well as dynamic contrast-enhanced MR imaging parameters, including the volume transfer coefficient (K(trans)) and initial area under the gadolinium concentration-time curve until 60 seconds (iAUC), were measured. IVIM DW imaging parameters were correlated with dynamic contrast-enhanced MR imaging parameters by using Pearson correlation analysis between subjects at each given time and by using a linear mixed model for within-subject longitudinal data. In the treated group, D*, f, K(trans), and iAUC significantly decreased (-40.7% to -26.3%) at 4-hour follow-up compared with these values in the control group (-6.9% to +5.9%) (P < .05). For longitudinal monitoring of CKD-516 treatment, D* and f showed significant positive correlations with K(trans) and iAUC (P = .004 and P = .02; P < .001 and P = .006, respectively), while no significant correlations were observed between IVIM DW imaging and dynamic contrast-enhanced MR imaging parameters between subjects at any given time (P > .05). In a rabbit tumor model, perfusion parameters serially quantified with IVIM DW imaging can be used as alternatives to dynamic contrast-enhanced MR imaging parameters in reflecting the dynamic changes in tumor perfusion during the within-subject longitudinal monitoring of VDA treatment.

Breast Cancer: Radiogenomic Biomarker Reveals Associations among Dynamic Contrast-enhanced MR Imaging, Long Noncoding RNA, and Metastasis.

To perform a radiogenomic analysis of women with breast cancer to study the multiscale relationships among quantitative computer vision-extracted dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging phenotypes, early metastasis, and long noncoding RNA (lncRNA) expression determined by means of high-resolution next-generation RNA sequencing. In this institutional review board-approved study, an automated image analysis platform extracted 47 computational quantitative features from DCE MR imaging data in a training set (n = 19) to screen for MR imaging biomarkers indicative of poor metastasis-free survival (MFS). The lncRNA molecular landscape of the candidate feature was defined by using an RNA sequencing-specific negative binomial distribution differential expression analysis. Then, this radiogenomic biomarker was applied prospectively to a validation set (n = 42) to allow prediction of MFS and lncRNA expression by using quantitative polymerase chain reaction analysis. The quantitative MR imaging feature, enhancing rim fraction score, was predictive of MFS in the training set (P = .007). RNA sequencing analysis yielded an average of 55.7 × 10(6) reads per sample and identified 14 880 lncRNAs from a background of 189 883 transcripts per sample. Radiogenomic analysis allowed identification of three previously uncharacterized and five named lncRNAs significantly associated with high enhancing rim fraction, including Homeobox transcript antisense intergenic RNA (HOTAIR) (P < .05), a known predictor of poor MFS in patients with breast cancer. Independent validation confirmed the association of the enhancing rim fraction phenotype with both MFS (P = .002) and expression of four of the top five differentially expressed lncRNAs (P < .05), including HOTAIR. The enhancing rim fraction score, a quantitative DCE MR imaging lncRNA radiogenomic biomarker, is associated with early metastasis and expression of the known predictor of metastatic progression, HOTAIR.

Addition of shear-wave elastography during second-look MR imaging-directed breast US: effect on lesion detection and biopsy targeting.

To determine if adding shear-wave elastography (SWE) to second-look ultrasonography (US) after breast dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging helps find or target lesions seen on DCE MR images for US-guided biopsy. This HIPAA-compliant prospective study was approved by the institutional review board, and written informed consent was obtained from patients. From May 2011 to July 2012, 73 women with 96 Breast Imaging Reporting and Data System (BI-RADS) category 4 or 5 lesions after DCE MR imaging prospectively consented to undergo SWE during second-look US. If a lesion was not confidently seen with B-mode US, SWE during real-time scanning was performed to determine if SWE helped find or target lesions for US biopsy. A qualitative SWE six-point color scale was used to record the maximum elasticity in and around lesions. All lesions underwent US or DCE MR imaging-guided core biopsy. Median participant age was 52 years (range, 21-81 years). In 72 patients who underwent DCE MR imaging, 96 BI-RADS category 4 or 5 lesions were detected in 81 breasts. There were 29 (30%) malignancies (one malignancy was of nonbreast origin), 14 (15%) high-risk lesions, and 53 (55%) benign lesions. US revealed 22 cancers, and seven cancers were detected only with MR imaging. Real-time SWE helped find one lesion and target four lesions that were incompletely assessed with gray-scale US. These five lesions that were localized or targeted for biopsy were invasive cancers, representing 23% of the 22 malignancies detected with US. Real-time SWE added to second-look US after DCE MR imaging increased the detection rate of cancers and helped target cancers for US-guided biopsy.

Breast Cancer: Early Prediction of Response to Neoadjuvant Chemotherapy Using Parametric Response Maps for MR Imaging

To prospectively compare the performance of dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging using parametric response map (PRM) analysis with that using pharmacokinetic parameters (transfer constant [K(trans)], rate constant [kep ], and relative extravascular extracellular space [ve]) in the early prediction of pathologic responses to neoadjuvant chemotherapy (NAC) in breast cancer patients. The institutional review board approved this study; informed consent was obtained. Between August 2010 and December 2012, 48 women (mean age, 46.4 years; range, 29-65 years) with breast cancer were enrolled and treated with an anthracycline-taxane regimen. DCE MR imaging was performed before and after the first cycle of chemotherapy, and the pathologic response was assessed after surgery. Tumor size and volume, PRM characteristics, and pharmacokinetic parameters (K(trans), kep, and ve) on MR images were assessed and compared according to the pathologic responses by using the Fisher exact test or the independent-sample t test. Six of 48 (12%) patients showed pathologic complete response (CR) (pCR) and 42 (88%) showed nonpathologic CR (npCR). Thirty-eight (79%) patients showed a good response (Miller-Payne score of 3, 4, or 5), and 10 (21%) showed a minor response (Miller-Payne score of 1 or 2). The mean proportion of voxels with increased signal intensity (PRMSI+) in the pCR or good response group was significantly lower than that in the npCR or minor response group (14.0% ± 6.5 vs 40.7% ± 27.2, P < .001; 34.3% ± 26.4 vs 52.8% ± 24.9, P = .041). Area under the receiver operating characteristic curve for PRMSI+ in the pCR group was 0.770 (95% confidence interval: 0.626, 0.879), and that for the good response group was 0.716 (95% confidence interval: 0.567, 0.837). No difference in tumor size, tumor volume, or pharmacokinetic parameters was found between groups. PRM analysis of DCE MR images may enable the early identification of the pathologic response to NAC after the first cycle of chemotherapy, whereas pharmacokinetic parameters (K(trans), kep, and ve) do not.

Identification of Intrinsic Imaging Phenotypes for Breast Cancer Tumors: Preliminary Associations with Gene Expression Profiles

To present a method for identifying intrinsic imaging phenotypes in breast cancer tumors and to investigate their association with prognostic gene expression profiles. The authors retrospectively analyzed dynamic contrast material-enhanced (DCE) magnetic resonance (MR) images of the breast in 56 women (mean age, 55.6 years; age range, 37-74 years) diagnosed with estrogen receptor-positive breast cancer between 2005 and 2010. The study was approved by the institutional review board and compliant with HIPAA. The requirement to obtain informed consent was waived. Primary tumors were assayed with a validated gene expression assay that provides a score for the likelihood of recurrence. A multiparametric imaging phenotype vector was extracted for each tumor by using quantitative morphologic, kinetic, and spatial heterogeneity features. Multivariate linear regression was performed to test associations between DCE MR imaging features and recurrence likelihood. To identify intrinsic imaging phenotypes, hierarchical clustering was performed on the extracted feature vectors. Multivariate logistic regression was used to classify tumors at high versus low or medium risk of recurrence. To determine the additional value of intrinsic phenotypes, the phenotype category was tested as an additional variable. Receiver operating characteristic analysis and the area under the receiver operating characteristic curve (Az) were used to assess classification performance. There was a moderate correlation (r = 0.71, R(2) = 0.50, P < .001) between DCE MR imaging features and the recurrence score. DCE MR imaging features were predictive of recurrence risk as determined by the surrogate assay, with an Az of 0.77 (P < .01). Four dominant imaging phenotypes were detected, with two including only low- and medium-risk tumors. When the phenotype category was used as an additional variable, the Az increased to 0.82 (P < .01). Intrinsic imaging phenotypes exist for breast cancer tumors and correlate with recurrence likelihood as determined with gene expression profiling. These imaging biomarkers could ultimately help guide treatment decisions.

Changes in Primary Breast Cancer Heterogeneity May Augment Midtreatment MR Imaging Assessment of Response to Neoadjuvant Chemotherapy

To evaluate whether changes in magnetic resonance (MR) imaging heterogeneity may aid assessment for pathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) in primary breast cancer and to compare pCR with standard Response Evaluation Criteria in Solid Tumors response. Institutional review board approval, with waiver of informed consent, was obtained for this retrospective analysis of 36 consecutive female patients, with unilateral unifocal primary breast cancer larger than 2 cm in diameter who were receiving sequential anthracycline-taxane NACT between October 2008 and October 2012. T2- and T1-weighted dynamic contrast material-enhanced MR imaging was performed before, at midtreatment (after three cycles), and after NACT. Changes in tumor entropy (irregularity) and uniformity (gray-level distribution) were determined before and after MR image filtration (for different-sized features). Entropy and uniformity for pathologic complete responders and nonresponders were compared by using the Mann-Whitney U test and receiver operating characteristic analysis. With NACT, there was an increase in uniformity and a decrease in entropy on T2-weighted and contrast-enhanced subtracted T1-weighted MR images for all filters (uniformity: 23.45% and 22.62%; entropy: -19.15% and -19.26%, respectively). There were eight complete pathologic responders. An area under the curve of 0.84 for T2-weighted MR imaging entropy and uniformity (P = .004 and .003) and 0.66 for size (P = .183) for pCR was found, giving a sensitivity and specificity of 87.5% and 82.1% for entropy and 87.5% and 78.6% for uniformity compared with 50% and 82.1%, respectively, for tumor size change for association with pCR. Tumors become more homogeneous with treatment. An increase in T2-weighted MR imaging uniformity and a decrease in T2-weighted MR imaging entropy following NACT may provide an earlier indication of pCR than tumor size change.

The Effects of Applying Breast Compression in Dynamic Contrast Material–enhanced MR Imaging

To evaluate the effects of breast compression on breast cancer masses, contrast material enhancement of glandular tissue, and quality of magnetic resonance (MR) images in the identification and characterization of breast lesions. This was a HIPAA-compliant, institutional review board-approved retrospective study, with waiver of informed consent. Images from 300 MR imaging examinations in 149 women (mean age ± standard deviation, 51.5 years ± 10.9; age range, 22-76 years) were evaluated. The women underwent diagnostic MR imaging (no compression) and MR-guided biopsy (with compression) between June 2008 and February 2013. Breast compression was expressed as a percentage relative to the noncompressed breast. Percentage enhancement difference was calculated between noncompressed- and compressed-breast images obtained in early and delayed contrast-enhanced phases. Breast density, lesion type (mass vs non-masslike enhancement [NMLE]), lesion size, percentage compression, and kinetic curve type were evaluated. Linear regression, receiver operating characteristic (ROC) curve analysis, and κ test were performed. Mean percentage compression was 31.3% ± 9.2 (range, 5.8%-53.2%). Percentage enhancement was higher in noncompressed- versus compressed-breast studies in early (146% ± 66 vs 107% ± 42, respectively; P < .001) and delayed (158% ± 68 vs 107% ± 42, respectively; P = .1) phases. Among breast lesions, 12% (seven of 59) were significantly smaller when compressed, which led to underestimation of TNM classification (P < .001). Breast masses (n = 35) showed significantly higher early percentage enhancement (157% ± 71) than lesions with NMLE (n = 15, 120% ± 40; P = .02) and a percentage enhancement difference (47.5% ± 64 vs 17% ± 28, respectively; P = .023). Kinetic curve performance for identifying invasive cancer decreased after compression (area under ROC curve = 0.53 vs 0.71, respectively; P = .02). Breast compression resulted in complete loss of enhancement of nine of 210 lesions (4%). Breast compression during biopsy affected breast lesion detection, lesion size, and dynamic contrast-enhanced MR imaging interpretation and performance. Limiting the application of breast compression is recommended, except when clinically necessary.

Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study

To determine the feasibility of using a computer-aided diagnosis (CAD) system to differentiate among triple-negative breast cancer, estrogen receptor (ER)-positive cancer, human epidermal growth factor receptor type 2 (HER2)-positive cancer, and benign fibroadenoma lesions on dynamic contrast material-enhanced (DCE) magnetic resonance (MR) images. This is a retrospective study of prospectively acquired breast MR imaging data collected from an institutional review board-approved, HIPAA-compliant study between 2002 and 2007. Written informed consent was obtained from all patients. The authors collected DCE MR images from 65 women with 76 breast lesions who had been recruited into a larger study of breast MR imaging. The women had triple-negative (n = 21), ER-positive (n = 25), HER2-positive (n = 18), or fibroadenoma (n = 12) lesions. All lesions were classified as Breast Imaging Reporting and Data System category 4 or higher on the basis of previous imaging. Images were subject to quantitative feature extraction, feed-forward feature selection by means of linear discriminant analysis, and lesion classification by using a support vector machine classifier. The area under the receiver operating characteristic curve (Az) was calculated for each of five lesion classification tasks involving triple-negative breast cancers. For each pair-wise lesion type comparison, linear discriminant analysis helped identify the most discriminatory features, which in conjunction with a support vector machine classifier yielded an Az of 0.73 (95% confidence interval [CI]: 0.59, 0.87) for triple-negative cancer versus all non-triple-negative lesions, 0.74 (95% CI: 0.60, 0.88) for triple-negative cancer versus ER- and HER2-positive cancer, 0.77 (95% CI: 0.63, 0.91) for triple-negative versus ER-positive cancer, 0.74 (95% CI: 0.58, 0.89) for triple-negative versus HER2-positive cancer, and 0.97 (95% CI: 0.91, 1.00) for triple-negative cancer versus fibroadenoma. Triple-negative cancers possess certain characteristic features on DCE MR images that can be captured and quantified with CAD, enabling good discrimination of triple-negative cancers from non-triple-negative cancers, as well as between triple-negative cancers and benign fibroadenomas. Such CAD algorithms may provide added diagnostic benefit in identifying the highly aggressive triple-negative cancer phenotype with DCE MR imaging in high-risk women.

Prediction of Esophageal Varices in Patients with Cirrhosis: Usefulness of Three-dimensional MR Elastography with Echo-planar Imaging Technique

To determine the diagnostic performance of magnetic resonance (MR) elastography in comparison to spleen length and dynamic contrast material-enhanced (DCE) MR imaging in association with esophageal varices in patients with liver cirrhosis by using endoscopy as the reference standard. This retrospective study received institutional review board approval, and informed consent was waived. One hundred thirty-nine patients with liver cirrhosis who underwent liver DCE MR imaging, including MR elastography, were included. Hepatic stiffness (HS) and spleen stiffness (SS) values assessed with MR elastography, as well as spleen length, were correlated with the presence of esophageal varices and high-risk varices by using Spearman correlation analysis. The diagnostic performance of MR elastography was compared with that of DCE MR imaging and combined assessment of MR elastography and DCE MR imaging by using receiver operating characteristic analysis. MR elastography reproducibility was assessed prospectively, with informed consent, in another 15 patients by using intraclass correlation coefficients. There were significant positive linear correlations between HS, SS, and spleen length and the grade of esophageal varices (r = 0.46, r = 0.48, and r = 0.36, respectively; all P < .0001). HS and SS values (>4.81 kPa and >7.60 kPa, respectively) showed better performance than did spleen length in the association with esophageal varices (P = .0306 and P = .0064, respectively). Diagnostic performance of HS and SS in predicting high-risk varices was comparable to that of DCE MR imaging (P = .1282 and P = .1371, respectively). When MR elastography and DCE MR imaging were combined, sensitivity improved significantly (P = .0004). MR elastography was highly reproducible (intraclass correlation coefficient > 0.9). HS and SS are associated with esophageal varices and showed better performance than did spleen length in assessing the presence of esophageal varices. MR elastography is comparable to DCE MR imaging in predicting the presence of esophageal varices and high-risk varices, but, when assessed in combination, sensitivity is higher.

Triple-Negative and Non–Triple-Negative Invasive Breast Cancer: Association between MR and Fluorine 18 Fluorodeoxyglucose PET Imaging

Purpose To assess the relationship between parameters measured on dynamic contrast material–enhanced (DCE) magnetic resonance (MR) imaging and fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in primary invasive breast cancer. Materials and Methods This HIPAA-compliant study was a retrospective review of medical records and therefore approved by the institutional review board without the requirement for informed consent. Patients with a diagnosis of invasive breast cancer from January 2005 through December 2009 who underwent both DCE MR imaging and FDG PET/CT before treatment initiation were retrospectively identified. Fractional volumes were measured for ranges of signal enhancement ratio (SER) values from DCE MR imaging data and compared with maximum standardized uptake values (SUVmax) from FDG PET/CT data. Linear regression analysis was performed to clarify the relationship between SER and SUVmax, adjusting for tumor size, pathologic grade, and receptor status. Results Analyzed were 117 invasive breast cancers in 117 patients. Overall, a higher percentage of high washout kinetics was positively associated with SUVmax (1.57% increase in SUVmax per 1% increase in high washout; P = .020), and a higher percentage of low plateau kinetics was negatively associated with SUVmax (1.19% decrease in SUVmax per 1% increase in low plateau; P = .003). These relationships were strongest among triple-negative (TN) tumors (4.34% increase in SUVmax per 1% increase in high washout and 2.65% decrease in SUVmax per 1% increase in low plateau; P = .018 and .004, respectively). Conclusion In invasive breast carcinoma, there is a positive relationship between the percentage of high washout and SUVmax and a negative relationship between the percentage of low plateau and SUVmax. These results are stronger in TN tumors. © RSNA, 2013 Supplemental material: S1

Effect of Iodinated Contrast Media on Renal Function Evaluated with Dynamic Three-dimensional MR Renography

To assess the hemodynamic effect of iodinated contrast media (CM) on glomerular filtration rate (GFR) by using dynamic three-dimensional magnetic resonance (MR) renography in a rabbit model. This study was approved by the university animal care and use committee. Twelve healthy male New Zealand rabbits (body mass range, 2.5-3.0 kg) were included. Two of them were sacrificed before MR examination to obtain renal histologic samples as controls. The other ten rabbits completed 4-minute dynamic contrast material-enhanced MR imaging 24 hours before and 20 minutes after intravenous injection of iopamidol (370 mg of iodine per milliliter) at a dose of 6 mL per kilogram of body weight. Blood volume (V(B)), GFR, and tubule volume (V(E)) of the renal cortex were determined with a two-compartment kinetic model. Maximum upslope (K(m)), peak concentration (P(c)), and initial 60-second area under the curve (IAUC) of the whole kidney renogram curve were measured with semiquantitative analysis. The self-control data were compared by using the Student paired t test. Iopamidol significantly decreased cortical V(B) (mean, 42.53% ± 10.16 [standard deviation] before CM administration vs 27.23% ± 16.13 after CM administration; P < .01), V(E) (mean, 22.40% ± 11.69 before CM administration vs 11.51% ± 6.58 after CM administration; P < .01), and GFR (mean, 31.92 mL/100 g per minute ± 12.52 before CM administration vs 21.48 mL/100 g per minute ± 10.02 after CM administration; P < .01). Results of whole-kidney renogram analysis showed a decrease in K(m), P(c), and IAUC caused by iopamidol administration. High-dose iopamidol resulted in a marked decrease in renal function, which could be detected at dynamic three-dimensional MR renography.

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.

Triple-Negative and Non–Triple-Negative Invasive Breast Cancer: Association between MR and Fluorine 18 Fluorodeoxyglucose PET Imaging

To assess the relationship between parameters measured on dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging and fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in primary invasive breast cancer. This HIPAA-compliant study was a retrospective review of medical records and therefore approved by the institutional review board without the requirement for informed consent. Patients with a diagnosis of invasive breast cancer from January 2005 through December 2009 who underwent both DCE MR imaging and FDG PET/CT before treatment initiation were retrospectively identified. Fractional volumes were measured for ranges of signal enhancement ratio (SER) values from DCE MR imaging data and compared with maximum standardized uptake values (SUVmax) from FDG PET/CT data. Linear regression analysis was performed to clarify the relationship between SER and SUVmax, adjusting for tumor size, pathologic grade, and receptor status. Analyzed were 117 invasive breast cancers in 117 patients. Overall, a higher percentage of high washout kinetics was positively associated with SUVmax (1.57% increase in SUVmax per 1% increase in high washout; P = .020), and a higher percentage of low plateau kinetics was negatively associated with SUVmax (1.19% decrease in SUVmax per 1% increase in low plateau; P = .003). These relationships were strongest among triple-negative (TN) tumors (4.34% increase in SUVmax per 1% increase in high washout and 2.65% decrease in SUVmax per 1% increase in low plateau; P = .018 and .004, respectively). In invasive breast carcinoma, there is a positive relationship between the percentage of high washout and SUVmax and a negative relationship between the percentage of low plateau and SUVmax. These results are stronger in TN tumors. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.13130058/-/DC1.

Ovarian Carcinoma: Quantitative Biexponential MR Imaging Relaxometry Reveals the Dynamic Recruitment of Ferritin-expressing Fibroblasts to the Angiogenic Rim of Tumors

To quantitatively monitor the dynamic perivascular recruitment of ferritin heavy chain (FHC)-overexpressing fibroblasts to ovarian carcinoma xenografts by using R2 mapping and biexponential magnetic resonance (MR) relaxometry. In vivo studies of female mice were approved by the institutional animal care and use committee. In vitro analysis included MR-based R2 relaxation measurements of monkey kidney cell line (CV1) fibroblasts that overexpress FHC, followed by inductively coupled plasma mass spectrometry to assess cellular iron content. For in vivo analysis, CV1-FHC fibroblasts were either mixed with fluorescent human ovarian carcinoma cells before subcutaneous implantation (coinjection) or injected intraperitoneally 4 days after the cancer cells were injected (remote recruitment). Dynamic changes in tumor R2 were used to derive CV1-FHC cell fraction in both models. In coinjection tumors, dynamic contrast material-enhanced MR imaging was used to measure tumor fractional blood volume. Whole-body fluorescence imaging and immunohistochemical staining were performed to validate MR results. One-way repeated measures analysis of variance was used to assess MR and fluorescence imaging results and tumor volume, and one-way analysis of variance was used to assess spectrometric results, fractional blood volume, and immunohistochemical evaluation. CV1-FHC fibroblasts (vs CV1 fibroblasts) showed enhanced iron uptake (1.8 mmol ± 0.5 × 10(-8) vs 0.9 mmol ± 0.5 × 10(-8); P < .05), retention (1.6 mmol ± 0.5 × 10(-8) vs 0.5 mmol ± 0.5 × 10(-8), P < .05), and cell density-dependent R2 contrast. R2 mapping in vivo revealed preferential recruitment of CV1-FHC cells to the tumor rim in both models. Measurement of fractional blood volume was similar in all tumors (2.6 AU ± 0.5 × 10(-3) for CV1, 2.3 AU ± 0.3 × 10(-3) for CV1-FHC, 2.9 ± 0.3 × 10(-3) for CV1-FHC-ferric citrate). Dynamic changes in CV1-FHC cell fraction determined at MR relaxometry in both models were confirmed at immunohistochemical analysis. FHC overexpression, when combined with R2 mapping and MR relaxometry, enabled in vivo detection of the dynamic recruitment of exogenously administered fibroblasts to the vasculature of solid tumors.

Multiparametric Prostate MR Imaging with T2-weighted, Diffusion-weighted, and Dynamic Contrast-enhanced Sequences: Are All Pulse Sequences Necessary to Detect Locally Recurrent Prostate Cancer after Radiation Therapy?

To compare diagnostic accuracy of T2-weighted magnetic resonance (MR) imaging with that of multiparametric (MP) MR imaging combining T2-weighted imaging with diffusion-weighted (DW) MR imaging, dynamic contrast material-enhanced (DCE) MR imaging, or both in the detection of locally recurrent prostate cancer (PCa) after radiation therapy (RT). This retrospective HIPAA-compliant study was approved by the institutional review board; informed consent was waived. Fifty-three men (median age, 70 years) suspected of having post-RT recurrence of PCa underwent MP MR imaging, including DW and DCE sequences, within 6 months after biopsy. Two readers independently evaluated the likelihood of PCa with a five-point scale for T2-weighted imaging alone, T2-weighted imaging with DW imaging, T2-weighted imaging with DCE imaging, and T2-weighted imaging with DW and DCE imaging, with at least a 4-week interval between evaluations. Areas under the receiver operating characteristic curve (AUC) were calculated. Interreader agreement was assessed, and quantitative parameters (apparent diffusion coefficient [ADC], volume transfer constant [K(trans)], and rate constant [k(ep)]) were assessed at sextant- and patient-based levels with generalized estimating equations and the Wilcoxon rank sum test, respectively. At biopsy, recurrence was present in 35 (66%) of 53 patients. In detection of recurrent PCa, T2-weighted imaging with DW imaging yielded higher AUCs (reader 1, 0.79-0.86; reader 2, 0.75-0.81) than T2-weighted imaging alone (reader 1, 0.63-0.67; reader 2, 0.46-0.49 [P ≤ .014 for all]). DCE sequences did not contribute significant incremental value to T2-weighted imaging with DW imaging (reader 1, P > .99; reader 2, P = .35). Interreader agreement was higher for combinations of MP MR imaging than for T2-weighted imaging alone (κ = 0.34-0.63 vs κ = 0.17-0.20). Medians of quantitative parameters differed significantly (P < .0001 to P = .0233) between benign tissue and PCa (ADC, 1.64 × 10(-3) mm(2)/sec vs 1.13 × 10(-3) mm(2)/sec; K(trans), 0.16 min(-1) vs 0.33 min(-1); k(ep), 0.36 min(-1) vs 0.62 min(-1)). MP MR imaging has greater accuracy in the detection of recurrent PCa after RT than T2-weighted imaging alone, with no additional benefit if DCE is added to T2-weighted imaging and DW imaging.

Seminal Vesicle Invasion in Prostate Cancer: Evaluation by Using Multiparametric Endorectal MR Imaging

To retrospectively evaluate the diagnostic performance of multiparametric endorectal magnetic resonance (MR) imaging, including T2-weighted, diffusion-weighted (DW), and dynamic contrast material-enhanced (DCE) MR techniques, for the diagnosis of seminal vesicle invasion (SVI) and to determine the incremental value of DW MR and DCE MR images. This retrospective HIPAA-compliant study was approved by the institutional review board, with a waiver of informed consent. The study included 131 patients (mean age, 68 years; range, 43-75 years) who underwent endorectal MR imaging before radical prostatectomy between January 2007 and April 2010. Two radiologists (A: experienced, B: less experienced) estimated the likelihood of SVI by using a five-point ordinal scale in three image-viewing settings: T2-weighted images alone; T2-weighted and DW MR images; and T2-weighted, DW MR, and DCE MR images. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated. Confidence intervals estimated with bootstrapping and the McNemar test or Fisher exact test were used to compare sensitivity, specificity, positive predictive value, and negative predictive value. Of the 131 patients, 23 (17.6%) had SVI identified after surgery. Review of T2-weighted MR images alone resulted in high specificity (93.1% and 93.6%, for radiologists A and B, respectively) and high negative predictive value (94.8% and 94.0%) but moderate sensitivity (59% and 52%) and positive predictive value (52% and 50%). Review of T2-weighted and DW MR images significantly improved specificity (96.6% [P = .02] and 98.3% [P = .003]) and positive predictive value (70% [P < .05] and 79% [P < .05]) without significantly improving AUC. Additional review of DCE MR images did not yield further incremental improvement. Additional review of DW MR images improves specificity and positive predictive value in SVI detection compared with reviewing T2-weighted images alone. Addition of DCE MR images to this combination, however, does not provide incremental value for diagnosis of SVI.

A Method to Quantify Breast MRI for Predicting Tumor Invasion in Patients with Preoperative Biopsy- Proven Ductal Carcinoma in Situ (DCIS)

Dynamic contrast material-enhanced magnetic resonance imaging (DCE-MRI) can visualize alterations of vascularity and capillary permeability of breast lesions and enables us to identify breast lesions differentially from normal tissue (1-3). Owing to this characteristic of DCE-MRI, it has been widely used as INTRODUCTION �Received; June 30, 2012�Revised; March 22, 2013 �Accepted; March 22, 2013 Corresponding author : Sung Hun Kim, M.D. Department of Radiology, Seoul St. Mary’ Hospital, College of Medicine, The Catholic University of Korea, 505 Banpo-dong, Seocho-gu, Seoul 137-701, Korea. Tel. 82-2-2258-6250, Fax. 82-2-599-6771 E-mail : rad-ksh@catholic.ac.kr A Method to Quantify Breast MRI for Predicting Tumor Invasion in Patients with Preoperative BiopsyProven Ductal Carcinoma in Situ (DCIS)