The development of real-time, label-free imaging techniques has recently attracted research interest for in situ differentiation of cancerous lesions from normal tissues. Molecule-specific intrinsic contrast can arise from label-free imaging techniques such as Coherent Anti-Stokes Raman Scattering (CARS), Two-Photon Excited AutoFluorescence (TPEAF), and Second Harmonic Generation (SHG), which, in combination, would hold the promise of a powerful label-free tool for cancer diagnosis. Among cancer-related deaths, lung carcinoma is the leading cause for both sexes. Although early treatment can increase the survival rate dramatically, lesion detection and precise diagnosis at an early stage is unusual due to its asymptomatic nature and limitations of current diagnostic techniques that make screening difficult. We investigated the potential of using multimodality nonlinear optical microscopy that incorporates CARS, TPEAF, and SHG techniques for differentiation of lung cancer from normal tissue. Cancerous and non-cancerous lung tissue samples from patients were imaged using CARS, TPEAF, and SHG techniques for comparison. These images showed good pathology correlation with hematoxylin and eosin (H and E) stained sections from the same tissue samples. Ongoing work includes imaging at various penetration depths to show three-dimensional morphologies of tumor cell nuclei using CARS, elastin using TPEAF, and collagen using SHG and developing classification algorithms for quantitative feature extraction to enable lung cancer diagnosis. Our results indicate that via real-time morphology analyses, a multimodality nonlinear optical imaging platform potentially offers a powerful minimally-invasive way to differentiate cancer lesions from surrounding non-tumor tissues in vivo for clinical applications.
The ability to visualize cellular structures and tissue molecular signatures in a live body could revolutionize the practice
of surgery. Specifically, such technology is promising for replacing tissue extraction biopsy and offering new strategies
for a broad range of intraoperative or surgical applications, including early cancer detection, tumor margin identification,
nerve damage avoidance, and surgical outcomes enhancement. Coherent anti-Stokes Raman scattering (CARS)
microendoscopy offers a way to achieve this with label-free imaging capability and sub-cellular resolution. However,
efficient collection of epi-CARS signals and reduction of nonlinear effects in fibers are two major challenges
encountered in the development of fiber-based CARS microendoscopy. To circumvent this problem, we designed and
developed a fiber bundle for a CARS microendoscopy prototype. The excitation lasers were delivered by a single
multimode fiber at the center of the bundle while the epi-CARS signals were collected by multiple MMFs surrounding
the central fiber. A polarization scheme was employed to suppress the four-wave mixing (FWM) effect in the excitation
fiber. Our experimental results suggest that, with this fiber bundle and the polarization FWM-suppressing scheme, the
signal-to-noise ratio of the CARS images was greatly enhanced through a combination of high collection efficiency of
epi-CARS signals, isolation of excitation lasers, and suppression of FWM. Tissue imaging capability of the
microendoscopy prototype was demonstrated by ex vivo imaging on mouse skin and lung tissues. This fiber bundle-based
CARS microendoscopy prototype, with the polarization FWM-suppressing scheme, offers a promising platform
for constructing efficient fiber-based CARS microendoscopes for label free intraoperative imaging applications.
The advent of molecularly targeted therapies requires effective identification of the various cell types of non-small cell lung carcinomas (NSCLC). Currently, cell type diagnosis is performed using small biopsies or cytology specimens that are often insufficient for molecular testing after morphologic analysis. Thus, the ability to rapidly recognize different cancer cell types, with minimal tissue consumption, would accelerate diagnosis and preserve tissue samples for subsequent molecular testing in targeted therapy. We report a label-free molecular vibrational imaging framework enabling three-dimensional (3-D) image acquisition and quantitative analysis of cellular structures for identification of NSCLC cell types. This diagnostic imaging system employs superpixel-based 3-D nuclear segmentation for extracting such disease-related features as nuclear shape, volume, and cell-cell distance. These features are used to characterize cancer cell types using machine learning. Using fresh unstained tissue samples derived from cell lines grown in a mouse model, the platform showed greater than 97% accuracy for diagnosis of NSCLC cell types within a few minutes. As an adjunct to subsequent histology tests, our novel system would allow fast delineation of cancer cell types with minimum tissue consumption, potentially facilitating on-the-spot diagnosis, while preserving specimens for additional tests. Furthermore, 3-D measurements of cellular structure permit evaluation closer to the native state of cells, creating an alternative to traditional 2-D histology specimen evaluation, potentially increasing accuracy in diagnosing cell type of lung carcinomas.
We report the development and application of a knowledge-based coherent anti-Stokes Raman scattering (CARS) microscopy system for label-free imaging, pattern recognition, and classification of cells and tissue structures for differentiating lung cancer from non-neoplastic lung tissues and identifying lung cancer subtypes. A total of 1014 CARS images were acquired from 92 fresh frozen lung tissue samples. The established pathological workup and diagnostic cellular were used as prior knowledge for establishment of a knowledge-based CARS system using a machine learning approach. This system functions to separate normal, non-neoplastic, and subtypes of lung cancer tissues based on extracted quantitative features describing fibrils and cell morphology. The knowledge-based CARS system showed the ability to distinguish lung cancer from normal and non-neoplastic lung tissue with 91% sensitivity and 92% specificity. Small cell carcinomas were distinguished from nonsmall cell carcinomas with 100% sensitivity and specificity. As an adjunct to submitting tissue samples to routine pathology, our novel system recognizes the patterns of fibril and cell morphology, enabling medical practitioners to perform differential diagnosis of lung lesions in mere minutes. The demonstration of the strategy is also a necessary step toward in vivo point-of-care diagnosis of precancerous and cancerous lung lesions with a fiber-based CARS microendoscope.
Lung carcinoma is the most prevalent type of cancer in the world, and it is responsible for more deaths than other types
of cancer. During diagnosis, a pathologist primarily aims to differentiate small cell carcinoma from non-small cell
carcinoma on biopsy and cytology specimens, which is time consuming due to the time required for tissue processing
and staining. To speed up the diagnostic process, we investigated the feasibility of using coherent anti-Stokes Raman
scattering (CARS) microscopy as a label-free strategy to image lung lesions and differentiate subtypes of lung cancers.
Different mouse lung cancer models were developed by injecting human lung cancer cell lines, including
adenocarcinoma, squamous cell carcinoma, and small cell carcinoma, into lungs of the nude mice. CARS images were
acquired from normal lung tissues and different subtypes of cancer lesions ex vivo using intrinsic contrasts from
symmetric CH2 bonds. These images showed good correlation with the hematoxylin and eosin (H&E) stained sections
from the same tissue samples with regard to cell size, density, and cell-cell distance. These features are routinely used in
diagnosing lung lesions. Our results showed that the CARS technique is capable of providing a visualizable platform to
differentiate different kinds of lung cancers using the same pathological features without histological staining and thus
has the potential to serve as a more efficient examination tool for diagnostic pathology. In addition, incorporating with
suitable fiber-optic probes would render the CARS technique as a promising approach for in vivo diagnosis of lung
cancer.
Breast cancer is a common disease in women. Current imaging and diagnostic methods for breast cancer confront several
limitations, like time-consuming, invasive and with a high cost. Alternative strategies are in high demand to alleviate
patients' trauma and lower medical expenses. Coherent anti-Stokes Raman scattering (CARS) imaging technique offers
many advantages, including label-free, sub-wavelength spatial resolution and video-rate imaging speed. Therefore, it has
been demonstrated as a powerful tool for various biomedical applications. In this study, we present a label-free fast
imaging method to identify breast cancer and its subtypes using CARS microscopy. Human breast tissues, including
normal, benign and invasive carcinomas, were imaged ex vivo using a custom-built CARS microscope. Compared with
results from corresponding hematoxylin and eosin (H&E) stains, the CARS technique has demonstrated its capability in
identifying morphological features in a similar way as in H&E stain. These features can be used to distinguish breast
cancer from normal and benign tissues, and further separate cancer subtypes from each other. Our pilot study suggests
that CARS microscopy could be used as a routine examination tool to characterize breast cancer ex vivo. Moreover, its
label-free and fast imaging properties render this technique as a promising approach for in vivo and real-time imaging
and diagnosis of breast cancer.
Ionic self-assembled multilayers (ISAMs) adsorbed on long period fiber gratings (LPGs) can serve as an inexpensive,
robust, portable, biosensor platform. The ISAM technique is a layer-by-layer deposition technique that creates thin films
on the nanoscale level. The combination of ISAMs with LPGs yields exceptional sensitivity of the optical fiber
transmission spectrum. We have shown theoretically that the resonant wavelength shift for a thin-film coated LPG can
be caused by the variation of the film's refractive index and/or the variation of the thickness of the film. We have
experimentally demonstrated that the deposition of nm-thick ISAM films on LPGs induces shifts in the resonant
wavelength of > 1.6 nm per nm of thin film. It has also been shown that the sensitivity of the LPG to the thickness of the
ISAM film increases with increased film thickness. We have further demonstrated that ISAM-coated LPGs can function
effectively as biosensors by using the biotin-streptavidin system and by using the Bacillus anthracis (Anthrax) antibody-
PA (Protective Antigen) system. Experiments have been successfully performed in both air and solution, which
illustrates the versatility of the biosensor. The results confirm that ISAM-LPGs yield a reusable, thermally-stable, and
robust platform for designing and building efficient optical biosensors.
We have shown that ionic self-assembled multilayers (ISAMs) deposited on optical fiber long period gratings (LPGs) yield dramatic resonant-wavelength shifts, even with nanometer-thick films. Precise control of the refractive index and the thickness of these films was achieved by altering the relative fraction of the anionic and cationic materials combined with layer-by-layer deposition. We demonstrate the feasibility of this highly controllable deposition-technique for fine-tuning grating properties for grating applications. In addition, we confirm theoretically that the resonant wavelength shift can result from either the variation of the thickness of the film and/or the variation of its refractive index. Finally, we demonstrate that ISAMs adsorbed on LPGs function effectively as biosensors. These simulations and experimental results confirm that ISAM-coated-LPGs provide a thermally-stable, reusable, robust, and attractive platform for building efficient fiber optic sensors and devices.
A novel fiber optic pressure sensor system with self-compensation capability for harsh environment applications is reported. The system compensates for the fluctuation of source power and the variation of fiber losses by self-referencing the two channel outputs of a fiber optic extrinsic Fabry-Pérot interfrometric (EFPI) sensor probe. A novel sensor fabrication system based on the controlled thermal bonding method is also described. For the first time, high-performance fiber optic EFPI sensor probes can be fabricated in a controlled fashion with excellent mechanical strength and temperature stability to survive and operate in the high-pressure and high-temperature coexisting harsh environment. Using a single-mode fiber sensor probe and the prototype signal-processing unit, we demonstrate pressure measurement up to 8400 psi and achieved resolution of 0.005% (2=0.4 psi) at atmospheric pressure, repeatability of ±0.15% (±13 psi), and 25-h stability of 0.09% (7 psi). The system also shows excellent remote operation capability when tested by separating the sensor probe from its signal-processing unit at a distance of 6.4 km.
Detailed studies on fiber optic pressure and temperature sensors for oil down-hole applications are described in this paper. The sensor head is an interferometric based fiber optic senor in which the air-gap will change with the pressure or temperature. For high-speed applications, a novel self-calibrating interferometric/intensity-based (SCIIB) scheme, which realizes compensations for both the light source drift and the fiber loss variation, was used to demodulate the pressure (or temperature) signals. An improved white light system was developed for sensor fabrication. This system is also used as the signal demodulation system providing very high resolution. Experiment results show that the SCIIB system achieves 0.1% accuracy with a 0-8000psi working range for the pressure sensor and a 0-600 degree(s)C working range for the temperature sensor. The resolution of the white light system is about +/- 0.5 nm with a dynamic range up to 10 micrometers. The long -term testing results in the oil site are also presented in this paper.
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