An analysis-ready and quality controlled resource for pediatric brain white-matter research

Abstract

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets.

Fiber-specific structural properties relate to reading skills in children and adolescents

“…Phenotypic data were accessed in accordance with a data use agreement provided by the Child Mind Institute. Preprocessed DWI data were provided as part of the HBN Preprocessed Open Diffusion Derivatives (HBN-POD2) dataset ( Richie-Halford et al, 2022 ). The HBN project was approved by the Chesapeake Institutional Review Board (now called Advarra, Inc; https://www.advarra.com/ , protocol number: Pro00012309).…”

Fiber-Specific Structural Properties Relate to Reading Skills in Children and Adolescents

“…We downloaded preprocessed DWI ( Richie-Halford et al, 2022 ) and phenotypic data from 2136 participants across the first eight data releases of the Healthy Brain Network (HBN) project ( Alexander et al, 2017 ). HBN-POD2 distributes a quality metric accompanying each image that predicts the probability that the image would pass manual expert quality review (“”, or “” if the former score was not available) ( Richie-Halford et al, 2022 ). It ranges from 0 (no chance of passing expert review) to 1 (image will definitely pass expert review).…”

“…Preprocessed neuroimaging data can be downloaded following directions from the HBN-POD2 manuscript ( Richie-Halford et al, 2022 ), and phenotypic data can be collected following directions on the Healthy Brain Network data portal (http://fcon_1000.projects.nitrc.org/indi/cmi_healthy_brain_network/index.html) after signing a data use agreement. All instructions and code for further processing data and running the statistical models can be found at https://github.com/smeisler/Meisler_Reading_FBA.…”

“…Phenotypic data were accessed in accordance with a data use agreement provided by the Child Mind Institute. Preprocessed DWI data were provided as part of the HBN Preprocessed Open Diffusion Derivatives (HBN-POD2) data set(Richie-Halford et al, 2022).The Healthy Brain Network project was approved by the Chesapeake Institutional Review Board (now called Advarra, Inc.; https://www.advarra.com/). Informed consent was obtained from all participants ages 18 or older.…”

“…(HBN) project(Alexander et al, 2017). HBN-POD2 distributes a quality metric accompanying each image that predicts the probability that the image would pass manual expert quality review ("xgb_qc_score", or "dl_qc_score" if the former score was not available)(Richie-Halford et al, 2022).…”