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Updated: Jul 12, 2026

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
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Real-Time Targeted Slice Reacquisition for Motion-Corrupted Fetal Diffusion MRI.

Jordina Aviles Verdera1,2,3,4,5, Sara Neves Silva1,5, Susanne Schulz-Heise4

  • 1Imaging Physics and Engineering Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Magnetic Resonance in Medicine
|July 11, 2026
PubMed
Summary

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This summary is machine-generated.

This study introduces a novel real-time framework for fetal diffusion MRI, improving image quality through targeted slice reacquisition. This advancement paves the way for routine quantitative fetal diffusion MRI in clinical practice.

Area of Science:

  • Medical Imaging
  • Biophysics
  • Computational Biology

Background:

  • Fetal diffusion MRI is crucial for assessing fetal development and detecting abnormalities.
  • Current fetal diffusion MRI techniques face challenges with motion artifacts and limited resolution.
  • Developing robust methods for real-time image acquisition is essential for clinical translation.

Purpose of the Study:

  • To develop and validate a real-time framework for targeted slice-level reacquisition in fetal diffusion MRI.
  • To enhance image quality and reliability in fetal diffusion MRI through automated artifact correction.
  • To establish a foundation for routine quantitative fetal diffusion MRI in research and clinical settings.

Main Methods:

  • A modified diffusion-weighted, spin-echo, echo-planar imaging (DW-SE-EPI) sequence enabling independent diffusion preparation per slice.
Keywords:
artifact detectionbrain segmentationfetal diffusion MRIreal‐time reacquisition

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  • Implementation of a pathology-robust nnU-Net segmentation network (V2) trained on pathological fetal cases with physics-inspired augmentation.
  • Integration of intensity-based artifact detection for automated reacquisition prioritization, validated retrospectively and prospectively.

    • Main Results:

    • Segmentation network V2 significantly outperformed V1 across all cohorts (p < 0.001), particularly at higher b-values (b > 0 s/mm²).
    • Median Dice Similarity Coefficient (DSC) gain of +0.87 at 1.5T demonstrated substantial improvement in segmentation accuracy.
    • Automated blackout detection achieved an F1 score of 0.81 ± 0.29, confirming the system's effectiveness in real-time artifact management.

    Conclusions:

    • Real-time slice-level fetal diffusion MRI reacquisition has been successfully demonstrated for the first time.
    • The developed framework shows significant potential for improving the quality and consistency of fetal diffusion MRI.
    • This work represents a critical step towards the routine clinical application of quantitative fetal diffusion MRI.