Quantifying cerebral changes in adolescence with MRI and deformation based morphometry

Abstract

Purpose: To identify and quantify structural changes in the maturing brain between childhood and adolescence. Materials and Methods:Two three-dimensional T1-weighted MR volumes of the brain were acquired from eight subjects, 6 to 7 years apart. The subjects were 9 to 12 years old on the first scan and 15 to 19 years old on the second scan. The MR scans were converted to one millimeter isotropic volumes, globally aligned with a rigid transform, inhomogeneity corrected, and nonrigid deformation fields between the aligned volumes were calculated. Masks for brain regions were automatically warped with the deformation fields and volumes of brain regions calculated. Color overlays based on the nonrigid deformation fields were generated to identify local volume changes.Results: Gray matter decreased as much as 60% and white matter increased as much as 250%. The biggest gray matter changes were in the head of the caudates, areas of the putamens, and areas of the thalamus. Some of the biggest white matter changes were in the forceps minor, forceps major, and internal capsule. Conclusion:Deformation based morphometry with serial scans provides a method to study regional structural changes with brain growth and maturation.

Investigating the ‘latent’ deficit hypothesis: Age at time of head injury, implicit and executive functions and behavioral insight

“…Gogtay et al, (2004) found that changes in gray matter volume follow a non-linear pattern across different brain regions, with loss of gray matter density (either through synaptic pruning or intracortical myelination - Paus, 2005) to dorsolateral prefrontal cortex and posterior superior temporal gyrus only evident after age 16-17 years in healthy adolescents. In a longitudinal study of 8 healthy subjects aged 11 to 17.5 the greatest mean increase in white matter volume was found in frontal lobes (ranging from 8.4 -26.8%) across the two time points, indicating rapid maturation of these regions during late adolescence compared to other brain regions (Riddle et al, 2008). Subcortical tracts (extending into frontal regions) and corticospinal tract continue to undergo change up to age 25 (Lebel, Walker, Phillips & Beaulieu, 2008), and there is some indication that maturational change may continue to age 30 in superior temporal cortex (Sowell et al, 2003).…”

Longitudinal Progression of Cognitive Decline Correlates with Changes in the Spatial Pattern of Brain 18F-FDG PET

“…For each subject, the T1-weighted MR image volume was used to define the binary ROI with the methods described by Riddle et al (25). Briefly, the T1-weighted MR image volume of each subject was aligned with a reference brain with a rigid transform (3 translation vectors and 3 rotation angles), then the deformation field between the reference brain and the globally aligned T1-weighted MR image volume was calculated with a nonrigid demons registration algorithm (26,27).…”

Modeling clustered activity increase in amyloid-beta positron emission tomographic images with statistical descriptors

“…For each subject we sampled axial PiB image slices from several different brain regions, including the occipital lobe and the bilateral temporal, parietal, and frontal lobes. The T1-weighted MRI volume was used to define these regions using the methods described by Riddle et al 21 Briefly, these anatomical regions were obtained by aligning the subject’s T1-weighted MRI volume (acquired at a time point close to the PiB PET baseline scan) with the T1-weighted MRI volume from a reference brain where the regions were segmented manually. The deformation field between the reference brain and the subject’s T1-weighted MRI volume was calculated with a nonrigid demons registration algorithm.…”