Alex C.-T. Ko

Ex vivo detection and characterization of early dental caries by optical coherence tomography and Raman spectroscopy.

Early dental caries detection will facilitate implementation of nonsurgical methods for arresting caries progression and promoting tooth remineralization. We present a method that combines optical coherence tomography (OCT) and Raman spectroscopy to provide morphological information and biochemical specificity for detecting and characterizing incipient carious lesions found in extracted human teeth. OCT imaging of tooth samples demonstrated increased light backscattering intensity at sites of carious lesions as compared to the sound enamel. The observed lesion depth on an OCT image was approximately 290 microm matching those previously documented for incipient caries. Using Raman microspectroscopy and fiber-optic-based Raman spectroscopy to characterize the caries further, spectral changes were observed in PO4 (3-) vibrations arising from hydroxyapatite of mineralized tooth tissue. Examination of various ratios of PO4 (3-) nu2, nu3, nu4 vibrations against the nu1 vibration showed consistent increases in carious lesions compared to sound enamel. The changes were attributed to demineralization-induced alterations of enamel crystallite morphology and/or orientation. OCT imaging is useful for screening carious sites and determining lesion depth, with Raman spectroscopy providing biochemical confirmation of caries. The combination has potential for development into a new fiber-optic diagnostic tool enabling dentists to identify early caries lesions with greater sensitivity and specificity.

Detection of early dental caries using polarized Raman spectroscopy

A new technique based on polarized Raman spectroscopy is demonstrated for detecting early dental caries on extracted human teeth. Sound tooth enamel exhibited strong Raman polarization anisotropy whereas early caries consistently showed a lower degree of Raman polarization anisotropy. In particular, for sound enamel, the Raman peak arising from the symmetric nu1 vibration of PO(4) (3-) at 959 cm(-1) is strongly polarized. This is in contrast to the spectra of carious lesions that displayed weaker polarization dependence at 959 cm(-1). Such difference in the degree of Raman polarization anisotropy allows for discrimination between early dental caries and sound enamel.

Collagen morphology and texture analysis: from statistics to classification

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage.

Early dental caries detection using a fibre-optic coupled polarization-resolved Raman spectroscopic system

A new fibre-optic coupled polarization-resolved Raman spectroscopic system was developed for simultaneous collection of orthogonally polarized Raman spectra in a single measurement. An application of detecting incipient dental caries based on changes observed in Raman polarization anisotropy was also demonstrated using the developed fibre-optic Raman spectroscopic system. The predicted reduction of polarization anisotropy in the Raman spectra of caries lesions was observed and the results were consistent with those reported previously with Raman microspectroscopy. The capability of simultaneous collection of parallel- and cross-polarized Raman spectra of tooth enamel in a single measurement and the improved laser excitation delivery through fibre-optics demonstrated in this new design illustrates its future clinical potential.

Multimodal nonlinear optical imaging of atherosclerotic plaque development in myocardial infarction-prone rabbits.

Label-free imaging of bulk arterial tissue is demonstrated using a multimodal nonlinear optical microscope based on a photonic crystal fiber and a single femtosecond oscillator operating at 800 nm. Colocalized imaging of extracellular elastin fibers, fibrillar collagen, and lipid-rich structures within aortic tissue obtained from atherosclerosis-prone myocardial infarction-prone Watanabe heritable hyperlipidemic (WHHLMI) rabbits is demonstrated through two-photon excited fluorescence, second harmonic generation, and coherent anti-Stokes Raman scattering, respectively. These images are shown to differentiate healthy arterial wall, early atherosclerotic lesions, and advanced plaques. Clear pathological changes are observed in the extracellular matrix of the arterial wall and correlated with progression of atherosclerotic disease as represented by the age of the WHHLMI rabbits.

Differentiating atherosclerotic plaque burden in arterial tissues using femtosecond CARS-based multimodal nonlinear optical imaging

A femtosecond CARS-based nonlinear optical microscope was used to simultaneously image extracellular structural proteins and lipid-rich structures within intact aortic tissue obtained from myocardial infarction-prone Watanabe heritable hyperlipidemic rabbits (WHHLMI). Clear differences in the NLO microscopic images were observed between healthy arterial tissue and regions dominated by atherosclerotic lesions. In the current ex-vivo study, we present a single parameter based on intensity changes derived from multi-channel NLO image to classify plaque burden within the vessel. Using this parameter we were able to differentiate between healthy regions of the vessel and regions with plaque, as well as distinguish plaques relative to the age of the WHHLMI rabbit.

NIR initiated and pH sensitive single-wall carbon nanotubes for doxorubicin intracellular delivery

In this work, we synthesized a pH sensitive poly(ethylene glycol)-doxorubicin (PEG-DOX) on single-wall carbon nanotubes (SWNTs). Using multimodal nonlinear optical imaging microscopy, we found that low power (1 mW cm-2) near-infrared radiation can initiate prodrug burst release from the carbon nanotubes in seconds. The successful SWNTs capping with PEG-DOX (denoted PEG-DOX@SWNT) was determined by transmission electron microscopy and FTIR results. The in vitro release of DOX from the PEG-DOX@SWNT was evaluated upon changes of pH values and NIR treating time. The cytotoxicity of the PEG-DOX@SWNT was also evaluated. This dual-sensitive delivery system based on SWNTs provides a facile approach to promote drug release and kill cancer cells.

Light- and pH-activated intracellular drug release from polymeric mesoporous silica nanoparticles

Surface modified mesoporous silica nanoparticles (MSNs) with reduced toxicity were prepared for light and pH dual triggerable drug delivery system. Both 413 nm light and acidic environment can activate the drug release process, improving the pharmacological action. By applying rhodamine B (RhB) as a model drug, the accumulative RhB release is as high as 95% in pH 5.0 and in irradiation of 413 nm light, compared to only 55% in pH 7.4 and in dark. The anti-cancer drug camptothecin (CPT) loaded nanoparticles can kill cancer cells with IC₅₀ value of 0.02 μg mL(-1) in exposure of 413 nm light, which is much lower than free CPT (about 0.1 μg mL(-1)). Multimodal nonlinear optical imaging microscopy (NLOM) was employed to acquire in vitro coherent anti-Stokes Raman (CARS) and two-photon excited fluorescence (TPEF) images of live MCF-7 cells and showed that the nanoparticles can be taken up by breast tumor cell MCF-7 with high efficiency, indicating its great potential for anti-cancer drug delivery system.

Nonlinear Optical Measurements of the Artery Wall: Parameters Related to the Progression of Atherosclerosis

Nonlinear Optical Measurements of the Artery Wall: Parameters Related to the Progression of Atherosclerosis Nonlinear optical (NLO) microscopy is used to follow key structural and biochemical changes associated with the progression of atherosclerosis. Arteries from WHHL-MI rabbits are examined using a 3 channel NLO microscope that can simultaneously monitor the coherent anti-stokes Raman scattered light (CARS), the two-photon excited fluorescence (TPEF) and the second harmonic generation (SHG) from a sample. Distinct differences in the nonlinear optical signals are observed that correlate with the age of the vessel and the presence of atherosclerotic plaque. These differences are attributed to the changing extracellular matrix and the increased lipid deposition associated with plaque development. The capability of NLO to perform 3D sectioning in thick highly scattering vessels in order to visualize structural details of the artery wall and highlight vessel pathology is demonstrated. These features make NLO a potentially valuable tool to help understand the progression of atherosclerosis.

Semi-Parametric Estimation in the Compositional Modeling of Multicomponent Systems from Raman Spectroscopic Data:

Identification and quantification of molecular species are central applications of molecular spectroscopy. In complex multicomponent systems like tissue samples, linear parametric models are often used to estimate the relative concentrations of the biochemical components of the sample. In situations where not all of the components of the sample are known or modeled, such parametric models can suffer from omitted variable bias and result in skewed estimates of component concentrations. We propose a semi-parametric approach that tries to avoid this omitted variable bias by effectively including unknown covariates as a non-parametric term in the regression equation. Constituent concentrations estimated with such partial linear models should outperform strict parametric linear models when the user has limited information on the composition of a multi-constituent system.