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Using dynamic contrast-enhanced magnetic resonance imaging data to constrain a positron emission tomography kinetic model: theory and simulations.

Fluckiger JU, Li X, Whisenant JG, Peterson TE, Gore JC, Yankeelov TE - Int J Biomed Imaging (2013)

Bottom Line: We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET) data.We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs) available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES), and the extravascular-intracellular space (EIS).The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Northwestern University, Chicago, IL 60611, USA.

ABSTRACT
We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET) data. We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs) available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES), and the extravascular-intracellular space (EIS). Then we simulate whole tissue TACs over a range of physiologically relevant kinetic parameter values and show that using appropriate DCE-MRI data can separate the PET TAC into the three components with accuracy that is noise dependent. The simulations show that accurate blood, EES, and EIS TACs can be obtained as evidenced by concordance correlation coefficients >0.9 between the true and estimated TACs. Additionally, provided that the estimated DCE-MRI parameters are within 10% of their true values, the errors in the PET kinetic parameters are within approximately 20% of their true values. The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies.

No MeSH data available.


Related in: MedlinePlus

The concordance correlation coefficient between the estimated and true values for the time courses as a function of error in the DCE-MRI parameters for a single set of PET kinetic parameters. The method is able to return the time courses faithfully when the DCE-MRI parameter error is less than 5%. With higher error in the DCE-MRI parameters, the CCC remains above 0.95 on average, though some realizations returned CCC values as low as 0.9.
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fig5: The concordance correlation coefficient between the estimated and true values for the time courses as a function of error in the DCE-MRI parameters for a single set of PET kinetic parameters. The method is able to return the time courses faithfully when the DCE-MRI parameter error is less than 5%. With higher error in the DCE-MRI parameters, the CCC remains above 0.95 on average, though some realizations returned CCC values as low as 0.9.

Mentions: Figures 5 and 6 display similar results as those in Figures 3 and 4. These two figures display the results from the simulations where the error in the DCE-MRI parameters increased from 0 to 15%. As stated above, in these simulations, the error in the Ct time course was fixed to the square root of the concentration in the tissue. Figure 5 shows the CCC between the extracted and true CEES, CEIS, and Cb time courses as a function of percent error in the DCE-MRI parameters for a single set of PET kinetic parameters. The mean CCCs are all above 0.9 across all parameter combinations and noise realizations. The minimum CCC over all the realizations was 0.6, which occurred when the error in the DCE parameters is 15%.


Using dynamic contrast-enhanced magnetic resonance imaging data to constrain a positron emission tomography kinetic model: theory and simulations.

Fluckiger JU, Li X, Whisenant JG, Peterson TE, Gore JC, Yankeelov TE - Int J Biomed Imaging (2013)

The concordance correlation coefficient between the estimated and true values for the time courses as a function of error in the DCE-MRI parameters for a single set of PET kinetic parameters. The method is able to return the time courses faithfully when the DCE-MRI parameter error is less than 5%. With higher error in the DCE-MRI parameters, the CCC remains above 0.95 on average, though some realizations returned CCC values as low as 0.9.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3814089&req=5

fig5: The concordance correlation coefficient between the estimated and true values for the time courses as a function of error in the DCE-MRI parameters for a single set of PET kinetic parameters. The method is able to return the time courses faithfully when the DCE-MRI parameter error is less than 5%. With higher error in the DCE-MRI parameters, the CCC remains above 0.95 on average, though some realizations returned CCC values as low as 0.9.
Mentions: Figures 5 and 6 display similar results as those in Figures 3 and 4. These two figures display the results from the simulations where the error in the DCE-MRI parameters increased from 0 to 15%. As stated above, in these simulations, the error in the Ct time course was fixed to the square root of the concentration in the tissue. Figure 5 shows the CCC between the extracted and true CEES, CEIS, and Cb time courses as a function of percent error in the DCE-MRI parameters for a single set of PET kinetic parameters. The mean CCCs are all above 0.9 across all parameter combinations and noise realizations. The minimum CCC over all the realizations was 0.6, which occurred when the error in the DCE parameters is 15%.

Bottom Line: We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET) data.We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs) available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES), and the extravascular-intracellular space (EIS).The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology, Northwestern University, Chicago, IL 60611, USA.

ABSTRACT
We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET) data. We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs) available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES), and the extravascular-intracellular space (EIS). Then we simulate whole tissue TACs over a range of physiologically relevant kinetic parameter values and show that using appropriate DCE-MRI data can separate the PET TAC into the three components with accuracy that is noise dependent. The simulations show that accurate blood, EES, and EIS TACs can be obtained as evidenced by concordance correlation coefficients >0.9 between the true and estimated TACs. Additionally, provided that the estimated DCE-MRI parameters are within 10% of their true values, the errors in the PET kinetic parameters are within approximately 20% of their true values. The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies.

No MeSH data available.


Related in: MedlinePlus