A Coherent Anti-Stokes Raman Scattering (CARS) microendoscope probe for early stage label-free prostate cancer diagnosis at single cell resolution is presented. The handheld CARS microendoscope probe includes a customized micro-electromechanical systems (MEMS) scanning mirror as well as miniature optical and mechanical components. In our design, the excitation laser (pump and stokes beams) from the fiber is collimated, reflected by the reflecting mirror, and transmitted via a 2D MEMS scanning mirror and a micro-objective system onto the sample; emission in the epi-direction is returned through the micro-objective lens, MEMS and reflecting mirror, and collimation system, and finally the emission signal is collected by a photomultiplier tube (PMT). The exit pupil diameter of the collimator system is designed to match the diameter of the MEMS mirror and the entrance pupil diameter of the micro-objective system. The back aperture diameter of the micro-objective system is designed according to the largest MEMS scanning angle and the distance between the MEMS mirror and the back aperture. To increase the numerical aperture (NA) of the micro-objective system in order to enhance the signal collection efficiency, the back aperture diameter of the micro-objective system is enlarged with an upfront achromatic wide angle Keplerian telescope beam expander. The integration of a miniaturized micro-optics probe with optical fiber CARS microscopy opens up the possibility of in vivo molecular imaging for cancer diagnosis and surgical intervention.
Label-free multiphoton imaging is promising for replacing biopsy and could offer new strategies for intraoperative or surgical applications. Coherent anti-Stokes Raman scattering (CARS) imaging could provide lipid-band contrast, and second harmonic generation (SHG) imaging is useful for imaging collagen, tendon and muscle fibers. A combination of these two imaging modalities could provide rich information and this combination has been studied by researchers to investigate diseases through microscopy imaging. The combination of these two imaging modalities in endomicroscopy imaging has been rarely investigated. In this research, a fiber bundle consisted of one excitation fiber and 18 collection fibers was developed in our endomicroscopy prototype. The 18 collection fibers were divided into two collection channels with 9 fibers in each channel. These two channels could be used together as one channel for effective signal collection or used separately for simplifying detection part of the system. Differences of collection pattern of these two channels were investigated. Collection difference of central excitation fiber and surrounding 18 fibers was also investigated, which reveals the potential ability of this system to measure forward to backward (F/B) ratio in SHG imaging. CARS imaging of mouse adipocyte and SHG imaging of mouse tail tendon were performed to demonstrate the CARS and SHG tissue imaging performance of this system. Simultaneous CARS and SHG imaging ability of this system was demonstrated by mouse tail imaging. This fiber bundle based endomicroscopy imaging prototype, offers a promising platform for constructing efficient fiber-based CARS and SHG multimodal endomicroscopes for label free intraoperative imaging applications.
Fluorescence microendoscopy can potentially be a powerful modality in minimally invasive percutaneous intervention for cancer diagnosis because it has an exceptional ability to provide micron-scale resolution images in tissues inaccessible to traditional microscopy. After targeting the tumor with guidance by macroscopic images such as computed tomorgraphy or magnetic resonance imaging, fluorescence microendoscopy can help select the biopsy spots or perform an on-site molecular imaging diagnosis. However, one challenge of this technique for percutaneous lung intervention is that the respiratory and hemokinesis motion often renders instability of the sequential image visualization and results in inaccurate quantitative measurement. Motion correction on such serial microscopy image sequences is, therefore, an important post-processing step. We propose a nonlinear motion compensation algorithm using a cubature Kalman filter (NMC-CKF) to correct these periodic spatial and intensity changes, and validate the algorithm using preclinical imaging experiments. The algorithm integrates a longitudinal nonlinear system model using the CKF in the serial image registration algorithm for robust estimation of the longitudinal movements. Experiments were carried out using simulated and real microendoscopy videos captured from the CellVizio 660 system in rabbit VX2 cancer intervention. The results show that the NMC-CKF algorithm yields more robust and accurate alignment results.
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.
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