Stochastic modelling of physiologic processes with radiotracers and positron emission tomography

Rescigno, A; Lambrecht, R M; Duncan, C C

Title: Stochastic modelling of physiologic processes with radiotracers and positron emission tomography

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Abstract

The compartment model, so often used in nuclear medicine and in pharmacokinetics, is formed by a set of linear differential equations of order one with constant coefficients; its validity depends upon the hypothesis that the system described contains a finite number of components, and that each component is homogeneous. These hypotheses exclude the presence of diffusion and of age-dependent processes, or in general of transport of a non-Markovian nature. The fact that frequently the experimental data agree with this model does not necessarily prove the model is appropriate, but only that it is flexible. In addition to the consistency with the experimental data, an obvious conceptual requirement of the model is that its parameters could be interpreted in terms of perceivable physical properties. All this considered, it will be demonstrated that the experimental data can be examined in terms of a model making a minimum number of assumptions and giving the best physical interpretations to the parameters involved. By way of example, a high resolution positron emission tomograph will be used to determine the successive moments describing the blood circulation through different sections of the brain. Whereever the relative moments form a geometric progression, the circulation in that section followsmore »« less

Authors:: Rescigno, A; Lambrecht, R M; Duncan, C C

Publication Date:: Fri Jan 01 00:00:00 EST 1982

Research Org.:: Brookhaven National Lab., Upton, NY (USA)

OSTI Identifier:: 5176922

Report Number(s):: BNL-31102; CONF-820354-1
ON: DE82012468; TRN: 82-016439

DOE Contract Number:: AC02-76CH00016

Resource Type:: Conference

Resource Relation:: Conference: Conference on applications of physics to medicine and biology, Trieste, Italy, 30 Mar 1982

Country of Publication:: United States

Language:: English

Subject:: 62 RADIOLOGY AND NUCLEAR MEDICINE; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; 59 BASIC BIOLOGICAL SCIENCES; BLOOD FLOW; MATHEMATICAL MODELS; BRAIN; POSITRON COMPUTED TOMOGRAPHY; COMPARTMENTS; DIFFERENTIAL EQUATIONS; PATIENTS; STOCHASTIC PROCESSES; BODY; CENTRAL NERVOUS SYSTEM; COMPUTERIZED TOMOGRAPHY; DIAGNOSTIC TECHNIQUES; EMISSION COMPUTED TOMOGRAPHY; EQUATIONS; NERVOUS SYSTEM; ORGANS; TOMOGRAPHY; 550601* - Medicine- Unsealed Radionuclides in Diagnostics; 990200 - Mathematics & Computers; 551001 - Physiological Systems- Tracer Techniques

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                    Rescigno, A, Lambrecht, R M, and Duncan, C C. Stochastic modelling of physiologic processes with radiotracers and positron emission tomography.  United States: N. p., 1982. 
        Web.

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                    Rescigno, A, Lambrecht, R M, & Duncan, C C. Stochastic modelling of physiologic processes with radiotracers and positron emission tomography.  United States.

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                    Rescigno, A, Lambrecht, R M, and Duncan, C C. 1982.  
        "Stochastic modelling of physiologic processes with radiotracers and positron emission tomography".  United States.  https://www.osti.gov/servlets/purl/5176922.

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@article{osti_5176922,

  title        = {Stochastic modelling of physiologic processes with radiotracers and positron emission tomography},

  author       = {Rescigno, A and Lambrecht, R M and Duncan, C C},

  abstractNote = {The compartment model, so often used in nuclear medicine and in pharmacokinetics, is formed by a set of linear differential equations of order one with constant coefficients; its validity depends upon the hypothesis that the system described contains a finite number of components, and that each component is homogeneous. These hypotheses exclude the presence of diffusion and of age-dependent processes, or in general of transport of a non-Markovian nature. The fact that frequently the experimental data agree with this model does not necessarily prove the model is appropriate, but only that it is flexible. In addition to the consistency with the experimental data, an obvious conceptual requirement of the model is that its parameters could be interpreted in terms of perceivable physical properties. All this considered, it will be demonstrated that the experimental data can be examined in terms of a model making a minimum number of assumptions and giving the best physical interpretations to the parameters involved. By way of example, a high resolution positron emission tomograph will be used to determine the successive moments describing the blood circulation through different sections of the brain. Whereever the relative moments form a geometric progression, the circulation in that section follows the rules of a perfect compartment; if this is not the case, the analytical method described can be used to describe the behavior of a tracer particle in the part of the organ. (ERB)},

  doi          = {},

  url          = {https://www.osti.gov/biblio/5176922},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Jan 01 00:00:00 EST 1982},

  month        = {Fri Jan 01 00:00:00 EST 1982}

}

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