The pediatric template of brain perfusion

Abstract

Magnetic resonance imaging (MRI) captures the dynamics of brain development with multiple modalities that quantify both structure and function. These measurements may yield valuable insights into the neural patterns that mark healthy maturation or that identify early risk for psychiatric disorder. The Pediatric Template of Brain Perfusion (PTBP) is a free and public neuroimaging resource that will help accelerate the understanding of childhood brain development as seen through the lens of multiple modality neuroimaging and in relation to cognitive and environmental factors. The PTBP uses cross-sectional and longitudinal MRI to quantify cortex, white matter, resting state functional connectivity and brain perfusion, as measured by Arterial Spin Labeling (ASL), in 120 children 7-18 years of age. We describe the PTBP and show, as a demonstration of validity, that global summary measurements capture the trajectories that demarcate critical turning points in brain maturation. This novel resource will allow a more detailed understanding of the network-level, structural and functional landmarks that are obtained during normal adolescent brain development.

Figure 1. Overview of the PTBP.

The multiple modality processing pipeline inputs and outputs. The population average T1 template is shown at upper right. The AAL labels are mapped to each modality and, along with 6-tissue segmentation, used to help compute summary measurements for all modalities and for multivariate prediction.

Figure 2. Overview of the PTBP demographics.

The age distribution (12.4 +/− 3.12 years) for male (n=59) and female (n=61) subjects in the cohort is shown at top left. The histogram of paternal education (16 +/− 3.22 years) is at top right. The histogram of family income, in USD, across the full cohort is a bottom left. At bottom right is the histogram of full-scale IQ, grouped by gender, as measured by WASI (109 +/− 14.6).

Figure 3. Age modeling from structural imaging variables.

Relationship of global structural measurements, age and gender for each modality while controlling for brain volume (BV, above). n=91.

Figure 4. Age modeling from functional imaging variables.

Relationship of global functional measurements, age and gender for each modality, controlling for brain volume within the regression, except where noted by a dagger †. N=91.

Figure 5. Age prediction from all imaging variables.

We train on half of the data and predict age in the other half of the data using a general linear model age ≈ BStem+CBF+FA+Thickness+DGM. See Table 1 for evidence that each of these predictors is important to the model. We obtained this predictor set by performing a supervised backward variable elimination in the regression on the training data. n=91 for the full data-set, split into testing and training sets of 45/46 100 times, to validate predictive relationship of multiple modalities with age.