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Related Experiment Video

Updated: Mar 22, 2026

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
06:56

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

Published on: January 7, 2021

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Robust preprocessing for stimulus-based functional MRI of the moving fetus.

Wonsang You1, Iordanis E Evangelou2, Zungho Zun1

  • 1Children's National Medical Center , Department of Diagnostic Imaging and Radiology, 111 Michigan Avenue N.W., Washington, DC 20852, United States.

Journal of Medical Imaging (Bellingham, Wash.)
|April 16, 2016
PubMed
Summary

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Fetal motion artifacts in functional MRI (fMRI) are reduced by a new processing pipeline. This method improves blood oxygen level dependent (BOLD) signal analysis in fetal brain and placenta studies.

Area of Science:

  • Neuroimaging
  • Developmental Biology
  • Medical Physics

Background:

  • Fetal motion during functional magnetic resonance imaging (fMRI) causes significant signal degradation and artifacts.
  • This motion complicates the analysis of blood oxygen level dependent (BOLD) signals in fetal brain and placenta.
  • Existing preprocessing methods are often insufficient for the unique challenges of in-utero fMRI.

Purpose of the Study:

  • To develop and validate a robust preprocessing pipeline for stimulus-based fMRI in the living fetus.
  • To specifically address and mitigate motion-induced artifacts from fetal and placental movement.
  • To improve the quality and reliability of BOLD signal analysis in fetal neuroimaging.

Main Methods:

  • A novel preprocessing pipeline optimized for stimulus-based fMRI with a block design.
Keywords:
fetal brainfunctional magnetic resonance imagingmaternal hyperoxiamotion correctionplacentapreprocessing

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Related Experiment Videos

Last Updated: Mar 22, 2026

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  • Motion correction applied separately to each phase and region of interest (ROI) to account for differential motion.
  • Automated detection and exclusion of misaligned volumes and noisy voxels.
  • Imputation of missing data using statistical estimation with local polynomial smoothing.

    • Main Results:

    • The proposed pipeline effectively reduced motion-induced artifacts in fetal fMRI data.
    • Improved signal quality was observed in both fetal brain and placental BOLD time series.
    • The method demonstrated robustness in handling complex motion patterns inherent in fetal studies.

    Conclusions:

    • The developed preprocessing pipeline offers a significant advancement for fetal fMRI research.
    • It enables more accurate BOLD signal acquisition and analysis in the developing fetus.
    • This approach holds promise for future studies investigating fetal brain function and development.