Micro-relief characterization of benign and malignant skin lesions by polarization speckle analysis in vivo.

BACKGROUND/PURPOSE: A recent direction in skin disease classification is to develop quantitative diagnostic techniques. Skin relief, colloquially known as roughness, is an important clinical feature. The aim of this study is to demonstrate a novel polarization speckle technique to quantitatively measure roughness on skin lesions in vivo. We then calculate the average roughness of different types of skin lesions to determine the extent to which polarization speckle roughness measurements can be used to identify skin cancer. METHODS: The experimental conditions were set to target the fine relief structure on the order of ten microns within a small field of view of 3 mm. The device was tested in a clinical study on patients with malignant and benign skin lesions that resemble cancer. The cancer group includes 37 malignant melanomas (MM), 43 basal cell carcinomas (BCC), and 26 squamous cell carcinomas (SCC), all categories confirmed by gold standard biopsy. The benign group includes 109 seborrheic keratoses (SK), 79 nevi, and 11 actinic keratoses (AK). Normal skin roughness was obtained for the same patients (301 different body sites proximal to the lesion). RESULTS: The average root mean squared (rms) roughness ± standard error of the mean for MM and nevus was equal to 19 ± 5 µm and 21 ± 3 µm, respectively. Normal skin has rms roughness of 31 ± 3 µm, other lesions have roughness of 35 ± 10 µm (AK), 35 ± 7 µm (SCC), 31 ± 4 µm (SK), and 30 ± 5 µm (BCC). CONCLUSION: An independent-samples Kruskal-Wallis test indicates that MM and nevus can be separated from each of the tested types of lesions, except each other. These results quantify clinical knowledge of lesion roughness and could be useful for optical cancer detection.

Mechanistic insights into ceramidase inhibitor LCL521-enhanced tumor cell killing by photodynamic and thermal ablation therapies.

Our recent investigation uncovered that the acid ceramidase inhibitor LCL521 enhances the direct tumor cell killing effect of photodynamic therapy (PDT) treatment. The present study aimed at elucidating the mechanisms underlying this effect. Exposing mouse squamous cell carcinoma SCCVII cells treated with temoporfin-based PDT to LCL521 (rising ceramide concentration) produced a much greater decrease in cell survival than comparable exposure to the sphingosine kinase-1 inhibitor PF543 (that reduces sphingosine-1-phosphate concentration). This is consistent with recognizing the rising levels of pro-apoptotic sphingolipid ceramide as being more critical in promoting the death of PDT-treated cells than the reduction in the availability of pro-survival acting sphingosine-1 phosphate. This pro-apoptotic impact of LCL521, which was suppressed by the apoptosis inhibitor bongkrekic acid, involves the interaction with the cellular stress signaling network. Hence, inhibiting the key elements of these pathways markedly influenced the adjuvant effect of LCL521 on the PDT response. Particularly effective was the inositol-requiring element-1 (IRE1) kinase inhibitor STF-083010 that dramatically enhanced the killing of cells treated with PDT plus LCL521. An important role in the survival of these cells was exhibited by master transcription factors STAT3 and HIF-1α. The STAT3 inhibitor NSC 74859 was especially effective in further reducing the cell survival rates, suggesting its possible exploitation for therapeutic gain. An additional finding in this study is that LCL521-promoted PDT-mediated cell killing through ceramide-mediated lethal effects is extended to the interaction with other cancer treatment modalities with a rapid cellular stress impact such as photothermal therapy (PTT) and cryoablation therapy (CAT).

Confocal Raman Spectral Imaging Study of DAPT, a γ-secretase Inhibitor, Induced Physiological and Biochemical Reponses in Osteosarcoma Cells.

Confocal Raman microspectral imaging was adopted to elucidate the cellular drug responses of osteosarcoma cells (OC) to N-[N-(3, 5-difluorophenyl acetyl)-L-alanyl]-sphenylglycine butyl ester (DAPT), a γ-secretase inhibitor, by identifying the drug induced subcellular compositional and structural changes. Methods: Spectral information were acquired from cultured osteosarcoma cells treated with 0 (Untreated Group, UT), 10 (10 µM DAPT treated, 10T), 20 µM (20 µM DAPT treated, 20T) DAPT for 24 hours. A one-way ANOVA and Tukey's honest significant difference (HSD) post hoc multiple test were sequentially applied to address spectral features among three groups. Multivariate algorithms such as K-means clustering analysis (KCA) and Principal component analysis (PCA) were used to highlight the structural and compositional differences, while, univariate imaging was applied to illustrate the distribution pattern of certain cellular components after drug treatment. Results: Major biochemical changes in DAPT-induced apoptosis came from changes in the content and structure of proteins, lipids, and nucleic acids. By adopted multivariate algorithms, the drug induced cellular changes was identified by the morphology and spectral characteristics between untreated cells and treated cells, testified that DAPT mainly acted in the nuclear region. With the increase of the drug concentration, the content of main subcellular compositions, such nucleic acid, protein, and lipid decreased. In an addition, DAPT-induced nuclear fragmentation and apoptosis was depicted by the univariate Raman image of major cellular components (nucleic acids, proteins and lipids). Conclusions: The achieved Raman spectral and imaging results illustrated detailed DAPT-induced subcellular compositional and structural variations as a function of drug dose. Such observations can not only explain drug therapeutic mechanisms of OC DAPT treatment, and also provide new insights for accessing the medicine curative efficacy and predicting prognosis.

Precise in vivo tissue micro-Raman spectroscopy with simultaneous reflectance confocal microscopy monitoring using a single laser.

Raman spectroscopy provides molecular finger-printing of biological tissues. To achieve high spatial resolution, confocal Raman spectroscopy (micro-Raman) has been developed. To guide where micro-Raman is acquired, imaging guidance is necessary, especially for high scattering biological tissue. Reflectance confocal microscopy (RCM) has been integrated with micro-Raman. However, existing systems do not allow point-of-interest micro-Raman measurement with simultaneous RCM guidance. Here we demonstrate how a single laser can be used to localize and acquire micro-Raman signals within tissue with simultaneous real-time RCM imaging. Applications of this RCM-guided micro-Raman system for ex vivo samples and in vivo skin measurements are presented.

Assessment of treatment efficacy using surface-enhanced Raman spectroscopy analysis of urine in rats with kidney transplantation or kidney disease.

BACKGROUND: Individuals who have kidney disease or kidney transplants need routine assessment of their kidney damage and function, which are largely measured based on histological examination of kidney biopsies, blood test, and urinalysis. These methods are practically difficult or inconvenient, and expensive. The objective of this study was to develop a model to estimate the kidney damage and function by surface-enhanced Raman spectroscopy (SERS). METHODS: Urine samples were collected from two previous studies: renal allograft recipient Lewis rats receiving anti-TGF-ß antibody or control antibody treatment and obese diabetic ZSF1 rats with kidney disease fed with whole grape powder-containing chow or control chow. Silver nanoparticle-based SERS spectra of urine were measured. SERS spectra were analyzed using principal component analysis (PCA) combined with linear discriminant analysis (LDA) and partial least squires (PLS) analysis. RESULTS: PCA/LDA separated anti-TGF-ß antibody-treated group from control group with 90% sensitivity and 70% specificity in kidney transplants, and grape-fed group from controls with 72.7% sensitivity and 60% specificity in diabetic kidneys. The receiver operating characteristic curves showed that the integration area under the curve was 0.850 ± 0.095 (p = 0.008) in kidney transplant groups and 0.800 ± 0.097 (p = 0.02) in diabetic kidney groups. PLS predicted the biochemical parameters of kidney function using the SERS spectra, resulting in R2 = 0.8246 (p < 0.001,urine protein), R2 = 0.8438 (p < 0.001, urine creatinine), R2 = 0.9265 (p < 0.001, urea), R2 = 0.8719 (p < 0.001, serum creatinine), and R2 = 0.6014 (p < 0.001, urine protein to creatinine ratio). CONCLUSION: Urine SERS spectral analysis suggesting that it may become a convenient method for rapid assessment of renal impairment.

Site-specific variations in cutaneous autofluorescence revealed by excitation-emission matrix spectroscopy.

BACKGROUND AND PURPOSE: Although cutaneous autofluorescence has been utilized for evaluation of skin conditions, there is a paucity of data on normal human skin autofluorescence and its dependence on anatomical site. The objective of this study is to use excitation-emission matrix spectroscopy to quantify and characterize skin autofluorescence at different body sites. METHODS: Ten anatomical sites from 30 healthy volunteers were measured with a double-grating excitation-emission matrix spectrofluorometer. RESULTS: For the 10 body sites evaluated, there were four overall patterns of autofluorescence: skin from the head and neck exhibits high superficial and low bilayer fluorescence; the dorsal forearm and dorsal hand have both low superficial and bilayer fluorescence; the upper inner arm and back have high superficial and intermediate bilayer fluorescence; while the palm and thumbnail have both high superficial and bilayer fluorescence. The corresponding fluorescence excitation-emission peaks for these patterns were as follows: head and neck, 3 peaks at 290-300/330-350, 360-380/460-485, and 380-420/610-630 nm; dorsal forearm and dorsal hand, 2 peaks around 295-300/345-360 and 385-395/460-485 nm; upper inner arm and back, 3 peaks around 295-300/335-355, 335-340/390-410, and 375-390/455-480 nm; palm and thumbnail, 3 peaks around 285-300/345-355, 335-345/390-410, and 365-390/450-480 nm. CONCLUSION: Cutaneous fluorescence varies in distinct patterns according to anatomical site, due to the component fluorophores present, skin thickness, and the degree of melanization and long term sun exposure. These EEM patterns for normal skin should be accounted for when interpreting fluorescence signals from disease states and can also be used to guide the selection of optimal wavebands when applying this optical modality.

Label-free liquid biopsy based on blood circulating DNA detection using SERS-based nanotechnology for nasopharyngeal cancer screening.

Development of a sensitive, rapid and easy-to-use liquid biopsy method is of imperative clinical value for point-of-care caner diagnostics. Here, a label-free and modification-free nanotechnology based on surface-enhanced Raman spectroscopy (SERS) was employed for DNA analysis. Using the SERS signals of phosphate backbone as internal standard, quantitative detection for nucleobases was achieved even at single base level. The method combined with principal component analysis and linear discriminant analysis was further applied for real blood circulating DNA detection for the first time, and an ideal diagnostic sensitivity of 83.3% and specificity of 82.5% could be obtained for differentiating the nasopharyngeal cancer from the normal group, demonstrating promising potential as an alternative nanotechnology for nasopharyngeal cancer screening based on liquid biopsy.

Colorectal Cancer and Colitis Diagnosis Using Fourier Transform Infrared Spectroscopy and an Improved K-Nearest-Neighbour Classifier.

Combining Fourier transform infrared spectroscopy (FTIR) with endoscopy, it is expected that noninvasive, rapid detection of colorectal cancer can be performed in vivo in the future. In this study, Fourier transform infrared spectra were collected from 88 endoscopic biopsy colorectal tissue samples (41 colitis and 47 cancers). A new method, viz., entropy weight local-hyperplane k-nearest-neighbor (EWHK), which is an improved version of K-local hyperplane distance nearest-neighbor (HKNN), is proposed for tissue classification. In order to avoid limiting high dimensions and small values of the nearest neighbor, the new EWHK method calculates feature weights based on information entropy. The average results of the random classification showed that the EWHK classifier for differentiating cancer from colitis samples produced a sensitivity of 81.38% and a specificity of 92.69%.

Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity.

Real-time Raman spectroscopy can be used to assist in assessing skin lesions suspicious for cancer. Most of the diagnostic algorithms are based on full band of the Raman spectra, either in the fingerprint region or the high wavenumber region. In this paper we explored wavenumber selection based analysis in Raman spectroscopy for skin cancer diagnosis. Wavenumber selection was implemented using windows of wavenumber and leave-one-out cross-validated stepwise regression or least and shrinkage selection operator (LASSO). The diagnostic algorithms were then generated from the selected windows of wavenumber using multivariate statistical analyses, including principal component and general discriminate analysis (PC-GDA) and partial least squares (PLS). In total a combined cohort of 645 confirmed lesions from 573 patients encompassing skin cancers, precancers and benign skin lesions were included, which were divided into training cohort (n = 518) and testing cohort (n = 127) according to the measurement time. It was found that the area under the receiver operating characteristic curve (ROC) was improved from 0.861-0.891 to 0.891-0.911 and the diagnostic specificity for fixed sensitivity 0.99-0.90 was improved from 0.17-0.65 to 0.20-0.75 with wavenumber selection based analysis.

Accurate assessment of liver steatosis in animal models using a high throughput Raman fiber optic probe.

Due to the shortage of healthy donor organs, steatotic livers are commonly used for transplantation, placing patients at higher risk for graft dysfunction and lower survival rates. Raman Spectroscopy is a technique which has shown the ability to rapidly detect the vibration state of C-H bonds in triglycerides. The aim of this study is to determine whether conventional Raman spectroscopy can reliably detect and quantify fat in an animal model of liver steatosis. Mice and rats fed a methionine and choline-deficient (MCD) and control diets were sacrificed on one, two, three and four weeks' time points. A confocal Raman microscope, a commercial Raman (iRaman) fiber optic probe and a highly sensitive Raman fiber optic probe system, the latter utilizing a 785 nm excitation laser, were used to detect changes in the Raman spectra of steatotic mouse livers. Thin layer chromatography was used to assess the triglyceride content of liver specimens, and sections were scored blindly for fat content using histological examination. Principal component analysis (PCA) of Raman spectra was used to extract the principal components responsible for spectroscopic differences with MCD week (time on MCD diet). Confocal Raman microscopy revealed the presence of saturated fats in mice liver sections. A commercially available handheld Raman spectroscopy probe could not distinguish the presence of fat in the liver whereas our specially designed, high throughput Raman system could clearly distinguish lobe-specific changes in fat content. In the left lobe in particular, the Raman PC scores exhibited a significant correlation (R(2) = 0.96) with the gold standard, blinded scoring by histological examination. The specially designed, high throughput Raman system can be used for clinical purposes. Its application to the field of transplantation would enable surgeons to determine the hepatic fat content of the donor's liver in the field prior to proceeding with organ retrieval. Next steps include validating these results in a prospective analysis of human liver transplantation implant biopsies.

Ultrasound-mediated method for rapid delivery of nano-particles into cells for intracellular surface-enhanced Raman spectroscopy and cancer cell screening.

Surface-enhanced Raman spectroscopy (SERS) is a powerful technology for providing finger-printing information of cells. A big challenge has been the long time duration and inefficient uptake of metal nano-particles into living cells as substrate for SERS analysis. Herein, a simple method (based on ultrasound) for the rapid transfer of silver nanoparticles (NPs) into living cells for intracellular SERS spectroscopy was presented. In this study, the ultrasound-mediated method for NP delivery overcame the shortcoming of 'passive uptake', and achieved quick acquisition of reproducible SERS spectra from living human nasopharyngeal carcinoma cell lines (C666 and CNE1) and normal nasopharyngeal cell line (NP69). Tentative assignment of the Raman bands in the measured SERS spectra showed cancer cell specific biomolecular differences, including significantly lower DNA concentrations and higher protein concentrations in cancerous nasopharyngeal cells as compared to those of normal cells. Combined with PCA-LDA multivariate analysis, ultrasound-mediated cell SERS spectroscopy differentiated the cancerous cells from the normal nasopharyngeal cells with high diagnostic accuracy (98.7%), demonstrating great potential for high-throughput cancer cell screening applications.

Real-time Raman spectroscopy for automatic in vivo skin cancer detection: an independent validation.

In a recent study, we have demonstrated that real-time Raman spectroscopy could be used for skin cancer diagnosis. As a translational study, the objective of this study is to validate previous findings through a completely independent clinical test. In total, 645 confirmed cases were included in the analysis, including a cohort of 518 cases from a previous study, and an independent cohort of 127 new cases. Multi-variant statistical data analyses including principal component with general discriminant analysis (PC-GDA) and partial least squares (PLS) were used separately for lesion classification, which generated similar results. When the previous cohort (n = 518) was used as training and the new cohort (n = 127) was used as testing, the area under the receiver operating characteristic curve (ROC AUC) was found to be 0.889 (95 % CI 0.834-0.944; PLS); when the two cohorts were combined, the ROC AUC was 0.894 (95 % CI 0.870-0.918; PLS) with the narrowest confidence intervals. Both analyses were comparable to the previous findings, where the ROC AUC was 0.896 (95 % CI 0.846-0.946; PLS). The independent study validates that real-time Raman spectroscopy could be used for automatic in vivo skin cancer diagnosis with good accuracy.

Real-time visualization of melanin granules in normal human skin using combined multiphoton and reflectance confocal microscopy.

BACKGROUND: Recent advances in biomedical optics have enabled dermal and epidermal components to be visualized at subcellular resolution and assessed noninvasively. Multiphoton microscopy (MPM) and reflectance confocal microscopy (RCM) are noninvasive imaging modalities that have demonstrated promising results in imaging skin micromorphology, and which provide complementary information regarding skin components. This study assesses whether combined MPM/RCM can visualize intracellular and extracellular melanin granules in the epidermis and dermis of normal human skin. METHODS: We perform MPM and RCM imaging of in vivo and ex vivo skin in the infrared domain. The inherent three-dimensional optical sectioning capability of MPM/RCM is used to image high-contrast granular features across skin depths ranging from 50 to 90 µm. The optical images thus obtained were correlated with conventional histologic examination including melanin-specific staining of ex vivo specimens. RESULTS: MPM revealed highly fluorescent granular structures below the dermal-epidermal junction (DEJ) region. Histochemical staining also demonstrated melanin-containing granules that correlate well in size and location with the granular fluorescent structures observed in MPM. Furthermore, the MPM fluorescence excitation wavelength and RCM reflectance of cell culture-derived melanin were equivalent to those of the granules. CONCLUSION: This study suggests that MPM can noninvasively visualize and quantify subepidermal melanin in situ.

Phase and Texture Characterizations of Scar Collagen Second-Harmonic Generation Images Varied with Scar Duration.

This work developed a phase congruency algorithm combined with texture analysis to quantitatively characterize collagen morphology in second-harmonic generation (SHG) images from human scars. The extracted phase and texture parameters of the SHG images quantified collagen directionality, homogeneity, and coarseness in scars and varied with scar duration. Phase parameters showed an increasing tendency of the mean of phase congruency with scar duration, indicating that collagen fibers are better oriented over time. Texture parameters calculated from local difference local binary pattern (LD-LBP) and Haar wavelet transform, demonstrated that the LD-LBP variance decreased and the energy of all subimages increased with scar duration. It implied that collagen has a more regular pattern and becomes coarser with scar duration. In addition, the random forest regression was used to predict scar duration, demonstrating reliable performance of the extracted phase and texture parameters in characterizing collagen morphology in scar SHG images. Results indicate that the extracted parameters using the proposed method can be used as quantitative indicators to monitor scar progression with time and can help understand the mechanism of scar progression.

Characterization and application of chirped photonic crystal fiber in multiphoton imaging.

Fiber delivery of ultrashort pulses is important for multiphoton endoscopy. A chirped photonic crystal fiber (CPCF) is first characterized for its transmission bandwidth, propagation loss, and dispersion properties. Its extremely low dispersion (~150 fs(2)/m) enables the delivery of sub-30 fs pulses through a ~1 m-long CPCF. The CPCF is then incorporated into a multiphoton imaging system and its performance is demonstrated by imaging various biological samples including yew leaf, mouse tendon, and human skin. The imaging quality is further compared with images acquired by a multiphoton imaging system with free-space or hollow-core photonic band-gap fiber (PBF) delivery of pulses. Compared with free-space system, the CPCF delivered system maintains the same ultrashort pulsewidth and the image qualities are comparable. Compared with the PBF delivery, CPCF provides a 35 times shorter pulsewidth at the sample location, which results in a ~12 and 50 times improvement in two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) signals respectively. Our results show that CPCF has great potential for fiber delivery of ultrashort pulses for multiphoton endoscopy.

Label-free identification and characterization of murine hair follicle stem cells located in thin tissue sections with Raman micro-spectroscopy.

Stem cells offer tremendous opportunities for regenerative medicine. Over the past decade considerable research has taken place to identify and characterize the differentiation states of stem cells in culture. Raman micro-spectroscopy has emerged as an ideal technology since it is fast, nondestructive, and does not require potentially toxic dyes. Raman spectroscopy systems can also be incorporated into confocal microscope imaging systems allowing spectra to be obtained from below the tissue surface. Thus there is significant potential for monitoring stem cells in living tissue. Stem cells that reside in hair follicles are suitable for testing this possibility since they are close to the skin surface, and typically clustered around the bulge area. One of the first steps needed would be to obtain Raman micro-spectra from stem cells located in thin sections of tissue, and then see whether these spectra are clearly different from those of the surrounding differentiated cells. To facilitate this test, standard 5 µm thick sections of murine skin tissue were stained to identify the location of hair follicle stem cells and their progeny. Raman spectra were then obtained from adjacent cells in a subsequent unstained 10 µm thick section. The spectra revealed significant differences in peak intensities associated with nucleic acids, proteins, lipids and amino acids. Statistical analyses of the Raman micro-spectra identified stem cells with 98% sensitivity and 94% specificity, as compared with a CD34 immunostaining gold standard. Furthermore analyses of the spectral variance indicated differences in cellular dynamics between the two cell groups. This study shows that Raman micro-spectroscopy has a potential role in identifying adult follicle stem cells, laying the groundwork for future applications of hair follicle stem cells and other somatic stem cells in situ.

Improving skin cancer detection by Raman spectroscopy using convolutional neural networks and data augmentation.

Background: Our previous studies have demonstrated that Raman spectroscopy could be used for skin cancer detection with good sensitivity and specificity. The objective of this study is to determine if skin cancer detection can be further improved by combining deep neural networks and Raman spectroscopy. Patients and methods: Raman spectra of 731 skin lesions were included in this study, containing 340 cancerous and precancerous lesions (melanoma, basal cell carcinoma, squamous cell carcinoma and actinic keratosis) and 391 benign lesions (melanocytic nevus and seborrheic keratosis). One-dimensional convolutional neural networks (1D-CNN) were developed for Raman spectral classification. The stratified samples were divided randomly into training (70%), validation (10%) and test set (20%), and were repeated 56 times using parallel computing. Different data augmentation strategies were implemented for the training dataset, including added random noise, spectral shift, spectral combination and artificially synthesized Raman spectra using one-dimensional generative adversarial networks (1D-GAN). The area under the receiver operating characteristic curve (ROC AUC) was used as a measure of the diagnostic performance. Conventional machine learning approaches, including partial least squares for discriminant analysis (PLS-DA), principal component and linear discriminant analysis (PC-LDA), support vector machine (SVM), and logistic regression (LR) were evaluated for comparison with the same data splitting scheme as the 1D-CNN. Results: The ROC AUC of the test dataset based on the original training spectra were 0.886±0.022 (1D-CNN), 0.870±0.028 (PLS-DA), 0.875±0.033 (PC-LDA), 0.864±0.027 (SVM), and 0.525±0.045 (LR), which were improved to 0.909±0.021 (1D-CNN), 0.899±0.022 (PLS-DA), 0.895±0.022 (PC-LDA), 0.901±0.020 (SVM), and 0.897±0.021 (LR) respectively after augmentation of the training dataset (p<0.0001, Wilcoxon test). Paired analyses of 1D-CNN with conventional machine learning approaches showed that 1D-CNN had a 1-3% improvement (p<0.001, Wilcoxon test). Conclusions: Data augmentation not only improved the performance of both deep neural networks and conventional machine learning techniques by 2-4%, but also improved the performance of the models on spectra with higher noise or spectral shifting. Convolutional neural networks slightly outperformed conventional machine learning approaches for skin cancer detection by Raman spectroscopy.

Single source CARS-based multimodal microscopy system for biological tissue imaging [Invited].

A coherent anti-Stokes Raman scattering (CARS)-based multimodality microscopy system was developed using a single Ti:sapphire femtosecond laser source for biological imaging. It provides three complementary and co-registered imaging modalities: CARS, MPM (multiphoton microscopy), and RCM (reflectance confocal microscopy). The imaging speed is about 1 frame-per-second (fps) with a digital resolution of 1024 × 1024 pixels. This microscopy system can provide clear 2-dimensional and 3-dimensional images of ex-vivo biological tissue samples. Its spectral selection initiates vibrational excitation in lipid cells (approximately 2850 cm-1) using two filters on the pump and Stokes beam paths. The excitation can be tuned over a wide spectral range with adjustable spectral filters. The imaging capability of this CARS-based multimodal microscopy system was demonstrated using porcine fat, murine skin, and murine liver tissue samples.

Precise Serial Microregistration Enables Quantitative Microscopy Imaging Tracking of Human Skin Cells In Vivo.

We developed an automated microregistration method that enables repeated in vivo skin microscopy imaging of the same tissue microlocation and specific cells over a long period of days and weeks with unprecedented precision. Applying this method in conjunction with an in vivo multimodality multiphoton microscope, the behavior of human skin cells such as cell proliferation, melanin upward migration, blood flow dynamics, and epidermal thickness adaptation can be recorded over time, facilitating quantitative cellular dynamics analysis. We demonstrated the usefulness of this method in a skin biology study by successfully monitoring skin cellular responses for a period of two weeks following an acute exposure to ultraviolet light.

Using high frequency Raman spectra for colonic neoplasia detection.

Raman systems have tremendous potential as adjunct devices for endoscopes to improve the identification of early colon cancers. However, the traditional low frequency (LF) measurement range has several obstacles that make it challenging to develop a routine clinical tool. An alternative is to use high frequency (HF) range. To test this idea Raman spectra were obtained in both the LF and HF ranges from the same colon lesions. Multivariate analyses predicted the pathology with high sensitivity and specificity for both the LF and HF data sets. This suggests that Raman systems that measure HF spectra, and are simpler to adopt into the clinic, could be used in vivo to improve the identification of neoplastic lesions.