Fenghua Tian

A portable ECG and blood pressure telemonitoring system

This article discusses a cost-effective portable home unit for electrocardiogram (ECG) and blood pressure (BP) monitoring. Based on feedback from our previous work concerning a PC-based ECG/BP telemonitoring system, the system described helps to overcome past problems by simplifying home installation, operation, and maintenance, and by reducing cost. The strategy and methodology used in the design and development of the system, as well as the results, are presented.

Development of a compensation algorithm for accurate depth localization in diffuse optical tomography

Diffuse optical tomography endures poor depth localization, since its sensitivity decreases severely with increased depth. In this study, we demonstrate a depth compensation algorithm (DCA), which optimally counterbalances the decay nature of light propagation in tissue so as to accurately localize absorbers in deep tissue. The novelty of DCA is to directly modify the sensitivity matrix, rather than the penalty term of regularization. DCA is based on maximum singular values (MSVs) of layered measurement sensitivities; these MSVs are inversely utilized to create a balancing weight matrix for compensating the measurement sensitivity in increased depth. Both computer simulations and laboratory experiments were performed to validate DCA. These results demonstrate that one (or two) 3-cm-deep absorber(s) can be accurately located in both lateral plane and depth within the laboratorial position errors.

Endogenous optical biomarkers of normal and human papillomavirus immortalized epithelial cells

Cellular transformation is associated with a number of phenotypic, cell biological, biochemical and metabolic alterations. The detection and classification of morphological cellular abnormalities represents the foundation of classical histopathology and remains an important mainstay in the clinic. More recently, significant effort is being expended towards the development of noninvasive modalities for the detection of cancer at an early stage, when therapeutic interventions are highly successful. Methods that rely on the detection of optical signatures represent one class of such approaches that have yielded promising results. In our study, we have applied two spectroscopic imaging approaches to systematically identify in a quantitative manner the fluorescence and light scattering signatures of subcellular abnormalities that are associated with cellular transformation. Notably, we find that tryptophan images reveal not only intensity but also localization differences between normal and human papillomavirus immortalized cells, possibly originating from changes in the expression, 3D packing and organization of proteins and protein‐rich subcellular organelles. Additionally, we detect alterations in cellular metabolism through quantitative evaluation of the NADH, FAD fluorescence and the corresponding redox ratio. Finally, we use light scattering spectroscopy to identify differences in nuclear morphology and subcellular organization that occur from the nanometer to the micrometer scale. Thus, these optical approaches provide complementary biomarkers based on endogenous fluorescence and scattering cellular changes that occur at the molecular, biochemical and morphological level. Since they obviate the need for staining and tissue removal and can be easily combined, they provide desirable options for further clinical development and assessment.

Optimization of probe geometry for diffuse optical brain imaging based on measurement density and distribution

Optode geometry plays an important role in achieving both good spatial resolution and spatial uniformity of detection in diffuse-optical-imaging-based brain activation studies. The quality of reconstructed images for six optode geometries were studied and compared using a laboratory tissue phantom model that contained an embedded object at two separate locations. The number of overlapping measurements per pixel (i.e., the measurement density) and their spatial distributions were quantified for all six geometries and were correlated with the quality of the resulting reconstructed images. The latter were expressed by the area ratio (AR) and contrast-to-noise ratio (CNR) between reconstructed and actual objects. Our results revealed clearly that AR and CNR depended on the measurement density asymptotically, having an optimal point for measurement density beyond which more overlapping measurements would not significantly improve the quality of reconstructed images. Optimization of probe geometry based on our method demonstrated that a practical compromise can be attained between DOI spatial resolution and measurement density.

Using Simultaneous Repetitive Transcranial Magnetic Stimulation/Functional Near Infrared Spectroscopy (rTMS/fNIRS) to Measure Brain Activation and Connectivity

INTRODUCTION Simultaneously acquiring functional Near Infrared Spectroscopy (fNIRS) during Transcranial Magnetic Stimulation (rTMS) offers the possibility of directly investigating superficial cortical brain activation and connectivity. In addition, the effects of rTMS in distinct brain regions without quantifiable behavioral changes can be objectively measured. METHODS Healthy, nonmedicated participants age 18-50 years were recruited from the local community. After written informed consent was obtained, the participants were screened to ensure that they met inclusion criteria. They underwent two visits of simultaneous rTMS/fNIRS separated by 2 to 3 days. In each visit, the motor cortex and subsequently the prefrontal cortex (5 cm anterior to the motor cortex) were stimulated (1 Hz, max 120% MT, 10 s on with 80 s off, for 15 trains) while simultaneous fNIRS data were acquired from the ipsilateral and contralateral brain regions. RESULTS Twelve healthy volunteers were enrolled with one excluded prior to stimulation. The 11 participants studied (9 male) had a mean age of 31.8 (s.d. 10.2, range 20-49) years. There was no significant difference in fNIRS between Visit 1 and Visit 2. Stimulation of both the motor and prefrontal cortices resulted in a significant decrease in oxygenated hemoglobin (HbO(2)) concentration in both the ipsilateral and contralateral cortices. The ipsilateral and contralateral changes showed high temporal consistency. DISCUSSION Simultaneous rTMS/fNIRS provides a reliable measure of regional cortical brain activation and connectivity that could be very useful in studying brain disorders as well as cortical changes induced by rTMS.

Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm

A depth compensation algorithm (DCA) can effectively improve the depth localization of diffuse optical tomography (DOT) by compensating the exponentially decreased sensitivity in the deep tissue. In this study, DCA is investigated based on computer simulations, tissue phantom experiments, and human brain imaging. The simulations show that DCA can largely improve the spatial resolution of DOT in addition to the depth localization, and DCA is also effective for multispectral DOT with a wide range of optical properties in the background tissue. The laboratory phantom experiment demonstrates that DCA can effectively differentiate two embedded objects at different depths in the medium. DCA is further validated by human brain imaging using a finger-tapping task. To our knowledge, this is the first demonstration to show that DCA is capable of accurately localizing cortical activations in the human brain in three dimensions.

Sparsity enhanced spatial resolution and depth localization in diffuse optical tomography

Abstract: In diffuse optical tomography (DOT), researchers often face challenges to accurately recover the depth and size of the reconstructed objects. Recent development of the Depth Compensation Algorithm (DCA) solves the depth localization problem, but the reconstructed images commonly exhibit over-smoothed boundaries, leading to fuzzy images with low spatial resolution. While conventional DOT solves a linear inverse model by minimizing least squares errors using L2 norm regularization, L1 regularization promotes sparse solutions. The latter may be used to reduce the over-smoothing effect on reconstructed images. In this study, we combined DCA with L1 regularization, and also with L2 regularization, to examine which combined approach provided us with an improved spatial resolution and depth localization for DOT. Laboratory tissue phantoms were utilized for the measurement with a fiber-based and a camera-based DOT imaging system. The results from both systems showed that L1 regularization clearly outperformed L2 regularization in both spatial resolution and depth localization of DOT. An example of functional brain imaging taken from human in vivo measurements was further obtained to support the conclusion of the study.

Functional near-infrared spectroscopy to investigate hemodynamic responses to deception in the prefrontal cortex

Deception involves complex neural processes and correlates in the brain. Functional brain imaging techniques have been used to study and understand brain mechanisms during deception. In this study, we utilized functional near-infrared spectroscopy (fNIRS) to investigate hemodynamic responses to deception in the prefrontal cortex (PFC) at the individual level. The protocol involved a mock theft scenario that was previously used in a functional MRI (fMRI) study of detecting deception. Subjects (N=11) were instructed to steal a ring or a watch and then conceal the item that they stole. Participants then responded to visually presented questions regarding which item they took. While the subjects were answering the questions, their PFC activity was measured using fNIRS. The brain activity associated with deceptive responses demonstrated significant changes in hemoglobin concentrations with respect to the baseline, while the response of truth telling was not statistically different from baseline. The regions of greater activation induced by deception identified by fNIRS were approximately consistent with those reported by the previous fMRI study using a similar protocol. This study demonstrates that fNIRS is a promising new technique to understand hemodynamic and neural correlates of deception and thus to detect deception with the added advantages of being compact, technically easier to implement, and inexpensive compared to functional MRI.

Enhanced Functional Brain Imaging by Using Adaptive Filtering and a Depth Compensation Algorithm in Diffuse Optical Tomography

Reflectance diffuse optical tomography (rDOT) of brain function is limited by its high sensitivity to the superficial tissues (i.e., the scalp and skull) and by its severe decrease in measurement sensitivity with increased depth. Significant interference in rDOT results from spontaneous fluctuations that are embedded in both the superficial tissues and brain, such as arterial pulsation and vasomotion. In this study, first we investigate coherence and phase shift of the spontaneous fluctuations in the resting state, within the superficial tissues and at various depths of the brain, respectively. We demonstrate that the spontaneous fluctuations originating from arterial pulsations (~ 1 Hz) are spatially global and temporally coherent, while the fluctuations originating from vasomotion (~ 0.1 Hz) tend to have less coherence with increased depth. Second, adaptive cancellation of spontaneous fluctuations with a frequency-specific strategy is utilized and validated in both resting and activation (evoked by a finger-tapping task) states. Third, improved depth localization of motor activation in reconstructed rDOT images is achieved by combining adaptive cancellation with a depth compensation algorithm that we recently reported.

Depth-compensated diffuse optical tomography enhanced by general linear model analysis and an anatomical atlas of human head

One of the main challenges in functional diffuse optical tomography (DOT) is to accurately recover the depth of brain activation, which is even more essential when differentiating true brain signals from task-evoked artifacts in the scalp. Recently, we developed a depth-compensated algorithm (DCA) to minimize the depth localization error in DOT. However, the semi-infinite model that was used in DCA deviated significantly from the realistic human head anatomy. In the present work, we incorporated depth-compensated DOT (DC-DOT) with a standard anatomical atlas of human head. Computer simulations and human measurements of sensorimotor activation were conducted to examine and prove the depth specificity and quantification accuracy of brain atlas-based DC-DOT. In addition, node-wise statistical analysis based on the general linear model (GLM) was also implemented and performed in this study, showing the robustness of DC-DOT that can accurately identify brain activation at the correct depth for functional brain imaging, even when co-existing with superficial artifacts.