RESUMEN
OBJECTIVE: To describe the role of the Diffusion Weighted Imaging (DWI) in the assessment of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Several electronic databases were evaluated in the present review. The search included articles published from January 2010 to May 2019. The references of all articles were also evaluated. All titles and abstracts were assessed, and only the studies of DWI in patients with HCC were retained. RESULTS: HCC is the most common primitive hepatic cancer. The non-invasive radiological criteria for HCC diagnosis are based on the presence of the specific vascular profile characterized by contrast uptake during arterial phase, defined as arterial hyperenhancement, followed by washout in the venous/portal phase. However, arterial hyperenhancement and wash out appearance have a sensitivity rate of 50-60% in lesion smaller than 2 cm. Therefore, other functional parameters have been introduced in the detection and characterization of HCC nodules. DWI has been applied to liver imaging as an excellent tool for detection and characterization of focal liver lesions, increasing clinical confidence and decreasing false positives. The assessment of DW images can be done qualitatively and quantitatively, through the apparent diffusion coefficient (ADC) map. Intravoxel incoherent motion (IVIM) is a more sophisticated analysis, a biexponential model, to better defining the relationship between signal attenuation and increasing b value that separately reproduces tissue diffusivity and tissue perfusion. Traditionally DWI approach to analyze data is founded on the hypothesis that water molecules diffuse within a voxel following a single direction with a Gaussian behavior without any restriction. However, according to the presence of microstructures, water molecules within biologic tissues exhibits a non-Gaussian phenomena proposed by Jensen in 2005 called Diffusion Kurtosis Imaging (DKI). This approach assesses the kurtosis coefficient (K) that shows the deviance of diffusion from a Gaussian approach, and the diffusion coefficient (D) with the correction of non-Gaussian bias. DKI is an advanced DWI model that quantifies non-Gaussian behavior of diffusion and provides both a corrected ADC, as well as the excess kurtosis of tissue, a measure of the extent to which tissue diffusion deviates from a Gaussian pattern. It is believed that the DKI model is more sensitive to tissue microstructural complexity than standard DW. CONCLUSIONS: DWI should be an integral part of study protocol for HCC patients, considering the great advantages due to DWI and DWI-based approaches in detection and characterization of HCC.