Parametric analysis of breast MRI

What's Hot in Breast MRI

Several articles in the literature have demonstrated a promising role for breast MRI techniques that are more economic in total exam time than others when used as supplement to mammography for detection and diagnosis of breast cancer. There are many technical factors that must be considered in the shortened breast MRI protocols to cut down time of standard ones, including using optimal fat suppression, gadolinium-chelates intravascular contrast administrations for dynamic imaging with post processing subtractions and maximum intensity projections (MIP) high spatial and temporal resolution among others. Multiparametric breast MRI that includes both gadolinium-dependent, i.e., dynamic contrast-enhanced (DCE-MRI) and gadolinium-free techniques, i.e., diffusion-weighted/diffusion-tensor magnetic resonance imaging (DWI/DTI) are shown by several investigators that can provide extremely high sensitivity and specificity for detection of breast cancer. This article provides an overview of the proven indications for breast MRI including breast cancer screening for higher than average risk, determining chemotherapy induced tumor response, detecting residual tumor after incomplete surgical excision, detecting occult cancer in patients presenting with axillary node metastasis, detecting residual tumor after incomplete breast cancer surgical excision, detecting cancer when results of conventional imaging are equivocal, as well patients suspicious of having breast implant rupture. Despite having the highest sensitivity for breast cancer detection, there are pitfalls, however, secondary to false positive and false negative contrast enhancement and contrast-free MRI techniques. Awareness of the strengths and limitations of different approaches to obtain state of the art MR images of the breast will facilitate the work-up of patients with suspicious breast lesions.

Supramolecular recognition of phosphocholine by an enzyme-like cavitand receptor

The first example of supramolecular recognition of phosphocholine by a cavitand receptor has been reported here. The chemical structure of the receptor has been optimized by DFT calculations. The recognition mechanism is based on a "multi-topic approach", which leads to highly efficient (K value up to 10⁷ M^-1), selective and sensitive (ppb level) sensing of phosphocholine. The recognition mechanism proposed here is similar to those exploited by Nature, and paves the way for the realization of new sensors with important applications in medicine and security fields.

Semi-quantitative parameter analysis of DCE-MRI revisited: monte-carlo simulation, clinical comparisons, and clinical validation of measurement errors in patients with type 2 neurofibromatosis

PURPOSE

To compare semi-quantitative (SQ) and pharmacokinetic (PK) parameters for analysis of dynamic contrast enhanced MR data (DCE-MRI) and investigate error-propagation in SQ parameters.

METHODS

Clinical data was collected from five patients with type 2-neurofibromatosis (NF2) receiving anti-angiogenic therapy for rapidly growing vestibular schwannoma (VS). There were 7 VS and 5 meningiomas. Patients were scanned prior to therapy and at days 3 and 90 of treatment. Data was collected using a dual injection technique to permit direct comparison of SQ and PK parameters. Monte Carlo modeling was performed to assess potential measurement errors in SQ parameters in persistent, washout, and weakly enhancing tissues. The simulation predictions for five semi-quantitative parameters were tested using the clinical DCE-MRI data.

RESULTS

In VS, SQ parameters and Ktrans showed close correlation and demonstrated similar therapy induced reductions. In meningioma, only the denoised Signal Enhancement Ratio (Rse1/se2(DN)) showed a significant therapy induced reduction (p<0.05). Simulation demonstrated: 1) Precision of SQ metrics normalized to the pre-contrast-baseline values (MSErel and ∑MSErel) is improved by use of an averaged value from multiple baseline scans; 2) signal enhancement ratio Rmse1/mse2 shows considerable susceptibility to noise; 3) removal of outlier values to produce a new parameter, Rmse1/mse2(DN), improves precision and sensitivity to therapy induced changes. Direct comparison of in-vivo analysis with Monte Carlo simulation supported the simulation predicted error distributions of semi-quantitative metrics.

CONCLUSION

PK and SQ parameters showed similar sensitivity to anti-angiogenic therapy induced changes in VS. Modeling studies confirmed the benefits of averaging baseline signal from multiple images for normalized SQ metrics and demonstrated poor noise tolerance in the widely used signal enhancement ratio, which is corrected by removal of outlier values.

Standardization of radiological evaluation of dynamic contrast enhanced MRI: application in breast cancer diagnosis

Dynamic contrast enhanced MRI is applied as an adjuvant tool for breast cancer detection, diagnosis, and follow-up of therapy. Despite improvements through the years in achieving higher spatial and temporal resolution, it still suffers from lack of scanning and processing standardization, and consequently, high variability in the radiological evaluation, particularly differentiating malignant from benign lesions. We describe here a hybrid method for achieving standardization of the radiological evaluation of breast dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) protocols, based on integrating the model based three time point (3TP) method with principal component analysis (PCA). The scanning and image processing procedures consisted of three main steps: 1. 3TP standardization of the MRI acquisition parameters according to a kinetic model, 2. Applying PCA to test cases and constructing an eigenvectors' base related to the contrast-enhancement kinetics and 3. Projecting all new cases on the eigenvectors' base and evaluating the clinical outcome. Datasets of overall 96 malignant and 26 benign breast lesions were recorded on 1.5T and 3T scanners, using three different MRI acquisition parameters optimized by the 3TP method. The final radiological evaluation showed similar detection and diagnostic ability for the three different MRI acquisition parameters. The area under the curve of receiver operating characteristic analysis yielded a value of 0.88 ± 0.034 for differentiating malignant from benign lesions. This 3TP + PCA hybrid method is fast and can be readily applied as a computer aided diagnostic tool of breast cancer. The underlying principles of this method can be extended to standardize the evaluation of malignancies in other organs.

Magnetic resonance in the detection of breast cancers of different histological types

Breast cancer incidence is increasing worldwide. Early detection is critical for long-term patient survival, as is monitoring responses to chemotherapy for management of the disease. Magnetic resonance imaging and spectroscopy (MRI/MRS) has gained in importance in the last decade for the diagnosis and monitoring of breast cancer therapy. The sensitivity of MRI/MRS for anatomical delineation is very high and the consensus is that MRI is more sensitive in detection than x-ray mammography. Advantages of MRS include delivery of biochemical information about tumor metabolism, which can potentially assist in the staging of cancers and monitoring responses to treatment. The roles of MRS and MRI in screening and monitoring responses to treatment of breast cancer are reviewed here. We rationalize how it is that different histological types of breast cancer are differentially detected and characterized by MR methods.

The effect of temporal sampling on quantitative pharmacokinetic and three-time-point analysis of breast DCE-MRI

The effects of temporal sampling on the previously published three-time-point (3TP) method are compared with those of a Tofts-Kety model using an arterial input function from the alternating minimization with model (AMM) method. Computer simulations are done to estimate the expected error in both the 3TP and Tofts-Kety models as a function of the temporal sampling rate of the data. The error in the 3TP model parameters remained essentially constant with respect to temporal sampling. The Tofts-Kety model showed a linear increase in parameter error with respect to temporal sampling. Both analysis methods were also applied to 87 clinically acquired breast scans. These scans were downsampled in time by a factor of 2 and 4, and the methods were reapplied. The spatial resolution was held constant throughout this study. At temporal resolutions less than 19.4 s, the Tofts-Kety model outperformed the 3TP model using receiver operating characteristic curve analysis (area under the ROC curve [AUC] of 0.94 compared to 0.91). As the temporal sampling rate decreased, the 3TP model outperformed the Tofts-Kety model (AUC of 0.89 versus 0.85). When the temporal sampling rate of the data was less than 20 s, the Tofts-Kety model with the AMM method had lower parameter error than the 3TP method.

Phenomenological universalities: a novel tool for the analysis of dynamic contrast enhancement in magnetic resonance imaging

Dynamic contrast enhancement in magnetic resonance imaging (DCE-MRI) is a promising tool for the clinical diagnosis of tumors, whose implementation may be improved through the use of suitable hemodynamic models. If one prefers to avoid assumptions about the tumor physiology, empirical fitting functions may be adopted. For this purpose, in this paper we discuss the exploitation of a recently proposed phenomenological universalities (PUN) formalism. In fact, we show that a novel PUN class may be used to describe the time-signal intensity curves in both healthy and tumoral tissues, discriminating between the two cases and thus potentially providing a convenient diagnostic tool. The proposed approach is applied to analysis of the DCE-MRI data relative to a study group composed of ten patients with spine tumors.

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

PURPOSE

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.

MATERIALS AND METHODS

3D gradient-echo DCE breast images of 31 malignant and 38 benign lesions, recorded on a 1.5T scanner, were retrospectively analyzed by PCA and by the model-based three-timepoints (3TP) method.

RESULTS

Intensity-scaled (IS) and enhancement-scaled (ES) datasets were reduced by PCA yielding a first IS-eigenvector that captured the signal variation between fat and fibroglandular tissue; two IS-eigenvectors and the two first ES-eigenvectors captured contrast-enhanced changes, whereas the remaining eigenvectors captured predominantly noise changes. Rotation of the two contrast-related eigenvectors led to a high congruence between the projection coefficients and the 3TP parameters. The ES-eigenvectors and the rotation angle were highly reproducible across malignant lesions, enabling calculation of a general rotated eigenvector base. Receiver operating characteristic (ROC) curve analysis of the projection coefficients of the two eigenvectors indicated high sensitivity of the first rotated eigenvector to detect lesions (area under the curve [AUC] > 0.97) and of the second rotated eigenvector to differentiate malignancy from benignancy (AUC = 0.87).

CONCLUSION

PCA adjusted with a model-based method provided a fast and objective computer-aided diagnostic tool for breast DCE-MRI.

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

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.

Recent advances in breast MRI and MRS

Breast MRI is an area of intense research and is fast becoming an important tool for the diagnosis of breast cancer. This review covers recent advances in breast MRI, MRS, and image post-processing and analysis. Several studies have explored a multi-parametric approach to breast imaging that combines analysis of traditional contrast enhancement patterns and lesion architecture with novel methods such as diffusion, perfusion, and spectroscopy to increase the specificity of breast MRI studies. Diffusion-weighted MRI shows some potential for increasing the specificity of breast lesion diagnosis and is even more promise for monitoring early response to therapy. MRS also has great potential for increasing specificity and for therapeutic monitoring. A limited number of studies have evaluated perfusion imaging based on first-pass contrast bolus tracking, and these clearly identify that vascular indices have great potential to increase specificity. The review also covers the relatively new acquisition technique of MR elastography for breast lesion characterization. A brief survey of image processing algorithms tailored for breast MR, including registration of serial dynamic images, segmentation and extraction of morphological features of breast lesions, and contrast uptake modeling, is also included. Recent advances in MRI, MRS, and automated image analysis have increased the utility of breast MR in diagnosis, screening, management, and therapy monitoring of breast cancer.

An illustration of the potential for mapping MRI/MRS parameters with genetic over-expression profiles in human prostate cancer

INTRODUCTION

Magnetic resonance imaging (MRI) and MR spectroscopy can probe a variety of physiological (e.g. blood vessel permeability) and metabolic characteristics of prostate cancer. However, little is known about the changes in gene expression that underlie the spectral and imaging features observed in prostate cancer. Tumor induced changes in vascular permeability and angiogenesis are thought to contribute to patterns of dynamic contrast enhanced (DCE) MRI images of prostate cancer even though the genetic basis of tumor vasculogenesis is complex and the specific mechanisms underlying these DCEMRI features have not yet been determined.

MATERIALS AND METHODS

In order to identify the changes in gene expression that correspond to MRS and DCEMRI patterns in human prostate cancers, we have utilized tissue print micropeel techniques to generate "whole mount" molecular maps of radical prostatectomy specimens that correspond to pre-surgical MRI/MRS studies. These molecular maps include RNA expression profiles from both Affymetrix GeneChip microarrays and quantitative reverse transcriptase PCR (qrt-PCR) analysis, as well as immunohistochemical studies.

RESULTS

Using these methods on patients with prostate cancer, we found robust over-expression of choline kinase a in the majority of primary tumors. We also observed overexpression of neuropeptide Y (NPY), a newly identified angiogenic factor, in a subset of prostate cancers, visualized on DCEMRI.

CONCLUSION

These studies set the stage for establishing MRI/MRS parameters as validated biomarkers for human prostate cancer.

MRI mediated, non-invasive tracking of intratumoral distribution of nanocarriers in rat glioma

Nanocarrier mediated therapy of gliomas has shown promise. The success of systemic nanocarrier-based chemotherapy is critically dependent on the so-called leaky vasculature to permit drug extravasation across the blood-brain barrier. Yet, the extent of vascular permeability in individual tumors varies widely, resulting in a correspondingly wide range of responses to the therapy. However, there exist no tools currently for rationally determining whether tumor blood vessels are amenable to nanocarrier mediated therapy in an individualized, patient specific manner today. To address this need for brain tumor therapy, we have developed a multifunctional 100 nm scale liposomal agent encapsulating a gadolinium-based contrast agent for contrast-enhanced magnetic resonance imaging with prolonged blood circulation. Using a 9.4 T MRI system, we were able to track the intratumoral distribution of the gadolinium-loaded nanocarrier in a rat glioma model for a period of three days due to improved magnetic properties of the contrast agent being packaged in a nanocarrier. Such a nanocarrier provides a tool for non-invasively assessing the suitability of tumors for nanocarrier mediated therapy and then optimizing the treatment protocol for each individual tumor. Additionally, the ability to image the tumor in high resolution can potentially constitute a surgical planning tool for tumor resection.

Invasive breast cancer: predicting disease recurrence by using high-spatial-resolution signal enhancement ratio imaging

PURPOSE

To retrospectively evaluate high-spatial-resolution signal enhancement ratio (SER) imaging for the prediction of disease recurrence in patients with breast cancer who underwent preoperative magnetic resonance (MR) imaging.

MATERIALS AND METHODS

This retrospective study was approved by the institutional review board and was HIPAA compliant; informed consent was waived. From 1995 to 2002, gadolinium-enhanced MR imaging data were acquired with a three time point high-resolution method in women undergoing neoadjuvant therapy for invasive breast cancers. Forty-eight women (mean age, 49.1 years; range, 29.7-72.4 years) were divided into recurrence-free or recurrence groups. Volume measurements were tabulated for SER values between set ranges; cutoff criteria were defined to predict disease recurrence after surgery. Wilcoxon rank sum tests and the multivariate Cox proportional hazards regression model were used for evaluation.

RESULTS

Breast tumor volume calculated from the number of voxels with SER values above a threshold corresponding to the upper limit of mean redistribution rate constant in benign tumors (0.88 minutes(-1)) and the volume of cancerous breast tissue infiltrating into the parenchyma were important predictors of disease recurrence. Seventy-five percent of patients with recurrence and 100% of deceased patients were identified as being at high risk for recurrence. Thirty percent of patients with recurrence and 67% of deceased patients were identified as having high risk before chemotherapy. No patients in the recurrence-free group were misidentified as likely to have recurrence. All three prechemotherapy parameters (total tumor volume, tumor volumes with high and low SER) and the postchemotherapy tumor volume with high SER were significantly different between the two groups. The multivariate Cox proportional hazards regression showed that, of the three prechemotherapy covariates, only the low SER and high SER tumor volumes (P = .017 and .049, respectively) were significant and independent predictors of tumor recurrence. Tumor volume with high SER was the only significant postchemotherapy covariate predictor (P = .038).

CONCLUSION

High-spatial-resolution SER imaging may improve prediction for patients at high risk for disease recurrence and death.

Removing undersampling artifacts in DCE-MRI studies using independent components analysis

In breast MRI mammography both high temporal resolution and high spatial resolution have been shown to be important in improving specificity. Adaptive methods such as projection reconstruction time-resolved imaging of contrast kinetics (PR-TRICKS) allow images to be reconstructed at various temporal and spatial resolutions from the same data set. The main disadvantage is that the undersampling, which is necessary to produce high temporal resolution images, leads to the presence of streak artifacts in the images. We present a novel method of removing these artifacts using independent components analysis (ICA) and demonstrate that this results in a significant improvement in image quality for both simulation studies and for patient dynamic contrast-enhanced (DCE)-MRI images. We also investigate the effect of artifacts on two quantitative measures of contrast enhancement. Using simulation studies we demonstrate that streak artifacts lead to pronounced periodic oscillations in pixel concentration curves which, in turn, lead to increased errors and introduce bias into heuristic measurements. ICA filtering significantly reduces this bias and improves accuracy. Pharmacokinetic modeling was more robust and there was no evidence of bias due to the presence of streak artifacts. ICA filtering did not significantly reduce the errors in the estimated pharmacokinetic parameters; however, the chi-squared error was greatly reduced after ICA filtering.

Differentiation between benign and malignant breast lesions detected by bilateral dynamic contrast-enhanced MRI: a sensitivity and specificity study

The purpose of this study was to apply an empirical mathematical model (EMM) to kinetic data acquired under a clinical protocol to determine if the sensitivity and specificity can be improved compared with qualitative BI-RADS descriptors of kinetics. 3D DCE-MRI data from 100 patients with 34 benign and 79 malignant lesions were selected for review under an Institutional Review Board (IRB)-approved protocol. The sensitivity and specificity of the delayed phase classification were 91% and 18%, respectively. The EMM was able to accurately fit these curves. There was a statistically significant difference between benign and malignant lesions for several model parameters: the uptake rate, initial slope, signal enhancement ratio, and curvature at the peak enhancement (at most P=0.04). These results demonstrated that EMM analysis provided at least the diagnostic accuracy of the kinetic classifiers described in the BI-RADS lexicon, and offered a few key advantages. It can be used to standardize data from institutions with different dynamic protocols and can provide a more objective classification with continuous variables so that thresholds can be set to achieve desired sensitivity and specificity. This suggests that the EMM may be useful for analysis of routine clinical data.

Quantitative 2- and 3-dimensional analysis of pharmacokinetic model-derived variables for breast lesions in dynamic, contrast-enhanced MR mammography

PURPOSE

2- and 3-dimensional evaluation of quantitative pharmacokinetic parameters derived from the Tofts model modeling dynamic contrast enhancement of lesions in MR mammography.

MATERIALS AND METHODS

In 95 patients, MR mammography revealed 127 suspicious lesions. The initial rate of enhancement was coded by color intensity, the post-initial enhancement change is coded by color hue. 2D and 3D analysis of distribution of color hue and intensity, vascular permeability and extracellular volume were performed.

RESULTS

In 2D, malignant lesions showed significant higher number of bright red, medium red, dark red, bright green, medium green, dark green and bright blue pixels than benign lesions. In 3D, statistical significant differences between malignant and benign lesions was found for all this parameters. Vascular permeability was significant higher in malignant lesions than in benign lesions. Regression model using the 3D data found that the best discriminator between malignant and benign lesions was combined number of voxels and medium green pixels, with a sensitivity of 79.4% and a specificity of 83.1%.

CONCLUSIONS

Quantitative analysis of pharmacokinetic variables of contrast kinetics showed significant differences between malignant and benign lesions. 3D analysis showed superior diagnostic differentiation between malignant and benign lesions than 2D analysis. The parametric analysis using a pharmacokinetic model allows objective analysis of contrast enhancement in breast lesions.

Implementation of a semi-automated post-processing system for parametric MRI mapping of human breast cancer

Magnetic resonance imaging (MRI) investigations of breast cancer incorporate computationally intense techniques to develop parametric maps of pathophysiological tissue characteristics. Common approaches employ, for example, quantitative measurements of T (1), the apparent diffusion coefficient, and kinetic modeling based on dynamic contrast-enhanced MRI (DCE-MRI). In this paper, an integrated medical image post-processing and archive system (MIPAS) is presented. MIPAS demonstrates how image post-processing and user interface programs, written in the interactive data language (IDL) programming language with data storage provided by a Microsoft Access database, and the file system can reduce turnaround time for creating MRI parametric maps and provide additional organization for clinical trials. The results of developing the MIPAS are discussed including potential limitations of the use of IDL for the application framework and how the MIPAS design supports extension to other programming languages and imaging modalities. We also show that network storage of images and metadata has a significant (p < 0.05) increase in data retrieval time compared to collocated storage. The system shows promise for becoming both a robust research picture archival and communications system working with the standard hospital PACS and an image post-processing environment that extends to other medical image modalities.

Optimal clustering of kinetic patterns on malignant breast lesions: comparison between K-means clustering and three-time-points method in dynamic contrast-enhanced MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for breast cancer diagnosis and treatment planning. Nevertheless, due to the multi-temporal nature of DCE-MRI data, the assessment of early stage breast cancer is a challenging task. In this study, we applied an unsupervised clustering approach and cluster validation technique to the analysis of malignant intral-tumoral kinetic curves in DCE-MRI. K-means cluster analysis was performed from real world malignant tumor cases and the data were transformed into an optimal number of reference patterns representative each cluster. The optimal number of clusters was estimated by a cluster validation index, which was calculated with the ratio of inter-class scatter to intra-class scatter. This technique then classifies tumor specific patterns from a given MRI data by measuring the vector distances from the reference pattern set, and compared the result from the k-means clustering with that from three-time-points (3TP) method, which represents a clinical standard protocol for analysis of tumor kinetics. The evaluation of twenty five cases indicates that optimal k-means clustering reflects partitioning intra-tumoral kinetic patterns better than the 3TP technique. This method will greatly enhance the capability of radiologists to identify and characterize internal kinetic heterogeneity and vascular change of a tumor in breast DCE-MRI.

Kinetic assessment of breast tumors using high spatial resolution signal enhancement ratio (SER) imaging

The goal of this study was to investigate the relationship between an empirical contrast kinetic parameter, the signal enhancement ratio (SER), for three-timepoint, high spatial resolution contrast-enhanced (CE) MRI, and a commonly analyzed pharmacokinetic parameter, kep, using dynamic high temporal resolution CE-MRI. Computer simulation was performed to investigate: 1) the relationship between the SER and the contrast agent concentration ratio (CACR) of two postcontrast timepoints (tp1 and tp2); 2) the relationship between the CACR and the redistribution rate constant (kep) based on a two-compartment pharmacokinetic model; and 3) the sensitivity of the relationship between the SER and kep to native tissue T1 relaxation time, T10, and to errors in an assumed vascular input function. The relationship between SER and kep was verified experimentally using a mouse model of breast cancer. The results showed that a monotonic mathematical relationship between SER and kep could be established if the acquisition parameters and the two postinjection timepoints of SER, tp1, tp2, were appropriately chosen. The in vivo study demonstrated a close correlation between SER and kep on a pixel-by-pixel basis (Spearman rank correlation coefficient=0.87+/-0.03). The SER is easy to calculate and may have a unique role in breast tissue characterization.

An evaluation of four parametric models of contrast enhancement for dynamic magnetic resonance imaging of the breast

This paper presents an empirical evaluation of the goodness-of-fit (GOF) of four parametric models of contrast enhancement for dynamic resonance imaging of the breast: the Tofts, Brix, and Hayton pharmacokinetic models, and a novel empiric model. The goodness-of-fit of each model was evaluated with respect to: (i) two model-fitting algorithms (Levenberg-Marquardt and Nelder-Mead) and two fitting tolerances; and (ii) temporal resolution. In the first case the GOF was measured using data from three dynamic contrast-enhanced (DCE) MRI data sets from routine clinical examinations: one case with benign enhancement, one with malignant enhancement, and one with normal findings. Results are presented for fits to both the whole breast volume and to a selected region of interest. In the second case the GOF was measured by first fitting the models to several temporally sub-sampled versions of a custom high temporal resolution data set (subset of the breast volume containing a malignant lesion), and then comparing the fitted results to the original full temporal resolution data. Our results demonstrate that under the various optimization conditions considered, in general, both the proposed empiric model and the Hayton model fit the data equally well and that both of these models fit the data better than the Tofts and Brix models.

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

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.

Prostate cancer: accurate determination of extracapsular extension with high-spatial-resolution dynamic contrast-enhanced and T2-weighted MR imaging--initial results

PURPOSE

To prospectively compare the sensitivity and specificity of high-spatial-resolution dynamic contrast material-enhanced magnetic resonance (MR) imaging with those of high-spatial-resolution T2-weighted MR imaging, performed with an endorectal coil (ERC), for assessment of extracapsular extension (ECE) and staging in patients with prostate cancer, with histopathologic findings as reference.

MATERIALS AND METHODS

The study was approved by the institutional internal review board; a signed informed consent was obtained. MR imaging of the prostate at 1.5 T was performed with combined surface coils and ERCs in 32 patients (mean age, 65 years; range, 42-78 years) before radical prostatectomy. High-spatial-resolution T2-weighted fast spin-echo and high-spatial-resolution dynamic contrast-enhanced three-dimensional gradient-echo images were acquired with gadopentetate dimeglumine. Dynamic contrast-enhanced MR images were analyzed with a computer-generated color-coded scheme. Two experienced readers independently assessed ECE and tumor stage. MR imaging-based staging results were compared with histopathologic results. For the prediction of ECE, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Staging accuracy was determined with the area under the receiver operating characteristic curve (AUC) by using the Wilcoxon-Mann-Whitney index of diagnostic accuracy.

RESULTS

The mean sensitivity, specificity, PPV, and NPV for assessment of ECE with the combined data sets for both readers were 86%, 95%, 90%, and 93%, respectively. The sensitivity of MR images for determination of ECE was significantly improved for both readers (>25%) with combined data sets compared with T2-weighted MR images alone. The combined data sets had a mean overall staging accuracy for both readers of 95%, as determined with AUC. Staging results for both readers were significantly improved (P<.05) with the combined data sets compared with T2-weighted MR images alone.

CONCLUSION

The combination of high-spatial-resolution dynamic contrast-enhanced MR imaging and T2-weighted MR imaging yields improved assessment of ECE and better results for prostate cancer staging compared with either technique independently.

Evaluating an optical-flow-based registration algorithm for contrast-enhanced magnetic resonance imaging of the breast

Dynamic contrast-enhanced magnetic resonance imaging studies of the breast are frequently degraded by patient motion. In order to correct for this, any registration algorithm must overcome two major challenges: the highly deformable nature of the breast itself and the need to remove changes in signal intensity due to patient motion whilst leaving potentially significant changes in signal intensity due to changes in contrast agent concentration unchanged. In this paper, we evaluate the use of a non-rigid registration method that uses optical flow equations to drive the displacement of a grid of control points. With conventional optical flow techniques it is assumed that changes in image intensity are solely due to motion, making it unsuitable for use with contrast-enhanced studies. The registration algorithm evaluated in this paper overcomes this problem by including an additional term to account for changes in image intensity. Studies simulating physiologically plausible deformations of the breast together with realistic changes in contrast-enhancement derived from patient studies demonstrate that the algorithm is capable of registering images to sub-voxel accuracy within minutes. This technique has now been successfully incorporated into a breast cancer screening protocol allowing registered images to be provided routinely to the radiologist immediately after the scanning session.

Monitoring breast cancer response to neoadjuvant systemic chemotherapy using parametric contrast-enhanced MRI: a pilot study

RATIONALE AND OBJECTIVES

Neoadjuvant systemic therapy (NST) is the standard treatment for locally advanced breast cancer and a common option for primary operable disease. It is important to develop standardized imaging techniques that can monitor and quantify response to NST enabling treatment tailored to each individual patient, and facilitating surgical planning. Here we present a high spatial resolution, parametric method based on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), which evaluates breast cancer response to NST.

MATERIALS AND METHODS

DCE-MRI examinations were performed twice on 17 breast cancer patients, before and after treatment. Seven sets of axial breast images were sequentially recorded at 1.5 Tesla applying a three-dimensional, gradient echo at a spatial resolution approximately 2 x 1.2 x 0.6 mm(3) and temporal resolution approximately 2 minutes, using gadopentate dimeglumine (0.1 mmol/kg wt). Image analysis was based on a color-coded scheme related to physiologic perfusion parameters.

RESULTS

A high Pearson correlation coefficient of 0.96 (P < .0001) was found between the histopathologic estimation of viable neoplastic tissue volume and the segmented volume of all the pixels demonstrating fast and steady state washout after NST (colored in light red and green). Segmentation of these pixels before and after NST indicated response in terms of reduced tumor volume and a parallel decrease in enhancement rate which reflects diminished transcapillary transfer of the contrast agent.

CONCLUSIONS

The use of a parametric MRI technique provided a means to standardize segmentation and quantify changes in the perfusion of breast neoplastic tissue in response to NST. Whether this technique can serve to predict breast cancer recurrence and survival rates requires further clinical testing.

Phosphocholine as a biomarker of breast cancer: Molecular and biochemical studies

The discovery of metabolic and molecular markers that help improving the detection and diagnosis of breast cancer is an important goal to be achieved. A high composite-choline signal in magnetic resonance spectra of breast lesions has been demonstrated to improve the accuracy of breast cancer diagnosis. In the present study we revealed the principal molecular and biochemical steps associated with the induction of choline metabolism and phosphocholine accumulation in human breast cancer cell-lines in comparison with normal human mammary epithelial cells. We found upregulation of the expression levels of specific choline transporters: organic cation transporter-2 and choline high affinity transporter-1, as well as of the enzyme choline kinase alpha in the cancerous cells in comparison with that in the normal mammary epithelial cells. The expression levels of choline transporter like-1, organic cation transporter-1 and choline kinase beta were similar in normal and cancerous cells. We further showed that choline transport rates and choline kinase activity indeed increased by several fold in the cancer cells leading to the elevation of phosphocholine. The results strongly suggest that phosphocholine can serve as a biomarker of breast cancer reflecting upregulation of specific choline transporters and choline kinase genes.

Evaluation of the three-time-point method for diagnosis of breast lesions in contrast-enhanced MR mammography

PURPOSE

To evaluate the three-time-point (3TP) method for diagnosis of breast lesions detected on contrast-enhanced MR mammography.

MATERIALS AND METHODS

MR imaging was performed in 40 women with 120 suspected breast lesions in mammography and/or sonography. The contrast kinetics was converted by 3TP software on a pixel-by-pixel basis into color-coded images. Lesion diagnosis was made by analysis of color intensity and color hue. The 3TP results were compared with the results of the region-of-interest (ROI) method. In 16 patients, we were able to correlate the results with histopathological findings.

RESULTS

The 3TP method could successfully be performed in all MR mammographies. Forty (33%) lesions had a diameter of less than 5 mm, 56 (47%) lesions between 5 and 10 mm, and 24 (20%) lesions were greater than 1 cm. Of all 120 lesions, 65 (54%) showed heterogeneous contrast enhancement. In 117 (97%) of all 120 lesions the results of ROI and the automated 3TP method were considered equivalent. However, in three lesions the manual ROI differed from the 3TP method. After a second, repeated manual ROI placement, we were able to confirm equivalent results with the 3TP images as well.

CONCLUSIONS

The 3TP method automatically and reliably converts contrast kinetic information of the entire breast into a color-coded image. The 3TP method presents kinetic information of the entire dynamic series in an easy-to-interpret format and this automated method may allow to forego time-consuming and sometimes subjective manual ROI placements. This method displays the heterogeneity of the contrast enhancement pattern often observed in malignant lesions and makes it usable as diagnostic criterion.

Functional magnetic resonance imaging for defining the biological target volume

Morphology as demonstrated by CT is the basis for radiotherapy planning. Intensity-modulated and adaptive radiotherapy techniques would greatly benefit from additional functional information allowing for definition of the biological target volume. MRI techniques include several which can characterize and quantify different tissue properties and their tumour-related changes. Results of perfusion MRI represent microvascular density and permeability; MR spectroscopy depicts particular metabolites; diffusion weighted imaging shows tissue at risk and tumour cellularity; while dynamic 3D acquisition (4D MRI) shows organ motion and the mobility of tumours within them.

Dynamic breast MRI: image registration and its impact on enhancement curve estimation

A novel algorithm for performing registration of dynamic contrast-enhanced (DCE) MRI data of the breast is presented. It is based on an algorithm known as iterated dynamic programming originally devised to solve the stereo matching problem. Using artificially distorted DCE-MRI breast images it is shown that the proposed algorithm is able to correct for movement and distortions over a larger range than is likely to occur during routine clinical examination. In addition, using a clinical DCE-MRI data set with an expertly labeled suspicious region, it is shown that the proposed algorithm significantly reduces the variability of the enhancement curves at the pixel level yielding more pronounced uptake and washout phases.

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

BACKGROUND

Tumor 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.

METHODS

Perfusion 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 (k(trans)) and the efflux transcapillary rate constant (k(ep)). 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.

RESULTS

The 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, k(trans) increased from low-grade DCIS to high-grade DCIS. Fibroadenomas were characterized uniquely by high k(trans) but low k(ep). Stepwise logistic regression selected k(trans) as the best predictor for distinguishing benign fibrocystic changes from IDC, yielding 93% sensitivity and 96% specificity.

CONCLUSIONS

The 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.

Multimodal imaging and computer assisted diagnosis for functional tumour characterisation

Radiological modalities, especially CT, mainly provide morphological and structural information with high spatial resolution covering large volumes. Novel developments, which are predominantly MR-based, also deliver 'functional' information, which can be used for individual characterisation of tumour biology. Both aspects and modalities, additionally complemented by ultrasound, have to be combined in the radiological workflow of cancer patients including volumetric visualisation, information extraction from multimodal imaging, quantitative surrogates, intelligent interpretation assistance and image-guided procedures. Based on volumetric visualisation and the generation of 3D+t maps, CAD tools have to address registration of different image series from different modalities, and extraction of quantitative surrogates. The latter will then serve tumour characterisation, therapeutic decision-making, image-guided procedures and efficacy evaluation.

Techniques for delivery and monitoring of TOOKAD (WST09)-mediated photodynamic therapy of the prostate: Clinical experience and practicalities

Photodynamic therapy of solid organs requires sufficient PDT dose throughout the target tissue while minimizing the dose to proximal normal structures. This requires treatment planning for position and power of the multiple delivery channels, complemented by on-line monitoring during treatment of light delivery, drug concentration and oxygen levels. We describe our experience in implementing this approach in Phase I/II clinical trials of the Pd-bacteriophephorbide photosensitizer TOOKAD (WST09)-mediated PDT of recurrent prostate cancer following radiation failure. We present several techniques for delivery and monitoring of photodynamic therapy, including beam splitters for light delivery to multiple delivery fibers, multi-channel light dosimetry devices for monitoring the fluence rate in the prostate and surrounding organs, methods of measuring the tissue optical properties in situ, and optical spectroscopy for monitoring drug pharmacokinetics of TOOKAD in whole blood samples and in situ in the prostate. Since TOOKAD is a vascular-targeted agent, the design and implementation of the techniques are different than for cellular-targeted agents. Further development of these delivery and monitoring techniques will permit full on-line monitoring of the treatment that will enable real-time, patient-specific and optimized delivery of PDT.

High-resolution magnetic resonance imaging of disparities in the transcapillary transfer rates in orthotopically inoculated invasive breast tumors

In vivo mapping of the transcapillary fluxes in tumors can help predict the efficacy of delivery of blood-borne anticancer drugs. These fluxes are primarily affected by the vascular permeability and the pressure gradients across the blood vessels' walls. We describe herein high-resolution dynamic contrast-enhanced magnetic resonance imaging of the influx and outflux transcapillary transfer rates in vivo in invasive MDA-MB-231 tumors orthotopically inoculated in severe combined immunodeficient mice. The tumors were noted for rapid growth, impaired drainage of fluid, and subsequent formation of cysts. Consequently, the time evolution of the contrast enhancement, induced by i.v. injection of Gadolinium diethylene-triamine-penta-acetate, exhibited two distinct patterns: transcapillary transfer in the cellular regions and simple diffusion in the cyst fluid. Both processes were analyzed at pixel resolution applying to each a physiological model and a corresponding algorithm. In the cellular region, the influx and outflux transcapillary transfer rates decreased during tumor growth; however, an increased disparity between the transfer constants was observed, with the outflux rate exceeding the influx rate. This quantitative spatial and temporal mapping of this disparity can provide a means to assess the physiological barriers to tracer delivery. It is hypothesized that both the increased disparity in transcapillary transfer rates and impaired fluid drainage in these tumors could arise from the development of interstitial hypertension.