Objectives This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. Methods An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. Results Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. Discussion This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding.

Purpose:To investigate whether variability in reported renal apparent diffusion coeffi cient (ADC ) values in literature can be explained by the use of different diffusion weightings ( b values) and the use of a monoexponential model to calculate ADC . Materials and Methods:This prospective study was approved by institutional review board and was HIPAA-compliant, and all subjects gave written informed consent. Diffusion-weighted (DW) imaging of the kidneys was performed in three healthy volunteers to generate reference diffusion decay curves. In a literature meta-analysis, the authors resampled the ref- Results:Signifi cant correlation was found between the reported and predicted ADC values for whole renal parenchyma ( R 2 = 0.50, P = .002), cortex ( R 2 = 0.87, P = .0002), and medulla ( R 2 = 0.61, P = .0129), indicating that most of the variability in reported ADC values arises from limitations of a monoexponential model and use of different b values. Conclusion:The use of a monoexponential function for DW imaging analysis and variably sampled diffusion weighting plays a substantial role in causing the variability in ADC of healthy kidneys. For maximum reliability in renal apparent diffusion coeffi cient quantifi cation, data for monoexponential analysis should be acquired at a fi xed set of b values or a biexponential model should be used.q RSNA, 2010

Purpose To compare fitting methods and sampling strategies, including the implementation of an optimized b-value selection for improved estimation of intravoxel incoherent motion (IVIM) parameters in breast cancer. Methods Fourteen patients (age, 48.4 ± 14.27 years) with cancerous lesions underwent 3 Tesla breast MRI examination for a HIPAA-compliant, institutional review board approved diffusion MR study. IVIM biomarkers were calculated using “free” versus “segmented” fitting for conventional or optimized (repetitions of key b-values) b-value selection. Monte Carlo simulations were performed over a range of IVIM parameters to evaluate methods of analysis. Relative bias values, relative error, and coefficients of variation (CV) were obtained for assessment of methods. Statistical paired t-tests were used for comparison of experimental mean values and errors from each fitting and sampling method. Results Comparison of the different analysis/sampling methods in simulations and experiments showed that the “segmented” analysis and the optimized method have higher precision and accuracy, in general, compared with “free” fitting of conventional sampling when considering all parameters. Regarding relative bias, IVIM parameters fp and Dt differed significantly between “segmented” and “free” fitting methods. Conclusion: IVIM analysis may improve using optimized selection and “segmented” analysis, potentially enabling better differentiation of breast cancer subtypes and monitoring of treatment.

Diffusion-weighted imaging (DWI) involves data acquisitions at multiple b values. In this paper, we presented a method of selecting the b values that maximize estimation precision of the biexponential analysis of renal DWI data. We developed an error propagation factor for the biexponential model, and proposed to optimize the b-value samplings by minimizing the error propagation factor. A prospective study of four healthy human subjects (eight kidneys) was done to verify the feasibility of the proposed protocol and to assess the validity of predicted precision for DWI measures, followed by Monte Carlo simulations of DWI signals based on acquired data from renal lesions of 16 subjects. In healthy subjects, the proposed methods improved precision (P = 0.003) and accuracy (P < 0.001) significantly in region-of-interest based biexponential analysis. In Monte Carlo simulation of renal lesions, the b-sampling optimization lowered estimation error by at least 20–30% compared with uniformly distributed b values, and improved the differentiation between malignant and benign lesions significantly. In conclusion, the proposed method has the potential of maximizing the precision and accuracy of the biexponential analysis of renal DWI.

A three-compartment model is proposed for analyzing magnetic resonance renography (MRR) and computed tomography renography (CTR) data to derive clinically useful parameters such as glomerular filtration rate (GFR) and renal plasma flow (RPF). The model fits the convolution of the measured input and the predefined impulse retention functions to the measured tissue curves. A MRR study of 10 patients showed that relative root mean square errors by the model were significantly lower than errors for a previously reported three-compartmental model (11.6% ؎ 4.9 vs 15.5% ؎ 4.1; P < 0.001). GFR estimates correlated well with reference values by 99m Tc-DTPA scintigraphy (correlation coefficient r ‫؍‬ 0.82), and for RPF, r ‫؍‬ 0.80. Parameter-sensitivity analysis and Monte Carlo simulation indicated that model parameters could be reliably identified. Key words: computed tomography; glomerular filtration rate; impulse retention function; magnetic resonance renography; renal plasma flow MR renography (MRR) and computed tomography renography (CTR) are increasingly used for noninvasive measurement of single-kidney function (1-7). These dynamic imaging techniques record the transit of a tracer, such as Gd-DTPA or iodinated contrast agents, from the aorta through the renal system. Tracer activity versus time curves can then be derived for intrarenal regions such as renal cortex, medulla, and collecting system. Design of an appropriate physiologic model is an essential part of accurate quantification of renal function (1,2).Several models have been proposed to estimate glomerular filtration rate (GFR) from MRR (3-6) and CTR (7). Baumann and Rudin (3) computed the GFR from the medullary uptake of the tracer using the cortical concentration as the input function. Another method (4) used a PatlakRutland plot to estimate GFR from the clearance of the tracer from the vascular compartment. This approach used whole-kidney concentration, obviating the need for regional segmentation of the kidneys. Both of these methods ignored the outflow of the tracer, and the results can be biased by improper selection of the "upslope" interval. Annet et al. (5) extended these techniques to account for tracer leaving the nephron space, thus enabling fitting of the model to measured data over a longer time period. All of these models assume instantaneous mixing of tracer within every compartment.More recently, models have been proposed with the aim of extending physiologic measures beyond GFR. Krier et al. (7) represented the cortex and medulla curves as extended gamma-variate functions with parameters shown to yield renal plasma flow (RPF) and tubular transit times in addition to GFR. GFR and RPF measures were validated against the reference values in pig model using CT renography. Hermoye et al. (8) determined RPF and GFR in rabbits from the cortical impulse response function by numerical deconvolution of renal cortical enhancement curves. The impulse response function exhibited three sequential peaks presumed to reflect the contrast in glomeruli, pro...

Intravoxel incoherent motion parameters fp and Dt can discriminate renal tumor subtypes. Perfusion fraction demonstrates good correlation with CIAUC60 and can assess degree of tumor vascularity without the use of exogenous contrast agent.

Renal function is characterized by different physiologic aspects, including perfusion, glomerular filtration, interstitial diffusion and tissue oxygenation. MRI shows great promise in assessing these renal tissue characteristics noninvasively. The last decade has witnessed a dramatic progress in MRI techniques for renal function assessment. This article briefly describes relevant renal anatomy and physiology, reviews the applications of functional MRI techniques for the diagnosis of renal diseases, and lists unresolved issues that will require future work.

Established as a method to study anatomic changes, such as renal tumors or atherosclerotic vascular disease, magnetic resonance imaging (MRI) to interrogate renal function has only recently begun to come of age. In this review, we briefly introduce some of the most important MRI techniques for renal functional imaging, and then review current findings on their use for diagnosis and monitoring of major kidney diseases. Specific applications include renovascular disease, diabetic nephropathy, renal transplants, renal masses, acute kidney injury and pediatric anomalies. With this review, we hope to encourage more collaboration between nephrologists and radiologists to accelerate the development and application of modern MRI tools in nephrology clinics.