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Related Concept Videos

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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Related Experiment Video

Updated: Jun 13, 2026

Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance Imaging-Arterial Spin Labeling
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Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance Imaging-Arterial Spin Labeling

Published on: May 31, 2024

Dynamic susceptibility contrast MRI with localized arterial input functions.

John J Lee1, G Larry Bretthorst, Colin P Derdeyn

  • 1Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Missouri 63110, USA.

Magnetic Resonance in Medicine
|May 1, 2010
PubMed
Summary

Dynamic susceptibility contrast MRI offers accessible, less invasive cerebral perfusion measurement. A novel method using localized arterial input function improves accuracy and quantitation, correlating well with positron emission tomography.

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Simultaneous PET/MRI Imaging During Mouse Cerebral Hypoxia-ischemia
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Simultaneous PET/MRI Imaging During Mouse Cerebral Hypoxia-ischemia
10:35

Simultaneous PET/MRI Imaging During Mouse Cerebral Hypoxia-ischemia

Published on: September 20, 2015

Area of Science:

  • Neuroimaging
  • Medical Physics
  • Cardiovascular Imaging

Background:

  • Dynamic susceptibility contrast (DSC) MRI is a more accessible alternative to positron emission tomography (PET) for measuring cerebral perfusion.
  • Current DSC MRI analysis methods struggle with accurately modeling the arterial input function (AIF), leading to potential inaccuracies in perfusion quantification.
  • Limitations include sensitivity to delays and dispersion in a single, global AIF.

Purpose of the Study:

  • To develop and validate a novel method for DSC MRI analysis that estimates a unique, localized arterial input function (AIF) for each voxel.
  • To improve the accuracy and physiological relevance of DSC MRI-derived perfusion measurements.
  • To enable accurate quantitation of cerebral perfusion on a physiological scale using DSC MRI.

Main Methods:

  • A new model of tissue microcirculation based on tracer kinetic modeling was developed.
  • Localized arterial input functions (AIFs) were estimated for each voxel.
  • Bayesian probability theory and Markov-chain Monte Carlo methods were employed for parameter estimation, avoiding numerical deconvolution issues.
  • The method was applied to DSC MRI data from 14 patients with chronic occlusive cerebrovascular disease.

Main Results:

  • Strong correlations were observed between cerebral perfusion measurements obtained using the novel localized AIF DSC MRI method and quantitative H(2)[(15)O] PET.
  • Regression analysis allowed conversion of DSC MRI perfusion values to a physiological scale.
  • The localized AIF method provided accurate quantitation of perfusion, even in patients with significant hemodynamic impairment.

Conclusions:

  • The developed localized arterial input function (AIF) method significantly enhances the accuracy and quantitation of dynamic susceptibility contrast MRI for cerebral perfusion assessment.
  • This approach overcomes limitations of global AIF modeling and allows for physiologically relevant measurements.
  • The localized AIF method provides a robust and scalable approach for quantifying cerebral perfusion, comparable to gold-standard PET imaging.