Clinical Testing of High-Spatial-Resolution Parametric Contrast-Enhanced  MR Imaging of the Breast

Kelcz, Frederick; Furman‐Haran, Edna; Grobgeld, Dov; Degani, Hadassa

doi:10.2214/ajr.179.6.1791485

Cited by 76 publications

(79 citation statements)

References 26 publications

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“…Degani et al (30) developed a mapping technique that displays both information of microvascular permeability and extracellular fraction (obtained from pharmacokinetic analysis of the enhancement time course measured using a threetime-point acquisition) using one composite color map. This method has been shown helpful in differentiating between benign and malignant tumors (31).…”

Section: Discussionmentioning

confidence: 99%

Correlation of dynamic contrast enhancement MRI parameters with microvessel density and VEGF for assessment of angiogenesis in breast cancer

Cheung

Fruehauf

et al. 2003

Magnetic Resonance Imaging

150

115

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Purpose:To investigate the association between parameters obtained from dynamic contrast enhanced MRI (DCE-MRI) of breast cancer using different analysis approaches, as well as their correlation with angiogenesis biomarkers (vascular endothelial growth factor and vessel density).Materials and Methods: DCE-MRI results were obtained from 105 patients with breast cancer (108 lesions). Three analysis methods were applied: 1) whole tumor analysis, 2) regional hot-spot analysis, and 3) intratumor pixel-by-pixel analysis. Early enhancement intensities and fitted pharmacokinetic parameters were studied. Paraffin blocks of 71 surgically resected specimens were analyzed by immunohistochemical staining to measure microvessel counts (with CD31) and vascular endothelial growth factor (VEGF) expression levels.Results: MRI parameters obtained from the three analysis methods showed significant correlations (P Ͻ 0.0001), but a substantial dispersion from the linear regression line was noted (r ϭ 0.72-0.97). The entire region of interest (ROI) vs. pixel population analyses had a significantly higher association compared to the entire ROI vs. hot-spot analyses. Cancer specimens with high VEGF expression had significantly higher CD31 microvessel densities than did specimens with low VEGF levels (P Ͻ 0.005). No significant association was found between MRI parameters obtained from the three analysis strategies and IHC based measurements of angiogenesis. Conclusion:A consistent analysis strategy was important in the DCE-MRI study. In this series, none of these strategies yielded results for MRI based quantitation of tumor vascularity that were associated with IHC based measurements. Therefore, different analyses could not account for the lack of association.

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Section: Discussionmentioning

confidence: 99%

Correlation of dynamic contrast enhancement MRI parameters with microvessel density and VEGF for assessment of angiogenesis in breast cancer

Cheung

Fruehauf

et al. 2003

Magnetic Resonance Imaging

150

115

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“…The patients were selected for MRI based on a finding of a palpable mass or mammographic or sonographic abnormality, as was described previously. 23,24 The reported diagnoses were confirmed by histopathology of specimens obtained by excision biopsy, core biopsy, or fine-needle aspiration. All patients signed an informed consent form that was approved by the Human Subjects Committee of each institution.…”

Section: Patientsmentioning

confidence: 99%

Magnetic resonance imaging reveals functional diversity of the vasculature in benign and malignant breast lesions

Furman‐Haran

Schechtman

Kelcz

et al. 2005

Cancer

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BACKGROUNDTumor perfusion through the microvascular network can be imaged noninvasively by dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI). The objective of the current study was to quantify the microvascular perfusion parameters in various human breast lesions and to determine whether they varied between benign lesions and malignancy and whether they were altered with increased invasiveness.METHODSPerfusion parameters in 22 benign fibrocystic changes, 15 ductal carcinomas in situ (DCIS), 30 infiltrating ductal carcinomas (IDC), and 22 fibroadenomas were measured using high‐resolution DCE‐MRI. Pixel‐by‐pixel image analysis yielded parametric images of two perfusion indicators: the influx transcapillary transfer constant (ktrans) and the efflux transcapillary rate constant (kep). Correlations of lesion type and perfusion parameters were calculated using Spearman correlation. Logistic regression analysis evaluated the best predictors of the kinetic parameters that differentiate between IDC and benign lesions.RESULTSThe perfusion parameters exhibited a progressive increase from benign fibrocystic changes to DCIS and IDC, with a significant correlation between lesion type and the parameters' values (range of correlation coefficients, 0.56–0.76; P < 0.0001). In addition, ktrans increased from low‐grade DCIS to high‐grade DCIS. Fibroadenomas were characterized uniquely by high ktrans but low kep. Stepwise logistic regression selected ktrans as the best predictor for distinguishing benign fibrocystic changes from IDC, yielding 93% sensitivity and 96% specificity.CONCLUSIONSThe microvascular perfusion parameters in breast lesions were elevated with invasiveness. Quantification of these parameters using high‐resolution DCE‐MRI was helpful for differentiating between breast lesions and should improve breast carcinoma diagnosis. Cancer 2005. © 2005 American Cancer Society.

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“…For visual inspection, the time-series signals are typically displayed as relative-enhancement curves depicting the signal enhancement with respect to the signal intensity in the precontrast image. Model-based 3TP method [14,15] as the basis for pseudo-coloring of lesions voxels: the intensity of the pseudo-color represents the amount of signal uptake between the precontrast and the early postcontrast image. The presence or absence of a wash-out is associated with the color hue, yielding thus a simple lesions' evaluation method which is capable to integrate information from exactly one precontrast and two postcontrast images.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…Pixel-mapping functions are used to map individual time-series signals to pseudo-colors which reflect dedicated features of the temporal signal. These signal features are derived from explicit mathematical models of the time-series signals, like in the threetime-points (3TP) method [14] illustrated in Figure 3, or from more sophisticated pharmacokinetic models [16][17][18] describing the exchange of CA molecules between tissue compartments over time. Beside these model-based approaches, an increasing number of applications apply pattern recognition methods to extract and to visually appreciate clinically relevant information [5][6][7][8][9][10][11]13].…”

Section: Introductionmentioning

confidence: 99%

Model-free visualization of suspicious lesions in breast MRI based on supervised and unsupervised learning

Twellmann

Meyer‐Baese

Lange

et al. 2008

Engineering Applications of Artificial Intelligence

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Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become an important tool in breast cancer diagnosis, but evaluation of multitemporal 3D image data holds new challenges for human observers. To aid the image analysis process, we apply supervised and unsupervised pattern recognition techniques for computing enhanced visualizations of suspicious lesions in breast MRI data. These techniques represent an important component of future sophisticated computer-aided diagnosis (CAD) systems and support the visual exploration of spatial and temporal features of DCE-MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogeneity of cancerous tissue, these techniques reveal signals with malignant, benign and normal kinetics. They also provide a regional subclassification of pathological breast tissue, which is the basis for pseudo-color presentations of the image data. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging.

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Clinical Testing of High-Spatial-Resolution Parametric Contrast-Enhanced MR Imaging of the Breast

Abstract: Application of the three-time-point method permitted, in most cases, differentiation of malignant and benign lesions, even in the presence of complex breast enhancement patterns. Sensitivity for solid tumors was higher than for ductal carcinoma in situ.

Cited by 76 publications

References 26 publications

Correlation of dynamic contrast enhancement MRI parameters with microvessel density and VEGF for assessment of angiogenesis in breast cancer

Correlation of dynamic contrast enhancement MRI parameters with microvessel density and VEGF for assessment of angiogenesis in breast cancer

Magnetic resonance imaging reveals functional diversity of the vasculature in benign and malignant breast lesions

Model-free visualization of suspicious lesions in breast MRI based on supervised and unsupervised learning

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