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Age-specific MRI brain and head templates for healthy adults from 20 through 89 years of age.

Fillmore PT, Phillips-Meek MC, Richards JE - Front Aging Neurosci (2015)

Bottom Line: The participants included healthy adults from 20 through 89 years of age.It was found that age-appropriate templates provided less biased tissue classification estimates than age-inappropriate reference data and reference data based on young adult templates.This database is available for use by other investigators and clinicians for their MRI studies, as well as other types of neuroimaging and electrophysiological research.

View Article: PubMed Central - PubMed

Affiliation: Department of Communication Sciences and Disorders, University of South Carolina Columbia, SC, USA.

ABSTRACT
This study created and tested a database of adult, age-specific MRI brain and head templates. The participants included healthy adults from 20 through 89 years of age. The templates were done in five-year, 10-year, and multi-year intervals from 20 through 89 years, and consist of average T1W for the head and brain, and segmenting priors for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). It was found that age-appropriate templates provided less biased tissue classification estimates than age-inappropriate reference data and reference data based on young adult templates. This database is available for use by other investigators and clinicians for their MRI studies, as well as other types of neuroimaging and electrophysiological research.

No MeSH data available.


Comparing segmentation methods across age ranges. Dice similarity values are shown for both gray matter (GM) and white matter (WM) for comparisons to the manually segmented IBSR18 and IBSR20 datasets. Values are shown for the MNI-based and Image-based prior sets, for a priori and a posteriori specification, and for age-appropriate five-year (“5”) and ten-year (“10”) templates, as well as our young adult (“20–24”) template. “MNI” refers to the standard MNI152 priors, and “Image” refers to segmentation from the base image, without explicitly specifying priors. Note that performance is generally best for a posteriori specification, using age-appropriate priors within a five-year range. Selected significant post hoc comparisons are highlighted; the “MNI” template had the lowest Dice values for each comparison.
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Figure 5: Comparing segmentation methods across age ranges. Dice similarity values are shown for both gray matter (GM) and white matter (WM) for comparisons to the manually segmented IBSR18 and IBSR20 datasets. Values are shown for the MNI-based and Image-based prior sets, for a priori and a posteriori specification, and for age-appropriate five-year (“5”) and ten-year (“10”) templates, as well as our young adult (“20–24”) template. “MNI” refers to the standard MNI152 priors, and “Image” refers to segmentation from the base image, without explicitly specifying priors. Note that performance is generally best for a posteriori specification, using age-appropriate priors within a five-year range. Selected significant post hoc comparisons are highlighted; the “MNI” template had the lowest Dice values for each comparison.

Mentions: The purpose of this analysis was to evaluate the overlap between the manually segmented brain volumes from the IBSR and the primary segmentation routines (listed in Figure 2). Figure 4 illustrates the general pattern of the segmentation outputs for a single participant. We used a one-way ANOVA to examine the relative fit of the five methods (Image, MNI-a priori, Image-AVG-a priori, Image-AVG-a posteriori, MNI-AVG-a posteriori) to the manually guided segmentations, separately for GM and WM, and for each IBSR dataset. The segment type main effect was significant for all four comparisons; GM, IBSR-18, F(4,41) = 42.86, p < 0.001; WM, IBSR-18, F(4,45) = 16.07, p < 0.001; GM, IBSR-20, F(4,34) = 139.57, p < 0.001; WM, IBSR-20, F(4,34) = 81.61, p < 0.0001. Figure 5 show the means separately for these five segmentation procedures; and the segmentations with average template priors are shown separately for the young adult, five-year and 10-year age-appropriate average templates. We did post hoc tests to compare averages from individual segment types, and there were many significant differences. For GM, segmentation with age-appropriate five-year template was the best fit and the participant’s individual MNI segmentation was the worst fit. A particularly relevant comparison is the Image and the Image-AVG-a posteriori comparison, which showed a significantly larger dice value for the age-appropriate segmentation. The same general pattern occurred for WM, with the exception that for WM, segmentation with age-appropriate Image-AVG-a posteriori method was not significantly different from the Image (no priors) segmentation (see Figure 5, bottom figures).


Age-specific MRI brain and head templates for healthy adults from 20 through 89 years of age.

Fillmore PT, Phillips-Meek MC, Richards JE - Front Aging Neurosci (2015)

Comparing segmentation methods across age ranges. Dice similarity values are shown for both gray matter (GM) and white matter (WM) for comparisons to the manually segmented IBSR18 and IBSR20 datasets. Values are shown for the MNI-based and Image-based prior sets, for a priori and a posteriori specification, and for age-appropriate five-year (“5”) and ten-year (“10”) templates, as well as our young adult (“20–24”) template. “MNI” refers to the standard MNI152 priors, and “Image” refers to segmentation from the base image, without explicitly specifying priors. Note that performance is generally best for a posteriori specification, using age-appropriate priors within a five-year range. Selected significant post hoc comparisons are highlighted; the “MNI” template had the lowest Dice values for each comparison.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4389545&req=5

Figure 5: Comparing segmentation methods across age ranges. Dice similarity values are shown for both gray matter (GM) and white matter (WM) for comparisons to the manually segmented IBSR18 and IBSR20 datasets. Values are shown for the MNI-based and Image-based prior sets, for a priori and a posteriori specification, and for age-appropriate five-year (“5”) and ten-year (“10”) templates, as well as our young adult (“20–24”) template. “MNI” refers to the standard MNI152 priors, and “Image” refers to segmentation from the base image, without explicitly specifying priors. Note that performance is generally best for a posteriori specification, using age-appropriate priors within a five-year range. Selected significant post hoc comparisons are highlighted; the “MNI” template had the lowest Dice values for each comparison.
Mentions: The purpose of this analysis was to evaluate the overlap between the manually segmented brain volumes from the IBSR and the primary segmentation routines (listed in Figure 2). Figure 4 illustrates the general pattern of the segmentation outputs for a single participant. We used a one-way ANOVA to examine the relative fit of the five methods (Image, MNI-a priori, Image-AVG-a priori, Image-AVG-a posteriori, MNI-AVG-a posteriori) to the manually guided segmentations, separately for GM and WM, and for each IBSR dataset. The segment type main effect was significant for all four comparisons; GM, IBSR-18, F(4,41) = 42.86, p < 0.001; WM, IBSR-18, F(4,45) = 16.07, p < 0.001; GM, IBSR-20, F(4,34) = 139.57, p < 0.001; WM, IBSR-20, F(4,34) = 81.61, p < 0.0001. Figure 5 show the means separately for these five segmentation procedures; and the segmentations with average template priors are shown separately for the young adult, five-year and 10-year age-appropriate average templates. We did post hoc tests to compare averages from individual segment types, and there were many significant differences. For GM, segmentation with age-appropriate five-year template was the best fit and the participant’s individual MNI segmentation was the worst fit. A particularly relevant comparison is the Image and the Image-AVG-a posteriori comparison, which showed a significantly larger dice value for the age-appropriate segmentation. The same general pattern occurred for WM, with the exception that for WM, segmentation with age-appropriate Image-AVG-a posteriori method was not significantly different from the Image (no priors) segmentation (see Figure 5, bottom figures).

Bottom Line: The participants included healthy adults from 20 through 89 years of age.It was found that age-appropriate templates provided less biased tissue classification estimates than age-inappropriate reference data and reference data based on young adult templates.This database is available for use by other investigators and clinicians for their MRI studies, as well as other types of neuroimaging and electrophysiological research.

View Article: PubMed Central - PubMed

Affiliation: Department of Communication Sciences and Disorders, University of South Carolina Columbia, SC, USA.

ABSTRACT
This study created and tested a database of adult, age-specific MRI brain and head templates. The participants included healthy adults from 20 through 89 years of age. The templates were done in five-year, 10-year, and multi-year intervals from 20 through 89 years, and consist of average T1W for the head and brain, and segmenting priors for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). It was found that age-appropriate templates provided less biased tissue classification estimates than age-inappropriate reference data and reference data based on young adult templates. This database is available for use by other investigators and clinicians for their MRI studies, as well as other types of neuroimaging and electrophysiological research.

No MeSH data available.