Cervical Cancer Tissue Analysis Using Photothermal Midinfrared Spectroscopic Imaging.

Hyperspectral photothermal mid-infrared spectroscopic imaging (HP-MIRSI) is an emerging technology with promising applications in cervical cancer diagnosis and quantitative, label-free histopathology. This study pioneers the application of HP-MIRSI to the evaluation of clinical cervical cancer tissues, achieving excellent tissue type segmentation accuracy of over 95%. This achievement stems from an integrated approach of optimized data acquisition, computational data reconstruction, and the application of machine learning algorithms.

Rapid Hyperspectral Photothermal Mid-Infrared Spectroscopic Imaging from Sparse Data for Gynecologic Cancer Tissue Subtyping.

Ovarian cancer detection has traditionally relied on a multistep 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.

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 mm and a 10 mm working distance.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

Characterization of tumor progression in engineered tissue using infrared spectroscopic imaging.

Engineered tissues can provide models for imaging and disease progression and the use of such models is becoming increasingly prevalent. While structural characterization of these systems is documented, a combination of biochemical and structural knowledge is often helpful. Here, we apply Fourier transform infrared (FT-IR) spectroscopic imaging to examine an engineered tissue model of melanoma.