الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Accurate assessment of renal lesions is important for establishing whether tumors require surgical intervention or not. CT and MRI are the primary investigative tools for diagnosing and characterization of cystic or solid renal masses discovered accidentally by ultrasonography. Renal lesions are commonly evaluated using contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI), with attempts to identify enhancing soft tissue foci suggestive of malignancy. Despite all efforts false-negative results can occur when imaging substantially necrotic or cystic malignant lesions, which may be mistakenly written off as complex renal cysts because of a lack of extensive enhancement. Diffusion-weighted imaging (DWI) is a functional technology that develops image contrast based on the inhibition of migration of water molecules in tissues by tissue microstructures. As a result of the dense cellularity, malignant tissue has restricted diffusion, which is reflected by a low mean apparent diffusion coefficient (ADC). Diffusion-weighted imaging (DWI) sequences characterize the restriction of random (Brownian) movement of water molecules within tissues. The strength of diffusion weighting is characterized by the b value. Through linear regression, images taken at various b-values can be used to calculate the apparent diffusion coefficient (ADC) in a particular region of interest. Restriction to the molecular diffusion in neoplastic tissues can be related to the greater cellular density in the tissues, generated by the high index of neoplastic replication with a consequent reduction in the width of intercellular spaces, and to the ultrastructural alteration of the kidney tissue. DW-MRI can be evaluated in two ways: qualitatively, by visual assessment of signal intensity, and quantitatively, by measurement of the apparent diffusion coefficient (ADC). The ADC value has been conventionally calculated from a small region of interest (ROI) arbitrarily positioned in a small part of the targeted lesion, it was advocated that detailed profiles of lesions diffusion environments should be analyzed from the ROI contoured around the targeted lesion. Diffusion-weighted imaging (DWI) is frequently used in cranial MRI studies and has shown potential for the characterization of lesions such as acute cerebral infarctions, intracranial tumors, various infectious diseases and metabolic disorders. The role of DWI is limited outside the central nervous system, owing to its inherent extreme sensitivity to motion, such as that related to respiration, peristalsis and artifacts, thus resulting in a high signal to noise ratio. With the development of advanced MR technology and the use of faster robust sequences, better quality has been obtained in abdominal imaging. The main aim of this study was to evaluate the role of Diffusion Weighted MR Imaging (DW-MRI) supplemented with ADC values in characterization of different renal masses. This cross-sectional study was conducted, included thirty (30) patients presented to the diagnostic radiology department in Tanta University Hospitals with signs and symptoms of renal masses either by clinical or previous radiological examination. The duration of the study ranged from 6-12 months. The main findings of the study revealed that: The mean age was 50.77 ± 2.79 years. There were 56.57% males and 43.33% females. There were 60% had hematuria. There were 83.33% had loin pain. There were 66.67% had heaviness. There were 26.67% had fever. There were 13 participants had clear renal cell carcinoma with mean ADC 1.32 ± 0.15. There were 7 participants had papillary renal carcinoma with mean ADC 1.33 ± 0.13. There were 6 participants had oncocytoma with mean ADC 1.3 ± 0. There were 4 participants had angiomyolipoma with mean ADC 0.76 ± 0.13. As regard Diffusion-weighted imaging (DWI) sequence parameters; the TR/TE was 3150/55. The thickness was 5 mm. The FOV was 330 mm. The matrix was 96 X 94. ADC can significantly discriminate malignant masses from benign (AUC= 0.82, P value<0.001) at cut off >1.29 (x10²mm²/s) with 70% sensitivity, 40% specificity, 70% PPV and 40% NPV. Based on our findings, we recommend for further studies on larger sample size and on large geographical scale to emphasize our conclusion.