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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 error in the estimated PET kinetic parameters as a function of the noise in the tissue curves. Each panel corresponds to a different set of PET kinetic parameters. For each set of parameters, when the error in Ct is less than 10 times the square root of the activity level, the parameter error is less than 50. As the error in Ct continues to increase, the error in k3 and k4 increases rapidly. The error in K1 and k2 also continues to increase, but less rapidly.
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fig4: The error in the estimated PET kinetic parameters as a function of the noise in the tissue curves. Each panel corresponds to a different set of PET kinetic parameters. For each set of parameters, when the error in Ct is less than 10 times the square root of the activity level, the parameter error is less than 50. As the error in Ct continues to increase, the error in k3 and k4 increases rapidly. The error in K1 and k2 also continues to increase, but less rapidly.

Mentions: As stated above, two sets of noise realizations were performed. Figures 3 and 4 display results of simulations done with varying levels of noise added to the simulated Ctissue curves, and with no error in the DCE-MRI parameters. Figure 3 shows the CCC (vertical axis) between the extracted and true CEES, CEIS, and Cb time courses as a function of increasing Ctissue noise for one combination of PET kinetic parameters. The results are presented as the mean ± the minimum and maximum CCC values obtained over the 1000 noise realizations. The results from the other seven combinations of PET kinetic parameters are similar. In all cases, when no noise is added to the simulated Ctissue curves, the CCC values are uniformly 1.00. The mean CCC values decrease with increased noise, with the CCC for Cb and CEES decreasing to 0.2 at the maximum level of noise tested here. For all combinations of PET kinetic parameters, the CEIS time courses are the least affected by noise in the tissue curves.


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 error in the estimated PET kinetic parameters as a function of the noise in the tissue curves. Each panel corresponds to a different set of PET kinetic parameters. For each set of parameters, when the error in Ct is less than 10 times the square root of the activity level, the parameter error is less than 50. As the error in Ct continues to increase, the error in k3 and k4 increases rapidly. The error in K1 and k2 also continues to increase, but less rapidly.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig4: The error in the estimated PET kinetic parameters as a function of the noise in the tissue curves. Each panel corresponds to a different set of PET kinetic parameters. For each set of parameters, when the error in Ct is less than 10 times the square root of the activity level, the parameter error is less than 50. As the error in Ct continues to increase, the error in k3 and k4 increases rapidly. The error in K1 and k2 also continues to increase, but less rapidly.
Mentions: As stated above, two sets of noise realizations were performed. Figures 3 and 4 display results of simulations done with varying levels of noise added to the simulated Ctissue curves, and with no error in the DCE-MRI parameters. Figure 3 shows the CCC (vertical axis) between the extracted and true CEES, CEIS, and Cb time courses as a function of increasing Ctissue noise for one combination of PET kinetic parameters. The results are presented as the mean ± the minimum and maximum CCC values obtained over the 1000 noise realizations. The results from the other seven combinations of PET kinetic parameters are similar. In all cases, when no noise is added to the simulated Ctissue curves, the CCC values are uniformly 1.00. The mean CCC values decrease with increased noise, with the CCC for Cb and CEES decreasing to 0.2 at the maximum level of noise tested here. For all combinations of PET kinetic parameters, the CEIS time courses are the least affected by noise in the tissue curves.

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