3190

MRI Technique and Interpretation in the Evaluation of Hepatic Steatosis
Zachary Borden1 and Scott Reeder2

1Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, 2Department of Radiology, University of Wisconsin-Madison, WI, United States

Synopsis

Hepatic steatosis is a common affliction with important prognostic implications. Conventionally, liver biopsy has been required for the diagnosis of steatosis although this may result in inadequate spatial sampling and significant associated complications. The non-interventional imaging methods of ultrasound and computed tomography may be used but are limited in accuracy. MRI offers an ideal method to globally and accurately interrogate for liver fat. Multiple MRI techniques including spectroscopy, in-phase/out-phase, conventional fat suppression, complex and magnitude-based CSE-MRI methods have been used in the evaluation of hepatic steatosis. These techniques possess unique advantages and disadvantages which must be understood to optimize patient care.

Purpose

To provide an educational overview of available MRI imaging acquisition techniques and their interpretation in the evaluation of hepatic steatosis due to multiple etiologies and through the course of diagnosis and treatment.

Outline

Introduction: Hepatic steatosis is a highly prevalent pathologic process affecting an estimated 20-80 million Americans. In addition to presenting as a hallmark feature of non-alcoholic fatty liver disease (NAFLD) it also exists in patients with viral hepatitis, alcohol abuse, HIV, chemotherapy, or genetic disorders. Intracellular fat deposition results in oxidative stress and cytokine production which leads to apoptosis and resultant progressive hepatic disease including the estimated development of cirrhosis in 5-15% of patients with NAFLD. Furthermore, hepatic steatosis is a risk factor for hepatocellular carcinoma with 7% of NAFLD patients developing HCC within ten years[1]. Steatosis is also an independent risk factor in cardiovascular mortality including early mortality beginning at age 45[2]. A variety of interventions including weight loss programs, bariatric surgery, and medical treatment of underlying insulin resistance have been shown to improve steatosis. The current gold standard technique is liver biopsy which is limited by failure of global liver characterization, complication risk, and sampling variability [3]–[6].

Imaging: While MRI is the most promising imaging technique, ultrasound has shown a positive predictive value of 77% [7]. CT can also provide a global evaluation of steatosis but evaluation of liver attenuation is complicated by safety concerns of radiation exposure [8].

Magnetic Resonance:

MR Spectroscopy: Limited studies indicate highly accurate characterization of liver fat however the technique is limited by poor spatial coverage, required expertise in interpretation, acquisition time, and lack of availability outside of academic centers.

In-Phase/Out-Phase two-point Dixon imaging: Exploiting the difference in resonance frequency of fat and water, echo times are based on timing of peaks to be in phase and out of phase with each other. Through normalization of image signal, fat fraction calculations may be performed. Technique is limited by a dynamic range of 0-50%.

Conventional Fat Suppression: Fat suppression radiofrequency pulses can be used to proportionally decrease liver signal which may be qualitatively assessed.

Confounder-Corrected Magnitude and Complex Chemical Shift Encoded MRI: Low flip angle, multi-echo spoiled gradient echo (SGRE) techniques have emerged as quantitative biomarkers of liver fat content. By addressing all known confounders that include T1 related bias, T2* decay, spectral complexity of fact, Eddy currents and noise bias these techniques provide unbiased estimates of the "proton density fat fraction" (PDFF). PDFF is a fundamental property of tissue that is defined as the ratio of the number of protons from tissue triglycerides divided by the total number of protons of triglycerides and free water. CSE-MRI methods come in two flavors, specifically "magnitude" CSE-MRI that describe the phase information from the raw signal, or “complex” CSE-MRI that uses both the phase and the magnitude information. Both methods are highly accurate in the liver, although complex techniques have the advantage of a full dynamic range from 0-100%.

Acknowledgements

The authors wish to acknowledge support from the NIH (UL1TR00427, R01 DK083380, R01 DK088925, R01 DK100651, and K24 DK102595), as well GE Healthcare who provides research support to the University of Wisconsin.

References

1. Sanyal AJ, Banas C, Sargeant C, et al. Similarities and differences in outcomes of cirrhosis due to nonalcoholic steatohepatitis and hepatitis C. Hepatology. 2006;43(4):682-689. doi:10.1002/hep.21103.

2. Schindhelm RK, Diamant M, Heine RJ. Nonalcoholic fatty liver disease and cardiovascular disease risk. Curr Diab Rep. 2007;7(3):181-187. http://www.ncbi.nlm.nih.gov/pubmed/17547835. Accessed October 11, 2016.
3. Ratziu V, Charlotte F, Heurtier A, et al. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. Gastroenterology. 2005;128(7):1898-1906. http://www.ncbi.nlm.nih.gov/pubmed/15940625. Accessed October 11, 2016.

4. Bravo AA, Sheth SG, Chopra S. Liver Biopsy. N Engl J Med. 2001;344(7):495-500. doi:10.1056/NEJM200102153440706.

5. Bedossa P, Dargere D, Paradis V. Sampling variability of liver fibrosis in chronic hepatitis C. Hepatology. 2003;38(6):ajhep09022. doi:10.1016/j.hep.2003.09.022.

6. Ratziu V, Charlotte F, Heurtier A, et al. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. Gastroenterology. 2005;128(7):1898-1906.

7. Graif M, Yanuka M, Baraz M, et al. Quantitative estimation of attenuation in ultrasound video images: correlation with histology in diffuse liver disease. Invest Radiol. 2000;35(5):319-324. http://www.ncbi.nlm.nih.gov/pubmed/10803673. Accessed October 4, 2016.

8. Limanond P, Raman SS, Lassman C, et al. Macrovesicular Hepatic Steatosis in Living Related Liver Donors: Correlation between CT and Histologic Findings. Radiology. 2004;230(1):276-280. doi:10.1148/radiol.2301021176.

Proc. Intl. Soc. Mag. Reson. Med. 25 (2017)
3190