David Bonekamp1, Peter B Barker, Richard Leigh, Peter C M van Zijl, Xu Li. 1. The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; FM Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland.
Abstract
PURPOSE: An algorithm is developed for the reconstruction of dynamic, gadolinium (Gd) bolus MR perfusion images of the human brain, based on quantitative susceptibility mapping (QSM). METHODS: The method is evaluated in five perfusion scans obtained from four different patients scanned at 3 Tesla, and compared with the conventional analysis based on changes in the transverse relaxation rate ΔR2 * and to theoretical predictions. QSM images were referenced to ventricular cerebrospinal fluid (CSF) for each dynamic of the perfusion sequence. RESULTS: Images of cerebral blood flow and blood volume were successfully reconstructed from the QSM-analysis, and were comparable to those reconstructed using ΔR2 *. The magnitudes of the Gd-associated susceptibility effects in gray and white matter were consistent with theoretical predictions. CONCLUSION: QSM-based analysis may have some theoretical advantages compared with ΔR2 *, including a simpler relationship between signal change and Gd concentration. However, disadvantages are its much lower contrast-to-noise ratio, artifacts due to respiration and other effects, and more complicated reconstruction methods. More work is required to optimize data acquisition protocols for QSM-based perfusion imaging.
PURPOSE: An algorithm is developed for the reconstruction of dynamic, gadolinium (Gd) bolus MR perfusion images of the human brain, based on quantitative susceptibility mapping (QSM). METHODS: The method is evaluated in five perfusion scans obtained from four different patients scanned at 3 Tesla, and compared with the conventional analysis based on changes in the transverse relaxation rate ΔR2 * and to theoretical predictions. QSM images were referenced to ventricular cerebrospinal fluid (CSF) for each dynamic of the perfusion sequence. RESULTS: Images of cerebral blood flow and blood volume were successfully reconstructed from the QSM-analysis, and were comparable to those reconstructed using ΔR2 *. The magnitudes of the Gd-associated susceptibility effects in gray and white matter were consistent with theoretical predictions. CONCLUSION: QSM-based analysis may have some theoretical advantages compared with ΔR2 *, including a simpler relationship between signal change and Gd concentration. However, disadvantages are its much lower contrast-to-noise ratio, artifacts due to respiration and other effects, and more complicated reconstruction methods. More work is required to optimize data acquisition protocols for QSM-based perfusion imaging.
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