Liver fat imaging-a clinical overview of ultrasound, CT, and MR imaging

Abstract

Hepatic steatosis is a frequently encountered imaging finding that may indicate chronic liver disease, the most common of which is non-alcoholic fatty liver disease. Non-alcoholic fatty liver disease is implicated in the development of systemic diseases and its progressive phenotype, non-alcoholic steatohepatitis, leads to increased liver-specific morbidity and mortality. With the rising obesity epidemic and advent of novel therapeutics aimed at altering metabolism, there is a growing need to quantify and monitor liver steatosis. Imaging methods for assessing steatosis range from simple and qualitative to complex and highly accurate metrics. Ultrasound may be appropriate in some clinical instances as a screening modality to identify the presence of abnormal liver morphology. However, it lacks sufficient specificity and sensitivity to constitute a diagnostic modality for instigating and monitoring therapy. Newer ultrasound techniques such as quantitative ultrasound show promise in turning qualitative assessment of steatosis on conventional ultrasound into quantitative measurements. Conventional unenhanced CT is capable of detecting and quantifying moderate to severe steatosis but is inaccurate at diagnosing mild steatosis and involves the use of radiation. Newer CT techniques, like dual energy CT, show potential in expanding the role of CT in quantifying steatosis. MRI proton-density fat fraction is currently the most accurate and precise imaging biomarker to quantify liver steatosis. As such, proton-density fat fraction is the most appropriate noninvasive end point for steatosis reduction in clinical trials and therapy response assessment.

Figures

Figure 1.

Ultrasound, CT and MR at steatosis—examples. B-mode ultrasound transverse images of the liver (first row), axial unenhanced CT images of the liver at the level of the spleen (second row), and axial MRI PDFF images of the liver (third row) are shown for four patients. Steatosis grade was determined at liver biopsy with direct histological visualisation for the number of cells with intracellular fat vacuoles: none (0% hepatocytes), mild (0–33% hepatocytes), moderate (33–66% hepatocytes) and severe (>66% hepatocytes). As steatosis grade increases from left to right in each row, the following patterns are seen: on ultrasound, increased liver parenchyma echogenicity and decreased definition of intrahepatic structures such as vessel walls; on unenhanced CT, liver density on CT in HU decreases though spleen density in HU is variable; on MR, PDFF values increase. HU, Hounsfield unit; PDFF, proton-density fat fraction.

Figure 2.

Conventional unenhanced CT and DECT at steatosis– adapted from Kramer et al. Conventional unenhanced CT acquired at 120 kVp (first row) and DECT acquired by rapidly switching tube voltages between 80 and 140 kVp, then post-processed into fat-density images (second row) are shown for three patients with varying degrees of steatosis. Patients A, B, and C have 0, 10, and 40% liver fat fraction, respectively, as determined by MRS PDFF (not shown). As liver fat fraction increases across the rows, liver attenuation at conventional unenhanced CT visibly decreases and liver fat density on DECT visibly increases. Reprinted with permission from the American Journal of Roentgenology. DECT, dual energy CT; PDFF, proton-density fat fraction; MRS, MR spectroscopy.

Figure 3.

Typical liver MR spectrum showing water peak at 4.7 ppm (chemical shift measured in ppm) and multiple fat peaks (Peaks 1–6). There is one main fat peak (Peak 5). There are also Peak 4 and Peak 6, which partially overlap with the main fat peak. Peak 1 and Peak 2 overlap with the single water peak. Different correction techniques exist in advanced MR to address the problem of teasing apart contributions from individual peaks. ppm, parts per million.

Figure 4.

Complex data-based (c-MRI) and magnitude data-based (m-MRI) MR, acquisitions from 64-year-old female patient with mild histological grade steatosis in Figure 1. Startinginary source images with the output PDFF map to the right. The echo times at which the c-MRIs are acquired are listed on the far left. Further to the right are the magnitude source echoes for the m-MRI with the corresponding PDFF map on the far right. The echo times at which the m-MRIs are acquired are adjacent to the magnitude source echoes. The average PDFF measurement derived from c-MRI is 7.5% while that derived from m-MRI on the same patient is 7.4%. PDFF, proton-density fat fraction.