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Journal Article

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

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Valk,  Sofie L.       
Otto Hahn Group Cognitive Neurogenetics, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Richie-Halford, A., Cieslak, M., Ai, L., Caffarra, S., Covitz, S., Franco, A. R., et al. (2022). An analysis-ready and quality controlled resource for pediatric brain white-matter research. Scientific Data, 9(1): 616. doi:10.1038/s41597-022-01695-7.


Cite as: https://hdl.handle.net/21.11116/0000-000B-63EB-D
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.