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Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling
Published on: May 30, 2011
Imaging Clinically Relevant Pain States Using Arterial Spin Labeling
Marco Luciano Loggia1, Andrew Reilly Segerdahl2, Matthew Alexander Howard3
1A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Abstract:
Arterial Spin Labeling (ASL) is a perfusion-based functional magnetic resonance imaging technique that uses water in arterial blood as a freely diffusible tracer to measure regional cerebral blood flow (rCBF) noninvasively. To date its application to the study of pain has been relatively limited. Yet, ASL possesses key features that make it uniquely positioned to study pain in certain paradigms. For instance, ASL is sensitive to very slowly fluctuating brain signals (in the order of minutes or longer). This characteristic makes ASL particularly suitable to the evaluation of brain mechanisms of tonic experimental, post-surgical and ongoing/or continuously varying pain in chronic or acute pain conditions (whereas BOLD fMRI is better suited to detect brain responses to short-lasting or phasic/evoked pain). Unlike positron emission tomography or other perfusion techniques, ASL allows the estimation of rCBF without requiring the administration of radioligands or contrast agents. Thus, ASL is well suited for within-subject longitudinal designs (e.g., to study evolution of pain states over time, or of treatment effects in clinical trials). ASL is also highly versatile, allowing for novel paradigms exploring a flexible array of pain states, plus it can be used to simultaneously estimate not only pain-related alterations in perfusion but also functional connectivity. In conclusion, ASL can be successfully applied in pain paradigms that would be either challenging or impossible to implement using other techniques. Particularly when used in concert with other neuroimaging techniques, ASL can be a powerful tool in the pain imager's toolbox.
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