Abstract
Accurate evaluation of liver function is a central task in hepatology. Dynamic liver function tests (DLFT) based on the time-dependent elimination of a test substance provide an important tool for such a functional assessment. These tests are used in the diagnosis and monitoring of liver disease as well as in the planning of hepatobiliary surgery. A key challenge in the evaluation of liver function with DLFTs is the large inter-individual variability. Indocyanine green (ICG) is a widely applied test compound used for the evaluation of liver function. After an intravenous administration, pharmacokinetic (PK) parameters are calculated from the plasma disappearance curve of ICG which provide an estimate of liver function. The hepatic elimination of ICG is affected by physiological factors such as hepatic blood flow or binding of ICG to plasma proteins, anthropometric factors such as body weight, age, and sex, or the protein amount of the organic anion-transporting polypeptide 1B3 (OATP1B3) mediating the hepatic uptake of ICG. Being able to account for and better understand these various sources of inter-individual variability would allow to improve the power of ICG based DLFTs and move toward an individualized evaluation of liver function. Within this work we systematically analyzed the effect of various factors on ICG elimination by the means of computational modeling. For the analysis, a recently developed and validated physiologically based pharmacokinetics (PBPK) model of ICG distribution and hepatic elimination was utilized. Key results are (i) a systematic analysis of the variability in ICG elimination due to hepatic blood flow, cardiac output, OATP1B3 abundance, liver volume, body weight and plasma bilirubin level; (ii) the evaluation of the inter-individual variability in ICG elimination via a large in silico cohort of n = 100,000 subjects based on the NHANES cohort with special focus on stratification by age, sex, and body weight; (iii) the evaluation of the effect of various degrees of cirrhosis on variability in ICG elimination. The presented results are an important step toward individualizing liver function tests by elucidating the effects of confounding physiological and anthropometric parameters in the evaluation of liver function via ICG.
Highlights
Accurate evaluation of liver function is a central task in hepatology
Within this work we systematically investigated the individual contribution of these factors to the large inter-individual variability in liver function tests based on Indocyanine green (ICG) using a recently developed and validated physiologically based pharmacokinetics (PBPK) model of ICG (Köller et al, 2021)
The systemic blood flow of the PBPK model is based on the cardiac output, which is scaled by the body weight
Summary
Dynamic liver function tests (DLFT) based on timedependent elimination of test substances provide an important tool for the functional assessment of the liver. It is bound to plasma proteins in the blood, eliminated exclusively by the liver, and subsequently excreted into the bile. PDD measures ICG plasma concentration by measuring absorption at wavelengths of 805 nm (absorption maximum of ICG) and 905 nm (no absorption by ICG) (Vos, 2015). Measurements from both methods correlate well (Purcell et al, 2006). From the concentration-time profile a set of pharmacokinetic parameters can be calculated (e.g., ICG clearance, plasma disappearance rate (ICG-PDR), retention ratio after 15 min (ICG-R15), ICG half-life), which provide estimates of liver function based on the ICG elimination capacity of the liver (Sakka, 2018; Köller et al, 2021)
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