Empirical evaluation of human fetal fMRI preprocessing steps

Author:

Ji Lanxin1ORCID,Hendrix Cassandra L.1,Thomason Moriah E.123

Affiliation:

1. Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA

2. Department of Population Health, New York University School of Medicine, New York, NY, USA

3. Neuroscience Institute, New York University School of Medicine, New York, NY, USA

Abstract

Abstract Increased study and methodological innovation have led to growth in the field of fetal brain fMRI. An important gap yet to be addressed is optimization of fetal fMRI preprocessing. Rapid developmental changes, imaged within the maternal compartment using an abdominal coil, introduce novel constraints that challenge established methods used in adult fMRI. This study evaluates the impact of (1) normalization to a group mean-age template versus normalization to an age-matched template; (2) independent components analysis (ICA) denoising at two criterion thresholds; and (3) smoothing using three kernel sizes. Data were collected from 121 fetuses (25–39 weeks, 43.8% female). Results indicate that the mean age template is superior in older fetuses, but less optimal in younger fetuses. ICA denoising at a more stringent threshold is superior to less stringent denoising. A larger smoothing kernel can enhance cross-hemisphere functional connectivity. Overall, this study provides improved understanding of the impact of specific steps on fetal image quality. Findings can be used to inform a common set of best practices for fetal fMRI preprocessing.

Funder

Foundation for the National Institutes of Health

Publisher

MIT Press - Journals

Subject

Applied Mathematics,Artificial Intelligence,Computer Science Applications,General Neuroscience

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