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Related Concept Videos

Brain Imaging01:14

Brain Imaging

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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...
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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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Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
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Related Experiment Video

Updated: Jun 4, 2025

3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
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Decoding Brain Development and Aging: Pioneering Insights From MRI Techniques.

Akifumi Hagiwara1, Satoru Kamio, Junko Kikuta

  • 1From the Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan (A.H., S.K., J.K., M.N., W.U., S.F., T.A., A.W., K.K., S.A.); Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan (A.H., M.N., S.F.); Polytechnique Montréal, Montreal, Quebec, Canada (S.N.); Montreal Heart Institute, University of Montreal, Montreal, Quebec, Canada (S.N.); and Center for Advanced Interdisciplinary Research, Ss. Cyril and Methodius University in Skopje, Skopje, North Macedonia (S.N.).

Investigative Radiology
|December 26, 2024
PubMed
Summary
This summary is machine-generated.

Aging alters brain structure and function, detectable by magnetic resonance imaging (MRI). MRI techniques reveal changes in brain volume, white matter, and tissue properties, aiding diagnosis of aging and neurodegenerative diseases.

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Area of Science:

  • Neuroimaging
  • Gerontology
  • Radiology

Background:

  • The aging process is associated with significant structural and microstructural changes in the brain.
  • Magnetic resonance imaging (MRI) is a powerful tool for visualizing these age-related alterations.
  • Understanding these changes is crucial for differentiating normal aging from neurodegenerative diseases.

Purpose of the Study:

  • To provide a comprehensive overview of age-related brain changes detectable by various MRI techniques.
  • To highlight how MRI can distinguish normal aging from pathological conditions.
  • To discuss the role of advanced MRI methods and AI in assessing brain age and identifying biomarkers.

Main Methods:

  • Review of various MRI techniques including standard MRI, fluid-attenuated inversion recovery (FLAIR), tissue relaxometry, susceptibility-sensitive MRI, and diffusion MRI.
  • Analysis of neurofluid imaging techniques.
  • Inclusion of recent advances in machine learning and artificial intelligence for brain age estimation.

Main Results:

  • Age-related changes observed include decreased gray matter volume, increased ventricular volume, white matter hyperintensities, and alterations in myelin and iron content.
  • MRI reveals changes in tissue relaxivity and microstructural properties like neurite density.
  • Neurofluid imaging shows age-dependent shifts in cerebrospinal and interstitial fluid dynamics.

Conclusions:

  • Various MRI techniques offer unique insights into the complex structural and compositional changes in the aging brain.
  • These findings are vital for distinguishing normal aging from neurodegenerative processes and for developing targeted interventions.
  • AI-driven brain age estimation presents promising biomarkers for neurological and psychiatric disorders.