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.National Institutes of Health (U.S) ( Grant No. P41-RR-02594

Clinical feasibility of Raman spectroscopy for quantitative blood glucose measurement

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 167-175).Diabetes mellitus is a leading cause of morbidity and mortality worldwide, and close monitoring of blood glucose levels is crucial for its diagnosis and management. Currently, blood glucose monitoring is done by blood withdrawal or through invasive access to the interstitial fluid. While Raman spectroscopy has been studied as a possible non-invasive optical technique for measuring blood glucose, it still faces several practical difficulties. These include tissue turbidity and autofluorescence, the lag between blood and interstitial fluid glucose concentrations, and the inherently weak intensity of aqueous glucose Raman signatures with respect to those of the interfering tissue. This thesis investigates the feasibility of using Raman spectroscopy as a non-invasive technique for blood glucose monitoring, and studies different strategies to overcome the barriers to clinical application. In particular, the study proposes a dynamic concentration correction scheme to correct for the calibration errors arising from the lag between glucose concentrations in the bloodstream and the interstitial fluid. In addition, Monte Carlo simulations were employed to study the differences in the distribution of Raman scattered photons along the depth of the tissue between backscattered and transmission mode Raman spectroscopy. Finally, a portable clinical Raman spectroscopy unit was developed utilizing a non-imaging optical element called a compound hyperbolic concentrator (CHC). The CHC coupled with a matching focusing lens efficiently collects and collimates Raman light from highly scattering tissues, while maintaining much smaller physical dimensions than a compound parabolic concentrator. Using the clinical instrument, skin Raman spectra were collected from healthy human subjects undergoing oral glucose tolerance tests, while the corresponding reference blood glucose concentrations were measured simultaneously with a conventional finger-stick glucose meter. From these datasets, linear and non-linear multivariate calibration techniques were used to relate the Raman spectral intensities to the glucose concentrations. The calibrated algorithms were then tested to demonstrate clinical accuracy as required by the Food and Drug Administration and the International Organization for Standardization. Despite the remaining challenges, the promising results obtained in this study provide important insights required in the clinical translation of Raman spectroscopy for non-invasive blood glucose monitoring.by Chae-Ryon Kong.Ph.D

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.National Center for Research Resources (U.S.) (Grant P41-RR02594)Bayer HealthcareMassachusetts Institute of Technology. Laser Biomedical Research Center. Lester Wolfe Fellowshi

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.National Center for Research Resources (U.S.) (Grant No. P41-RR02594)Massachusetts Institute of Technology. Laser Biomedical Research Center (Lester Wolfe Fellowship

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

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 β-carotene/ceroid [beta-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.National Institutes of Health (U.S.) (NIH grant P41-RR-02594