Variability of renal apparent diffusion coefficients: limitations of the monoexponential model for diffusion quantification.
meta_analysis · Level I
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- Record sourced from PubMed, PMID 20089719.
- Also identified by DOI 10.1148/radiol.09090891 and PMC identifier 2851010.
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Abstract
To investigate whether variability in reported renal apparent diffusion coefficient (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. 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 reference curves at the various b values used in 19 published studies of normal kidneys (reported ADC = [2.0-4.1] x 10(-3) mm(2) / sec for cortex and [1.9-5.1] x 10(-3) mm(2) / sec for medulla) and then fitted the resampled signals by monoexponential model to produce "predicted" ADC. Correlation plots were used to compare the predicted ADC values with the published values obtained with the same b values. Significant 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. 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 coefficient quantification, data for monoexponential analysis should be acquired at a fixed set of b values or a biexponential model should be used. (c) RSNA, 2010.
Medical subject headings
- Diffusion Magnetic Resonance Imaging
- Kidney
- Models, Statistical