Bedside functional imaging of the premature infant brain during passive motor activation

Hintz, Susan R.; Benaron, David A.; Siegel, Andrew M.; Zourabian, Anna; Stevenson, David K.; Boas, David A.

doi:10.1515/jpm.2001.048

Cited by 117 publications

(90 citation statements)

References 26 publications

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“…Here, we refer to the image obtained by an optimal solution of the inverse problem as the diffuse optical tomography (DOT) image. There are only a few published examples of DOT images of brain hemodynamics, for example, in rodents (Culver et al, 2003a,b;Siegel et al, 1999), in newborn human babies (Hintz et al, 2001), and in adult humans (Bluestone et al, 2001). The advancement of true DOT for brain activation in humans would improve the image spatial resolution and quantitative accuracy over that of current interpolating backprojection methods.…”

Section: Improving Image Resolution With Overlapping Measurementsmentioning

confidence: 99%

Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy

2004

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Near-infrared spectroscopy (NIRS) and diffuse optical imaging (DOI) are finding widespread application in the study of human brain activation, motivating further application-specific development of the technology. NIRS and DOI offer the potential to quantify changes in deoxyhemoglobin (HbR) and total hemoglobin (HbT) concentration, thus enabling distinction of oxygen consumption and blood flow changes during brain activation. While the techniques implemented presently provide important results for cognition and the neurosciences through their relative measures of HbR and HbT concentrations, there is much to be done to improve sensitivity, accuracy, and resolution. In this paper, we review the advances currently being made and issues to consider for improving optical image quality. These include the optimal selection of wavelengths to minimize random and systematic error propagation in the calculation of the hemoglobin concentrations, the filtering of systemic physiological signal clutter to improve sensitivity to the hemodynamic response to brain activation, the implementation of overlapping measurements to improve image spatial resolution and uniformity, and the utilization of spatial prior information from structural and functional MRI to reduce DOI partial volume error and improve image quantitative accuracy. D 2004 Elsevier Inc. All rights reserved.

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Section: Improving Image Resolution With Overlapping Measurementsmentioning

confidence: 99%

Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy

2004

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“…However, in spite of a significant amount of theoretical work (Boas et al, 2004a,b;Boas and Dale, 2005;Guven et al, 2005;Li et al, 2005;Xu et al, 2005), the literature on practical three dimensional fNIRSI of the human brain is limited to a few papers (Bluestone et al, 2001;Boas et al, 2004b;Hintz et al, 2001;Hoshi et al, 2000;Zhang et al, 2005a,b). The reason for the modest progress in full three-dimensional fNIRS is the combination of the extremely high scattering of light in biological tissue, together with the optical heterogeneity of the human head.…”

Section: Introductionmentioning

confidence: 99%

A spatial and temporal comparison of hemodynamic signals measured using optical and functional magnetic resonance imaging during activation in the human primary visual cortex

2007

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Functional near infrared spectro-imaging (fNIRSI) is potentially a very useful technique for obtaining information about the underlying physiology of the blood oxygenation level dependent (BOLD) signal used in functional magnetic resonance imaging (fMRI). In this paper the temporal and spatial statistical characteristics of fNIRSI data are compared to those of simultaneously acquired fMRI data in the human visual cortex during a variable-frequency reversing checkerboard activation paradigm. Changes in the size of activated volume caused by changes in checkerboard reversal frequency allowed a comparison of the behavior of the spatial responses measured by the two imaging methods. fNIRSI and fMRI data were each analyzed using standard correlation and fixed-effect group analyses of variance pathways. The statistical significance of fNIRSI data was found to be much lower than that of the fMRI data, due mainly to the low signal-to-noise of the measurements. Reconstructed images also showed that, while the time-course of changes in the oxy-, deoxy-, and total hemoglobin concentrations all exhibit high correlation with that of the BOLD response, the changes in the volume of tissue measured as "activated" by the BOLD response demonstrate a closer similarity to the corresponding changes in the oxy-and total hemoglobin concentrations than to that of the deoxyhemoglobin.

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“…Potential clinical and research applications for DOT abound in brain injury (Vernieri et al, 1999;Chen et al, 2000;Nemoto et al, 2000;Saitou et al, 2000), neurological diseases (Hock et al, 1996;Fallgatter et al, 1997;Hanlon et al, 1999;Steinhoff et al, 1996;Adelson et al, 1999;Sokol et al, 2000;Watanabe et al, 2000), psychiatric disorders (Okada et al, 1996b;Eschweiler et al, 2000;Matsuo et al, 2000;Okada et al, 1994;Fallgatter and Strik, 2000) and in cognitive and behavioral neuroscience (Ruben et al, 1997;Sakatani et al, 1999;Franceschini et al, 2003;Colier et al, 1999;Sato et al, 1999). Other research areas for DOT include infant monitoring (Chen et al, 2002;Hintz et al, 2001;Meek et al, 1999;Baird et al, 2002;Pena et al, 2003;Taga et al, 2003) and breast cancer detection Shah et al, 2004;Dehghani et al, 2003;Srinivasan et al, 2003). DOT is particularly suitable for in situ monitoring and multimodal imaging (Strangman et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

“…The spatial inverse problem is highly ill posed and requires regularization. Both linear (Boas et al, 2004b;Yamamoto et al, 2002;Hintz et al, 2001) and nonlinear (Bluestone et al, 2001;Prince et al, 2003;Xu et al, 2005;Hebden et al, 2004) reconstructions are commonly used in DOT.…”

Section: Introductionmentioning

confidence: 99%

Dynamic physiological modeling for functional diffuse optical tomography

et al. 2006

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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.

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Bedside functional imaging of the premature infant brain during passive motor activation

Abstract: In the intensive care setting, continuous non-invasive optical functional imaging could be critically important and, with further study, may provide a bedside monitoring tool for prospectively identifying patients at high risk for brain injury.

Cited by 117 publications

References 26 publications

Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy

Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy

A spatial and temporal comparison of hemodynamic signals measured using optical and functional magnetic resonance imaging during activation in the human primary visual cortex

Dynamic physiological modeling for functional diffuse optical tomography

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