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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of ...

Weizmann Institute of Science

Novel estrogen-conjugated pyridine-containing Gd(III) and Eu(III) contrast agents (EPTA-Gd/Eu) were designed and effectively synthesized. Convenient to administration and MRI experiments, both EPTA-Gd and EPTA-Eu are soluble in water. The EPTA-Gd selectively binds with a micromolar affinity to the estrogen receptor and induces proliferation of human breast cancer cells. The EPTA-Gd is not lethal and does not cause any adverse effects when administrated intravenously. It enhances T1 and T2 nuclear relaxation rates of water and serves as a selective contrast agent for localizing the estrogen receptor by MRI.

Water-soluble contrast agents targeted at the estrogen receptor for molecular magnetic resonance imaging.

A wide range of dynamic-contrast-enhanced (DCE) sequences and protocols, image processing methods, and interpretation criteria have been developed and evaluated over the last 20 years. In particular, attempts have been made to better understand the origin of the contrast observed in breast lesions using physiological models that take into account the vascular and tissue-specific features that influence tracer perfusion. In addition, model-free algorithms to decompose enhancement patterns in order to segment and classify different breast tissue types have been developed. This review includes a description of the mechanism of contrast enhancement by gadolinium-based contrast agents, followed by the current status of the physiological models used to analyze breast DCE-MRI and related critical issues. We further describe more recent unsupervised and supervised methods that use a range of different common algorithms. The model-based and model-free methods strive to achieve scientific accuracy and high clinical performance--both important goals yet to be reached.

Model-based and model-free parametric analysis of breast dynamic-contrast-enhanced MRI.

Solid tumors often develop high interstitial fluid pressure (IFP) as a result of increased water leakage and impaired lymphatic drainage, as well as changes in the extracellular matrix composition and elasticity. This high fluid pressure forms a barrier to drug delivery and hence, resistance to therapy. We have developed techniques based on contrast enhanced magnetic resonance imaging for mapping in tumors the vascular and transport parameters determining the delivery efficiency of blood borne substances. Sequential images are recorded during continuous infusion of a Gd-based contrast agent and analyzed according to a new physiological model, yielding maps of microvascular transfer constants, as well as outward convective interstitial transfer constants and steady state interstitial contrast agent concentrations both reflecting IFP distribution. We further demonstrated in non small cell human lung cancer xenografts the capability of our techniques to monitor in vivo collagenase induced increase in contrast agent delivery as a result of decreased IFP. These techniques can be applied to test drugs that affect angiogenesis and modulate interstitial fluid pressure and has the potential to be extended to cancer patients for assessing resistance to drug delivery.

Non-invasive imaging of barriers to drug delivery in tumors.

To investigate a fast, objective, and standardized method for analyzing breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) applying principal component analysis (PCA) adjusted with a model-based method.

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

To develop and evaluate a fast, objective and standardized method for image processing of dynamic contrast enhanced MRI of the prostate based on principal component analysis (PCA).

Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer.

To investigate the ability of parametric diffusion tensor imaging (DTI), applied at 3 Tesla, to dissect breast tissue architecture and evaluate breast lesions.

Erez Eyal

Department of Biological Regulation

Weizmann Institute of Science

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Erez Eyal

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Biological Regulation

Weizmann Institute of Science

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Department of Biological Regulation