Structural MRI🔗

HBCD protocols for structural MRI were informed by recent large-scale developmental neuroimaging studies including ABCD, HCP Lifespan, and BCP (Howell et al., 2019). These studies laid critical foundation for the development of well-validated, high-resolution protocols harmonized across all three major scanner vendors (Casey et al., 2018). In addition, the findings emphasized the importance of T2w acquisition in infants due to suboptimal grey/white T1w contrast resulting from incomplete myelination (Howell et al., 2019, Myers et al., 2023). Acquisition parameters are as follows:

  • 0.8 mm isotropic resolution
  • Compressed SENSE reconstruction enabling high acceleration and shorter acquisition times (<9 min total for T1w & T2w)
  • Embedded navigators for motion tracking (White et al., 2010, Tisdall et al., 2016, Andersen et al., 2019)
  • Harmonization approach similar to the ABCD Study:
    • T1w: contrast-relevant parameters matched as closely as possible across vendors
    • T2w: vendor-specific parameters selected to achieve comparable contrast and SNR, accounting for differences in 3D T2w pulse sequence implementation

Adamson, C. L., Alexander, B., Ball, G., Beare, R., Cheong, J. L. Y., Spittle, A. J., Doyle, L. W., Anderson, P. J., Seal, M. L., & Thompson, D. K. (2020). Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S). Scientific Reports, 10(1), 4359. https://doi.org/10.1038/s41598-020-61326-2

Andersen, M., Björkman-Burtscher, I. M., Marsman, A., Petersen, E. T., & Boer, V. O. (2019). Improvement in diagnostic quality of structural and angiographic MRI of the brain using motion correction with interleaved, volumetric navigators. PLoS One, 14(5), e0217145. https://doi.org/10.1371/journal.pone.0217145

Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M., Soules, M. E., Teslovich, T., Dellarco, D. V., Garavan, H., Orr, C. A., Wager, T. D., Banich, M. T., Speer, N. K., Sutherland, M. T., Riedel, M. C., Dick, A. S., Bjork, J. M., Thomas, K. M., … ABCD Imaging Acquisition Workgroup. (2018). The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites. Developmental Cognitive Neuroscience, 32, 43–54. https://doi.org/10.1016/j.dcn.2018.03.001

Hendrickson, T. J., Reiners, P., Moore, L. A., Lundquist, J. T., Fayzullobekova, B., Perrone, A. J., Lee, E. G., Moser, J., Day, T. K. M., Alexopoulos, D., Styner, M., Kardan, O., Chamberlain, T. A., Mummaneni, A., Caldas, H. A., Bower, B., Stoyell, S., Martin, T., Sung, S., … Feczko, E. (2024). BIBSNet: A deep learning Baby image brain segmentation network for MRI scans. In bioRxivorg. https://doi.org/10.1101/2023.03.22.533696

Howell, B. R., Styner, M. A., Gao, W., Yap, P.-T., Wang, L., Baluyot, K., Yacoub, E., Chen, G., Potts, T., Salzwedel, A., Li, G., Gilmore, J. H., Piven, J., Smith, J. K., Shen, D., Ugurbil, K., Zhu, H., Lin, W., & Elison, J. T. (2019). The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development. NeuroImage, 185, 891–905. https://doi.org/10.1016/j.neuroimage.2018.03.049

Myers, M. J., Labonte, A. K., Gordon, E. M., Laumann, T. O., Tu, J. C., Wheelock, M. D., Nielsen, A. N., Schwarzlose, R., Camacho, M. C., Warner, B. B., Raghuraman, N., Luby, J. L., Barch, D. M., Fair, D. A., Petersen, S. E., Rogers, C. E., Smyser, C. D., & Sylvester, C. M. (2023). Functional parcellation of the neonatal brain. In bioRxivorg. https://doi.org/10.1101/2023.11.10.566629

Tisdall, M. D., Reuter, M., Qureshi, A., Buckner, R. L., Fischl, B., & van der Kouwe, A. J. W. (2016). Prospective motion correction with volumetric navigators (vNavs) reduces the bias and variance in brain morphometry induced by subject motion. Neuroimage, 127, 11-22. https://doi.org/10.1016/j.neuroimage.2015.11.054

White, N., Roddey, C., Shankaranarayanan, A., Han, E., Rettmann, D., Santos, J., Kuperman, J., & Dale, A. (2010). PROMO: Real-time prospective motion correction in MRI using image-based tracking. Magnetic Resonance in Medicine, 63(1), 91–105. https://doi.org/10.1002/mrm.22176

Zöllei, L., Iglesias, J. E., Ou, Y., Grant, P. E., & Fischl, B. (2020). Infant FreeSurfer: An automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0-2 years. NeuroImage, 218(116946), 116946. https://doi.org/10.1016/j.neuroimage.2020.116946