Direct estimation of evoked hemoglobin changes by multimodality fusion imaging
Name
Huppert-2008-Direct estimation of.pdf
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1.32 MB
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Author(s)
Huppert, Theodore J.
Diamond, Solomon G.
Boas, David A.
Date Issued
October 2008
Journal
Journal of Biomedical Optics
Publisher
SPIE - International Society for Optical Engineering
Citation
Huppert, Theodore J., Solomon G. Diamond, and David A. Boas. “Direct Estimation of Evoked Hemoglobin Changes by Multimodality Fusion Imaging.” Journal of Biomedical Optics 13.5 (2008): 054031. Web. 15 Feb. 2012. © 2008 SPIE - International Society for Optical Engineering
Version
Final published version
Abstract
In the last two decades, both diffuse optical tomography (DOT) and blood oxygen level dependent (BOLD)-based functional magnetic resonance imaging (fMRI) methods have been developed as noninvasive tools for imaging evoked cerebral hemodynamic changes in studies of brain activity. Although these two technologies measure functional contrast from similar physiological sources, i.e., changes in hemoglobin levels, these two modalities are based on distinct physical and biophysical principles leading to both limitations and strengths to each method. In this work, we describe a unified linear model to combine the complimentary spatial, temporal, and spectroscopic resolutions of concurrently measured optical tomography and fMRI signals. Using numerical simulations, we demonstrate that concurrent optical and BOLD measurements can be used to create cross-calibrated estimates of absolute micromolar deoxyhemoglobin changes. We apply this new analysis tool to experimental data acquired simultaneously with both DOT and BOLD imaging during a motor task, demonstrate the ability to more robustly estimate hemoglobin changes in comparison to DOT alone, and show how this approach can provide cross-calibrated estimates of hemoglobin changes. Using this multimodal method, we estimate the calibration of the 3 tesla BOLD signal to be −0.55%±0.40% signal change per micromolar change of deoxyhemoglobin.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
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DOI of Published Version
https://doi.org/10.1117/1.2976432
