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Quantitative magnetization transfer imaging in human brain at 3 T via selective inversion recovery
Richard D Dortch1, Ke Li, Daniel F Gochberg
1Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee, USA. richard.dortch@vanderbilt.edu
Magnetic Resonance in Medicine
|May 25, 2011
Summary
This study introduces quantitative magnetization transfer imaging for in vivo human brain scans. The method shows reproducible results and detects subtle pathological changes in multiple sclerosis patients.
Area of Science:
- Neuroimaging
- Biophysics
- Medical Physics
Background:
- Quantitative magnetization transfer (qMT) imaging probes proton interactions between water and macromolecules.
- Key indices include the macromolecular to free pool size ratio (PSR) and transfer rate k(mf).
- Previous implementations were limited, hindering clinical application.
Purpose of the Study:
- To implement and validate the selective inversion recovery qMT method on a clinical 3.0-T scanner for in vivo human brain imaging.
- To assess the reproducibility and sensitivity of qMT indices in healthy subjects and multiple sclerosis patients.
Main Methods:
- Selective inversion recovery qMT data acquired at 16 inversion times.
- Fast spin-echo readout and reduced repetition time for a 4-minute single-slice acquisition.
- Study included 9 healthy subjects and 2 relapsing-remitting multiple sclerosis patients.
Main Results:
- Excellent intersubject and intrasubject reproducibility demonstrated in healthy subjects.
- PSR values in white and gray matter consistent with prior literature.
- k(mf) values were approximately 2-fold slower in white and gray matter compared to some previous reports.
- qMT indices detected pathological changes in lesions and normal-appearing white matter in MS patients.
Conclusions:
- The selective inversion recovery qMT method is feasible and reproducible on a clinical 3.0-T scanner for in vivo human brain imaging.
- qMT indices are sensitive to pathological alterations in multiple sclerosis, including in normal-appearing white matter.
- This technique holds promise for characterizing brain tissue microstructure and disease progression.
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