Dual blood supply to the liver
Quantitative studies of the liver are complicated by its dual input function. Blood supply from hepatic artery has the same tracer concentration as all other arteries, with very sharp curve peak in case of bolus administration of the tracer. However, most of the blood supply to the liver comes via portal vein; tracer is first distributed to the intestines, spleen, pancreas, and gallbladder, and as a result the concentration peak is dispersed, delayed, and possibly affected by the metabolic processes in the splanchnic organs: depending on the tracer, AUC and/or the fraction of label-carrying metabolites may be different in arterial blood and portal vein.
Since the tracer concentration in hepatic aorta is the same as in any artery, it can be measured as usual, but concentration in portal vein cannot be sampled noninvasively, and not at all in human studies. Small size and respiratory movement make it difficult to retrieve portal vein concentration reliably from dynamic PET image; in human [11C]palmitate study both arterial and portal input could be derived from the image (Gormsen et al., 2018).
In animal studies samples can be taken also from the portal vein. Blood flow (mL/min) in hepatic aorta (fHA) and portal vein (fPV) can be measured noninvasively (although not very precisely) using Doppler ultrasound method. Dual input function for liver can then be calculated as blood flow weighted average of arterial, CA, and portal vein, CPV, concentration curves (Brix et al., 2001; Munk et al., 2001; Iozzo et al., 2007; Keiding, 2012):
Program liverinp can be used to combine CA(t) and CPV(t) using the previous equation.
The fraction of flow via portal vein in dogs has been estimated to be 0.65-0.85 and in sheep ∼0.8 (Katz & Bergman, 1969). In rats, the portal vein fraction has been estimated to be 0.72±0.05 (Fleming et al., 1981). In rabbits the fraction was ∼0.79, as measured using microspheres (Materne et al., 2000). In pigs, ultrasound method has given fractions 0.83±0.03 (Iozzo et al., 2007), and 0.7, with range 0.6-0.9 (Winterdahl et al., 2012). In humans, CT-based assessment provided portal vein fraction 0.83 for healthy liver and 0.58 for liver tumours (Ng et al., 2012).
In human studies, the obvious approach has been to ignore the input via portal vein, and either validate that the results still are correct (Chen et al., 1991), or accept that the obtained results may be biased but correlate well with the physiological parameter of interest (Choi et al., 1994).
A more challenging approach is to estimate the portal vein concentration curve based on the arterial input by including additional compartment(s) and/or dispersion and delay parameters to the model (Choi et al., 1994; Taniguchi et al., 1996; Ziegler et al., 1996; Chen et al., 2004a and 2004b; Kudomi et al., 2008). Whole-body recirculatory model has been developed for [13N]NH4+ and its metabolites in artery and portal vein (Weiss et al., 2002).
and Munk et al (2003) applied the 2-compartmental model (n=2) for estimating the portal vein concentration:
The discretely sampled arterial data and the impulse-response function, h(t), need to be interpolated to even sample times and sampling durations for calculation of the convolution integral. The value of each interpolated sample must represent the mean value during the (short) Δt: in practise this means that arterial data should be interpolated to the midpoint of the even intervals, and since the response function is an integrable function, its definite integral during Δt, divided by Δt, should be used. Resulting convolution integral on the other hand should be scaled by Δt; thus Δt is cancelled out. Thus, the response function values at time points T can be calculated from equation:
Program liverpv can be used for computing portal vein curve from arterial curve using these equations. Winterdahl et al (2011) measured the β values in pigs for [18F]FDG (0.50 min), [15O]H2O (2.17 min), [15O]CO (0.10 min), [18F]FDGal (0.82 min), and [11C]methylglucose (0.57 min). Later, β value in pigs has been determined for [11C]CSar (13 s) (Sørensen et al., 2016).
- The liver
- The spleen
- The pancreas
- [15O]H2O PET in liver
- [18F]FTHA PET in liver
- [18F]FDG PET in liver
- [11C]palmitate PET in liver
Brix G, Ziegler SI, Bellemann ME, Doll J, Schosser R, Lucht R, Krieter H, Nosske D, Haberkorn U. Quantification of [18F]FDG uptake in the normal liver using dynamic PET: impact and modeling of the dual hepatic blood supply. J Nucl Med. 2001; 42: 1265-1273. PMID: 11483690.
Chen S, Feng D. Noninvasive quantification of the differential portal and arterial contribution to the liver blood supply from PET measurements using the 11C-acetate kinetic model. IEEE Trans Biomed Eng. 2004a; 51(9): 1579-1585. doi: 10.1109/TBME.2004.828032.
Chen S, Ho C, Feng D, Chi Z. Tracer kinetic modeling of 11C-acetate applied in the liver with positron emission tomography. IEEE Trans Med Imaging 2004b; 23(4): 426-432. doi: 10.1109/TMI.2004.824229.
Chen S, Feng D. Novel parameter estimation methods for 11C-acetate dual-input liver model with dynamic PET. IEEE Trans Biomed Eng. 2006; 53(5): 967-973. doi: 10.1109/TBME.2006.872817.
Choi Y, Hawkins RA, Huang S-C, Brunken RC, Hoh CK, Messa C, Nitzsche EU, Phelps ME, Schelbert HR. Evaluation of the effect of glucose ingestion and kinetic model configurations of FDG in the normal liver. J Nucl Med. 1994; 35: 818-823. PMID: 8176464.
DiStefano III J. Dynamic Systems Biology Modeling and Simulation. Academic Press, 2013. ISBN: 9780124104112.
Garbarino S, Vivaldi S, Delbary F, Caviglia G, Piana M, Marini C, Capitanio S, Calamia I, Buschiazzo A, Sambuceti G. A new compartmental method for the analysis of liver FDG kinetics in small animal models. EJNMMI Res. 2015; 5:35. doi: 10.1186/s13550-015-0107-1.
Guiducci L, Järvisalo MJ, Kiss J, Någren K, Viljanen A, Naum AG, Castaldelli A, Savunen T, Knuuti J, Salvadori PA, Ferrannini E, Nuutila P, Iozzo P. [11C]palmitate kinetics across the splanchnic bed in arterial, portal and hepatic venous plasma during fasting and euglycemic hyperinsulinemia. Nucl Med Biol. 2006; 33: 521-528. doi: 10.1016/j.nucmedbio.2006.02.003.
Guhlmann A, Krauss K, Oberdorfer F, Siegel T, Scheuber PH, Müller J, Csuk-Glänzer B, Ziegler S, Ostertag H, Keppler D. Noninvasive assessment of hepatobiliary and renal elimination of cysteinyl leukotrienes by positron emission tomography. Hepatology 1995; 21(6): 1568-1575. PMID: 7768501.
Iozzo P, Turpeinen AK, Takala T, Oikonen V, Solin O, Ferrannini E, Nuutila P, Knuuti J. Liver uptake of free fatty acids in vivo in humans as determined with 14(R,S)-[18F]fluoro-6-thia-heptadecanoic acid and PET. Eur J Nucl Med Mol Imaging 2003; 30: 1160-1164. doi: 10.1007/s00259-003-1215-0.
Iozzo P, Jarvisalo MJ, Kiss J, Borra R, Naum GA, Viljanen A, Viljanen T, Gastaldelli A, Buzzigoli E, Guiducci L, Barsotti E, Savunen T, Knuuti J, Haaparanta-Solin M, Ferrannini E, Nuutila P. Quantification of liver glucose metabolism by positron emission tomography: validation study in pigs. Gastroenterology 2007; 132: 531-542. doi: 10.1053/j.gastro.2006.12.040.
Keiding S, Munk OL, Schiøtt KM, Hansen SB. Dynamic 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography of liver tumours without blood sampling. Eur J Nucl Med. 2000; 27: 407-412. doi: 10.1007/s002590050523.
Keiding S. Bringing physiology into PET of the liver. J Nucl Med.2012; 53: 425-433. doi: 10.2967/jnumed.111.100214.
Kiss J, Naum A, Kudomi N, Knuuti J, Iozzo P, Savunen T, Nuutila P. Non-invasive diagnosis of acute mesenteric ischaemia using PET. Eur J Nucl Med Mol Imaging 2009; 36: 1338-1345. doi: 10.1007/s00259-009-1094-0.
Kudomi N, Järvisalo MJ, Kiss J, Borra R, Viljanen A, Viljanen T, Savunen T, Knuuti J, Iida H, Nuutila P, Iozzo P. Non-invasive estimation of hepatic glucose uptake from [18F]FDG PET images using tissue-derived input functions. Eur J Nucl Med Mol Imaging 2009; 36: 2014-2026. doi: 10.1007/s00259-009-1140-y.
Miyazaki S, Murase K, Yoshikawa T, Morimoto S, Ohno Y, Sugimura K. A quantitative method for estimating hepatic blood flow using a dual-input single-compartment model. Br J Radiol. 2008; 81(970): 790-800. doi: 10.1259/bjr/52166324.
Munk OL, Bass L, Roelsgaard K, Bender D, Hansen SB, Keiding S. Liver kinetics of glucose analogs measured in pigs by PET: importance of dual-input blood sampling. J Nucl Med. 2001; 42(5): 795-801. PMID: 11337579.
Munk OL, Keiding S, Bass L. Impulse-response function of splanchnic circulation with model-independent constraints: theory and experimental validation. Am J Physiol Gastrointest Liver Physiol. 2003; 285: G671-G680. doi: 10.1152/ajpgi.00054.2003.
Rani SD, Nemanich ST, Fettig N, Shoghi KI. Kinetic analysis of FDG in rat liver: effect of dietary intervention on arterial and portal vein input. Nucl Med Biol. 2013; 40: 537-546. doi: 10.1016/j.nucmedbio.2013.01.009.
Takashima T, Kitamura S, Wada Y, Tanaka M, Shigihara Y, Ishii H, Ijuin R, Shiomi S, Nakae T, Watanabe Y, Cui Y, Doi H, Suzuki M, Maeda K, Kusuhara H, Sugiyama Y, Watanabe Y. PET imaging-based evaluation of hepatobiliary transport in humans with (15R)-11C-TIC-Me. J Nucl Med. 2012; 53(5): 741-748. doi: 10.2967/jnumed.111.098681.
Taniguchi H, Masuyama M, Koyama H, Oguro A, Takahashi T. Quantitative measurement of human tissue hepatic blood volume by C15O inhalation with positron-emission tomography. Liver 1996; 16(4): 258-262. doi: 10.1111/j.1600-0676.1996.tb00739.x.
Taniguchi H, Oguro A, Takeuchi K, Miyata K, Takahashi T, Inaba T, Nakahashi H. Difference in regional hepatic blood flow in liver segments - non-invasive measurement of regional hepatic arterial and portal blood flow in human by positron emission tomography with H215O. Ann Nucl Med. 1993; 7(3): 141-145. doi: 10.1007/bf03164957.
Taniguchi H, Oguro A, Koyama H, Masuyama M, Takahashi T. Analysis of models for quantification of arterial and portal blood flow in the human liver using PET. J Comp Assist Tomogr. 1996; 20(1): 135-144. doi: 10.1097/00004728-199601000-00025.
Taniguchi H, Yamaguchi A, Kunishima S, Koh T, Masuyama M, Koyama H, Oguro A, Yamagishi H. Using the spleen for time-delay correction of the input function in measuring hepatic blood flow with oxygen-15 water by dynamic PET. Ann Nucl Med. 1999; 13(4): 215-221. doi: 10.1007/bf03164895.
Taniguchi H, Kunishima S, Koh T. The reproducibility of independently measuring human regional hepatic arterial, portal and total hepatic blood flow using [15O]water and positron emission tomography. Nucl Med Commun. 2003; 24: 497-501. doi: 10.1097/00006231-200305000-00003.
Trägårdh M, Møller N, Sørensen M. Methodologic considerations for quantitative 18F-FDG PET/CT studies of hepatic glucose metabolism in healthy subjects. J Nucl Med. 2015; 56: 1366-1371. doi: 10.2967/jnumed.115.154211.
Vivaldi V, Garbarino S, Caviglia G, Piana M, Sambuceti G. Compartmental analysis of nuclear imaging data for the quantification of FDG liver metabolism. arXiv: 1305.7435 [q-bio.TO] 2013.
Winterdahl M, Keiding S, Sørensen M, Mortensen F, Viborg F, Alstrup AKO, Munk OL. Tracer input for kinetic modelling of liver physiology determined without sampling portal venous blood in pigs. Eur J Nucl Med Mol Imaging 2011; 38: 263-270. doi: 10.1007/s00259-010-1620-0.
Ziegler SI, Haberkorn U, Byrne H, Tong C, Schosser R, Krieter H, Kaja S, Richolt JA, Lammertsma AA, Price P. Measurement of liver blood flow using oxygen-15 labelled water and dynamic positron emission tomography: limitations of model description. Eur J Nucl Med. 1996; 23: 169-177. doi: 10.1007/BF01731841.
Updated at: 2022-02-21
Created at: 2015-02-05
Written by: Vesa Oikonen