High-speed forward-viewing optical coherence tomography probe based on Lissajous sampling and sparse reconstruction.

We present a novel endoscopy probe using optical coherence tomography (OCT) that combines sparse Lissajous scanning and compressed sensing (CS) for faster data collection. This compact probe is only 4 mm in diameter and achieves a large field of view (FOV) of 2.25 mm2 and a 10 mm working distance. Unlike traditional OCT systems that use bulky raster scanning, our design features a dual-axis piezoelectric mechanism for efficient Lissajous pattern scanning. It employs compressive data reconstruction algorithms that minimize data collection requirements for efficient, high-speed imaging. This approach significantly enhances imaging speed by over 40%, substantially improving miniaturization and performance for endoscopic applications.

Rapid hyperspectral photothermal mid-infrared spectroscopic imaging from sparse data for gynecologic cancer tissue subtyping.

Ovarian cancer detection has traditionally relied on a multi-step process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. Our method significantly accelerates data collection by capturing a combination of highresolution and interleaved, lower-resolution infrared band images and applying computational techniques for data interpolation. We effectively minimize data collection requirements by leveraging sparse data acquisition and employing curvelet-based reconstruction algorithms. This approach enhances imaging speed without compromising image quality and ensures robust tissue segmentation. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled datasets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology. It represents a significant leap forward from traditional histopathological methods, offering profound implications for cancer diagnostics and treatment decision-making.

Leveraging mid-infrared spectroscopic imaging and deep learning for tissue subtype classification in ovarian cancer.

Mid-infrared spectroscopic imaging (MIRSI) is an emerging class of label-free techniques being leveraged for digital histopathology. Modern histopathologic identification of ovarian cancer involves tissue staining followed by morphological pattern recognition. This process is time-consuming and subjective and requires extensive expertise. This paper presents the first label-free, quantitative, and automated histological recognition of ovarian tissue subtypes using a new MIRSI technique. This optical photothermal infrared (O-PTIR) imaging technique provides a 10× enhancement in spatial resolution relative to prior instruments. It enables sub-cellular spectroscopic investigation of tissue at biochemically important fingerprint wavelengths. We demonstrate that the enhanced resolution of sub-cellular features, combined with spectroscopic information, enables reliable classification of ovarian cell subtypes achieving a classification accuracy of 0.98. Moreover, we present a statistically robust analysis from 78 patient samples with over 60 million data points. We show that sub-cellular resolution from five wavenumbers is sufficient to outperform state-of-the-art diffraction-limited techniques with up to 235 wavenumbers. We also propose two quantitative biomarkers based on the relative quantities of epithelia and stroma that exhibit efficacy in early cancer diagnosis. This paper demonstrates that combining deep learning with intrinsic biochemical MIRSI measurements enables quantitative evaluation of cancerous tissue, improving the rigor and reproducibility of histopathology.

Polarization Sensitive Photothermal Mid-Infrared Spectroscopic Imaging of Human Bone Marrow Tissue.

Collagen quantity and integrity play an important role in understanding diseases such as myelofibrosis (MF). Label-free mid-infrared spectroscopic imaging (MIRSI) has the potential to quantify collagen while minimizing the subjective variance observed with conventional histopathology. Infrared (IR) spectroscopy with polarization sensitivity provides chemical information while also estimating tissue dichroism. This can potentially aid MF grading by revealing the structure and orientation of collagen fibers. Simultaneous measurement of collagen structure and biochemical properties can translate clinically into improved diagnosis and enhance our understanding of disease progression. In this paper, we present the first report of polarization-dependent spectroscopic variations in collagen from human bone marrow samples. We build on prior work with animal models and extend it to human clinical biopsies with a practical method for high-resolution chemical and structural imaging of bone marrow on clinical glass slides. This is done using a new polarization-sensitive photothermal mid-infrared spectroscopic imaging scheme that enables sample and source independent polarization control. This technology provides 0.5 µm spatial resolution, enabling the identification of thin (≈1 µm) collagen fibers that were not separable using Fourier Transform Infrared (FT-IR) imaging in the fingerprint region at diffraction-limited resolution ( ≈ 5 µm). Finally, we propose quantitative metrics to identify fiber orientation from discrete band images (amide I and amide II) measured under three polarizations. Previous studies have used a pair of orthogonal polarization measurements, which is insufficient for clinical samples since human bone biopsies contain collagen fibers with multiple orientations. Here, we address this challenge and demonstrate that three polarization measurements are necessary to resolve orientation ambiguity in clinical bone marrow samples. This is also the first study to demonstrate the ability to spectroscopically identify thin collagen fibers (≈1 µm diameter) and their orientations, which is critical for accurate grading of human bone marrow fibrosis.

Feasibility and Safety of Tethered Capsule Endomicroscopy in Patients With Barrett's Esophagus in a Multi-Center Study.

BACKGROUND & AIMS: Tethered capsule endomicroscopy (TCE) involves swallowing a small tethered pill that implements optical coherence tomography (OCT) imaging, procuring high resolution images of the whole esophagus. Here, we demonstrate and evaluate the feasibility and safety of TCE and a portable OCT imaging system in patients with Barrett's esophagus (BE) in a multi-center (5-site) clinical study. METHODS: Untreated patients with BE as per endoscopic biopsy diagnosis were eligible to participate in the study. TCE procedures were performed in unsedated patients by either doctors or nurses. After the capsule was swallowed, the device continuously obtained 10-µm-resolution cross-sectional images as it traversed the esophagus. Following imaging, the device was withdrawn through mouth, and disinfected for subsequent reuse. BE lengths were compared to endoscopy findings when available. OCT-TCE images were compared to volumetric laser endomicroscopy (VLE) images from a patient who had undergone VLE on the same day as TCE. RESULTS: 147 patients with BE were enrolled across all sites. 116 swallowed the capsule (79%), 95/114 (83.3%) men and 21/33 (63.6%) women (P = .01). High-quality OCT images were obtained in 104/111 swallowers (93.7%) who completed the procedure. The average imaging duration was 5.55 ± 1.92 minutes. The mean length of esophagus imaged per patient was 21.69 ± 5.90 cm. A blinded comparison of maximum extent of BE measured by OCT-TCE and EGD showed a strong correlation (r = 0.77-0.79). OCT-TCE images were of similar quality to those obtained by OCT-VLE. CONCLUSIONS: The capabilities of TCE to be used across multiple sites, be administered to unsedated patients by either physicians or nurses who are not expert in OCT-TCE, and to rapidly and safely evaluate the microscopic structure of the esophagus make it an emerging tool for screening and surveillance of BE patients. Clinical trial registry website and trial number: NCT02994693 and NCT03459339.

Multi-modal image sharpening in fourier transform infrared (FTIR) microscopy.

Mid-infrared Spectroscopic Imaging (MIRSI) provides spatially-resolved molecular specificity by measuring wavelength-dependent mid-infrared absorbance. Infrared microscopes use large numerical aperture objectives to obtain high-resolution images of heterogeneous samples. However, the optical resolution is fundamentally diffraction-limited, and therefore wavelength-dependent. This significantly limits resolution in infrared microscopy, which relies on long wavelengths (2.5 µm to 12.5 µm) for molecular specificity. The resolution is particularly restrictive in biomedical and materials applications, where molecular information is encoded in the fingerprint region (6 µm to 12 µm), limiting the maximum resolving power to between 3 µm and 6 µm. We present an unsupervised curvelet-based image fusion method that overcomes limitations in spatial resolution by augmenting infrared images with label-free visible microscopy. We demonstrate the effectiveness of this approach by fusing images of breast and ovarian tumor biopsies acquired using both infrared and dark-field microscopy. The proposed fusion algorithm generates a hyperspectral dataset that has both high spatial resolution and good molecular contrast. We validate this technique using multiple standard approaches and through comparisons to super-resolved experimentally measured photothermal spectroscopic images. We also propose a novel comparison method based on tissue classification accuracy.

Optical coherence tomography-guided laser marking with tethered capsule endomicroscopy in unsedated patients.

Tethered capsule endomicroscopy (TCE) is an emerging screening technology that comprehensively obtains microstructural OCT images of the gastrointestinal (GI) tract in unsedated patients. To advance clinical adoption of this imaging technique, it will be important to validate TCE images with co-localized histology, the current diagnostic gold standard. One method for co-localizing OCT images with histology is image-targeted laser marking, which has previously been implemented using a driveshaft-based, balloon OCT catheter, deployed during endoscopy. In this paper, we present a TCE device that scans and targets the imaging beam using a low-cost stepper motor that is integrated inside the capsule. In combination with a 4-laser-diode, high power 1430/1450 nm marking laser system (800 mW on the sample and 1s pulse duration), this technology generated clearly visible marks, with a spatial targeting accuracy of better than 0.5 mm. A laser safety study was done on swine esophagus ex vivo, showing that these exposure parameters did not alter the submucosa, with a large, 4-5x safety margin. The technology was demonstrated in living human subjects and shown to be effective for co-localizing OCT TCE images to biopsies obtained during subsequent endoscopy.

Measuring efficiency of community health centers: a multi-model approach considering quality of care and heterogeneous operating environments.

Over 1300 federally-qualified health centers (FQHCs) in the US provide care to vulnerable populations in different contexts, addressing diverse patient health and socioeconomic characteristics. In this study, we use data envelopment analysis (DEA) to measure FQHC performance, applying several techniques to account for both quality of outputs and heterogeneity among FQHC operating environments. To address quality, we examine two formulations, the Two-Model DEA approach of Shimshak and Lenard (denoted S/L), and a variant of the Quality-Adjusted DEA approach of Sherman and Zhou (denoted S/Z). To mitigate the aforementioned heterogeneities, a data science approach utilizing latent class analysis (LCA) is conducted on a set of metrics not included in the DEA, to identify latent typologies of FQHCs. Each DEA quality approach is applied in both an aggregated (including all FQHCs in a single DEA model) and a partitioned case (solving a DEA model for each latent class, such that an FQHC is compared only to its peer group). We find that the efficient frontier for the aggregated S/L approach disproportionately included smaller FQHCs, whereas the aggregated S/Z approach's reference set included many larger FQHCs. The partitioned cases found that both the S/L and S/Z aggregated models disproportionately disfavored (different) members of certain classes with respect to efficiency scores. Based on these results, we provide general insights into the trade-offs of using these two models in conjunction with a clustering approach such as LCA.

In-line optical fiber metallic mirror reflector for monolithic common path optical coherence tomography probes.

BACKGROUND AND OBJECTIVES: Endoscopic optical coherence tomography probes suffer from various artifacts due to dispersion imbalance and polarization mismatch between reference and sample arm light. Such artifacts can be minimized using a common path approach. In this work, we demonstrate a miniaturized common path probe for optical coherence tomography using an inline fiber mirror. MATERIALS AND METHODS: A common path optical fiber probe suitable for performing high-resolution endoscopic optical coherence tomography imaging was developed. To achieve common path functionality, an inline fiber mirror was fabricated using a thin gold layer. A commercially available swept source engine was used to test the designed probe in a cadaver human coronary artery ex vivo. RESULTS: We achieved a sensitivity of 104 dB for this probe using a swept source optical coherence tomography system. To test the probe, images of a cadaver human coronary artery were obtained, demonstrating the quality that is comparable to those obtained by OCT systems with separate reference arms. Additionally, we demonstrate recovery of ranging depth by use of a Michelson interferometer in the detection path. CONCLUSION: We developed a miniaturized monolithic inline fiber mirror-based common path probe for optical coherence tomography. Owing to its simplicity, our design will be helpful in endoscopic applications that require high-resolution probes in a compact form factor while reducing system complexity. Lasers Surg. Med. 50:230-235, 2018. © 2017 Wiley Periodicals, Inc.

A Novel Approach for the Retrieval of Broken Catheter Fragment - Using Balloon Dilatation Technique.

In this era of an ever increasing number of interventions in cardiology, there is a parallel increase in the number of complications associated with these interventions, such as broken catheter tip and guide wire embolisation. The most commonly used and effective method for the percutaneous retrieval of such broken fragments is a goose neck snare. However in cases where this technique has been a failure, newer and novel innovations have been implemented for the retrieval of such broken fragments. We present a case of seven-year-old female child with a 3mm peri-membranous ventricular septal defect who was taken up for device closure. During the procedure the internal mammary catheter was broken in the left ventricle and subsequently the broken fragment was embolised to the left common carotid artery. The broken fragment was snared down upto the common iliac but could not be retrieved out of the sheath. A novel approach was used, consisting of negotiating a coronary guide wire across the broken catheter and inflating a balloon in the catheter fragment which helped to achieve a co-axial alignment with the arterial sheath and hence by which it was possible to retrieve the broken catheter fragment out of the circulatory system.

Development of a practical spatial-spectral analysis protocol for breast histopathology using Fourier transform infrared spectroscopic imaging.

Breast cancer screening provides sensitive tumor identification, but low specificity implies that a vast majority of biopsies are not ultimately diagnosed as cancer. Automated techniques to evaluate biopsies can prevent errors, reduce pathologist workload and provide objective analysis. Fourier transform infrared (FT-IR) spectroscopic imaging provides both molecular signatures and spatial information that may be applicable for pathology. Here, we utilize both the spectral and spatial information to develop a combined classifier that provides rapid tissue assessment. First, we evaluated the potential of IR imaging to provide a diagnosis using spectral data alone. While highly accurate histologic [epithelium, stroma] recognition could be achieved, the same was not possible for disease [cancer, no-cancer] due to the diversity of spectral signals. Hence, we employed spatial data, developing and evaluating increasingly complex models, to detect cancers. Sub-mm tumors could be very confidently predicted as indicated by the quantitative measurement of accuracy via receiver operating characteristic (ROC) curve analyses. The developed protocol was validated with a small set and statistical performance used to develop a model that predicts study design for a large scale, definitive validation. The results of evaluation on different instruments, at higher noise levels, under a coarser spectral resolution and two sampling modes [transmission and transflection], indicate that the protocol is highly accurate under a variety of conditions. The study paves the way to validating IR imaging for rapid breast tumor detection, its statistical validation and potential directions for optimization of the speed and sampling for clinical deployment.

µOCT imaging using depth of focus extension by self-imaging wavefront division in a common-path fiber optic probe.

Optical coherence tomography (OCT) is an attractive medical modality due to its ability to acquire high-resolution, cross-sectional images inside the body using flexible, small-diameter, scanning fiber optic probes. Conventional, cross-sectional OCT imaging technologies have approximately 10-µm axial resolution and 30-µm lateral resolution, specifications that enable the visualization of microscopic architectural morphology. While this resolution is useful for many clinical applications, it is insufficient for resolving individual cells that characterize many diseases. To address this gap, a supercontinuum-laser-based, µm-resolution OCT (µOCT) system and a 500 µm-diameter, extended depth of focus single fiber optic probe for endoscopic and intravascular imaging were designed and fabricated. At the distal tip of the fiber optic probe, a cylindrical waveguide was used to divide the wavefront to provide multiple circular propagation modes. Once transmitted through a relatively high NA lens (NA >0.1), these modes were projected as multiple coaxial foci (~3 µm full width at half maximum (FWHM)) over a greatly extended focal depth range. The distal tip of the probe also contained a common-path reference reflectance to minimize polarization and dispersion imbalances between sample and reference arm light. Measurements showed that the probe provides a 20-fold depth of focus extension, maintaining a 3-5 µm lateral resolution (FWHM of PSF) and a 2 µm axial resolution over a depth range of approximately 1 mm. These results suggest that this new optical configuration will be useful for achieving high-resolution, cross-sectional OCT imaging in catheter/endoscope-based medical imaging devices.

Compositional prior information in computed infrared spectroscopic imaging.

Compositional prior information is used to bridge a gap in the theory between optical coherence tomography (OCT), which provides high-resolution structural images by neglecting spectral variation, and imaging spectroscopy, which provides only spectral information without significant regard to structure. A constraint is proposed in which it is assumed that a sample is composed of N distinct materials with known spectra, allowing the structural and spectral composition of the sample to be determined with a number of measurements on the order of N. We present a forward model for a sample with heterogeneities along the optical axis and show through simulation that the N-species constraint allows unambiguous inversion of Fourier transform interferometric data within the spatial frequency passband of the optical system. We then explore the stability and limitations of this model and extend it to a general 3D heterogeneous sample.

High-definition infrared spectroscopic imaging.

The quality of images from an infrared (IR) microscope has traditionally been limited by considerations of throughput and signal-to-noise ratio (SNR). An understanding of the achievable quality as a function of instrument parameters, from first principals is needed for improved instrument design. Here, we first present a model for light propagation through an IR spectroscopic imaging system based on scalar wave theory. The model analytically describes the propagation of light along the entire beam path from the source to the detector. The effect of various optical elements and the sample in the microscope is understood in terms of the accessible spatial frequencies by using a Fourier optics approach and simulations are conducted to gain insights into spectroscopic image formation. The optimal pixel size at the sample plane is calculated and shown much smaller than that in current mid-IR microscopy systems. A commercial imaging system is modified, and experimental data are presented to demonstrate the validity of the developed model. Building on this validated theoretical foundation, an optimal sampling configuration is set up. Acquired data were of high spatial quality but, as expected, of poorer SNR. Signal processing approaches were implemented to improve the spectral SNR. The resulting data demonstrated the ability to perform high-definition IR imaging in the laboratory by using minimally-modified commercial instruments.

Discrete frequency infrared microspectroscopy and imaging with a tunable quantum cascade laser.

Fourier-transform infrared (FT-IR) imaging is a well-established modality but requires the acquisition of a spectrum over a large bandwidth, even in cases where only a few spectral features may be of interest. Discrete frequency infrared (DF-IR) methods are now emerging in which a small number of measurements may provide all the analytical information needed. The DF-IR approach is enabled by the development of new sources integrating frequency selection, in particular of tunable, narrow-bandwidth sources with enough power at each wavelength to successfully make absorption measurements. Here, we describe a DF-IR imaging microscope that uses an external cavity quantum cascade laser (QCL) as a source. We present two configurations, one with an uncooled bolometer as a detector and another with a liquid nitrogen cooled mercury cadmium telluride (MCT) detector and compare their performance to a commercial FT-IR imaging instrument. We examine the consequences of the coherent properties of the beam with respect to imaging and compare these observations to simulations. Additionally, we demonstrate that the use of a tunable laser source represents a distinct advantage over broadband sources when using a small aperture (narrower than the wavelength of light) to perform high-quality point mapping. The two advances highlight the potential application areas for these emerging sources in IR microscopy and imaging.

Analysis of variance in spectroscopic imaging data from human tissues.

The analysis of cell types and disease using Fourier transform infrared (FT-IR) spectroscopic imaging is promising. The approach lacks an appreciation of the limits of performance for the technology, however, which limits both researcher efforts in improving the approach and acceptance by practitioners. One factor limiting performance is the variance in data arising from biological diversity, measurement noise or from other sources. Here we identify the sources of variation by first employing a high throughout sampling platform of tissue microarrays (TMAs) to record a sufficiently large and diverse set data. Next, a comprehensive set of analysis of variance (ANOVA) models is employed to analyze the data. Estimating the portions of explained variation, we quantify the primary sources of variation, find the most discriminating spectral metrics, and recognize the aspects of the technology to improve. The study provides a framework for the development of protocols for clinical translation and provides guidelines to design statistically valid studies in the spectroscopic analysis of tissue.

Accurate histopathology from low signal-to-noise ratio spectroscopic imaging data.

Fourier Transform Infrared (FT-IR) spectroscopic imaging is emerging as an automated alternative to human examination in studying development and disease in tissue. The technology's speed and accuracy, however, are limited by the trade-off with signal-to-noise ratio (SNR). Signal processing approaches to reduce noise have been suggested but often involve manual decisions, compromising the automation benefits of using spectroscopic imaging for tissue analysis. In this manuscript, we describe an approach that utilizes the spatial information in the data set to select parameters for noise reduction without human input. Specifically, we expand on the Minimum Noise Fraction (MNF) approach in which data are forward transformed, eigenimages that correspond mostly to signal selected and used in inverse transformation. Our unsupervised eigenimage selection method consists of matching spatial features in eigenimages with a low-noise gold standard derived from the data. An order of magnitude reduction in noise is demonstrated using this approach. We apply the approach to automating breast tissue histology, in which accuracy in classification of tissue into different cell types is shown to strongly depend on the SNR of data. A high classification accuracy was recovered with acquired data that was ∼10-fold lower SNR. The results imply that a reduction of almost two orders of magnitude in acquisition time is routinely possible for automated tissue classifications by using post-acquisition noise reduction.

Dark field Raman microscopy.

Confocal Raman microscopy is often used for optical sectioning but is problematic when the sample plane of interest has a weak Raman cross-section/signal relative to areas that are out-of-focus. This is especially true for clinical samples in pathology, which consist of a thin tissue (approximately 5 microm) sample placed on a thick glass slide. Here, we recognize that the problem is the result of the extent of the illumination at the confocal plane being larger than the size of the sample and propose a dark field illumination scheme to efficiently reject substrate signals. The ability of several optical configurations in rejecting out-of-plane signal is investigated for two model systems: SU-8 photo resist over Teflon and SU-8 photo resist over polystyrene. The proposed reflective dark field approach, in which excitation converged to a focal point slightly above the focal plane of the collection optics, was found to be most effective in recording data from the sample. The proposed approach is validated by the rejection of substrate response (fluorescence) in spectra acquired from approximately 4 microm of breast tissue on a glass microscope slide. The proposed approach is easy to implement on existing confocal systems, has a straightforward optimization in acquiring data, and is not expected to result in loss of lateral resolution in mapping experiments.