Dataset Information

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit.

ABSTRACT: PURPOSE:To evaluate if a three-component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue. MATERIALS AND METHODS:Ten healthy volunteers were examined at 3T, with T2 -weighted imaging, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM). Diffusion tensor parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained by iterative weighted linear least squares fitting of the DTI data and mono-, bi-, and triexponential fit parameters (D1 , D2 , D3 , ffast2 , ffast3 , and finterm ) using a nonlinear fit of the IVIM data. Average parameters were calculated for three regions of interest (ROIs) (cortex, medulla, and rest) and from fiber tractography. Goodness of fit was assessed with adjusted R2 ( Radj2) and the Shapiro-Wilk test was used to test residuals for normality. Maps of diffusion parameters were also visually compared. RESULTS:Fitting the diffusion signal was feasible for all models. The three-component model was best able to describe fast signal decay at low b values (b < 50), which was most apparent in Radj2 of the ROI containing high diffusion signals (ROIrest ), which was 0.42?±?0.14, 0.61?±?0.11, 0.77?±?0.09, and 0.81?±?0.08 for DTI, one-, two-, and three-component models, respectively, and in visual comparison of the fitted and measured S0 . None of the models showed significant differences (P > 0.05) between the diffusion constant of the medulla and cortex, whereas the ffast component of the two and three-component models were significantly different (P < 0.001). CONCLUSION:Triexponential fitting is feasible for the diffusion signal in the kidney, and provides additional information. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:228-239.

SUBMITTER: van Baalen S

PROVIDER: S-EPMC5484284 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit.

van Baalen Sophie S Leemans Alexander A Dik Pieter P Lilien Marc R MR Ten Haken Bennie B Froeling Martijn M

Journal of magnetic resonance imaging : JMRI 20161027 1

<h4>Purpose</h4>To evaluate if a three-component model correctly describes the diffusion signal in the kidney and whether it can provide complementary anatomical or physiological information about the underlying tissue.<h4>Materials and methods</h4>Ten healthy volunteers were examined at 3T, with T<sub>2</sub> -weighted imaging, diffusion tensor imaging (DTI), and intravoxel incoherent motion (IVIM). Diffusion tensor parameters (mean diffusivity [MD] and fractional anisotropy [FA]) were obtained ...[more]

PMID: 27787931

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Project description:PurposeEarlier work showed that IVIM-NETorig , an unsupervised physics-informed deep neural network, was faster and more accurate than other state-of-the-art intravoxel-incoherent motion (IVIM) fitting approaches to diffusion-weighted imaging (DWI). This study presents a substantially improved version, IVIM-NEToptim , and characterizes its superior performance in pancreatic cancer patients.MethodIn simulations (signal-to-noise ratio [SNR] = 20), the accuracy, independence, and consistency of IVIM-NET were evaluated for combinations of hyperparameters (fit S0, constraints, network architecture, number of hidden layers, dropout, batch normalization, learning rate), by calculating the normalized root-mean-square error (NRMSE), Spearman's ρ, and the coefficient of variation (CVNET ), respectively. The best performing network, IVIM-NEToptim was compared to least squares (LS) and a Bayesian approach at different SNRs. IVIM-NEToptim 's performance was evaluated in an independent dataset of 23 patients with pancreatic ductal adenocarcinoma. Fourteen of the patients received no treatment between two repeated scan sessions and nine received chemoradiotherapy between the repeated sessions. Intersession within-subject standard deviations (wSD) and treatment-induced changes were assessed.ResultsIn simulations (SNR = 20), IVIM-NEToptim outperformed IVIM-NETorig in accuracy (NRMSE(D) = 0.177 vs 0.196; NMRSE(f) = 0.220 vs 0.267; NMRSE(D*) = 0.386 vs 0.393), independence (ρ(D*, f) = 0.22 vs 0.74), and consistency (CVNET (D) = 0.013 vs 0.104; CVNET (f) = 0.020 vs 0.054; CVNET (D*) = 0.036 vs 0.110). IVIM-NEToptim showed superior performance to the LS and Bayesian approaches at SNRs < 50. In vivo, IVIM-NEToptim showed significantly less noisy parameter maps with lower wSD for D and f than the alternatives. In the treated cohort, IVIM-NEToptim detected the most individual patients with significant parameter changes compared to day-to-day variations.ConclusionIVIM-NEToptim is recommended for accurate, informative, and consistent IVIM fitting to DWI data.

Dataset Information

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit.

Publications

Intravoxel incoherent motion modeling in the kidneys: Comparison of mono-, bi-, and triexponential fit.

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