Purpose: To assess the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in hepatocellular carcinoma (HCC) and liver parenchyma.
Materials And Methods: Twenty-five patients with HCC (M/F 23/2, mean age 58 years) underwent abdominal MRI at 1.5 or 3.0T, including IVIM-DWI (with 16 b-values) and DCE-MRI (3D FLASH sequence, mean temporal resolution of 2.3 sec). IVIM-DWI parameters (pseudodiffusion coefficient, D*, diffusion coefficient, D, and perfusion fraction, PF) were quantified in HCC lesions and liver parenchyma using a Bayesian fitting algorithm. DCE-MRI parameters (arterial flow, Fa , portal flow, Fp , total flow, Ft , mean transit time, MTT, distribution volume, DV, and arterial fraction, ART) were quantified using a dual-input single-compartment model. Correlations between IVIM-DWI and DCE-MRI parameters were assessed using a Spearman correlation test.
Results: Thirty-three HCC lesions (average size 5.0 ± 3.6 cm) were analyzed. D, D*, and PF were all significantly lower in HCC vs. liver (P < 0.05). Significantly higher Fa and ART and lower Fp were observed in HCC vs. liver (P < 0.001). Significant moderate to strong negative correlations were observed between ART and D* (r = -0.443, P = 0.028), ART and PF (r = -0.536, P = 0.006), ART and PFxD* (r = -0.655, P < 0.001), Fa and PF (r = 0.455, P = 0.023), and Fa and PFxD* (r = -0.475, P = 0.018) in liver parenchyma. There was no significant correlation between IVIM-DWI and DCE-MRI metrics in HCC lesions.
Conclusion: IVIM-DWI and DCE-MRI provide nonredundant information in HCC, while they correlate in liver parenchyma. These findings may be secondary to predominant portal inflow in the liver and tortuous vasculature and tissue heterogeneity in tumors. J. MAGN. RESON. IMAGING 2016;44:856-864.
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http://dx.doi.org/10.1002/jmri.25194 | DOI Listing |
Med Image Anal
December 2024
Faculty of Biomedical Engineering, Technion, Haifa, Israel. Electronic address:
Quantitative analysis of pseudo-diffusion in diffusion-weighted magnetic resonance imaging (DWI) data shows potential for assessing fetal lung maturation and generating valuable imaging biomarkers. Yet, the clinical utility of DWI data is hindered by unavoidable fetal motion during acquisition. We present IVIM-morph, a self-supervised deep neural network model for motion-corrected quantitative analysis of DWI data using the Intra-voxel Incoherent Motion (IVIM) model.
View Article and Find Full Text PDFMed Image Anal
November 2024
Department of Radiology and Nuclear Medicine, St. Olav's University Hospital, Trondheim, Norway; Department of Circulation and Medical Imaging, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
In medical image analysis, the utilization of biophysical models for signal analysis offers valuable insights into the underlying tissue types and microstructural processes. In diffusion-weighted magnetic resonance imaging (DWI), a major challenge lies in accurately estimating model parameters from the acquired data due to the inherently low signal-to-noise ratio (SNR) of the signal measurements and the complexity of solving the ill-posed inverse problem. Conventional model fitting approaches treat individual voxels as independent.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
This study aimed to establish and validate a multiparameter prediction model for Ki67 expression in hepatocellular carcinoma (HCC) patients while also exploring its potential to predict the one-year recurrence risk. The clinical, pathological, and imaging data of 83 patients with HCC confirmed by postoperative pathology were analyzed, and the patients were randomly divided into a training set (n = 58) and a validation set (n = 25) at a ratio of 7:3. All patients underwent a magnetic resonance imaging (MRI) scan that included multi-b value diffusion-weighted scanning before surgery, and quantitative parameters were obtained via intravoxel incoherent motion (IVIM) and diffusion kurtosis (DKI) models.
View Article and Find Full Text PDFAJNR Am J Neuroradiol
December 2024
From the Department of Diagnostic Medicine, Dell Medical School at The University of Texas at Austin, Austin, TX, USA (C.Y.H.), Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA (N.S., G.A., Q.W., P.C., M.A., J.G.P., B.R.G., P.R.T., G.D.H.), Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA (E.C., P.R.T., S.A.P.), Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA (P.R.T., S.A.P.), and the Department of Radiology at Texas Children's Hospital, Houston, TX, USA (S.F.K.).
Background And Purpose: There are multiple MRI perfusion techniques, with limited available literature comparing these techniques in the grading of pediatric brain tumors. For efficiency and limiting scan time, ideally only one MRI perfusion technique can be used in initial imaging. We compared DSC, DCE, and IVIM along with ADC from DWI for differentiating high versus low grade pediatric brain tumors.
View Article and Find Full Text PDFBMC Med Imaging
December 2024
Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Background: Diffusion-weighted imaging (DWI) can be used for quantitative tumor assessment. DWI with different models may show different aspects of tissue characteristics.
Objective: To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, stretched exponential magnetic resonance diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in differentiating benign from malignant solitary pulmonary lesions (SPLs).
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