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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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A Low-Field MRI Dataset For Spatiotemporal Analysis of Developing Brain.

Zhexian Sun1,2, Jian Huang1,2, Xiaohui Ma1

  • 1National Clinical Research Center for Child Health, National Children's Regional Medical Center, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, 310052, China.

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|January 20, 2025
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Low-field magnetic resonance (MR) imaging offers a safe and cost-effective method for studying infant brain development. This study presents a valuable dataset of infant brain MR images, enabling better tracking of developmental changes.

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Area of Science:

  • Neuroimaging
  • Developmental Neuroscience
  • Medical Imaging

Background:

  • High-field MR imaging for infant brain studies faces accessibility and reproducibility challenges.
  • Low-field MR imaging presents a safer, more portable, and cost-effective alternative for examining the developing brain.
  • Understanding infant brain development is crucial for linking brain structure to behavioral changes.

Purpose of the Study:

  • To demonstrate the feasibility of using low-field MR imaging for examining structural brain changes in infants.
  • To present a novel dataset of low-field structural MR images of the infant brain.
  • To address the scarcity of large, extended-span infant brain datasets for developmental trajectory analysis.

Main Methods:

  • Acquisition of 100 T2-weighted structural MR images from infants using low-field MR.
  • In-plane resolution of ~0.85 mm and slice thickness of ~6 mm.
  • Atlas-based whole brain segmentation and volumetric quantification for developmental analysis.

Main Results:

  • The presented low-field infant MR dataset enables the examination of brain structural changes in early postnatal life.
  • Atlas-based analysis demonstrated the utility of the dataset for quantifying brain development features within the first 10 weeks.
  • The dataset supports the development of routine low-field MR imaging pipelines for infant studies.

Conclusions:

  • Low-field MR imaging is a feasible and advantageous tool for infant brain research.
  • The created dataset facilitates the tracking of infant brain development trajectories.
  • This work contributes to advancing accessible and reproducible neuroimaging methods for early life brain studies.