Limits...
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.


Related in: MedlinePlus

The pipeline for age-specific template creation. First, participant brains were rigidly registered to the MNI brain, maintaining the volume and size of the original. Rigidly registered brains (V0) were then averaged to create a rough template (A0). This template was used as the first registration target, to which each participant brain was nonlinearly registered and transformed (Vn). With each iteration, the participant brains were nonlinearly registered to the new average (An−1), transformed and then re-averaged to create a new, relatively more precise average (An) for the next iteration.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4389545&req=5

Figure 1: The pipeline for age-specific template creation. First, participant brains were rigidly registered to the MNI brain, maintaining the volume and size of the original. Rigidly registered brains (V0) were then averaged to create a rough template (A0). This template was used as the first registration target, to which each participant brain was nonlinearly registered and transformed (Vn). With each iteration, the participant brains were nonlinearly registered to the new average (An−1), transformed and then re-averaged to create a new, relatively more precise average (An) for the next iteration.

Mentions: We constructed the age-specific templates with the iterative routines found in Sanchez et al. (2012a,b); also see Guimond et al., 2000; Yoon et al., 2009; Fonov et al., 2011, for examples of similar iterative routines). The whole-head MRI volumes and brain-extracted MRI volumes were performed separately. Figure 1 is a schematic representation of the steps used in the construction of the template for a specific age group for both whole-head and brain-extracted templates. The first step of the iterative procedure was to construct a tentative average (Figure 1, “A0”). A rigid rotation (FLIRT 6 parameter linear registration and transformation; Jenkinson and Smith, 2001) to the MNI-152 adult template ensured all images were oriented in the same way prior to averaging (ICBM-152 defined in Mazziotta et al., 2001a; Joshi et al., 2004). The second step of the iterative procedure consisted of a non-linear registration (ANTS, “Advanced Normalization Tools”; Avants et al., 2008, 2011a) to the current reference average (An−1), a transformation of each participant MRI into the template space (Vn), and then a averaging of the transformed MRIs (An). This average was then used as the reference model in the next iteration (An−1 on next step). The first non-linear registration was done with low resolution (50 × 0 × 0 iterations), the second with medium resolution (50 × 50 × 0 iterations), and the final steps with fine resolution (50 × 50 × 50). The root mean square (RMS) difference between successive average reference models was calculated, and the iterative procedure was done until leveling of the successive RMS values was obtained. The final reference model is the “age-specific” template. More details of this procedure may be found in Sanchez et al. (2012a).


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)

The pipeline for age-specific template creation. First, participant brains were rigidly registered to the MNI brain, maintaining the volume and size of the original. Rigidly registered brains (V0) were then averaged to create a rough template (A0). This template was used as the first registration target, to which each participant brain was nonlinearly registered and transformed (Vn). With each iteration, the participant brains were nonlinearly registered to the new average (An−1), transformed and then re-averaged to create a new, relatively more precise average (An) for the next iteration.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: The pipeline for age-specific template creation. First, participant brains were rigidly registered to the MNI brain, maintaining the volume and size of the original. Rigidly registered brains (V0) were then averaged to create a rough template (A0). This template was used as the first registration target, to which each participant brain was nonlinearly registered and transformed (Vn). With each iteration, the participant brains were nonlinearly registered to the new average (An−1), transformed and then re-averaged to create a new, relatively more precise average (An) for the next iteration.
Mentions: We constructed the age-specific templates with the iterative routines found in Sanchez et al. (2012a,b); also see Guimond et al., 2000; Yoon et al., 2009; Fonov et al., 2011, for examples of similar iterative routines). The whole-head MRI volumes and brain-extracted MRI volumes were performed separately. Figure 1 is a schematic representation of the steps used in the construction of the template for a specific age group for both whole-head and brain-extracted templates. The first step of the iterative procedure was to construct a tentative average (Figure 1, “A0”). A rigid rotation (FLIRT 6 parameter linear registration and transformation; Jenkinson and Smith, 2001) to the MNI-152 adult template ensured all images were oriented in the same way prior to averaging (ICBM-152 defined in Mazziotta et al., 2001a; Joshi et al., 2004). The second step of the iterative procedure consisted of a non-linear registration (ANTS, “Advanced Normalization Tools”; Avants et al., 2008, 2011a) to the current reference average (An−1), a transformation of each participant MRI into the template space (Vn), and then a averaging of the transformed MRIs (An). This average was then used as the reference model in the next iteration (An−1 on next step). The first non-linear registration was done with low resolution (50 × 0 × 0 iterations), the second with medium resolution (50 × 50 × 0 iterations), and the final steps with fine resolution (50 × 50 × 50). The root mean square (RMS) difference between successive average reference models was calculated, and the iterative procedure was done until leveling of the successive RMS values was obtained. The final reference model is the “age-specific” template. More details of this procedure may be found in Sanchez et al. (2012a).

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.


Related in: MedlinePlus