Abstract: With the reported intravoxel incoherent motion (IVIM) analyses, the diffusion image signal decay is computed starting from b=0 s/mm² image and then increasingly higher b-values using a biexponential decay model. In many organs such as the liver, the relationship between b-value and diffusion signal is composed of two parts: ① low b-values are associated with quick signal decay caused by fast moving water associated with blood perfusion; ② high b-values are associated with slow signal decay caused by pure water diffusion. These associations are represented by three parameters associated with a bi-exponential model, i.e. Dslow (D), Dfast (D^* ), PF (f). PF is the fraction of the pseudo-diffusion linked to microcirculation, Dslow is the true diffusion coefficient representing the pure molecular diffusion, and Dfast is the perfusion-related diffusion. Although the theory of IVIM is very appealing, the practical application in the liver is difficult due to the difficulties in curve fitting and instability of results. Due to its relatively high blood supply, the liver is a very suitable organ for IVIM study. However, the liver is in the meantime particularly affected by physiological motions such as respiration and heart beating; meanwhile, the left liver is also affected by susceptibility artefact due to contents in the stomach. Recently we published two small cohort studies. Study-1 had 16 healthy volunteers and 33 viral hepatitis-b liver fibrosis patients among them 15 patients had stage-1 liver fibrosis. Study-2 had 26 healthy volunteers and 12 viral hepatitis-b liver fibrosis patients among them 4 patients had stage-1 liver fibrosis. All patients and healthy volunteers can be separated by IVIM analysis. Interestingly, study-2 had four patients with biopsy showing no or minimal fibrosis, and these four subjects’ IVIM measurements resembled healthy volunteers. While our current data acquisition and analysis still remain not optimal, we believe we were able to achieve these good results by the following measures: ①IVIM analysis without b=0 data; ②Carefully select b value distribution and the threshold b-value; ③ Discard poor image quality files; ④ Incorporating all IVIM parameters for consideration. We expect that with further improvement in data acquisition and post-processing, IVIM technique will have high sensitivity and specificity for early liver fibrosis evaluation.

Key words: Intravoxel incoherent motion, Diffusion, Liver, Fibrosis