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Parameterization of the Age-Dependent Whole Brain Apparent Diffusion Coefficient Histogram.

Klose U, Batra M, Nägele T - Biomed Res Int (2015)

Bottom Line: The distribution of apparent diffusion coefficient (ADC) values in the brain can be used to characterize age effects and pathological changes of the brain tissue.This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects.The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects.

View Article: PubMed Central - PubMed

Affiliation: Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany.

ABSTRACT

Purpose: The distribution of apparent diffusion coefficient (ADC) values in the brain can be used to characterize age effects and pathological changes of the brain tissue. The aim of this study was the parameterization of the whole brain ADC histogram by an advanced model with influence of age considered.

Methods: Whole brain ADC histograms were calculated for all data and for seven age groups between 10 and 80 years. Modeling of the histograms was performed for two parts of the histogram separately: the brain tissue part was modeled by two Gaussian curves, while the remaining part was fitted by the sum of a Gaussian curve, a biexponential decay, and a straight line.

Results: A consistent fitting of the histograms of all age groups was possible with the proposed model.

Conclusions: This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects. The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects.

No MeSH data available.


Related in: MedlinePlus

Fitted parameters of the second part of the histogram for the different age classes: amplitudes A3 (-) and A4 (- -) of the exponential decay curves (a), the diffusion constants k3 and k4 of the exponential decays (b), the amplitude A6 of the Gaussian curve for the CSF component (-) and the value A5 of the straight line at the position 0.875 · 10−3 mm2/s (- -) (c), the peak position μ6 (d) and the width (FWHM) (e) of the Gaussian curve for the CSF component. In all cases, the parameters are shown for women (red), men (blue), and all patients (black).
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fig9: Fitted parameters of the second part of the histogram for the different age classes: amplitudes A3 (-) and A4 (- -) of the exponential decay curves (a), the diffusion constants k3 and k4 of the exponential decays (b), the amplitude A6 of the Gaussian curve for the CSF component (-) and the value A5 of the straight line at the position 0.875 · 10−3 mm2/s (- -) (c), the peak position μ6 (d) and the width (FWHM) (e) of the Gaussian curve for the CSF component. In all cases, the parameters are shown for women (red), men (blue), and all patients (black).

Mentions: The results of the fitting of the second part of the histogram using and the deviations are shown in Supplementary Table 3. The comparison of the second part of the mean histograms for the seven age classes with the fitted curves is shown in Figure 7(a). The fitted curves consist of three different components: the biexponential decay, a Gaussian curve to describe the local maximum at 2.8 · 10−3 mm2/s, and a straight line with a negative slope and a foot point at 4.3 · 10−3 mm2/s. These components are shown in Figure 7(b). The variation of the fitted parameters of the second part of the histogram for the different age classes is shown in Figure 8 again for all datasets in bold and in addition for the three subsets. The evaluation for male and female separately (Figure 9) showed no clear difference between the evaluated parameters. The comparison of the complete histograms with both parts of the fitted curves is shown in Figure 10(a). The small step between the fitted curves of hist1 and hist2 can be seen in Figure 10(b).


Parameterization of the Age-Dependent Whole Brain Apparent Diffusion Coefficient Histogram.

Klose U, Batra M, Nägele T - Biomed Res Int (2015)

Fitted parameters of the second part of the histogram for the different age classes: amplitudes A3 (-) and A4 (- -) of the exponential decay curves (a), the diffusion constants k3 and k4 of the exponential decays (b), the amplitude A6 of the Gaussian curve for the CSF component (-) and the value A5 of the straight line at the position 0.875 · 10−3 mm2/s (- -) (c), the peak position μ6 (d) and the width (FWHM) (e) of the Gaussian curve for the CSF component. In all cases, the parameters are shown for women (red), men (blue), and all patients (black).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4644831&req=5

fig9: Fitted parameters of the second part of the histogram for the different age classes: amplitudes A3 (-) and A4 (- -) of the exponential decay curves (a), the diffusion constants k3 and k4 of the exponential decays (b), the amplitude A6 of the Gaussian curve for the CSF component (-) and the value A5 of the straight line at the position 0.875 · 10−3 mm2/s (- -) (c), the peak position μ6 (d) and the width (FWHM) (e) of the Gaussian curve for the CSF component. In all cases, the parameters are shown for women (red), men (blue), and all patients (black).
Mentions: The results of the fitting of the second part of the histogram using and the deviations are shown in Supplementary Table 3. The comparison of the second part of the mean histograms for the seven age classes with the fitted curves is shown in Figure 7(a). The fitted curves consist of three different components: the biexponential decay, a Gaussian curve to describe the local maximum at 2.8 · 10−3 mm2/s, and a straight line with a negative slope and a foot point at 4.3 · 10−3 mm2/s. These components are shown in Figure 7(b). The variation of the fitted parameters of the second part of the histogram for the different age classes is shown in Figure 8 again for all datasets in bold and in addition for the three subsets. The evaluation for male and female separately (Figure 9) showed no clear difference between the evaluated parameters. The comparison of the complete histograms with both parts of the fitted curves is shown in Figure 10(a). The small step between the fitted curves of hist1 and hist2 can be seen in Figure 10(b).

Bottom Line: The distribution of apparent diffusion coefficient (ADC) values in the brain can be used to characterize age effects and pathological changes of the brain tissue.This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects.The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects.

View Article: PubMed Central - PubMed

Affiliation: Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany.

ABSTRACT

Purpose: The distribution of apparent diffusion coefficient (ADC) values in the brain can be used to characterize age effects and pathological changes of the brain tissue. The aim of this study was the parameterization of the whole brain ADC histogram by an advanced model with influence of age considered.

Methods: Whole brain ADC histograms were calculated for all data and for seven age groups between 10 and 80 years. Modeling of the histograms was performed for two parts of the histogram separately: the brain tissue part was modeled by two Gaussian curves, while the remaining part was fitted by the sum of a Gaussian curve, a biexponential decay, and a straight line.

Results: A consistent fitting of the histograms of all age groups was possible with the proposed model.

Conclusions: This study confirms the strong dependence of the whole brain ADC histograms on the age of the examined subjects. The proposed model can be used to characterize changes of the whole brain ADC histogram in certain diseases under consideration of age effects.

No MeSH data available.


Related in: MedlinePlus