PedsMRI study was an NIH funded multi-site longitudinal study using technologies such as anatomical MRI, DTI, MR spectroscopy to map pediatric brain development.
As part of this project, I analyzed the DTI data of 61 subjects ranging in age from 4 to 22 years old. For each subject two scans were collected with different protocols (low and high resolution). Our goal was to separate the contributions of biological variability and experimental noise to the overall measured variance, as well as to assess potential systematic effects related to the use of different protocols.
Contribution:
- Developed a methodology that enables analysis of different sources of variability that is observed in the repeated DTI scans such as biological variability, which is the inherent differences among individuals, and experimental noise, which is unique to the experimental conditions. Dividing the variance has important implications: if the observed variability is mainly due to the experimental noise, then one should aim at improving the experimental design and quality of data acquisition. On the other hand, if high variability is due to intrinsic differences in brain structure between individuals, then its association to inter-individual behavioral and cognitive differences should be investigated.
- Performed Monte Carlo simulations to validate the model and investigate its robustness in the range of experimental conditions typical of our data (SNR, differences between protocols in the test– retest replicates, relatively small number of subjects, etc.). For a large range of biological variability and experimental noise values, we tested the accuracy (potential bias effects) and uncertainty (standard error) of the estimated linear mixed effects model parameters for the diffusion metric of interest: MD and FA.
Findings: We found that biological variability for both FA and MD varies widely across brain regions; biological variability is highest for FA in the lateral part of the splenium and body of the corpus callosum along with the cingulum and the superior longitudinal fasciculus, and for MD in the optic radiations and the lateral part of the splenium. These regions with high inter-individual biological variability are the most likely candidates for assessing genetic and environmental effects in the developing brain. With respect to protocol-related effects, the lower resolution acquisition resulted in higher MD and lower FA values for the majority of regions compared with the higher resolution protocol. However, the majority of the regions did not show any age–protocol interaction, indicating similar trajectories were obtained irrespective of the protocol used.
Papers/abstracts: Sadeghi et al., NeuroImage 2015