A protocol for the analysis of DTI data collected from young children

• Main Authors: Maksym Tokariev, Virve Vuontela, Jaana Perkola, Piia Lönnberg, Aulikki Lano, Sture Andersson, Marjo Metsäranta, Synnöve Carlson
• Format: Article
• Language: English
• Published: Elsevier 2020-01-01
• Series: MethodsX
• Subjects: Diffusion tensor imaging (DTI); Nonlinear registration; Tract-based spatial statistics (TBSS); Pediatric
• Online Access: http://www.sciencedirect.com/science/article/pii/S2215016120300972

Analysis of scalar maps obtained by diffusion tensor imaging (DTI) produce valuable information about the microstructure of the brain white matter. The DTI scanning of child populations, compared with adult groups, requires specifically designed data acquisition protocols that take into consideration the trade-off between the scanning time, diffusion strength, number of diffusion directions, and the applied analysis techniques. Furthermore, inadequate normalization of DTI images and non-robust tensor reconstruction have profound effects on data analyses and may produce biased statistical results. Here, we present an acquisition sequence that was specifically designed for pediatric populations, and describe the analysis steps of the DTI data collected from extremely preterm-born young school-aged children and their age- and gender-matched controls. The protocol utilizes multiple software packages to address the effects of artifacts and to produce robust tensor estimation. The computation of a population-specific template and the nonlinear registration of tensorial images with this template were implemented to improve alignment of brain images from the children.