MR quantitative biomarkers of non-alcoholic fatty liver disease: technical evolutions and future trends
Quantitative Imaging in Medicine and Surgery
Non-alcoholic fatty liver disease (NAFLD) is characterized by hepatic steatosis as the earliest manifestation and hallmark, and ranges from benign fatty liver to non-alcoholic steatohepatitis (NASH). Liver biopsy (LB) is considered the reference standard for NAFLD diagnosis, grading and characterization, but it is limited by its invasiveness and observer-dependence. Among imaging surrogates for the assessment of hepatic steatosis, MR is the most accurate. (1)H MR spectroscopy (MRS) provides a
... antitative biomarker of liver fat content (LFC) called proton density fat fraction (PDFF), but it is time-consuming, not widely available and limited in sample size. Several MR imaging (MRI) techniques, in particular fat suppression and in-opposed phase techniques, have been used to quantify hepatic steatosis, mainly estimating LFC from water and fat signal intensities rather than proton densities. Several technical measures have been introduced to minimize the effect of confounding factors, in particular a low flip angle, a multiecho acquisition and a spectral modeling of fat with multipeak reconstruction to address respectively T1 effect, T2* effect, and the multifrequency interference effects of fat protons, allowing to use MRI to estimate LFC based on PDFF. Tang et al. evaluated MRI-estimated PDFF, obtained by applying the above-mentioned technical improvements, in the assessment of hepatic steatosis, using histopathology as the reference standard. The identification of PDFF thresholds, even though to be further explored and validated in larger and more diverse cohorts, is useful to identify steatosis categories based on MRI-based steatosis percentages. MRI, with the new refined techniques which provide a robust quantitative biomarker of hepatic steatosis (PDFF) evaluated on the whole liver parenchyma, is a promising non-invasive alternative to LB as the gold standard for steatosis diagnosis and quantification.