Magnetic resonance in medicine · 2026
Toward Optimized Intravoxel Incoherent Motion (IVIM) and Compartmental T2 Mapping in Abdominal Organs.
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Stabinska Julia, Thiel Thomas A, Wittsack Hans-Jörg, Ljimani Alexandra, Zöllner Helge J
Аннотация
PURPOSE: To quantitatively assess the bias in the intravoxel incoherent motions (IVIM)-derived pseudo-diffusion volume fraction (f) caused by the differences in relaxation times between the tissue and fluid compartments, and to develop a two-dimensional (b-value-TE) fitting approach for simultaneous T2 and IVIM parameter estimation along with an optimal acquisition protocol for the relaxation-compensated T2-IVIM imaging in the liver.
METHODS: Simulations were conducted to investigate the TR- and TE-dependent bias in f when using the IVIM model, and to evaluate the applicability of the 2D T2-IVIM model for reducing this bias. The numerical findings were then validated using the in vivo IVIM data from four healthy volunteers on a 3-Tesla MRI scanner. Finally, a numerical framework for optimizing the T2-IVIM protocol for relaxation-compensated f parameter estimation was proposed and tested using the in vivo data.
RESULTS: In vivo, the traditional IVIM model showed a trend toward higher f with increasing TE in the liver (R = 0.46, p = 0.023), but not in the kidney cortex (R = -0.067, p = 0.76) or medulla (R = 0.039, p = 0.86). In both simulations and in vivo, 2D T2-IVIM modeling yielded lower f values and reduced variability in the liver. Our results further suggest that a b-TE protocol with six b-values and three TEs (50, 60, and 100 ms) may be optimal for liver T2-IVIM.
CONCLUSION: The extended 2D T2-IVIM model effectively minimizes the TE-dependent bias in f and allows simultaneous estimation of the IVIM parameter and compartmental T2 values in abdominal organs.
METHODS: Simulations were conducted to investigate the TR- and TE-dependent bias in f when using the IVIM model, and to evaluate the applicability of the 2D T2-IVIM model for reducing this bias. The numerical findings were then validated using the in vivo IVIM data from four healthy volunteers on a 3-Tesla MRI scanner. Finally, a numerical framework for optimizing the T2-IVIM protocol for relaxation-compensated f parameter estimation was proposed and tested using the in vivo data.
RESULTS: In vivo, the traditional IVIM model showed a trend toward higher f with increasing TE in the liver (R = 0.46, p = 0.023), but not in the kidney cortex (R = -0.067, p = 0.76) or medulla (R = 0.039, p = 0.86). In both simulations and in vivo, 2D T2-IVIM modeling yielded lower f values and reduced variability in the liver. Our results further suggest that a b-TE protocol with six b-values and three TEs (50, 60, and 100 ms) may be optimal for liver T2-IVIM.
CONCLUSION: The extended 2D T2-IVIM model effectively minimizes the TE-dependent bias in f and allows simultaneous estimation of the IVIM parameter and compartmental T2 values in abdominal organs.