Background: Obstructive nephropathy is a common clinical disease. Objectives: To explore the value of Diffusion Tensor Imaging (DTI) in obstructive nephropathy. Materials and Methods: Forty healthy Sprague-Dawley (SD) rats were examined in this study. Thirty-two animals underwent complete obstruction of the left ureter, while eight animals underwent a sham surgery. Magnetic resonance Imaging (MRI) was performed before surgery and within different intervals after surgery. Eight rats from the experimental group and two rats from the sham group were used in each interval. Following MRI, the animals were sacrificed and sent for medical examinations. The scanning sequences included positioning, transverse T2-weighted (T2W), coronal, and coronal DTI sequences. Image postprocessing was performed after DTI to measure DTI parameters, including apparent Diffusion coefficient (ADC) and fractional anisotropy (FA), and to reconstruct DTI fiber traces. One-way analysis of variance was used to compare the parameters between the cortex and medulla and between different intervals. Results: The fiber tracing showed that the obstructed renal fiber bundles were sparse and disordered. The ADC and FA values of the renal cortex, extrarenal medulla, and inner medulla decreased with prolonged hydrops and were negatively correlated with the expression of alpha-smooth muscle actin (-SMA) and the renal tubulointerstitial lesion grade (r < 0, P < 0. 001). Comparison of the cortex, extrarenal medulla, and inner medulla showed the following trends for the ADC and FA values: cortex > extrarenal medulla > inner medulla and cortex < extrarenal medulla < inner medulla, respectively. Conclusions: DTI in obstructive nephropathy not only can reflect the degree of renal interstitial fibrosis and accurately indicate the renal function, but also can provide information regarding renal blood perfusion, water metabolism, and ultrastructural changes.

Rapidly evolving MR technology has allowed better understanding of structure and function of the human brain. Diffusion weighted MRI was developed two decades ago and it is now well established in diagnosis of acute ischaemia in patients with stroke. Diffusion Tensor MRI uses the same principles but takes a step further allowing us to measure magnitude of the Diffusion along different directions. This lead to the development of Diffusion Tensor tractography, a technique by which major neural pathways in the living brain can be visualized. There is a growing interest in exploring possible use of these techniques in clinical neurology and psychiatry. This article aims to review the principles of this technique and recent discoveries which may help us to better understand neurological and psychiatric disorders.

Introduction: The pathological changes associated with multiple sclerosis (MS) produce changes in uniformity of the neural networks of brain white matter that result in more perceptible changes on Diffusion Tensor Imaging (DTI). Increase in mean diffusivity (MD) and reduction in fractional anisotropy (FA) on DTI seen in MS patients may be due to the degradation of membrane or other cell structures. The aim of this study was to investigate the pathological changes made in the brains of MS patients using the DTI technique.Materials & methods: This study was performed on 15 patients with multiple sclerosis. To investigate the location of plaques and normal appearing white matter (NAWM) some routine protocols for the brain, including T2-FLAIR and T2, were taken and to normalize the images of DTI, the T1 MPRAGE protocol was applied. After image processing using SPM, FSL, and MedINRIA software, the data were analyzed with the Mann-Whitney test.Findings: The results showed that there is a significant difference between the mean of MD (mean=4.3±1.01) and FA (mean=0.24±0.05) values in MS plaques and the mean of MD (mean=2.1±1.1) and FA (mean=0.55±0.56) values in the normal white matter (NWM) tissue of the control group (P=0.00001). Comparing the data obtained from the NAWM tissue with expanded disability status scale (EDSS) of patients showed that patients with higher EDSS show higher MD values (P=0.004) and lower FA values than patients with lower EDSS (P=0.001).Discussion & Conclusion: This study showed that factors of MD and FA in DTI technique can provide valuable information as Imaging biomarkers about the MS plaques.

Background: Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease that affects the dopamine-containing neurons. In this study, the role of the Diffusion Tensor Imaging (DTI) method was investigated in the detection of PD. Objectives: The purpose of this study was to investigate the microstructural damage of the brain's white matter in PD using a non-invasive DTI technique. Methods: Twenty patients with PD were studied with comprehensive clinical assessments and DTI data. Also, 10 normal subjects were investigated. Fractional anisotropic (FA) and mean diffusivity (MD) values were calculated by drawing region of interest (ROI) on eight distinctive areas of the brain. Results: The level of FA and MD in substantia nigra (SN) was significantly different between the PD and healthy control (HC) groups. Also, differences were found in DTI parameters between PD and HC groups in some regions, such as genu, anterior limb of internal capsule (ALIC), splenium, and putamen. Conclusions: To summarize, DTI as a non-invasive method can be useful in the detection of Parkinson's disease.

Background: Brain segmentationfromDiffusion TensorImaging (DTI) into white matter (WM), gray matter (GM), andcerebrospinal fluid (CSF) with acceptable results is subjected to many factors.Objectives: The most important issue in brain segmentation from DTI images is the selection of suitable scalar indices that best describe the required tissue in the images. Specifying suitable clustering method and suitable number of clusters of the selected method are other factors which affects the segmentation process significantly.Materials and Methods: The segmentation process is evaluated using four different clustering methods with different number of clusters where some DTI scalar indices for 10 human brains are processed.Results: The aim was to produce results with less segmentation error and a lower computational cost while attempting to minimizing boundary overlapping and minimizing the effect of artifacts due to macroscale scanning.Conclusion: The volume ratios of the best produced outputs with respect to the total brain size are 16.7% 3.53% for CSF, 35.05%  1.13% for WM, and 48.2%2.88% for GM.

Introduction: The most common primary tumors of brain are gliomas and tumor grading is essential for designing proper treatment strategies. The gold standard choice to determine grade of glial tumor is biopsy which is an invasive method. The purpose of this study was to investigate the role of fiber density index (FDi) by means of Diffusion Tensor Imaging (DTI) (as a noninvasive method) in glial tumor grading.Methods: A group of 20 patients with histologically confirmed diagnosis of gliomas were evaluated in this study. We used a 1.5 Tesla MR system (AVANTO; Siemens, Germany) with a standard head coil for scanning. Multidirectional Diffusion weighted Imaging (measured in 12 no ncollinear directions), and T1 weighted no nenhanced were performed for all patients. We defined two regions of interest (ROIs); 1) White matter fibers near the tumor and 2) Similar fibers in the contralateral hemisphere.Results: FDi of the low-grade gliomas was higher than those of high-grade gliomas, which was significant (P=0.017). FDi ratio (ratio of fiber density in vicinity of the tumor to homologous fiber tracts in the contralateral hemisphere) is higher in low-grade than high-grade tumors, (P=0.05). In addition, we performed ROC (receiver operating characteristic) curve and the area under curve (AUC) was 0.813 (P=0.013).Conclusion: Our findings prove significant difference in FDi near by low-grade and high-grade gliomas. Therefore, FDi values and ratios are helpful in glial tumor grading.

Background: Prostate cancer is the third leading cause of death and is the most common cause of cancer in elderly men. Regarding to the low accuracy of screening methods such as prostate-specific antigen (PSA), Digital Rectal Examination (DRE) and trans rectal ultrasound (TRUS) in detection and localization of tumor, Magnetic Resonance Imaging (MRI) and Diffusion Weighted Imaging (DWI) attracted many attentions in the past years. DWI reveals micro-molecular Diffusion, which is the Brownian motion of the spins in biologic tissues. This technique can delineate pathologic lesions with high tissue contrast against generally suppressed background signal. In this paper, the value of DWI in detection of prostate cancer is studied.Methods: In this cross-sectional study, the studied population are suspicious patients to prostate cancer based on high Prostatic Specific Antigen level or abnormal Digital Rectal Examination who refered for prostate biopsy to radiology department of Hazrate- Rasoul Hospital during the year 2011. The results of DWI are compared to biopsy results for all patients.Results: Eighty five patients are selected. The DWI sensitivity in detecting of prostate cancer is 100%, specificity 97.1% and positive and negative predictive values are 89.5% and 100%, respectively. The results showed that if DWI reports the prostate cancer as negative, the result was highly reliable and if it reports as positive, although the report was not 100% reliable, but it still had high reliability, more than 90%.Conclusion: DWI had high accuracy in detecting prostate cancer for patients with cancer. Also the accuracy of this method for patients without prostate cancer was acceptable compared to the other common methods.