Ju Hee Lee1, Hyunhee Cheong, Seung Soo Lee, Chang Kyung Lee, Yu Sub Sung, Jae-Wan Huh, Jung-A Song, Han Choe. 1. From the *Department of Radiology, Center for Liver Cancer, National Cancer Center, Goyang; †Department of Radiology and Research Institute of Radiology, Asan Medical Center, Departments of ‡Biochemistry and Molecular Biology, and §Physiology and Biomedical Institute of Technology, University of Ulsan College of Medicine, Seoul, South Korea.
Abstract
OBJECTIVES: The aims of this study were to demonstrate the theoretical meaning of intravoxel incoherent motion (IVIM) parameters and to compare the robustness of 2 biexponential fitting methods through magnetic resonance experiments using IVIM phantoms. MATERIALS AND METHODS: Intravoxel incoherent motion imaging was performed on a 3 T magnetic resonance imaging scanner using 15 b values (0-800 s/mm) for 4 phantoms with different area fractions of the flowing water compartment (FWC%), at the infusion flow rates of 0, 1, 2, and 3 mL/min. Images were quantitatively analyzed using monoexponential free biexponential, and segmented biexponential fitting models. RESULTS: There were some inconsistent variations in Dslow with changing flow rates. The perfusion fraction, f, showed a significant positive correlation with the flow rate for both the free and segmented fitting methods (ρ = 0.838 to 0.969; P < 0.001). The fast diffusion coefficient, Dfast, had a significant positive correlation with the flow rate for segmented fitting (ρ = 0.745 to 0.969; P < 0.001), although it showed an inverse correlation with the flow rate for free fitting (ρ = -0.527 to -0.791; P ≤ 0.017). Significant positive correlations with the FWC% of the phantoms were noted for f (P = 0.510 for free fitting and P = 0.545 for segmented fitting, P < 0.001). CONCLUSIONS: The IVIM model allows for an approximate segmentation of molecular diffusion and perfusion, with a minor contribution of the perfusion effect on Dslow. The f and Dfast can provide a rough estimation of the flow fraction and flow velocity. Segmented fitting may be a more robust method than free fitting for calculating the IVIM parameters, especially for Dfast.
OBJECTIVES: The aims of this study were to demonstrate the theoretical meaning of intravoxel incoherent motion (IVIM) parameters and to compare the robustness of 2 biexponential fitting methods through magnetic resonance experiments using IVIM phantoms. MATERIALS AND METHODS: Intravoxel incoherent motion imaging was performed on a 3 T magnetic resonance imaging scanner using 15 b values (0-800 s/mm) for 4 phantoms with different area fractions of the flowing water compartment (FWC%), at the infusion flow rates of 0, 1, 2, and 3 mL/min. Images were quantitatively analyzed using monoexponential free biexponential, and segmented biexponential fitting models. RESULTS: There were some inconsistent variations in Dslow with changing flow rates. The perfusion fraction, f, showed a significant positive correlation with the flow rate for both the free and segmented fitting methods (ρ = 0.838 to 0.969; P < 0.001). The fast diffusion coefficient, Dfast, had a significant positive correlation with the flow rate for segmented fitting (ρ = 0.745 to 0.969; P < 0.001), although it showed an inverse correlation with the flow rate for free fitting (ρ = -0.527 to -0.791; P ≤ 0.017). Significant positive correlations with the FWC% of the phantoms were noted for f (P = 0.510 for free fitting and P = 0.545 for segmented fitting, P < 0.001). CONCLUSIONS: The IVIM model allows for an approximate segmentation of molecular diffusion and perfusion, with a minor contribution of the perfusion effect on Dslow. The f and Dfast can provide a rough estimation of the flow fraction and flow velocity. Segmented fitting may be a more robust method than free fitting for calculating the IVIM parameters, especially for Dfast.
Authors: Sau May Wong; C Eleana Zhang; Frank C G van Bussel; Julie Staals; Cécile R L P N Jeukens; Paul A M Hofman; Robert J van Oostenbrugge; Walter H Backes; Jacobus F A Jansen Journal: Neuroimage Clin Date: 2017-01-17 Impact factor: 4.881
Authors: Miriam E Peckham; Jeffrey S Anderson; Ulrich A Rassner; Lubdha M Shah; Peter J Hinckley; Adam de Havenon; Seong-Eun Kim; J Scott McNally Journal: Crit Care Date: 2018-06-20 Impact factor: 9.097