The purpose of this study was to quantify microcirculation and microvasculature in breast lesions by pharmacokinetic analysis of Gd-DTPA-enhanced MRI series. Strongly T 1 -weighted MR images were acquired in 18 patients with breast lesions using a saturation-recovery-TurboFLASH sequence. Concentrationtime courses were determined for blood, pectoral muscle, and breast masses and subsequently analyzed by a two-compartment model to estimate plasma flow and the capillary transfer coefficient per unit of plasma volume (F/V P , K PS /V P ) as well as fractional volumes of the plasma and interstitial space (f P , f I ). Breast cancer represents the most common malignancy in females, constituting a major health problem, particularly in developed countries. Conventional X-ray mammography, supplemented by sonography, has been proven to be the primary modality for breast imaging. However, despite the important role played by X-ray mammography as a diagnostic and screening tool, it suffers especially from a limited specificity and thus leads to unnecessary breast biopsies. Therefore, new noninvasive imaging strategies are required for discriminating between benign and malignant breast masses in women with equivocal findings in conventional breast imaging or women with breast implants, previous therapy, or predisposing mutations of tumor suppressor genes. Besides positron emission tomography (PET), dynamic contrast-enhanced MRI is the most promising approach providing information on tumor pathophysiology for improved diagnosis and management of breast lesions.As summarized in recent review articles on dynamic MR mammography (1-3), the kinetics of signal variation in breast lesions after injection of a paramagnetic contrast medium (CM) represents an important criterion for the detection and differentiation of suspicious breast masses. According to the analysis presented by Kuhl et al. (4), a persisting (accumulating) enhancement pattern or a washout phenomenon over a period of time of about 5-6 min after the initial perfusion phase is a strong indicator for benign and malignant lesions, respectively.Although the histopathological basis of the different enhancement patterns in breast masses is not yet fully understood, it is well known that angiogenesis, i.e., the formation of new vessels, is an important aspect (5,6). Microvessels in solid tumors exhibit a series of severe structural and functional abnormalities: They are often dilated, tortuous, elongated, and saccular and show an incomplete or even missing endothelial lining and an interrupted basement membrane. Moreover, there is an anarchic vascular organization of microvessels accompanied by significant arterio-venous shunt flow (6).To gain further insight into contrast enhancement in breast lesions and its histopathological basis, it is necessary to study tumor microvasculature and microcirculation in more detail in vivo. To this end, various MR studies were performed to quantify different aspects of contrast enhancement using either simple compartment models or princip...

It was the aim of this methodology-oriented clinical pilot study to compare the potential of dynamic MRI and 2-[18F]fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) for the detection and characterization of breast cancer. Fourteen women with suspicious breast lesions were examined. The MRI data were acquired with a turbo fast low-angle shot sequence and analyzed using a pharmacokinetic model. Emission data were detected in the sensitive 3D modus, iteratively reconstructed, and superimposed onto corresponding transmission images. In the 14 patients, 13 breast masses with a suspicious contrast enhancement and FDG uptake were detected. For these lesions, no statistically significant correlation between evaluated MR and PET parameters was found. Of the 9 histologically confirmed carcinomas, 8 were correctly characterized with MRI and PET. Two inflammatory lesions were concordantly classified as cancer. Moreover, dynamic MRI yielded another false-positive finding. In 6 patients, PET detected occult lymph node and/or distant metastases. Although both functional imaging techniques provide independent tissue information, the results concerning the diagnosis of primary breast lesions were almost identical. An advantage of PET, however, is its ability to localize lymph node involvement and distant metastases as an integral part of the examination.

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The present study aims at (i) the evaluation of the performance of a rigid and of an elastic matching algorithm for the coregistration of dynamic magnetic resonance (MR) images visualizing the female breast, and (ii) the evaluation of the mutual information (MI) as a matching criterion. To this end, ten patient data sets were analyzed. The comparison was performed with respect to the achieved increase in the MI and by visual inspection of the dynamic image series in a continuous film sequence ((cine mode). In most cases, the achieved increase in MI by elastic image registration is much higher than that achieved by rigid registration. Only for three of the ten data sets could the MI be increased by rigid image registration to a similar or even larger degree than by elastic image registration. Taking into account the results of the visual inspection of the rigid and elastic matched data sets, however, the elastic match leads to equal or better results for all data sets. Therefore, elastic matching is the gold standard for the registration of dynamic MR mammographic images of the female breast. The comparison of the increase in MI and the visual inspection further shows that the visual impression agrees in most cases with the result of the calculation of the MI. Therefore, the MI proves to be a suitable matching criterion for the type of data sets studied.

Dynamic magnetic resonance imaging (MRI) carried out with paramagnetic contrast media has been proven to increase sensitivity and specificity in the detection of breast cancer. Due to movements of the patients and changes in the shape of the breasts during the measurement period, a coregistration (matching) of the acquired data volumes is necessary to obtain higher accuracy for the localization of lesions. In this study, an algorithm for the elastic matching of dynamic MRI volume data is presented. The approach includes automatic feature extraction along with the analysis of corresponding features between the data sets. The matching is actually slice‐oriented, even though information on displacement vectors in adjacent slices is taken into account. An extension of the procedure to fully three‐dimensionally (3D) matching is straight forward. Up until now, the approach has been applied to 20 dynamic MRI studies. The matching time for two image data sets with 256 × 256 × 15 voxels each was about 4 min using a PC (Pentium Pro, 200MHz). Magn Reson Med 43:9–16, 2000. © 2000 Wiley‐Liss, Inc.

Quantitative classifiers can support the radiologist in the diagnosis of breast lesions.

The insufficient number of projections and the statistics of radioactive decay are supposed to lead to different textures in the images reconstructed by the diverse algorithms used in positron emission tomography (PET). In our study, four reconstruction methods were examined, including the filtered backprojection and three algebraic approaches. Grey-level morphological operators were used to extract the texture. To quantify the observations, we used the texture parameters directionality, fractal dimension, and lacunarity. By increasing the number of iteration steps, each of the algebraic reconstruction methods evolve the texture from coarse to fine granularities, but surprisingly, during the iteration process all methods follow a quite similar 'trail' of possible textures within the active zone. The texture of the termination points of the movement have been compared with the result that the 'hils' and 'valleys' of the activity distribution are located in the same positions. The texture derived from the filtered backprojection is included in the set of textures produced by the algebraic methods. Artefacts are restricted to zones without activity. We found that the texture is independent of the number of counts when more than ten counts are registered in each pixel within the examined region of interest. A high reliability in the reconstructed images is given. All methods allow texture based tissue classification.