The impact of quality assurance assessment on diffusion tensor imaging outcomes in a large-scale population-based cohort

摘要

Background: Diffusion tensor imaging (DTI) is applied in investigation of brain biomarkers for neurodevelopmental and neurodegenerative disorders. However, the quality of DTI measurements, like other neuroimaging techniques, is susceptible to several confounding factors (e.g., motion, eddy currents), which have only recently come under scrutiny. These confounds are especially relevant in adolescent samples where data quality may be compromised in ways that confound interpretation of maturation parameters. The current study aims to leverage DTI data from the Philadelphia Neurodevelopmental Cohort (PNC), a sample of 1601 youths with ages of 8-21 who underwent neuroimaging, to: 1) establish quality assurance (QA) metrics for the automatic identification of poor DTI image quality; 2) examine the performance of these QA measures in an external validation sample; 3) document the influence of data quality on developmental patterns of typical DTI metrics.