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ADC and to a lesser extent T2 are good indicators of cell density. Because of the potential link with Gleason score, MRI derived parameters may have a prognostic role with regard to potential metastatic activity and tumor aggressiveness.

Texture analysis was applied to high-resolution, contrast-enhanced (CE) images of the breast to provide a method of lesion discrimination. Significant differences were seen between benign and malignant lesions for a number of textural features, including entropy and sum entropy. Using logistic regression analysis (LRA), a diagnostic accuracy of A z ‫؍‬ 0. 80 Key words: texture analysis; breast imaging; contrast enhancement; co-occurrence matrices; image processing A fundamental goal of any diagnostic imaging investigation is tissue classification. Contrast-enhanced (CE) MRI of the breast has excellent sensitivity (1-3), but the reported specificity has varied greatly due to the rapid enhancement of fibroadenomas and some radial scars, in addition to the swift contrast uptake evident in malignant tumors. Various methods to improve specificity have been suggested, such as pharmacokinetic modeling of the time course of contrast enhancement (4,5). Other investigations have concentrated on refining methods of empirical analysis (6,7). However, these methods either aggregate data from the whole lesion or limit data sampling to specific areas of the lesion, and as such disregard morphological and textural information.Until recently, little attention had been paid to the diagnostic potential of texture analysis of MR images. When radiologists make a diagnosis, they employ the local properties of the tissue of interest in their assessment. Although visual assessment of texture is highly subjective, it is known to be a particularly sensitive means of determining pathology (8). Texture analysis is an attempt to quantify and emulate the expert eye of the radiologist. Unfortunately, the texture of an image is an ill-defined property, and texture analysis is a generic name for a series of techniques used to quantify spatial variation of the gray tones in an image. Various textural algorithms have been proposed, including the spatial gray-level dependence method, fractal methods, and Markov random field models (9). The most commonly used statistical technique is the spatial gray-level dependence matrix method proposed by Haralick et al. (10), because of its ability to study the second-order statistics of pixels at different spacings and angles. In comparative studies this method was found to provide as much discriminatory power as other techniques (11), and it performs well for small regions.Texture analysis has previously been applied to a limited extent in MRI. Kjaer et al. (12) reported good discrimination between normal brain tissues, but found texture analysis to be less successful in discriminating between benign and malignant tumor growth. Other such work in the brain has been published (8,13), and a classification rate of 91% was detailed in a study of Alzheimer's disease (14). Applications have also been reported in MR studies of prostate (15), skeletal muscle (16), and bone (17).With regard to breast disease, it has been suggested that ultrasonic image texture analysis could be used to reduce the number of benign l...

In this study, diffusion-weighted images of the human prostate were successfully obtained, enabling quantification of apparent diffusion coefficients (ADCs) in normal and pathologic regions. A dual acquisition fast spin-echo sequence was used for accurate T 2 calculation. T 2 values were significantly higher in the peripheral zone than the central gland (P ‫؍‬ 0.015). No significant correlations were found in either normal or pathologic tissue between ADC values and relaxation rates for all three gradient directions and the orientationally averaged water diffusion coefficient. Evidence suggesting that diffusional anisotropy is present in normal prostatic tissue is also detailed, with significant differences noted between the z-component and both the x-and y-components of the ADC for peripheral zone (P < 0.040) and central gland (P < 0.001 Over the past few years MR imaging of the human prostate has become more prevalent. However, due to the similarity in signal intensity between prostatic carcinoma and benign prostatic hyperplasia (BPH) on T 2 -weighted imaging, the usefulness of conventional MRI is reduced, particularly for the 35% of tumors which arise within the central gland (1). It is also recognized that unenhanced MRI can both under-and overestimate tumor volume when compared with pathological specimens. Lencioni et al. (2) obtained volume measurements that were only accurate to within 50% of the pathological volume. A recent review suggested that generalized use of MR imaging for tumor staging was not recommended, although MR did become cost-effective for men with moderate or high prior probability of extracapsular disease (3).Many authors have suggested that the use of dynamic contrast-enhanced imaging may improve delineation between conditions, since neovascularity is an independent indicator of pathological state (4 -7). Significant differences have been noted for various pharmacokinetic parameters, between benign and malignant disease, although patient numbers are often small (6,8). Various workers have explored the further addition of proton MR spectroscopy to improve clinical efficacy. Recently, Swanson et al. (9) have shown the potential of J-resolved spectroscopy of the prostate in obtaining additional physiologic information.An alternative approach may involve the utilization of diffusion-weighted imaging, which has seen increasing clinical relevance in the brain. A high degree of correlation between the trace of the diffusion tensor (Trace[D] and R 2 (1/T 2 ) has been noted during brain maturation in kittens (10). However, studies of stroke and ischemia have shown that there is a rapid decrease in Trace [D] with no detectable changes in T 2 data (11,12). These effects are often attributed to changes in extracellular volume fraction and increased tortuosity of the extracellular space. Good agreement of the histological measurement of infarct size with the total area of decreased apparent diffusion coefficient (ADC) has also been demonstrated in a rat model (11).MR diffusion-weighted imaging h...