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Related Concept Videos

Brain Imaging01:14

Brain Imaging

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 Stimulation (TMS).
Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
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Imaging Studies II: Positron Emission Tomography and Scintigraphy

Positron Emission Tomography (PET) is a medical imaging technique that provides crucial insights into the body's physiological functions at a molecular level. It is an indispensable resource for diagnosing, staging, and monitoring various illnesses, notably cancer, neurological disorders, and cardiovascular conditions.
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Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

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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Abbiategrasso Brain Bank Protocol for Collecting, Processing and Characterizing Aging Brains
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Abbiategrasso Brain Bank Protocol for Collecting, Processing and Characterizing Aging Brains

Published on: June 3, 2020

Brain imaging: your brain scan doesn't lie about your age.

Silvia A Bunge1, Kirstie J Whitaker

  • 1Department of Psychology, University of California, Berkeley, CA 94720, USA. sbunge@berkeley.edu

Current Biology : CB
|September 29, 2012
PubMed
Summary
This summary is machine-generated.

Multi-modal magnetic resonance imaging (MRI) analysis can predict age in children and young adults. While most brain-derived age estimates closely match chronological age, some individuals show discrepancies.

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Area of Science:

  • Neuroimaging
  • Developmental Neuroscience
  • Biomedical Data Analysis

Background:

  • Magnetic resonance imaging (MRI) provides detailed insights into brain structure and function.
  • Accurate age estimation is crucial for understanding neurodevelopmental trajectories.
  • Multi-modal MRI data offers a rich source of information for predictive modeling.

Purpose of the Study:

  • To investigate the efficacy of multi-modal MRI data in predicting chronological age for children and young adults.
  • To assess the concordance between brain-derived age estimates and actual age.

Main Methods:

  • Acquisition and analysis of multi-modal MRI data (e.g., structural, functional, diffusion MRI).
  • Development and application of machine learning algorithms for age prediction.
  • Comparison of predicted age with chronological age across a cohort of children and young adults.

Main Results:

  • Multi-modal MRI analysis successfully predicted chronological age in the studied pediatric and young adult population.
  • A majority of individuals exhibited brain-derived age estimates closely aligned with their chronological age.
  • Variability in prediction accuracy was observed, indicating potential individual differences in brain aging or development.

Conclusions:

  • Multi-modal MRI is a promising tool for non-invasively estimating age in pediatric and young adult populations.
  • The findings support the use of neuroimaging biomarkers for assessing developmental stages.
  • Further research is warranted to explore the reasons for age estimation discrepancies in certain individuals.