Multi-photon excited intensity and lifetime fluorescence images relying on endogenous contrast can be analyzed to quantify contributions from key metabolic co-enzymes and associated metabolic function and mitochondrial organization metrics. The high spatio-temporal resolution and context of these non-destructive measurements can be used to provide important insights related to a wide range of samples, conditions and disease models. Corresponding images are acquired from mitochondria, engineered tissues, excised and in vivo human tissues. Recent studies highlight the value of multi-parametric, label-free, metabolic assessments to improve our understanding of traumatic brain injury, (pre)cancer development, and vitiligo lesions.
KEYWORDS: Scattering, Tissues, Monte Carlo methods, Polarization, Laparoscopy, RGB color model, Light scattering, In vivo imaging, Visualization, Solid state lighting
Peritoneal metastases are characterized by significant disruptions in the extracellular matrix. Hence, the scattering cross sections of malignant and benign lesions and surrounding background tissues are distinct. In this work, Monte Carlo based regression was used to develop an empirical relation to extract the scattering power of tissue based on co- and cross-polarized RGB reflectance images of tissue. The empirical relation improved the sensitivity of lesion detection, and discrimination accuracy of malignant and benign lesions. The proposed empirical equation is both accurate and simple, paving the way for real-time diagnostic applications.
KEYWORDS: Laparoscopy, Yield improvement, Polarization, Collagen, Visualization, Cancer, In vivo imaging, Scattering, Monte Carlo methods, Light scattering
While white light laparoscopy (WLL) has been established as a method that yields improved detection of peritoneal metastatic lesions over radiographic imaging, its sensitivity and specificity remain sub-optimal, leading to thousands of cancer patients that are over- or under- treated every year. We present studies that establish the sensitivity of polarization enhanced (PEL) laparoscopy to changes in the cross-section and alignment of scattering centers using phantoms and report on our initial in vivo human feasibility trial. The design of our PEL probe is simple and highly compatible with current laparoscopes, the standard of patient care and the established procedure flow for WLL. It comprises of a sheath inserted on the WLL laparoscope to provide linearly polarized illumination and a modified detection optical path that allows for recording of co- and cross-polarized images relative to the incident illumination. The sum of these images is equivalent to WLL, while their difference corresponds to PEL. Using PDMS phantoms with features that contain either TiO2 and ZnO2 particles, we demonstrate the enhanced sensitivity of PEL to scattering cross-section differences. Measurements performed with collagen gels that are being stretched reveal improved sensitivity of PEL (over WLL) to collagen fiber alignment. Our initial feasibility study results support the improved diagnostic potential of PEL. In fact, a Monte Carlo-based analysis approach that utilizes the color content of the PEL images indicates that PEL yields improved contrast for detection and differentiation of benign and malignant metastatic lesions. These studies provide strong motivation for further development of PEL imaging as an approach that may improve significantly the detection of peritoneal metastatic lesions.
An experimental polarization enhanced laparoscopy (PEL) imaging system was developed to improve the visualization of peritoneal cancer lesions compared to conventional white light laparoscopy (WLL). The design modifications provide sensitivity to backscatter depolarization in tissue. Phantom studies demonstrated the sensitivity of PEL to altered scattering cross section and collagen organization. Implementation of the PEL for biopsy tissue study illustrated the feasibility and potential of PEL to improve the contrast between malignant lesions, and background tissue based on differences in their depolarization properties.
Oral cancer has a poor five-year survival rate and has not improved much in the past two decades which is due to late diagnosis. In current clinical practice analysis of Haematoxylin Eosin stained tissue biopsy is considered as a golden standard which is rather painful and routine check is not possible. In this regard, native fluorescence spectroscopy has been considered to discriminate cancer tissue based on relative alterations in the level of tryptophan. To estimate relative variations of tryptophan at different layers of tissue fluorescence polarization gating technique has been adopted which is based on the principle that the light from the superficial layer of tissue partially retain the polarization plane of incident light as they are less scattered while light from the deeper layer is completely depolarized due to multiple scattering. Integrated intensity of tryptophan was quantified, and subsequent statistical analysis has been carried out to evaluate the diagnostic potentiality of the proposed technique. It was found that the fractional variation of tryptophan in the superficial layer to the deeper layer was found to be statistically more significant in discriminating oral cancer than cumulative tryptophan in both layers.
Urinary tract infections (UTI) are one of the frequently encountered infections in clinical practice. As there are different strains of bacteria responsible for UTI, the identification of types of bacterial is necessary to administer a proper antibiotic. Conventional staining and biochemical methods for the identification of bacteria are time-consuming and it usually leads to administer patients with broad-spectrum antibiotics which are less effective and expensive. In this regard, Multiphoton fluorescence imaging based on the distribution of NADH and FAD in several bacterial species isolated from UTI is carried out. Metabolic imaging based on fluorescence enables to analyze both biochemical distribution and their conformation. Spectral deconvolution method is used to isolate fluorescence emission from the coenzymes NADH and FAD to generate redox imaging. Further, redox imaging of bacteria was analyzed using different machine learning algorithms to improve the accuracy of classification. The results of this study revealed that the proposed technique of redox imaging was found to discriminate bacterial species. As the proposed method is both effective and less time consuming, the proposed method may be considered for real-time classification of bacterial species in the clinical setup.
In vivo Native Fluorescence spectroscopic characterization of oral tissue and saliva of same group of normal, and patients with oral squamous cell carcinoma conditions were studied at 350 nm excitation. The measured fluorescence emission spectra exhibit broad emission with peaks due to NADH, FAD and Porphyrin. To resolve the emission from individual fluorophores, the measured fluorescence spectra were subjected to spectral deconvolution. Further, the variations in relative distribution, peak shifts and spectral broadening were analyzed with respect to the fluorophores, NADH, FAD, and porphyrin. The changes in the above photophysical characteristics of various native fluorophores between normal and cancer group in both tissue and saliva confirms that there is a significant molecular level changes during the transformation of normal into cancer. The extracted spectral signatures of tissues and saliva were also subjected to linear discriminant analysis and the diagnostic accuracy between tissue and saliva were compared.
Metabolic imaging of live cell may allow in understanding the molecular level changes in cells under various diseased state, including cancer. The intrinsic fluorophores, Nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) are crucial for electron transfer in the oxidation-reduction reactions in the cell. Metabolic imaging based on fluorescence polarization enables to analyze both biochemical distribution and their conformation. In this study, multiphoton fluorescence polarization imaging of NADH and FAD from cancer and normal cell lines of epithelial origin were carried out. Spectral deconvolution method was adopted to isolate fluorescence emission from different coenzymes NADH and FAD. The observed heterogeneity of the multiphoton autofluorescence in live cells was used in intensity-toconcentration image conversion. The multiphoton autofluorescence exhibits anisotropy features at the cellular level, that directly indicate the presence of NADH and FAD in two differing conformation states viz; free and protein-bound. Mapping of anisotropy of cellular autofluorescence enables to probe the distribution of population fractions of free and bound forms of NADH and FAD. Further, the redox ratio between normal and cancer cell lines confirms the changes in the metabolic activities between them. These molecular-level studies demonstrate the potential of probing cellular metabolism associated with cancer, without the need for cell destruction as in the case of conventional biochemical assays.
Fluorescence of Protein has been widely used in diagnostic oncology for characterizing cellular metabolism. However, the intensity of fluorescence emission is affected due to the absorbers and scatterers in tissue, which may lead to error in estimating exact protein content in tissue. Extraction of intrinsic fluorescence from measured fluorescence has been achieved by different methods. Among them, Monte Carlo based method yields the highest accuracy for extracting intrinsic fluorescence. In this work, we have attempted to generate a lookup table for Monte Carlo simulation of fluorescence emission by protein. Furthermore, we fitted the generated lookup table using an empirical relation. The empirical relation between measured and intrinsic fluorescence is validated using tissue phantom experiments. The proposed relation can be used for estimating intrinsic fluorescence of protein for real-time diagnostic applications and thereby improving the clinical interpretation of fluorescence spectroscopic data.
Cancer is one of the most common human threats around the world and diagnosis based on optical spectroscopy especially fluorescence technique has been established as the standard approach among scientist to explore the biochemical and morphological changes in tissues. In this regard, the present work aims to extract spectral signatures of the various fluorophores present in oral tissues using parallel factor analysis (PARAFAC). Subsequently, the statistical analysis also to be performed to show its diagnostic potential in distinguishing malignant, premalignant from normal oral tissues. Hence, the present study may lead to the possible and/or alternative tool for oral cancer diagnosis.
Cancer is one of the most common threat to human beings and it increases at an alarming level around the globe. In recent years, due to the advancements in opto-electronic technology, various optical spectroscopy techniques have emerged to assess the photophysicochemical and morphological conditions of normal and malignant tissues in micro as well as in macroscopic scale. In this regard, diffuse reflectance spectroscopy is considered to be the simplest, cost effective and rapid technique in diagnosis of cancerous tissues. In the present study, the hemoglobin concentration in normal and cancerous oral tissues was quantified and subsequent statistical analysis has been carried out to verify the diagnostic potentiality of the technique.
Diffuse reflectance spectroscopy has been widely used in diagnostic oncology and characterization of laser irradiated tissue. However, still accurate and simple analytical equation does not exist for estimation of diffuse reflectance from turbid media. In this work, a diffuse reflectance lookup table for a range of tissue optical properties was generated using Monte Carlo simulation. Based on the generated Monte Carlo lookup table, an empirical formula for diffuse reflectance was developed using surface fitting method. The variance between the Monte Carlo lookup table surface and the surface obtained from the proposed empirical formula is less than 1%. The proposed empirical formula may be used for modeling of diffuse reflectance from tissue.
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