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Related Concept Videos

Brain Imaging01:14

Brain Imaging

644
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
644

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Brain-age in ultra-low-field MRI: how well does it work?

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Area of Science:

  • Neuroimaging
  • Biomarkers
  • Magnetic Resonance Imaging (MRI)

Background:

  • Brain-age estimation, derived from neuroimaging, serves as a biomarker for brain health and disease risk.
  • High-field (HF) MRI is typically used but is costly and inaccessible.
  • Ultra-low-field (ULF) MRI offers a cheaper, more accessible alternative, but its lower resolution poses challenges for biomarker reliability.

Purpose of the Study:

  • To systematically evaluate different brain-age estimation pipelines using ULF MRI.
  • To compare the performance of ULF MRI brain-age estimation against HF MRI.
  • To assess the validity, correspondence, and reliability of ULF brain-age estimates.

Main Methods:

  • 23 adults were scanned using one HF MRI and two ULF MRI systems.
  • 14 distinct acquisition types (varying T1/T2-weighting, resolution, preprocessing) were analyzed.
  • Five brain-age software packages were employed to process 573 scans, evaluating validity, HF correspondence, and test-retest reliability.

Main Results:

  • Several ULF MRI pipelines achieved performance comparable to HF MRI.
  • The best-performing pipelines demonstrated moderate-to-strong validity (r=0.76-0.92) and correspondence to HF (r=0.84-0.93).
  • Excellent test-retest reliability (r=0.97-0.99) was observed across multiple ULF pipelines, with some anisotropic acquisitions performing comparably to enhanced images.

Conclusions:

  • Accurate and reliable brain-age estimates are achievable with ULF MRI across various pipelines, often without requiring image enhancement.
  • Pipeline performance is dependent on the specific combination of model, scan type, and preprocessing.
  • ULF brain-age estimation presents a practical, scalable tool for accessible neuroimaging biomarkers in clinical settings and research.