Quality Assessment in a DTI Multicenter Study

Amritha Nayak¹, Lindsay Walker¹, Carlo Pierpaoli¹, The Brain Development Cooperative Group²

Multicenter DTI studies are becoming increasingly popular for their ability to improve the statistical power of a study by recruiting a large number of subjects. Data from multicenter studies can be heterogeneous in nature when no strict quality control requirements are enforced. We have designed quality assessment criteria to enable the identification of protocol errors and artifacts in multicenter DTI data, and described strategies to remediate the data to make it more compatible between sites.