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Assessing Treatment Response Through Generalized Pharmacokinetic Modeling of DCE-MRI Data.

Kontopodis E, Kanli G, Manikis GC, Van Cauter S, Marias K - Cancer Inform (2015)

Bottom Line: Several assumptive PK models have been proposed to characterize microcirculation in the tumoral tissue.In this paper, we present a comparative study between the well-known extended Tofts model (ETM) and the more recent gamma capillary transit time (GCTT) model, with the latter showing initial promising results in the literature.The results indicate that GCTT model's PK parameters perform better than those of ETM, while the segmentation of the tumor regions of interest based on vascular heterogeneity further enhances the discriminatory power of the GCTT model.

View Article: PubMed Central - PubMed

Affiliation: Foundation for Research and Technology - Hellas (FORTH), Institute of Computer Science, Computational BioMedicine Lab, Heraklion, Greece.

ABSTRACT
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables the quantification of contrast leakage from the vascular tissue by using pharmacokinetic (PK) models. Such quantitative analysis of DCE-MRI data provides physiological parameters that are able to provide information of tumor pathophysiology and therapeutic outcome. Several assumptive PK models have been proposed to characterize microcirculation in the tumoral tissue. In this paper, we present a comparative study between the well-known extended Tofts model (ETM) and the more recent gamma capillary transit time (GCTT) model, with the latter showing initial promising results in the literature. To enhance the GCTT imaging biomarkers, we introduce a novel method for segmenting the tumor area into subregions according to their vascular heterogeneity characteristics. A cohort of 11 patients diagnosed with glioblastoma multiforme with known therapeutic outcome was used to assess the predictive value of both models in terms of correctly classifying responders and nonresponders based on only one DCE-MRI examination. The results indicate that GCTT model's PK parameters perform better than those of ETM, while the segmentation of the tumor regions of interest based on vascular heterogeneity further enhances the discriminatory power of the GCTT model.

No MeSH data available.


Related in: MedlinePlus

Workflow for calculation of PK parameters. The rectangles show the start and end points, the trapeziums show the extracted PK parameters, and the ellipsoids include the equations to be solved.
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Related In: Results  -  Collection


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f3-cin-suppl.4-2015-041: Workflow for calculation of PK parameters. The rectangles show the start and end points, the trapeziums show the extracted PK parameters, and the ellipsoids include the equations to be solved.

Mentions: Figure 3 presents the workflow for the conversion of concentrations to PK parameters. The PK parameters were calculated per voxel via nonlinear least squares problems†, by solving Equation (7) for ETM and Equation (11) for the GCTT model.


Assessing Treatment Response Through Generalized Pharmacokinetic Modeling of DCE-MRI Data.

Kontopodis E, Kanli G, Manikis GC, Van Cauter S, Marias K - Cancer Inform (2015)

Workflow for calculation of PK parameters. The rectangles show the start and end points, the trapeziums show the extracted PK parameters, and the ellipsoids include the equations to be solved.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4536783&req=5

f3-cin-suppl.4-2015-041: Workflow for calculation of PK parameters. The rectangles show the start and end points, the trapeziums show the extracted PK parameters, and the ellipsoids include the equations to be solved.
Mentions: Figure 3 presents the workflow for the conversion of concentrations to PK parameters. The PK parameters were calculated per voxel via nonlinear least squares problems†, by solving Equation (7) for ETM and Equation (11) for the GCTT model.

Bottom Line: Several assumptive PK models have been proposed to characterize microcirculation in the tumoral tissue.In this paper, we present a comparative study between the well-known extended Tofts model (ETM) and the more recent gamma capillary transit time (GCTT) model, with the latter showing initial promising results in the literature.The results indicate that GCTT model's PK parameters perform better than those of ETM, while the segmentation of the tumor regions of interest based on vascular heterogeneity further enhances the discriminatory power of the GCTT model.

View Article: PubMed Central - PubMed

Affiliation: Foundation for Research and Technology - Hellas (FORTH), Institute of Computer Science, Computational BioMedicine Lab, Heraklion, Greece.

ABSTRACT
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables the quantification of contrast leakage from the vascular tissue by using pharmacokinetic (PK) models. Such quantitative analysis of DCE-MRI data provides physiological parameters that are able to provide information of tumor pathophysiology and therapeutic outcome. Several assumptive PK models have been proposed to characterize microcirculation in the tumoral tissue. In this paper, we present a comparative study between the well-known extended Tofts model (ETM) and the more recent gamma capillary transit time (GCTT) model, with the latter showing initial promising results in the literature. To enhance the GCTT imaging biomarkers, we introduce a novel method for segmenting the tumor area into subregions according to their vascular heterogeneity characteristics. A cohort of 11 patients diagnosed with glioblastoma multiforme with known therapeutic outcome was used to assess the predictive value of both models in terms of correctly classifying responders and nonresponders based on only one DCE-MRI examination. The results indicate that GCTT model's PK parameters perform better than those of ETM, while the segmentation of the tumor regions of interest based on vascular heterogeneity further enhances the discriminatory power of the GCTT model.

No MeSH data available.


Related in: MedlinePlus