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Myocardial blood flow quantification with MRI by model-independent deconvolution
Michael Jerosch-Herold1, Cory Swingen, Ravi Teja Seethamraju
1Department of Radiology, University of Minnesota, Minneapolis 55455, USA. jeros001@umn.edu
Medical Physics
|May 30, 2002
Summary
Model-independent deconvolution accurately quantifies myocardial perfusion using magnetic resonance (MR) imaging. This method simplifies blood flow assessment, paving the way for broader clinical use of MR perfusion imaging.
Area of Science:
- Cardiovascular Imaging
- Medical Physics
- Physiology
Background:
- Magnetic resonance (MR) imaging assesses myocardial perfusion using contrast agents.
- Quantifying blood flow with MR imaging has been challenging due to complexity.
- Previous methods required significant user expertise and complex modeling.
Purpose of the Study:
- To demonstrate the feasibility of model-independent deconvolution for myocardial perfusion quantification.
- To simplify clinical application of MR-based blood flow measurements.
- To validate the accuracy and reliability of the model-independent approach.
Main Methods:
- Applied model-independent deconvolution to tissue residue curves from MR perfusion data.
- Utilized B-spline representation and Tikhonov regularization for impulse response.
- Validated accuracy using Monte Carlo simulations and compared with microsphere data.
Main Results:
- Achieved less than 1% bias in blood flow estimates across tested signal-to-noise ratios.
- Demonstrated relative dispersion of blood flow estimates below 7% in simulations.
- Showed excellent correlation (R2=0.995) with radio-isotope labeled microsphere measurements.
Conclusions:
- Model-independent deconvolution is a feasible and accurate method for myocardial blood flow quantification using MRI.
- This approach minimizes user interaction and modeling expertise requirements.
- The findings support wider clinical adoption of MR-based myocardial perfusion quantification.