Evaluation of Hepatic Fibrosis and Steatosis Using Magnetic Resonance Imaging

Chronic liver injury induces liver fibrosis. Its end stage, liver cirrhosis, is one of the leading causes of morbidity and mortality worldwide. Liver biopsy, the current gold standard for diagnosing liver disease, is an invasive procedure and is associated with sampling errors. In addition, liver biopsy is inappropriate for the longitudinal assessment of liver function. There is an urgent need for noninvasive evaluation of liver fibrosis. Among all popular imaging methods, MRI is a powerful modality for detecting liver disease noninvasively, which allows the whole liver imaging within a breathhold and embraces the flexibility of multiple image contrasts without ionizing radiation. Since liver fibrosis is associated with major increase of extracellular matrix (ECM), the liver tissue resistance is increased and hence a change in portal pressure gradient may occur. We have developed a new portal pressure gradient (PPG) model to assess liver fibrosis noninvasively. The PPG model is derived from fluid mechanics and applied in combination with MRI. Using a phase-contrast spoiled gradient echo, the PPG model is verified in a phantom study and tested in thirty-five rats and thirty-five humans with various degrees of fibrosis, which is determined by histology and biopsy examinations. The results demonstrate that PPG is moderately or highly correlated with fibrosis scores. Significant difference is observed between the control and fibrosis (non-cirrhosis) groups, as well as between the control and cirrhosis groups. In addition, the PPG approach does not require contrast agent. Therefore, the PPG measurement has clinical potential to evaluate hepatic fibrosis and liver cirrhosis noninvasively. We also compare the performance of the PPG model with that of a well-established hepatic perfusion model in rats. Using a two-input one-compartmental model with dynamic contrast enhanced (DCE) MRI, perfusion parameter portal fraction (PF) is obtained. Both PPG and PF are highly correlated with fibrosis scores. PPG shows higher accuracy than PF in diagnosing liver fibrosis and liver cirrhosis in the receiver operating characteristic (ROC) curves. In view of the complex and dynamic nature of liver fibrosis, no single MRI measurement can completely determine the severity of the disease. We seek to apply the combination of multiple MRI methods to detect the diverse pathological changes in liver fibrosis and steatosis. A multi-component MR protocol is designed to quantify fat accumulation, macromolecule content, hepatic perfusion, and PPG. Indeed, the results show that the multivariate MRI evaluation can diagnose liver fibrosis and steatosis more comprehensively and thus more accurately. For example, the misclassification rate for predicting the severity of liver fibrosis can be reduced from 28%, which is obtained using PPG predictor alone, to 7%, which is obtained using the multivariate model. In conclusion, the PPG model developed in this work may be a useful clinical tool to assess hepatic fibrosis and cirrhosis noninvasively. A multivariate method that combines different MRI measurements can provide a comprehensive evaluation of liver function.