Skip to main content
Log in

A State Space Transformation Can Yield Identifiable Models for Tracer Kinetic Studies with Enrichment Data

  • Original Article
  • Published:
Bulletin of Mathematical Biology Aims and scope Submit manuscript

Abstract

Tracer studies are analyzed almost universally by multicompartmental models where the state variables are tracer amounts or activities in the different pools. The model parameters are rate constants, defined naturally by expressing fluxes as fractions of the source pools. We consider an alternative state space with tracer enrichments or specific activities as the state variables, with the rate constants redefined by expressing fluxes as fractions of the destination pools. Although the redefinition may seem unphysiological, the commonly computed fractional synthetic rate actually expresses synthetic flux as a fraction of the product mass (destination pool). We show that, for a variety of structures, provided the structure is linear and stationary, the model in the enrichment state space has fewer parameters than that in the activities state space, and is hence better both to study identifiability and to estimate parameters. The superiority of enrichment modeling is shown for structures where activity model unidentifiability is caused by multiple exit pathways; on the other hand, with a single exit pathway but with multiple untraced entry pathways, activity modeling is shown to be superior. With the present-day emphasis on mass isotopes, the tracer in human studies is often of a precursor, labeling most or all entry pathways. It is shown that for these tracer studies, models in the activities state space are always unidentifiable when there are multiple exit pathways, even if the enrichment in every pool is observed; on the other hand, the corresponding models in the enrichment state space have fewer parameters and are more often identifiable. Our results suggest that studies with labeled precursors are modeled best with enrichments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Abbreviations

F :

flux

f :

vector of rate constants for entry from outside

FCR:

fractional catabolic rate

FSR:

fractional synthetic rate

g :

vector of rate constants for exit to outside

K,R:

system matrix of rate constants

k,r:

rate constant

P :

diagonal matrix of pool masses

Q :

total mass or activity of tracer+tracee

q :

mass or activity of tracer

q-model:

model for tracer activities or amounts

S :

synthetic flux

s :

synthetic rate constant

t :

time

u :

a vector whose every element is 1

w :

precursor enrichment

y :

tracer enrichment

y-model:

model for tracer enrichments or specific activities

z :

observed tracer enrichment

References

  • Anderson, D.H., 1983. Compartmental Modeling and Tracer Kinetics. Springer, Berlin.

    MATH  Google Scholar 

  • Arad, Y., Ramakrishnan, R., Ginsberg, H.N., 1990. Lovastatin therapy reduces low density lipoprotein apoB levels in subjects with combined hyperlipidemia by reducing the production of apoB-containing lipoproteins: implications for the pathophysiology of apoB production. J. Lipid Res. 31, 567–582.

    Google Scholar 

  • Barrett, P.H.R., Chan, D.C., Watts, G.F., 2006. Design and analysis of lipoprotein tracer kinetics studies in humans. J. Lipid Res. 47, 1607–1619.

    Article  Google Scholar 

  • Basu, R., Di Camillo, B., Toffolo, G., Basu, A., Shah, P., Vella, A., Rizza, R., Cobelli, C., 2003. Use of a novel triple-tracer approach to assess postprandial glucose metabolism. Am. J. Physiol.-Endocrinol. Metab. 284, E55–E69.

    Google Scholar 

  • Bellman, R., Åström, K.J., 1970. On structural identifiability. Math. Biosci. 7, 329–339.

    Article  Google Scholar 

  • Berglund, L., Witztum, J.L., Galeano, N.F., Khouw, A.S., Ginsberg, H.N., Ramakrishnan, R., 1998. Three-fold effect of lovastatin treatment on low density lipoprotein metabolism in subjects with hyperlipidemia: increase in receptor activity, decrease in apoB production, and decrease in particle affinity for the receptor. Results from a novel triple-tracer approach. J. Lipid Res. 39, 913–924.

    Google Scholar 

  • Berman, M., Schoenfeld, R., 1956. Invariants in experimental data on linear kinetics and the formulation of models. J. Appl. Phys. 27, 1361–1370.

    Article  Google Scholar 

  • Berman, M., Weiss, M.F., Shahn, E., 1962. Some formal approaches to the analysis of kinetic data in terms of linear compartmental systems. Biophys. J. 2, 289–316.

    Article  Google Scholar 

  • Bright, P.B., 1973. Volumes of some compartment systems with sampling and loss from one compartment. Bull. Math. Biol. 35, 69–79.

    Google Scholar 

  • Brown, R.F., Godfrey, K.R., 1978. Problems of determinacy in compartmental modeling with application to bilirubin kinetics. Math. Biosci. 40, 205–224.

    Article  MATH  Google Scholar 

  • Chapman, M.J., Godfrey, K.R., 1985. Some extensions to the exhaustive modelling approach to structural identifiability. Math. Biosci. 77, 305–323.

    Article  MathSciNet  MATH  Google Scholar 

  • Chau, N.P., 1985. Parameter identification in n-compartment mammillary models. Math. Biosci. 74, 199–218.

    Article  MathSciNet  MATH  Google Scholar 

  • Chen, B.C., Landaw, E.M., DiStefano, J.J. 3rd, 1985. Algorithms for the identifiable parameter combinations and parameter bounds of unidentifiable catenary compartmental models. Math. Biosci. 76, 59–68.

    Article  MathSciNet  MATH  Google Scholar 

  • Cobelli, C., DiStefano, J.J. 3rd, 1980. Parameter and structural identifiability concepts and ambiguities: a critical review and analysis. Am. J. Physiol.-Endocrinol. Metab. 239, R7–R24.

    Google Scholar 

  • Cobelli, C., Toffolo, G., 1984. Identifiability from parameter bounds, structural and numerical aspects. Math. Biosci. 71, 237–243.

    Article  MathSciNet  MATH  Google Scholar 

  • Cobelli, C., Toffolo, G., 1987. Theoretical aspects and practical strategies for the identification of unidentifiable compartmental systems. In: Walter, E. (Ed.), Identifiability of Parametric Models, pp. 85–91. Pergamon, Oxford.

    Google Scholar 

  • Cobelli, C., Lepschy, A., Jacur, G.R., 1979. Identifiability results on some constrained compartmental systems. Math. Biosci. 47, 173–195.

    Article  MathSciNet  MATH  Google Scholar 

  • Cobelli, C., Toffolo, G., Ferrannini, E., 1984. A model of glucose kinetics and their control by insulin, compartmental and noncompartmental approaches. Math. Biosci. 72, 291–315.

    Article  MATH  Google Scholar 

  • Cobelli, C., Toffolo, G., Bier, D.M., Nosadini, R., 1987. Models to interpret kinetic data in stable isotope tracer studies. Am. J. Physiol.-Endocrinol. Metab. 253, E551–E564.

    Google Scholar 

  • Cobelli, C., Foster, D., Toffolo, G., 2000. Tracer kinetics in biomedical research: from data to model. Kluwer Academic, New York.

    Google Scholar 

  • Demant, T., Packard, C.J., Demmelmair, H., Stewart, P., Bedynek, A., Bedford, D., Seidel, D., Shepherd, J., 1996. Sensitive methods to study human apolipoprotein B metabolism using stable isotope-labeled amino acids Am. J. Physiol.-Endocrinol. Metab. 270(6), E1022–E1036.

    Google Scholar 

  • DiStefano, J.J. 3rd, 1983. Complete parameter bounds and quasiidentifiability conditions for a class of unidentifiable linear systems. Math. Biosci. 65, 51–68.

    Article  MATH  Google Scholar 

  • DiStefano, J.J. 3rd, Chen, B.C., Landaw, E.M., 1988. Pool size and mass flux bounds and quasiidentifiability relations for catenary models. Math. Biosci. 88, 1–14.

    Article  MathSciNet  MATH  Google Scholar 

  • Eisenfeld, J., 1996. Partial identification of underdetermined compartmental models: a method based on positive linear Lyapunov functions. Math. Biosci. 132, 111–140.

    Article  MathSciNet  MATH  Google Scholar 

  • Evans, N.D., Erlington, R.J., Shelley, M., Feeney, G.P., Chapman, M.J., Godfrey, K.R., Smith, P.J., Chappell, M.J., 2004. A mathematical model for the in vitro kinetics of the anti-cancer agent topotecan. Math. Biosci. 189, 185–217.

    Article  MathSciNet  MATH  Google Scholar 

  • Ferrannini, E., Smith, J.D., Cobelli, C., Toffolo, G., Pilo, A., DeFronzo, R.A., 1985. Effect of insulin on the distribution and disposition of glucose in man. J. Clin. Investig. 76, 357–364.

    Article  Google Scholar 

  • García-Meseguer, M.J., Vidal de Labra, J.A., García-Moreno, M., García-Cánovas, F., Havsteen, B.H., Varón, R., 2003. Mean residence times in linear compartmental systems. Symbolic formulae for their direct evaluation. Bull. Math. Biol. 65, 279–308.

    Article  Google Scholar 

  • Garlick, P.J., Mcnurlan, M.A., Essen, P., Wernerman, J., 1994. Measurement of tissue protein-synthesis rates in-vivo—a critical analysis of contrasting methods. Am. J. Physiol.-Endocrinol. Metab. 266(3), E287–E297.

    Google Scholar 

  • Gastaldelli, A., Schwarz, J.M., Caveggion, E., Traber, I.D., Traber, D.L., Rosenblatt, J., Toffolo, G., Cobelli, C., Wolfe, R.R., 1997. Glucose kinetics in interstitial fluid can be predicted by compartmental modeling. Am. J. Physiol.-Endocrinol. Metab. 272, E494–E505.

    Google Scholar 

  • Hart, H.E., 1955. Analysis of tracer experiments in non-conservative steady-state systems. Bull. Math. Biophys. 17, 87–94.

    Article  Google Scholar 

  • Hart, H.E., 1965. Determination of equilibrium constants and maximum binding capacities in complex in vitro systems: I. The mammillary system. Bull. Math. Biophys. 27, 87–98.

    Article  Google Scholar 

  • Hearon, J.Z., 1963. Theorems on linear systems. Ann. N. Y. Acad. Sci. 108, 36–68.

    Article  MathSciNet  MATH  Google Scholar 

  • Hearon, J.Z., 1974. A note on open linear systems. Bull. Math. Biol. 36, 97–99.

    MathSciNet  MATH  Google Scholar 

  • Jacquez, J.A., 1985a. Richard Bellman. Math. Biosci. 77, 1–4.

    Article  MathSciNet  MATH  Google Scholar 

  • Jacquez, J.A., 1985b. Compartmental Analysis in Biology and Medicine. University of Michigan, Ann Arbor.

    Google Scholar 

  • Jacquez, J.A., Simon, C.P., 1993. Qualitative theory of compartmental systems. SIAM Rev. 35, 43–79.

    Article  MathSciNet  MATH  Google Scholar 

  • Landaw, E.M., Chen, B.C., DiStefano, J.J. 3rd, 1984. An algorithm for the identifiable parameter combinations of the general mammillary compartmental model. Math. Biosci. 72, 199–212.

    Article  MATH  Google Scholar 

  • Lindell, R., DiStefano, J.J. 3rd, Landaw, E.M., 1988. Statistical variability of parameter bounds for n-pool unidentifiable mammillary and catenary models. Math. Biosci. 91, 175–199.

    Article  MATH  Google Scholar 

  • Nagashima, K., Lopez, C., Donovan, D., Ngai, C., Fontanez, N., Bensadoun, A., Fruchart-Najib, J., Holleran, S., Cohn, J.S., Ramakrishnan, R., Ginsberg, H.N., 2005. Effects of the PPARgamma agonist pioglitazone on lipoprotein metabolism in patients with type 2 diabetes mellitus. J. Clin. Investig. 115, 1323–1332.

    Google Scholar 

  • Packard, C.J., Demant, T., Stewart, J.P., Bedford, D., Caslake, M.J., Schwertfeger, G., Bedynek, A., Shepherd, J., Seidel, D., 2000. Apolipoprotein B metabolism and the distribution of VLDL and LDL subfractions. J. Lipid Res. 41(2), 305–317.

    Google Scholar 

  • Perl, W., Lassen, N.A., Effros, R.M., 1975. Matrix proof of flow, volume and mean transit time theorems for regional and compartmental systems. Bull. Math. Biol. 37, 573–588.

    MATH  Google Scholar 

  • Pont, F., Duvillard, L., Verges, B., Gambert, P., 1998. Development of compartmental models in stable-isotope experiments—application to lipid metabolism Arterioscler. Thromb. Vasc. Biol. 18(6), 853–860.

    Google Scholar 

  • Ramakrishnan, R., 1984. An application of Berman’s work on pool-model invariants in analyzing indistinguishable models for whole-body cholesterol metabolism. Math. Biosci. 72, 373–385.

    Article  MathSciNet  MATH  Google Scholar 

  • Ramakrishnan, R., 2006. Studying apolipoprotein turnover with stable isotope tracers—correct analysis is by modeling enrichments. J. Lipid Res. 47, 2738–2753.

    Article  Google Scholar 

  • Ramakrishnan, R., Ramakrishnan, J.D., 2008. Utilizing mass measurements in tracer studies—a systematic approach to efficient modeling. Metab.-Clin. Exp. 57, 1078–1087.

    Google Scholar 

  • Ramakrishnan, R., Dell, R.B., Goodman, D.S., 1981. On determining the extent of side-pool synthesis in a three-pool model for whole body cholesterol kinetics. J. Lipid Res. 22, 1174–1180.

    Google Scholar 

  • Ramakrishnan, R., Leonard, E.F., Dell, R.B., 1984. A proof of the occupancy principle and the mean transit time theorem for compartmental models. Math. Biosci. 68, 121–136.

    Article  MathSciNet  MATH  Google Scholar 

  • Rescigno, A., Michels, L., 1973. Compartment modeling from tracer experiments. Bull. Math. Biol. 35, 245–257.

    Google Scholar 

  • Rescigno, A., Segre, G., 1964. On some topological properties of the systems of compartments. Bull. Math. Biophys. 26, 31–38.

    Article  MathSciNet  MATH  Google Scholar 

  • Rescigno, A., Segre, G., 1966. Drug and Tracer Kinetics. Blaisdell, Waltham.

    Google Scholar 

  • Rubinow, S.I., Winzer, A., 1971. Compartment analysis: an inverse problem. Math. Biosci. 11, 203–247.

    Article  MathSciNet  MATH  Google Scholar 

  • Shipley, R.A., Clark, R.E., 1972. Tracer Methods for Vivo Kinetics—Theory and Applications, Academic Press, New York.

    Google Scholar 

  • Tremblay, A.J., Lamarche, B., Cohn, J.S., Hogue, J.C., Couture, P., 2006. Effect of Ezetimibe on the in vivo kinetics of ApoB-48 and ApoB-100 in men with primary hypercholesterolemia. Arterioscler. Thromb. Vasc. Biol. 26(5), 1101–1106.

    Article  Google Scholar 

  • Vajda, S., 1984. Analysis of unique structural identifiability via submodels. Math. Biosci. 71, 125–146.

    Article  MathSciNet  MATH  Google Scholar 

  • Vajda, S., DiStefano, J.J. 3rd, Godfrey, K.R., Fagarasan, J., 1989. Parameter space boundaries for unidentifiable compartmental models. Math. Biosci. 97, 27–60.

    Article  MathSciNet  MATH  Google Scholar 

  • Vicini, P., Su, H., DiStefano, J.J. 3rd, 2000. Identifiability and interval identifiability of mammillary and catenary compartmental models with some known rate constants. Math. Biosci. 167, 145–161.

    Article  MATH  Google Scholar 

  • Walter, E., 1987. Identifiability of Parametric Models. Pergamon, Oxford.

    MATH  Google Scholar 

  • Zak, R., Martin, A.F., Blough, R., 1979. Assessment of protein turnover by use of radioisotopic tracers. Physiol. Rev. 59, 407–447.

    Google Scholar 

  • Zilversmit, D.B., 1960. The design and analysis of isotope experiments. Am. J. Med. 29, 832–848.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rajasekhar Ramakrishnan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ramakrishnan, R., Ramakrishnan, J.D. A State Space Transformation Can Yield Identifiable Models for Tracer Kinetic Studies with Enrichment Data. Bull. Math. Biol. 72, 2019–2046 (2010). https://doi.org/10.1007/s11538-010-9522-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11538-010-9522-7

Keywords

Navigation