Development of robust calibration models using support vector machines for spectroscopic monitoring of blood glucose.

Sample-to-sample variability has proven to be a major challenge in achieving calibration transfer in quantitative biological Raman spectroscopy. Multiple morphological and optical parameters, such as tissue absorption and scattering, physiological glucose dynamics and skin heterogeneity, vary significantly in a human population introducing nonanalyte specific features into the calibration model. In this paper, we show that fluctuations of such parameters in human subjects introduce curved (nonlinear) effects in the relationship between the concentrations of the analyte of interest and the mixture Raman spectra. To account for these curved effects, we propose the use of support vector machines (SVM) as a nonlinear regression method over conventional linear regression techniques such as partial least-squares (PLS). Using transcutaneous blood glucose detection as an example, we demonstrate that application of SVM enables a significant improvement (at least 30%) in cross-validation accuracy over PLS when measurements from multiple human volunteers are employed in the calibration set. Furthermore, using physical tissue models with randomized analyte concentrations and varying turbidities, we show that the fluctuations in turbidity alone causes curved effects which can only be adequately modeled using nonlinear regression techniques. The enhanced levels of accuracy obtained with the SVM based calibration models opens up avenues for prospective prediction in humans and thus for clinical translation of the technology.

Accurate spectroscopic calibration for noninvasive glucose monitoring by modeling the physiological glucose dynamics.

The physiological lag between blood and interstitial fluid (ISF) glucose is a major challenge for noninvasive glucose concentration measurements. This is a particular problem for spectroscopic techniques, which predominantly probe ISF glucose, creating inconsistencies in calibration, where blood glucose measurements are used as a reference. To overcome this problem, we present a dynamic concentration correction (DCC) scheme, based on the mass transfer of glucose between blood and ISF, to ensure consistency with the spectral measurements. The proposed formalism allows the transformation of glucose in the concentration domain, ensuring consistency with the acquired spectra in the calibration model. Taking Raman spectroscopy as a specific example, we demonstrate that the predicted glucose concentrations using the DCC-based calibration model closely match the measured glucose concentrations, while those generated with the conventional calibration methods show significantly larger deviations from the measured values. In addition, we provide an analytical formula for a previously unidentified source of limiting uncertainty arising in spectroscopic glucose monitoring from a lack of knowledge of glucose kinetics in prediction samples. A study with human volunteers undergoing glucose tolerance tests indicates that this lag uncertainty, which is comparable in magnitude to the uncertainty arising from noise and nonorthogonality in the spectral data set, can be reduced substantially by employing the DCC scheme in spectroscopic calibration.

Mechanoelectrical excitation by fluid jets in monolayers of cultured cardiac myocytes.

Although the prevailing view of mechanoelectric feedback (MEF) in the heart is in terms of longitudinal cell stretch, other mechanical forces are considerable during the cardiac cycle, including intramyocardial pressure and shear stress. Their contribution to MEF is largely unknown. In this study, mechanical stimuli in the form of localized fluid jet pulses were applied to neonatal rat ventricular cells cultured as confluent monolayers. Such pulses result in pressure and shear stresses (but not longitudinal stretch) in the monolayer at the point of impingement. The goal was to determine whether these mechanical stimuli can trigger excitation, initiate a propagated wave, and induce reentry. Cells were stained with the voltage-sensitive dye RH237, and multi-site optical mapping was used to record the spread of electrical activity in isotropic and anisotropic monolayers. Pulses (10 ms) with velocities ranging from 0.3 to 1.8 m/s were applied from a 0.4-mm diameter nozzle located 1 mm above the cell monolayer. Fluid jet pulses resulted in circular wavefronts that propagated radially from the stimulus site. The likelihood for mechanical stimulation was quantified as an average stimulus success rate (ASSR). ASSR increased with jet amplitude and time waited between stimuli and decreased with the application of gadolinium and streptomycin, blockers of stretch-activated channels, but not with nifedipine, a blocker of the L-type Ca channel. Absence of cellular injury was confirmed by smooth propagation maps and propidium iodide stains. In rare instances, the mechanical pulse resulted in the induction of reentrant activity. We conclude that mechanical stimuli other than stretch can evoke action potentials, propagated activity, and reentrant arrhythmia in two-dimensional sheets of cardiac cells.

Effect of photobleaching on calibration model development in biological Raman spectroscopy.

A major challenge in performing quantitative biological studies using Raman spectroscopy lies in overcoming the influence of the dominant sample fluorescence background. Moreover, the prediction accuracy of a calibration model can be severely compromised by the quenching of the endogenous fluorophores due to the introduction of spurious correlations between analyte concentrations and fluorescence levels. Apparently, functional models can be obtained from such correlated samples, which cannot be used successfully for prospective prediction. This work investigates the deleterious effects of photobleaching on prediction accuracy of implicit calibration algorithms, particularly for transcutaneous glucose detection using Raman spectroscopy. Using numerical simulations and experiments on physical tissue models, we show that the prospective prediction error can be substantially larger when the calibration model is developed on a photobleaching correlated dataset compared to an uncorrelated one. Furthermore, we demonstrate that the application of shifted subtracted Raman spectroscopy (SSRS) reduces the prediction errors obtained with photobleaching correlated calibration datasets compared to those obtained with uncorrelated ones.

Multimodal spectroscopy detects features of vulnerable atherosclerotic plaque.

Early detection and treatment of rupture-prone vulnerable atherosclerotic plaques is critical to reducing patient mortality associated with cardiovascular disease. The combination of reflectance, fluorescence, and Raman spectroscopy-termed multimodal spectroscopy (MMS)-provides detailed biochemical information about tissue and can detect vulnerable plaque features: thin fibrous cap (TFC), necrotic core (NC), superficial foam cells (SFC), and thrombus. Ex vivo MMS spectra are collected from 12 patients that underwent carotid endarterectomy or femoral bypass surgery. Data are collected by means of a unitary MMS optical fiber probe and a portable clinical instrument. Blinded histopathological analysis is used to assess the vulnerability of each spectrally evaluated artery lesion. Modeling of the ex vivo MMS spectra produce objective parameters that correlate with the presence of vulnerable plaque features: TFC with fluorescence parameters indicative of collagen presence; NC∕SFC with a combination of diffuse reflectance ß-carotene∕ceroid absorption and the Raman spectral signature of lipids; and thrombus with its Raman signature. Using these parameters, suspected vulnerable plaques can be detected with a sensitivity of 96% and specificity of 72%. These encouraging results warrant the continued development of MMS as a catheter-based clinical diagnostic technique for early detection of vulnerable plaques.

Wavelength selection-based nonlinear calibration for transcutaneous blood glucose sensing using Raman spectroscopy.

While Raman spectroscopy provides a powerful tool for noninvasive and real time diagnostics of biological samples, its translation to the clinical setting has been impeded by the lack of robustness of spectroscopic calibration models and the size and cumbersome nature of conventional laboratory Raman systems. Linear multivariate calibration models employing full spectrum analysis are often misled by spurious correlations, such as system drift and covariations among constituents. In addition, such calibration schemes are prone to overfitting, especially in the presence of external interferences that may create nonlinearities in the spectra-concentration relationship. To address both of these issues we incorporate residue error plot-based wavelength selection and nonlinear support vector regression (SVR). Wavelength selection is used to eliminate uninformative regions of the spectrum, while SVR is used to model the curved effects such as those created by tissue turbidity and temperature fluctuations. Using glucose detection in tissue phantoms as a representative example, we show that even a substantial reduction in the number of wavelengths analyzed using SVR lead to calibration models of equivalent prediction accuracy as linear full spectrum analysis. Further, with clinical datasets obtained from human subject studies, we also demonstrate the prospective applicability of the selected wavelength subsets without sacrificing prediction accuracy, which has extensive implications for calibration maintenance and transfer. Additionally, such wavelength selection could substantially reduce the collection time of serial Raman acquisition systems. Given the reduced footprint of serial Raman systems in relation to conventional dispersive Raman spectrometers, we anticipate that the incorporation of wavelength selection in such hardware designs will enhance the possibility of miniaturized clinical systems for disease diagnosis in the near future.

A novel non-imaging optics based Raman spectroscopy device for transdermal blood analyte measurement.

Due to its high chemical specificity, Raman spectroscopy has been considered to be a promising technique for non-invasive disease diagnosis. However, during Raman excitation, less than one out of a million photons undergo spontaneous Raman scattering and such weakness in Raman scattered light often require highly efficient collection of Raman scattered light for the analysis of biological tissues. We present a novel non-imaging optics based portable Raman spectroscopy instrument designed for enhanced light collection. While the instrument was demonstrated on transdermal blood glucose measurement, it can also be used for detection of other clinically relevant blood analytes such as creatinine, urea and cholesterol, as well as other tissue diagnosis applications. For enhanced light collection, a non-imaging optical element called compound hyperbolic concentrator (CHC) converts the wide angular range of scattered photons (numerical aperture (NA) of 1.0) from the tissue into a limited range of angles accommodated by the acceptance angles of the collection system (e.g., an optical fiber with NA of 0.22). A CHC enables collimation of scattered light directions to within extremely narrow range of angles while also maintaining practical physical dimensions. Such a design allows for the development of a very efficient and compact spectroscopy system for analyzing highly scattering biological tissues. Using the CHC-based portable Raman instrument in a clinical research setting, we demonstrate successful transdermal blood glucose predictions in human subjects undergoing oral glucose tolerance tests.

Combined confocal Raman and quantitative phase microscopy system for biomedical diagnosis.

We have developed a novel multimodal microscopy system that incorporates confocal Raman, confocal reflectance, and quantitative phase microscopy (QPM) into a single imaging entity. Confocal Raman microscopy provides detailed chemical information from the sample, while confocal reflectance and quantitative phase microscopy show detailed morphology. Combining these intrinsic contrast imaging modalities makes it possible to obtain quantitative morphological and chemical information without exogenous staining. For validation and characterization, we have used this multi-modal system to investigate healthy and diseased blood samples. We first show that the thickness of a healthy red blood cell (RBC) shows good correlation with its hemoglobin distribution. Further, in malaria infected RBCs, we successfully image the distribution of hemozoin (malaria pigment) inside the cell. Our observations lead us to propose morphological screening by QPM and subsequent chemical imaging by Raman for investigating blood disorders. This new approach allows monitoring cell development and cell-drug interactions with minimal perturbation of the biological system of interest.

A multimodal spectroscopy system for real-time disease diagnosis.

The combination of reflectance, fluorescence, and Raman spectroscopy-termed multimodal spectroscopy (MMS)-provides complementary and depth-sensitive information about tissue composition. As such, MMS is a promising tool for disease diagnosis, particularly in atherosclerosis and breast cancer. We have developed an integrated MMS instrument and optical fiber spectral probe for simultaneous collection of all three modalities in a clinical setting. The MMS instrument multiplexes three excitation sources, a xenon flash lamp (370-740 nm), a nitrogen laser (337 nm), and a diode laser (830 nm), through the MMS probe to excite tissue and collect the spectra. The spectra are recorded on two spectrograph/charge-coupled device modules, one optimized for visible wavelengths (reflectance and fluorescence) and the other for the near-infrared (Raman), and processed to provide diagnostic parameters. We also describe the design and calibration of a unitary MMS optical fiber probe 2 mm in outer diameter, containing a single appropriately filtered excitation fiber and a ring of 15 collection fibers, with separate groups of appropriately filtered fibers for efficiently collecting reflectance, fluorescence, and Raman spectra from the same tissue location. A probe with this excitation/collection geometry has not been used previously to collect reflectance and fluorescence spectra, and thus physical tissue models ("phantoms") are used to characterize the probe's spectroscopic response. This calibration provides probe-specific modeling parameters that enable accurate extraction of spectral parameters. This clinical MMS system has been used recently to analyze artery and breast tissue in vivo and ex vivo.

Functional reentry in cultured monolayers of neonatal rat cardiac cells.

Previous studies of reentrant arrhythmias in the heart have been performed in computer models and tissue experiments. We hypothesized that confluent monolayers of cardiac cells can provide a simple, controlled, and reproducible experimental model of reentry. Neonatal rat ventricular cells were cultured on 22-mm-diameter coverslips and stained with the voltage-sensitive dye RH-237. Recordings of transmembrane potentials were obtained from 61 sites with the use of a contact fluorescence imaging system. An electrical field stimulus, followed by a point stimulus, induced 39 episodes of sustained reentry and 21 episodes of nonsustained reentry. Sustained reentry consisted of single-loop (n = 18 monolayers) or figure-of-eight (n = 4) patterns. The cycle length, action potential duration at 80% repolarization, and conduction velocity were (in means +/- SE) 358 +/- 33 ms, 118 +/- 12 ms, and 12.9 +/- 1.0 cm/s for single loop and 311 +/- 78 ms, 137 +/- 18 ms, and 7.8 +/- 1.3 cm/s for figure-of-eight, respectively. Electrical termination by 6- to 13-V/cm field pulses or 15- to 20-V point stimuli was successful in 60% of the attempts. In summary, highly stable reentry can be induced, sustained for extensive periods of time, and electrically terminated in monolayers of cultured neonatal rat cardiac myocytes.