Contrast-enhanced magnetic resonance imaging of the breast: the value of pharmacokinetic parameters derived from fast dynamic imaging during initial enhancement in classifying lesions. Eur Radiol. 2008;18:1123-1133. [PMID: 18270714 PMCID: PMC2373858 DOI: 10.1007/s00330-008-0870-8]

High-Temporal/High-Spatial Resolution Breast Magnetic Resonance Imaging Improves Diagnostic Accuracy Compared With Standard Breast Magnetic Resonance Imaging in Patients With High Background Parenchymal Enhancement

PURPOSE

To compare breast magnetic resonance imaging (MRI) diagnostic performance using a standard high-spatial resolution protocol versus a simultaneous high-temporal/high-spatial resolution (HTHS) protocol in women with high levels of background parenchymal enhancement (BPE).

MATERIALS AND METHODS

We conducted a retrospective study of contrast-enhanced breast MRIs performed at our institution before and after the introduction of the HTHS protocol. We compared diagnostic performance of the HTHS and standard protocol by comparing cancer detection rate (CDR) and positive predictive value of biopsy (PPV3) among women with high BPE (ie, marked or moderate).

RESULTS

Among women with high BPE, the HTHS protocol demonstrated increased CDR (23.6 per 1,000 patients v 7.9 per 1,000 patients; P = 0. 013) and increased PPV3 (16.0% v 6.3%; P = .021) compared with the standard protocol. This corresponded to a 9.8% (95% CI, 1.29 to 18.3) decrease in the proportion of unnecessary biopsies among high-BPE patients and an additional cancer yield of 15.7 per 1,000 patients (95% CI, 1.3 to 18.3).

CONCLUSION

Among women with high BPE, HTHS MRI improved diagnostic performance, leading to an additional cancer yield of 15.7 cancers per 1,000 women and concomitantly decreasing unnecessary biopsies by 9.8%. A multisite prospective trial is warranted to confirm these findings and to pave the way for more widespread clinical implementation.

Ktrans Calculation Using Reference Method Corrected Native T10 for Breast Cancer Diagnosis

Purpose

The objective of the study is to use multiple tube phantoms to generate correction factor at different spatial locations for each breast coil cuff to correct the native T10 value in the corresponding spatial location of the breast lesion. The corrected T10 value was used to compute Ktrans and analyze its diagnostic accuracy in the classification of target condition, i.e., breast tumors into malignant and benign.

Materials and Methods

Both in vitro phantom study (external reference) and patient's studies were acquired on simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) Biograph molecular magnetic resonance (mMR) system using 4 channel mMR breast coil. The spatial correction factors derived using multiple tube phantom were used for a retrospective analysis of dynamic contrast-enhanced (DCE) MRI data of 39 patients with a mean age of 50 years (31-77 years) having 51 enhancing breast lesions.

Results

Corrected and non-corrected receiver operating characteristic (ROC) curve analysis revealed a mean Ktrans value of 0.64 min-1 and 0.60 min-1, respectively. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy for non-corrected data were 86.21%, 81.82%, 86.20%, 81.81%, and 84.31%, respectively, and for corrected data were 93.10%, 86.36%, 90%, 90.47%, and 90.20% respectively. The area under curve (AUC) of corrected data was improved to 0.959 (95% confidence interval [CI] 0.862-0.994) from 0.824 (95% CI 0.694-0.918) of non-corrected data, and for NPV, it was improved to 90.47% from 81.81%, respectively.

Conclusion

T10 values were normalized using multiple tube phantom which was used for computation of Ktrans. We found significant improvement in the diagnostic accuracy of corrected Ktrans values that results in better characterization of breast lesions.

The Influence of Data-Driven Compressed Sensing Reconstruction on Quantitative Pharmacokinetic Analysis in Breast DCE MRI

Radial acquisition with MOCCO reconstruction has been previously proposed for high spatial and temporal resolution breast DCE imaging. In this work, we characterize MOCCO across a wide range of temporal contrast enhancement in a digital reference object (DRO). Time-resolved radial data was simulated using a DRO with lesions in different PK parameters. The under sampled data were reconstructed at 5 s temporal resolution using the data-driven low-rank temporal model for MOCCO, compressed sensing with temporal total variation (CS-TV) and more conventional low-rank reconstruction (PCB). Our results demonstrated that MOCCO was able to recover curves with K^trans values ranging from 0.01 to 0.8 min⁻¹ and fixed V_e = 0.3, where the fitted results are within a 10% bias error range. MOCCO reconstruction showed less impact on the selection of different temporal models than conventional low-rank reconstruction and the greater error was observed with PCB. CS-TV showed overall underestimation in both K^trans and V_e. For the Monte-Carlo simulations, MOCCO was found to provide the most accurate reconstruction results for curves with intermediate lesion kinetics in the presence of noise. Initial in vivo experiences are reported in one patient volunteer. Overall, MOCCO was able to provide reconstructed time-series data that resulted in a more accurate measurement of PK parameters than PCB and CS-TV.

Improved value of whole-lesion histogram analysis on DCE parametric maps for diagnosing small breast cancer (≤ 1 cm)

OBJECTIVES

To determine if whole-lesion histogram analysis on dynamic contrast-enhanced (DCE) parametric maps help to improve the diagnostic accuracy of small suspicious breast lesions (≤ 1 cm).

METHODS

This retrospective study included 99 female patients with 114 lesions (40 malignant and 74 benign lesions) suspicious on magnetic resonance imaging (MRI).Two radiologists reviewed all lesions and descripted the morphologic and kinetic characteristics according to BI-RADS by consensus. Whole lesions were segmented on DCE parametric maps (washin and washout), and quantitative histogram features were extracted. Univariate analysis and multivariate logistic regression analysis with forward stepwise covariate selection were performed to identify significant variables. Diagnostic performance was assessed and compared with that of qualitative BI-RADS assessment and quantitative histogram analysis by ROC analysis.

RESULTS

For malignancy defined as a washout or plateau pattern, the qualitative kinetic pattern showed a significant difference between the two groups (p = 0.023), yielding an AUC of 0.603 (95% confidence interval [CI]: 0.507, 0.694). The mean and median of washout were independent quantitative predictors of malignancy (p = 0.002, 0.010), achieving an AUC of 0.796 (95% CI: 0. 709, 0.865). The AUC of the quantitative model was better than that of the qualitative model (p < 0.001).

CONCLUSIONS

Compared with the qualitative BI-RADS assessment, quantitative whole-lesion histogram analysis on DCE parametric maps was better to discriminate between small benign and malignant breast lesions (≤ 1 cm) initially defined as suspicious on DCE-MRI.

KEY POINTS

• For malignancy defined as a washout or plateau, the kinetic pattern may provide information to diagnose small breast cancer. • The mean and median of washout map were significantly lower for small malignant breast lesions than for benign lesions. • Quantitative histogram analysis on MRI parametric maps improves diagnostic accuracy for small breast cancer, which may obviate unnecessary biopsy.

Use of Multiple-Tube Phantom: A Method to Globally Correct Native T1 Relaxation Time Inhomogeneity in Dedicated Molecular Magnetic Resonance Breast Coil

Background:

Native T1 relaxation time (T1₀) presents an important prerequisite to reliably quantify pharmacokinetic parameter like K^trans (volume transfer constant). Native T1 value can be varied because of the inhomogeneity in the breast coil, thus influencing the K^trans measurement.

Purpose:

The current study aims to design and use a phantom with multiple tubes for both breast cuffs to assess native T1 inhomogeneity across the dedicated molecular magnetic resonance (mMR) breast coil and adopt corrective method to spatially normalize T1 values to improve homogeneity.

Materials and Methods:

Two phantoms with multiple tubes (19 tubes) specially designed and filled with contrast medium with known T1 value were placed in each mMR breast coil cuff. Native T1 at various spatial locations was calculated applying dual flip angle sequence. Correction factors were derived at various spatial locations as a function of deviation of the native T1 value from phantom and applied to correct the native T1 relaxation time.

Results:

A statistically significant difference between native T1 values of the right and left anterior (P = 0.0095), middle (P = 0.0081), and posterior (P = 0.0004) parts of the breast coil. No significant difference was seen in the corrected T1 values between anterior (P = 0.402), middle (P = 0.305), and posterior (P = 0.349) aspects of both sides of the breast coil.

Conclusion:

Inhomogeneity in the native T1 value exists in dedicated mMR breast coil, and significant improvement can be achieved using specially designed external phantom with multiple tubes.

Feasibility study of dual parametric 2D histogram analysis of breast lesions with dynamic contrast-enhanced and diffusion-weighted MRI

Background

This study aimed to investigate the diagnostic value of a dual-parametric 2D histogram classification method for breast lesions.

Methods

This study included 116 patients with 72 malignant and 44 benign breast lesions who underwent CAIPIRINHA-Dixon-TWIST-VIBE dynamic contrast-enhanced (CDT-VIBE DCE) and readout-segmented diffusion-weighted magnetic resonance examination. The volume of interest (VOI), which encompassed the entire lesion, was segmented from the last phase of DCE images. For each VOI, a 1D histogram analysis (mean, median, 10th percentile, 90th percentile, kurtosis and skewness) was performed on apparent diffusion coefficient (ADC) and volume transfer constant (Ktrans) maps; a 2D histogram image (Ktrans-ADC) was generated from the pixelwise aligned maps, and its kurtosis and skewness were calculated. Each parameter was correlated with pathological results using the Mann–Whitney test and receiver operating characteristic curve analysis.

Results

For the Ktrans histogram, the area under the curve (AUC) of the mean, median, 90th percentile and kurtosis had statistically diagnostic values (mean: 0.760; median: 0.661; 90th percentile: 0.781; and kurtosis: 0.620). For the ADC histogram, the AUC of the mean, median, 10th percentile, skewness and kurtosis had statistically diagnostic values (mean: 0.661; median: 0.677; 10th percentile: 0.656; skewness: 0.664; and kurtosis: 0.620). For the 2D Ktrans-ADC histogram, the skewness and kurtosis had statistically higher diagnostic values (skewness: 0.831, kurtosis: 0.828) than those of the 1D histogram (all P < 0.05).

Conclusions

The dual-parametric 2D histogram analysis revealed better diagnostic accuracy for breast lesions than single parametric histogram analysis of either Ktrans or ADC maps.

Novel High Spatiotemporal Resolution Versus Standard-of-Care Dynamic Contrast-Enhanced Breast MRI: Comparison of Image Quality

OBJECTIVE

Currently, dynamic contrast-enhanced (DCE) breast magnetic resonance imaging (MRI) prioritizes spatial resolution over temporal resolution given the limitations of acquisition techniques. The purpose of our intrapatient study was to assess the ability of a novel high spatial and high temporal resolution DCE breast MRI method to maintain image quality compared with the clinical standard-of-care (SOC) MRI.

MATERIALS AND METHODS

Thirty patients, each demonstrating a focal area of enhancement (29 benign, 1 cancer) on their SOC MRI, consented to undergo a research DCE breast MRI on a second date. For the research DCE MRI, a method (DIfferential Subsampling with Cartesian Ordering [DISCO]) using pseudorandom k-space sampling, view sharing reconstruction, 2-point Dixon fat-water separation, and parallel imaging was used to produce images with an effective temporal resolution 6 times faster than the SOC MRI (27 vs 168 seconds, respectively). Both the SOC and DISCO MRI scans were acquired with matching spatial resolutions of 0.8 × 0.8 × 1.6 mm. Image quality (distortion/artifacts, resolution, fat suppression, lesion conspicuity, perceived signal-to-noise ratio, and overall image quality) was scored by 3 radiologists in a blinded reader study.

RESULTS

Differences in image quality scores between the DISCO and SOC images were all less than 0.8 on a 10-point scale, and both methods were assessed as providing diagnostic image quality in all cases. DISCO images with the same high spatial resolution, but 6 times the effective temporal resolution as the SOC MRI scans, were produced, yielding 20 postcontrast time points with DISCO compared with 3 for the SOC MRI, over the same total time interval.

CONCLUSIONS

DISCO provided comparable image quality compared with the SOC MRI, while also providing 6 times faster effective temporal resolution and the same high spatial resolution.

TumourMetrics: a comprehensive clinical solution for the standardization of DCE-MRI analysis in research and routine use

Background

A reliable analysis methodology is needed to provide valuable imaging biomarkers for clinical trials, with particular regards to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) application using pharmacokinetic (PK) model analysis. In order to address this scientific challenge, we provided a comprehensive analysis solution that could overcome the impediments to clinical research and routine use.

Methods

TumourMetrics has been designed to meet the Quantitative Imaging Biomarkers Alliance (QIBA) v.1.0 profile. The quality performance was assessed using the QIBA test data and our customizable numeric phantom. The analysis workflow is made customizable to facilitate standardization of optimized protocol across centers.

Results

Our quantification workflow estimated the PK model parameters accurately. The method is robust, almost fully automatic and allows a direct integration of the results into the diagnostic workflow.

Conclusions

The analysis is easy-to-use and accessible for routine implementation of DCE-MRI into clinical practice.

Time to enhancement derived from ultrafast breast MRI as a novel parameter to discriminate benign from malignant breast lesions

OBJECTIVES

To investigate time to enhancement (TTE) as novel dynamic parameter for lesion classification in breast magnetic resonance imaging (MRI).

METHODS

In this retrospective study, 157 women with 195 enhancing abnormalities (99 malignant and 96 benign) were included. All patients underwent a bi-temporal MRI protocol that included ultrafast time-resolved angiography with stochastic trajectory (TWIST) acquisitions (1.0×0.9×2.5mm, temporal resolution 4.32s), during the inflow of contrast agent. TTE derived from TWIST series and relative enhancement versus time curve type derived from volumetric interpolated breath-hold examination (VIBE) series were assessed and combined with basic morphological information to differentiate benign from malignant lesions. Receiver operating characteristic analysis and kappa statistics were applied.

RESULTS

TTE had a significantly better discriminative ability than curve type (p<0.001 and p=0.026 for reader 1 and 2, respectively). Including morphology, sensitivity of TWIST and VIBE assessment was equivalent (p=0.549 and p=0.344, respectively). Specificity and diagnostic accuracy were significantly higher for TWIST than for VIBE assessment (p<0.001). Inter-reader agreement in differentiating malignant from benign lesions was almost perfect for TWIST evaluation (κ=0.86) and substantial for conventional assessment (κ=0.75).

CONCLUSIONS

TTE derived from ultrafast TWIST acquisitions is a valuable parameter that allows robust differentiation between malignant and benign breast lesions with high accuracy.

Role of pharmacokinetic parameters derived with high temporal resolution DCE MRI using simultaneous PET/MRI system in breast cancer: A feasibility study

PURPOSE

To evaluate the reliability of pharmacokinetic parameters like K^trans, Kep and v_e derived through DCE MRI breast protocol using 3T Simultaneous PET/MRI (3Tesla Positron Emission Tomography/Magnetic Resonance Imaging) system in distinguishing benign and malignant lesions.

MATERIALS AND METHODS

High temporal resolution DCE (Dynamic Contrast Enhancement) MRI performed as routine breast MRI for diagnosis or as a part of PET/MRI for cancer staging using a 3T simultaneous PET/MRI system in 98 women having 109 breast lesions were analyzed for calculation of pharmacokinetic parameters (K^trans, v_e, and Kep) at 60s time point using an in-house developed computation scheme.

RESULTS

Receiver operating characteristic (ROC) curve analysis revealed a cut off value for K^trans, Kep, v_e as 0.50, 2.59, 0.15 respectively which reliably distinguished benign and malignant breast lesions. Data analysis revealed an overall accuracy of 94.50%, 79.82% and 87.16% for K^trans, Kep, v_e respectively. Introduction of native T1 normalization with an externally placed phantom showed a higher accuracy (94.50%) than without native T1 normalization (93.50%) with an increase in specificity of 87% vs 84%.

CONCLUSION

Overall the results indicate that reliable measurement of pharmacokinetic parameters with reduced acquisition time is feasible in a 3TMRI embedded PET/MRI system with reasonable accuracy and application may be extended to exploit the potential of simultaneous PET/MRI in further work on breast cancer.

Predictive model for contrast-enhanced ultrasound of the breast: Is it feasible in malignant risk assessment of breast imaging reporting and data system 4 lesions?

AIM: To build and evaluate predictive models for contrast-enhanced ultrasound (CEUS) of the breast to distinguish between benign and malignant lesions.

METHODS: A total of 235 breast imaging reporting and data system (BI-RADS) 4 solid breast lesions were imaged via CEUS before core needle biopsy or surgical resection. CEUS results were analyzed on 10 enhancing patterns to evaluate diagnostic performance of three benign and three malignant CEUS models, with pathological results used as the gold standard. A logistic regression model was developed basing on the CEUS results, and then evaluated with receiver operating curve (ROC).

RESULTS: Except in cases of enhanced homogeneity, the rest of the 9 enhancement appearances were statistically significant (P < 0.05). These 9 enhancement patterns were selected in the final step of the logistic regression analysis, with diagnostic sensitivity and specificity of 84.4% and 82.7%, respectively, and the area under the ROC curve of 0.911. Diagnostic sensitivity, specificity, and accuracy of the malignant vs benign CEUS models were 84.38%, 87.77%, 86.38% and 86.46%, 81.29% and 83.40%, respectively.

CONCLUSION: The breast CEUS models can predict risk of malignant breast lesions more accurately, decrease false-positive biopsy, and provide accurate BI-RADS classification.

Effect of Radiofrequency Transmit Field Correction on Quantitative Dynamic Contrast-enhanced MR Imaging of the Breast at 3.0 T

PURPOSE

To investigate the effects of radiofrequency transmit field (B1(+)) correction on (a) the measured T1 relaxation times of normal breast tissue and malignant lesions and (b) the pharmacokinetically derived parameters of malignant breast lesions at 3 T.

MATERIALS AND METHODS

Ethics approval and informed consent were obtained. Between May 2013 and January 2014, 30 women (median age, 58 years; range, 32-83 years) with invasive ductal carcinoma of at least 10 mm were recruited to undergo dynamic contrast material-enhanced magnetic resonance (MR) imaging before surgery. B1(+) and T1 mapping sequences were performed to determine the effect of B1(+) correction on the native tissue relaxation time (T10) of fat, parenchyma, and malignant lesions in both breasts. Pharmacokinetic parameters were calculated before and after correction for B1(+) variations. Results were correlated with histologic grade by using the Kruskal-Wallis test.

RESULTS

Measurements showed a mean 37% flip angle difference between the right and left breast, which resulted in a 61% T10 difference in fat and a 41.5% difference in parenchyma between the two breasts. The T1 of lesions in the right breast increased by 58%, whereas that of lesions in the left breast decreased by 30% after B1(+) correction. The whole-tumor transendothelial permeability across the vascular compartment(K(trans)) of lesions in the right breast decreased by 41%, and that of lesions in the left breast increased by 46% after correction. A systematic increase in K(trans) was observed, with significant differences found across the histologic grades (P < .001). The effect size of B1(+) correction on K(trans) calculation was large for lesions in the right breast and moderate for lesions in the left breast (Cohen effect size, d = 0.86 and d = 0.59, respectively).

CONCLUSION

B1(+) correction demonstrates a substantial effect on the results of quantitative dynamic contrast-enhanced analysis of breast tissue at 3 T, which propagates into the pharmacokinetic analysis of tumors that is dependent on whether the tumor is located in the right or left breast.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Utilization of magnetic resonance imaging in breast cancer screening

Early detection of malignancy through breast cancer screening has contributed significantly to the decline in cancer-related mortality. [...]

Magnetic resonance imaging using gadolinium-based contrast agents

The purpose of this article was to review the basic properties of available gadolinium-based magnetic resonance contrast agents, discuss their fundamental differences, and explore common and evolving applications of gadolinium-based magnetic resonance contrast throughout the body excluding the central nervous system. A more specific aim of this article was to explore novel uses of these gadolinium-based contrast agents and applications where a particular agent has been demonstrated to behave differently or be better suited for certain applications than the other contrast agents in this class.

Is there any correlation between model-based perfusion parameters and model-free parameters of time-signal intensity curve on dynamic contrast enhanced MRI in breast cancer patients?

OBJECTIVE

To find out any correlation between dynamic contrast-enhanced (DCE) model-based parameters and model-free parameters, and evaluate correlations between perfusion parameters with histologic prognostic factors.

METHODS

Model-based parameters (Ktrans, Kep and Ve) of 102 invasive ductal carcinomas were obtained using DCE-MRI and post-processing software. Correlations between model-based and model-free parameters and between perfusion parameters and histologic prognostic factors were analysed.

RESULTS

Mean Kep was significantly higher in cancers showing initial rapid enhancement (P = 0.002) and a delayed washout pattern (P = 0.001). Ve was significantly lower in cancers showing a delayed washout pattern (P = 0.015). Kep significantly correlated with time to peak enhancement (TTP) (ρ = -0.33, P < 0.001) and washout slope (ρ = 0.39, P = 0.002). Ve was significantly correlated with TTP (ρ = 0.33, P = 0.002). Mean Kep was higher in tumours with high nuclear grade (P = 0.017). Mean Ve was lower in tumours with high histologic grade (P = 0.005) and in tumours with negative oestrogen receptor status (P = 0.047). TTP was shorter in tumours with negative oestrogen receptor status (P = 0.037).

CONCLUSIONS

We could acquire general information about the tumour vascular physiology, interstitial space volume and pathologic prognostic factors by analyzing time-signal intensity curve without a complicated acquisition process for the model-based parameters.

KEY POINTS

• Kep mainly affected the initial and delayed curve pattern in time-signal intensity curve. • There is significant correlation between model-based and model-free parameters. • We acquired information about tumour vascular physiology, interstitial space volume and prognostic factors.

Role of quantitative pharmacokinetic parameter (transfer constant: K(trans)) in the characterization of breast lesions on MRI

Background:

The semi-quantitative analysis of the time–intensity curves in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a limited specificity due to overlapping enhancement patterns after gadolinium administration. With the advances in technology and faster sequences, imaging of the entire breast can be done in a few seconds, which allows measuring the transit of contrast (transfer constant: K^trans) through the vascular bed at capillary level that reflects quantitative measure of porosity/permeability of tumor vessels.

Aim:

Our study aims to evaluate the pharmacokinetic parameter K^trans for enhancing breast lesions and correlate it with histopathology, and assess accuracy, sensitivity, and specificity of this parameter in discriminating benign and malignant breast lesions.

Materials and Methods:

One hundred and fifty-one women with 216 histologically proved enhancing breast lesions underwent high temporal resolution DCE-MRI for the early dynamic analysis for calculation of pharmacokinetic parameters (K^trans) using standard two compartment model. The calculated values of K^trans were correlated with histopathology to calculate the sensitivity, specificity, and accuracy.

Results:

Receiver operating characteristic (ROC) curve analysis revealed a mean K^trans value of 0.56, which reliably distinguished benign and malignant breast lesions with a sensitivity of 91.1% and specificity of 90.3% with an overall accuracy of 89.3%. The area under curve (AUC) was 0.907.

Conclusion:

K^trans is a reliable quantitative parameter for characterizing benign and malignant lesions in routine DCE-MRI of breasts.

Dynamic breast MRI: does lower temporal resolution negatively affect clinical kinetic analysis?

OBJECTIVE

The purpose of this study was to compare the differences in kinetic assessments of lesions at breast MRI performed with higher and lower temporal resolution.

MATERIALS AND METHODS

All consecutively evaluated BI-RADS category 4, 5, and 6 lesions imaged with breast MRI and pathologically confirmed from October 2005 to August 2009 were identified. Patients underwent MRI with one of two dynamic contrast-enhanced protocols: one with 90-second (October 2005-June 2006) and another with 180-second (July 2006-August 2009) temporal resolution. Studies were processed with a computer-aided evaluation system with initial and delayed contrast-enhanced time points with the k-space centered 90 and 450 seconds after contrast injection. Initial-phase peak enhancement, delayed-phase predominant curve type, and worst curve type were recorded and compared for benign and malignant lesions across protocols.

RESULTS

The analysis set comprised 993 lesions: 145 imaged with the 90-second acquisition (17 benign, 28 ductal carcinoma in situ [DCIS], 100 invasive cancer) and 848 imaged with the 180-second acquisition (212 benign, 145 DCIS, 491 invasive cancer). Peak enhancement was significantly higher for both benign lesions (p = 0.01) and invasive cancers (p = 0.0008) with the 180-second protocol. Peak enhancement of DCIS was similar in the two protocols (p = 0.88). Delayed-phase kinetics were similar for the two protocols for both benign and malignant lesions when defined by predominant or worst curve type.

CONCLUSION

Although it has lower temporal resolution, a 180-second acquisition may be preferable because it allows higher spatial resolution and captures higher initial-phase peak enhancement without loss of delayed-phase kinetic information.

Comparison of enhancement characteristics between invasive lobular carcinoma and invasive ductal carcinoma

PURPOSE

To compare enhancement characteristics between invasive lobular carcinoma (ILC) and invasive ductal carcinoma (IDC) on contrast enhanced MRI of the breast and to observe the magnitude of eventual differences as these may impair the diagnostic value of breast MRI in ILC.

MATERIALS AND METHODS

We performed an analysis of enhancement characteristics on biphasic breast MRI in a series of 136 patients (103 IDC, 33 ILC) using an in-house developed application for pharmacokinetic modeling of contrast enhancement and a commercially available CAD application that evaluated the contrast-enhancement versus time curve.

RESULTS

Pharmacokinetic analysis showed that the most enhancing voxels in IDC had significantly higher K(trans) -values than in ILC (P < 0.01). No difference in v(e) -values was noted between groups. Visual assessment of contrast-enhancement versus time curves revealed wash-out curves to be less common in ILC (48% versus 84%). However, when using the CAD-application to assess the most malignant looking curve, the difference was blotted out (76% versus 86%).

CONCLUSION

ILC enhances slower than IDC but peak enhancement is not significantly less. The use of a CAD-application may help to determine the most malignant looking contrast-enhancement versus time curve, and hence facilitates lesion classification.

3-T dynamic contrast-enhanced MRI of the breast: pharmacokinetic parameters versus conventional kinetic curve analysis

OBJECTIVE

The purpose of this article is to evaluate the incremental value of pharmacokinetic analysis of dynamic contrast-enhanced (DCE) MRI compared with conventional breast MRI (morphology plus kinetic curve type analysis) in characterizing breast lesions as malignant or benign.

SUBJECTS AND METHODS

Patients underwent 3D high-resolution T1-weighted contrast-enhanced MRI and DCE-MRI at 3 T and had pathology-proven diagnosis (95%) or more than 2 years of follow-up confirming lesion stability (5%). Lesions were identified using the high-spatial-resolution contrast-enhanced MRI. Morphologic features (margin, enhancement, and pattern) and conventional DCE-MRI results (kinetic curve types 1, 2, or 3) or pharmacokinetic parameters (forward volume transfer constant [K(trans)], reverse volume transfer constant [K(ep)], and the extravascular extracellular space volume per unit volume of tissue), were included in multivariate models for prediction of benign versus malignant diagnosis.

RESULTS

Ninety-five patients with 101 lesions were included: 52% of patients were premenopausal and 48% were postmenopausal. Sixty-eight lesions (67.3%) were malignant and 33 (32.7%) were benign. There was a significant association between K(trans) and K(ep) and the diagnosis of benign versus malignant (p < 0.001). The area under the curve for morphologic features (lesion margin and enhancement pattern) was 0.85, whereas inclusion of K(trans) or K(ep) in the model showed similar modest improvement in performance (area under the curve, 0.88-0.89). For DCE-MRI, both pharmacokinetic modeling and kinetic curve type analysis improved characterization of malignant and benign breast lesions. A diagnostic model including lesion morphology plus either pharmacokinetic parameters or kinetic curve assessment showed similar diagnostic performance in characterizing breast lesions.

CONCLUSION

The use of kinetic curve type assessment or pharmacokinetic modeling in conjunction with high-resolution 3D breast MRI appears to offer similar improvement in diagnostic performance. Although morphologic analysis alone provides good characterization of breast lesions on MRI as benign or malignant, analysis of the lesion perfusion on DCE-MRI using either kinetic curve shape assessment or a pharmacokinetic modeling approach improves diagnostic accuracy.

The effect of motion correction on pharmacokinetic parameter estimation in dynamic-contrast-enhanced MRI

A dynamic-contrast-enhanced magnetic resonance imaging (DCE-MRI) dataset consists of many imaging frames, often acquired both before and after contrast injection. Due to the length of time spent acquiring images, patient motion is likely and image re-alignment or registration is required before further analysis such as pharmacokinetic model fitting. Non-rigid image registration procedures may be used to correct motion artefacts; however, a careful choice of registration strategy is required to reduce misregistration artefacts associated with enhancing features. This work investigates the effect of registration on the results of model-fitting algorithms for 52 DCE-MR mammography cases for 14 patients. Results are divided into two sections: a comparison of registration strategies in which a DCE-MRI-specific algorithm is preferred in 50% of cases, followed by an investigation of parameter changes with known applied deformations, inspecting the effect of magnitude and timing of motion artefacts. Increased motion magnitude correlates with increased model-fit residual and is seen to have a strong influence on the visibility of strongly enhancing features. Motion artefacts in images close to the contrast agent arrival have a disproportionate effect on discrepancies in parameter estimation. The choice of algorithm, magnitude of motion and timing of the motion are each shown to influence estimated pharmacokinetic parameters even when motion magnitude is small.

The diverse pathology and kinetics of mass, nonmass, and focus enhancement on MR imaging of the breast

PURPOSE

To compare the pathology and kinetic characteristics of breast lesions with focus-, mass-, and nonmass-like enhancement.

MATERIALS AND METHODS

A total of 852 MRI detected breast lesions in 697 patients were selected for an IRB approved review. Patients underwent dynamic contrast enhanced MRI using one pre- and three to six postcontrast T(1)-weighted images. The "type" of enhancement was classified as mass, nonmass, or focus, and kinetic curves quantified by the initial enhancement percentage (E(1)), time to peak enhancement (T(peak)), and signal enhancement ratio (SER). These kinetic parameters were compared between malignant and benign lesions within each morphologic type.

RESULTS

A total of 552 lesions were classified as mass (396 malignant, 156 benign), 261 as nonmass (212 malignant, 49 benign), and 39 as focus (9 malignant, 30 benign). The most common pathology of malignant/benign lesions by morphology: for mass, invasive ductal carcinoma/fibroadenoma; for nonmass, ductal carcinoma in situ (DCIS)/fibrocystic change(FCC); for focus, DCIS/FCC. Benign mass lesions exhibited significantly lower E(1), longer T(peak), and lower SER compared with malignant mass lesions (P < 0.0001). Benign nonmass lesions exhibited only a lower SER compared with malignant nonmass lesions (P < 0.01).

CONCLUSION

By considering the diverse pathology and kinetic characteristics of different lesion morphologies, diagnostic accuracy may be improved.

Textural kinetics: a novel dynamic contrast-enhanced (DCE)-MRI feature for breast lesion classification

Dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) of the breast has emerged as an adjunct imaging tool to conventional X-ray mammography due to its high detection sensitivity. Despite the increasing use of breast DCE-MRI, specificity in distinguishing malignant from benign breast lesions is low, and interobserver variability in lesion classification is high. The novel contribution of this paper is in the definition of a new DCE-MRI descriptor that we call textural kinetics, which attempts to capture spatiotemporal changes in breast lesion texture in order to distinguish malignant from benign lesions. We qualitatively and quantitatively demonstrated on 41 breast DCE-MRI studies that textural kinetic features outperform signal intensity kinetics and lesion morphology features in distinguishing benign from malignant lesions. A probabilistic boosting tree (PBT) classifier in conjunction with textural kinetic descriptors yielded an accuracy of 90%, sensitivity of 95%, specificity of 82%, and an area under the curve (AUC) of 0.92. Graph embedding, used for qualitative visualization of a low-dimensional representation of the data, showed the best separation between benign and malignant lesions when using textural kinetic features. The PBT classifier results and trends were also corroborated via a support vector machine classifier which showed that textural kinetic features outperformed the morphological, static texture, and signal intensity kinetics descriptors. When textural kinetic attributes were combined with morphologic descriptors, the resulting PBT classifier yielded 89% accuracy, 99% sensitivity, 76% specificity, and an AUC of 0.91.

Molecular Imaging in Breast Cancer - Potential Future Aspects

SUMMARY: Molecular imaging aims to visualize and quantify biological, physiological, and pathological processes at cellular and molecular levels. Recently, molecular imaging has been introduced into breast cancer imaging. In this review, we will present a survey of the molecular imaging techniques that are either clinically available or are being introduced into clinical imaging. We will discuss nuclear imaging and multiparametric magnetic resonance imaging as well as the combined application of molecular imaging in the assessment of breast lesions. In addition, we will briefly discuss other evolving molecular imaging techniques, such as phosphorus magnetic resonance spectroscopic imaging and sodium imaging.

Characterizing early contrast uptake of ductal carcinoma in situ with high temporal resolution dynamic contrast-enhanced MRI of the breast: a pilot study

Improvements in the reliable diagnosis of preinvasive ductal carcinoma in situ (DCIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are needed. In this study, we present a new characterization of early contrast kinetics of DCIS using high temporal resolution (HiT) DCE-MRI and compare it with other breast lesions and normal parenchyma. Forty patients with mammographic calcifications suspicious for DCIS were selected for HiT imaging using T(1)-weighted DCE-MRI with ∼7 s temporal resolution for 90 s post-contrast injection. Pixel-based and whole-lesion kinetic curves were fit to an empirical mathematical model (EMM) and several secondary kinetic parameters derived. Using the EMM parameterized and fitted concentration time curve for subsequent analysis allowed for calculation of kinetic parameters that were less susceptible to fluctuations due to noise. The parameters' initial area under the curve (iAUC) and contrast concentration at 1 min (C(1 min)) provided the highest diagnostic accuracy in the task of distinguishing pathologically proven DCIS from normal tissue. There was a trend for DCIS lesions with solid architectural pattern to exhibit a negative slope at 1 min (i.e. increased washout rate) compared to those with a cribriform pattern (p < 0.04). This pilot study demonstrates the feasibility of quantitative analysis of early contrast kinetics at high temporal resolution and points to the potential for such an analysis to improve the characterization of DCIS.

Optimizing 1.5-Tesla and 3-Tesla dynamic contrast-enhanced magnetic resonance imaging of the breasts

The technical requirements for magnetic resonance imaging (MRI) of the breasts are challenging because high temporal and high spatial resolution are necessary. This article describes the necessary equipment and pulse sequences for performing a high-quality study. Although imaging at 3-Tesla (T) has a higher signal-to-noise ratio, the protocol needs to be modified from the 1.5-T system to provide optimal imaging. The article presents the requirements for performing breast MRI and discusses techniques to ensure high-quality examinations on 1.5-T and 3-T systems.

A combined high temporal and high spatial resolution 3 Tesla MR imaging protocol for the assessment of breast lesions: initial results

PURPOSE

To develop a 3.0 Tesla breast imaging protocol that combines high temporal and spatial resolution three-dimensional MR sequences for quantitative time course and morphologic analysis of breast lesions.

MATERIALS AND METHODS

Thirty-four patients were included in the study (age range, 31-82; mean age, 54.3). The study protocol was approved by the Institutional Review Board and written informed consent was obtained from all patients. The magnetic resonance imaging protocol included: a coronal T1-weighted volume-interpolated-breathhold-examination sequence, focused on high temporal resolution for optimal assessment of the contrast-enhancement behavior of lesions (SI 1.7 mm isotropic; TA 3.45 minutes for 17 measurements); a coronal T1-weighted turbo fast-low-angle-shot-three-dimensional sequence, with water-excitation and fat suppression, focused on high spatial resolution for morphologic analysis (SI 1 mm isotropic; TA 2 minutes); and a repeated coronal volume-interpolated-breathhold-examination sequence for detection of washout. Lesion size and morphology were assessed. Region-of-interests for suspicious areas were manually drawn and evaluated for contrast-enhancement behavior by plotting intensity courses against time. Sensitivity and specificity with a 95% confidence interval and the negative predictive value and positive predictive value were calculated. Diagnostic accuracy was assessed. The histopathological diagnoses were used as a standard of reference.

RESULTS

Fifty-five lesions were detected in 34 patients. All malignant breast lesions were identified correctly. There were 5 false-positive lesions. The sensitivity of contrast-enhanced magnetic resonance imaging of the breast at 3 T was 100%, with a 95% confidence interval (CI) of 90.6% to 100%. The specificity was 72.2%, with a 95% CI of 49.1% to 87.5%. The positive predictive value was 0.88 and the negative predictive value was 1. Diagnostic accuracy was 91% with a 95% CI of 80.4% to 96.1%.

CONCLUSION

Our prospective study demonstrates that the presented 3 Tesla MR imaging protocol, comprising both high temporal and high spatial resolution, enables accurate detection and assessment of breast lesions.

Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement

Purpose

To investigate methods developed for the characterisation of the morphology and enhancement kinetic features of both mass and non-mass lesions, and to determine their diagnostic performance to differentiate between malignant and benign lesions that present as mass versus non-mass types.

Methods

Quantitative analysis of morphological features and enhancement kinetic parameters of breast lesions were used to differentiate among four groups of lesions: 88 malignant (43 mass, 45 non-mass) and 28 benign (19 mass, 9 non-mass). The enhancement kinetics was measured and analysed to obtain transfer constant (K^trans) and rate constant (k_ep). For each mass eight shape/margin parameters and 10 enhancement texture features were obtained. For the lesions presenting as nonmass-like enhancement, only the texture parameters were obtained. An artificial neural network (ANN) was used to build the diagnostic model.

Results

For lesions presenting as mass, the four selected morphological features could reach an area under the ROC curve (AUC) of 0.87 in differentiating between malignant and benign lesions. The kinetic parameter (k_ep) analysed from the hot spot of the tumour reached a comparable AUC of 0.88. The combined morphological and kinetic features improved the AUC to 0.93, with a sensitivity of 0.97 and a specificity of 0.80. For lesions presenting as non-mass-like enhancement, four texture features were selected by the ANN and achieved an AUC of 0.76. The kinetic parameter k_ep from the hot spot only achieved an AUC of 0.59, with a low added diagnostic value.

Conclusion

The results suggest that the quantitative diagnostic features can be used for developing automated breast CAD (computer-aided diagnosis) for mass lesions to achieve a high diagnostic performance, but more advanced algorithms are needed for diagnosis of lesions presenting as non-mass-like enhancement.