Echo time dependence of biexponential and triexponential intravoxel incoherent motion parameters in the liver.
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Purpose Intravoxel incoherent motion (IVIM) studies are performed with different acquisition protocols. Comparing them requires knowledge of echo time (TE) dependencies. The TE-dependence of the biexponential perfusion fraction f is well-documented, unlike that of its triexponential counterparts f 1 and f 2 and the biexponential and triexponential pseudodiffusion coefficients D * , D1∗ , and D2∗ . The purpose was to investigate the TE-dependence of these parameters and to check whether the triexponential pseudodiffusion compartments are associated with arterial and venous blood. Methods Fifteen healthy volunteers (19-58 y; mean: 24.7 y) underwent diffusion-weighted imaging of the abdomen with 24 b-values (0.2-800 s/mm 2 ) at TEs of 45, 60, 75, and 90 ms. Regions of interest (ROIs) were manually drawn in the liver. One set of bi- and triexponential IVIM parameters per volunteer and TE was determined. The TE-dependence was assessed with the Kruskal-Wallis test. Results TE-dependence was observed for f (P < .001), f 1 (P = .001), and f 2 (P < .001). Their median values at the four measured TEs were: f: 0.198/0.240/0.274/0.359, f 1 : 0.113/0.139/0.146/0.205, f 2 : 0.115/0.155/0.182/0.194. D, D * , D1∗ , and D2∗ showed no significant TE-dependence. Their values were: diffusion coefficient D (10 -4 mm 2 /s): 9.45/9.63/9.75/9.41, biexponential D * (10 -2 mm 2 /s): 5.26/5.52/6.13/5.82, triexponential D1∗ (10 -2 mm 2 /s): 1.73/2.91/2.25/2.51, triexponential D2∗ (mm 2 /s): 0.478/1.385/0.616/0.846. Conclusion f 1 and f 2 show similar TE-dependence as f, ie, increase with rising TE; an effect that must be accounted for when comparing different studies. The diffusion and pseudodiffusion coefficients might be compared without TE correction. Because of the similar TE-dependence of f 1 and f 2 , the triexponential pseudodiffusion compartments are most probably not associated to venous and arterial blood.
Radiotherapy Physics Modelling
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Magnetic resonance in medicine, 2021