NDLI: Dynamic physiological modeling for functional diffuse optical tomography

Content Provider	PubMed Central
Author	Diamond, Solomon Gilbert Huppert, Theodore J. Kolehmainen, Ville Franceschini, Maria Angela Kaipio, Jari P. Arridge, Simon R. Boas, David A.
Abstract	Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n = 10, P < 0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis.
Related Links	http://dx.doi.org/10.1016/j.neuroimage.2005.09.016
Ending Page	101
Page Count	14
Starting Page	88
File Format	PDF
ISSN	10538119
e-ISSN	10959572
Journal	NeuroImage
Issue Number	1
Volume Number	30
Language	English
Publisher Date	2006-03-01
Access Restriction	Open
Subject Keyword	Cognitive Neuroscience Neurology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Neurology Cognitive Neuroscience

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