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It is final pathway in the progression of chronic kidney disease regardless of the initial insult and lead to irreversible kidney damage occurs and the kidney decrease in size ( 3). Renal fibrosis is the histologic hallmark of CKD. However, these biochemical markers are insensitive to early renal injury and they can only assess the global renal function but not insight of the morphological change of the kidney. Recently, Symmetric dimethylarginine is routinely used as a more sensitive biomarker than creatinine in estimating GFR. The International Renal Interest Society (IRIS) developed the guidelines for the staging of CKD based on the serum creatinine concentration, proteinuria, and systemic blood pressure. In veterinary medicine, the diagnosis and staging of chronic kidney disease (CKD) are based on the detection of structural change and renal dysfunction ( 1, 2). A combination of b = 0, 100, and 800 s/mm 2 can be used for ADC measurements when multiple b-values are not available in dogs. The results of this study indicated that DWI MRI using multiple b-values is feasible for the measurement of ADC and IVIM parameters with high reproducibility and repeatability in the kidneys of healthy dogs. The ADC obtained from a b-value combination of 0, 100, and 800 s/mm 2 had the highest intraclass correlation coefficient with the ADC from nine b-values. All the ADC, D, D *, and f p values measured from the renal cortex, medulla, and the entire kidney had excellent interobserver and intraobserver reproducibility, and test-retest repeatability. ADC values were measured using 10 different b-value combinations consisting of three b-values each, and were compared to the ADC obtained from nine b-values. Interobserver and intraobserver reproducibility, and test-retest repeatability of the measurements were calculated. In this experimental study, the ADC, pure diffusion coefficient (D), pseudodiffusion coefficient (D *), and perfusion fraction ( f p) were measured from both kidneys in nine healthy beagles using nine b-values (b = 0, 50, 70, 100, 150, 200, 500, 800, and 1,000 s/mm 2) twice with a 1-week interval between measurements. The purpose of this study was to assess the apparent diffusion coefficient (ADC) and the intravoxel incoherent motion model (IVIM) parameters of a normal kidney in healthy dogs, to evaluate the effect of b-value combinations on the ADC value, and the reproducibility and test-retest repeatability in monoexponential and IVIM analysis. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.Diffusion-weighted imaging (DWI) magnetic resonance imaging can evaluate alterations in the microstructure of the kidney. Rician bias correction diffusion MRI noise prostate. The proposed composite fitting approach permits accurate parameter estimation even in typical clinical scenarios with low SNR, which significantly simplifies comparison of complex diffusion parameters among studies. OBSIDIAN is a novel, alternative, simple to implement approach for rapid Rician bias correction applicable in any case where differences between true signal decay and underlying model function can be considered negligible in comparison to noise. For patient data, good agreement with high SNR reference data of diffusion in prostate is achieved. Increased accuracy in parameter prediction in a low signal-to-noise ratio (SNR) scenario is ideally achieved by using a composite of multiple signal decays from neighboring voxels as input for the algorithm. Model simulations show that the Rician bias correction algorithm is fast, with an accuracy and precision that is on par to model-based MLE and direct fitting in the case of pure Gaussian noise. A multidirectional analysis was performed with publically available brain data. The feasibility of the method is evaluated and compared to maximum likelihood estimation (MLE) for diffusion signal decay simulations and diffusion-weighted images of the prostate considering 21 linearly spaced b-values from 0 to 3000 s/mm 2. A precomputed function that relates absolute residuals between measured signals and model fit to σ g is used to iteratively estimate σ g. Correction of Rician signal bias in magnitude MR images.Ī model-based, iterative fitting procedure is used to simultaneously estimate true signal and underlying Gaussian noise with standard deviation σ g on a pixel-by-pixel basis in magnitude MR images.