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Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study

Author(s)
Siless, Viviana; Hubbard, Nicholas A; Jones, Robert; Wang, Jonathan; Lo, Nicole; Bauer, Clemens CC; Goncalves, Mathias; Frosch, Isabelle; Norton, Daniel; Vergara, Genesis; Conroy, Kristina; De Souza, Flavia Vaz; Rosso, Isabelle M; Wickham, Aleena Hay; Cosby, Elizabeth Ann; Pinaire, Megan; Hirshfeld-Becker, Dina; Pizzagalli, Diego A; Henin, Aude; Hofmann, Stefan G; Auerbach, Randy P; Ghosh, Satrajit; Gabrieli, John; Whitfield-Gabrieli, Susan; Yendiki, Anastasia; ... Show more Show less
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Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/
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Abstract
© 2020 The Authors The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14–17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and differences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA).
Date issued
2020
URI
https://hdl.handle.net/1721.1/134542
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; Harvard University--MIT Division of Health Sciences and Technology; Martinos Imaging Center (McGovern Institute for Brain Research at MIT); McGovern Institute for Brain Research at MIT
Journal
NeuroImage: Clinical
Publisher
Elsevier BV

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