Effects of diffusion time on non-Gaussian diffusion and intravoxel incoherent motion (IVIM) MRI parameters in breast cancer and hepatocellular carcinoma xenograft models. (January 2018) - Iima, Mami; Nobashi, Tomomi; Imai, Hirohiko; Koyasu, Sho; Saga, Tsuneo; Nakamoto, Yuji; Kataoka, Masako; Yamamoto, Akira; Matsuda, Tetsuya; Togashi, Kaori
Background: Perfusion-related intravoxel incoherent motion (IVIM) and non-Gaussian diffusion magnetic resonance (MR) parameters are becoming important biomarkers for differentiating malignant from benign tumors without contrast agents. However, diffusion-time dependence has rarely been investigated in tumors. Purpose: To investigate the relationship between diffusion time and diffusion parameters in breast cancer and hepatocellular carcinoma xenograft mouse models. Material and Methods: Diffusion-weighted MR images (DWI) were obtained on a 7-T magnetic resonance imaging (MRI) scanner at two different diffusion times (9.6 ms and 27.6 ms) in human breast cancer (MDA-MB-231) and hepatocellular carcinoma (HepG2 and PLC/PRF/5) xenograft mouse models. Perfusion-related IVIM (fIVIM and D*) and non-Gaussian diffusion (ADC0 and K) parameters were estimated. Parametric maps of diffusion changes with the diffusion times were generated using a synthetic apparent diffusion coefficient (sADC) obtained from b = 438 and 2584 s/mm 2 . Results: ADC0 values significantly decreased when diffusion times were changed from 9.6 ms to 27.6 ms in MDA-MB-231, HepG2, and PLC/PRF/5 groups ( P  = 0.0163, 0.0351, and 0.0170, respectively). K values significantly increased in MDA-MB-231 and HepG2 groups ( P  < 0.0003 and = 0.0007, respectively); however, no significant difference was detected in the PLC/PRF/5 group. fIVIM values increased, although not significantly ( P  = 0.164–0.748). The maps of sADC changes showed that diffusion changes with the diffusion time were not homogeneous across tumor tissues. Conclusion: Diffusion MR parameters in both breast cancer and HCC xenograft models were found to be diffusion time-dependent. Our results show that diffusion time is an important parameter to consider when interpreting DWI data.