Journal of biophotonics最新文献

Here we propose a not pupil-dependent microsaccades tracking technique and a novel detection method. We present a proof of concept for detecting microsaccades using a non-contact laser-based photonic system recording and processing the temporal changes of speckle patterns scattered from an eye sclera. The data, simultaneously recorded by the speckle-based tracker (SBT) and the video-based eye tracker (Eyelink), was analyzed by the frequently used detection method of Engbert and Kliegl (E&K) and by advanced machine learning detection (MLD) techniques. We detected 93% of microsaccades in the SBT data out of microsaccades detected in the Eyelink data with the E&K method. By utilizing MLD, a precision of 86% was achieved. The findings of our study demonstrate a potential improvement in measuring tiny eye movements, such as microsaccades, using speckle-based eye tracking and, thus, an alternative to video-based eye tracking for detecting microsaccades.

Optical properties determine how light interacts with biological tissues. The current methods for measuring these optical properties are influenced by both deep and superficial skin layers. Polarization-based methods have been proposed in order to determine the influence of deep layer scattering. Polarized light allows for the separation of ballistic photons from diffuse ones, enhancing image contrast and resolution while providing additional tissue information. The Q-sensing technique captures co-polarized $\left(I_{\parallel }\right)$ and cross-polarized $\left(I_{\perp }\right)$ signals, making it possible to isolate the superficial scattering. However, the random structure of tissues leads to rapid depolarization of the polarized light. Detecting where the light becomes depolarized aids in sensing abnormalities within the tissues. Hence, this research focuses on identifying where depolarization occurs within the tissue. Tissue-mimicking phantoms, simulating the optical properties of biological tissues, are created to measure depolarization at various thicknesses. Experimental findings are validated with a Monte Carlo simulation, modeling polarized light behavior through the polydisperse tissue (as the tissue scatterers are heterogeneous in size). Additionally, the research demonstrates how polarized light can extract the optical properties of the medium.

Optical coherence tomography (OCT) is a noninvasive 3D imaging technique that offers significant advantages over traditional microscopy and biopsy in measuring epidermal thickness (ET) when assessing skin conditions. However, OCT imagining is often required to be in a contact mode for mitigating the issues of subject movement and uneven skin topology. It is not known whether the contact would affect the ability of ET measurements. In this study, we investigate the relationship between the contact pressure applied and the ET measurements. We observed progressive deformation in the epidermis with the increase of compression forces, where a notable decrease of up to 13% in ET measurement and 70% decrease in capillary vessels was noted when imaging was in contact mode. We also observed 8.1% less deformation properties in scar tissue than in nearby healthy tissue. Our study underscored the importance of controlled pressure in contact imaging mode, which is often neglected.

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is one of the most prevalent chronic liver diseases worldwide. Thermal imaging combined with advanced image-processing and machine learning analysis accurately classified disease status in a study on mice; this study aimed to develop this tool for humans. This prospective study included 46 patients who underwent liver biopsy. Liver thermal imaging was performed on the same day as liver biopsy. We developed an image-processing algorithm that measured the relative spatial thermal variation across the skin covering the liver. The texture parameters obtained from the thermal images were input into the machine learning algorithm. Patients were diagnosed with MASLD and stratified according to nonalcoholic fatty liver disease activity score (NAS) and fibrosis stage using the METAVIR score. Twenty-one of 46 patients were diagnosed with MASLD. Using thermal imaging followed by processing, detection accuracy for patients with NAS >4 was 0.72.

Optical palpation is an emerging elastography technique that generates two-dimensional images of mechanical stress at the tissue surface, with clinical applications such as intraoperative cancer detection and scar assessment. It has been implemented using various imaging systems, however, an analysis of how deformation of the sample and layer influences image formation has not been performed. Here, an analysis framework is presented, which assesses performance independently of the imaging system used. Optical palpation of varying samples and layers is simulated using finite element analysis and validated with experiments on silicone phantoms, providing a characterization of detectability, feature resolution, and contrast ratio. Using our framework, we demonstrate that computational optical palpation, which incorporates realistic assumptions of layer deformation, improves the feature resolution up to a factor of four. This framework can guide the development of optical palpation and aid in the selection of appropriate imaging system and layer properties for a given application.

Autofluorescence spectroscopy has emerged in recent years as a powerful tool to report label-free contrast between normal and diseased tissues, both in vivo and ex-vivo. We report the application of an instrument employing an optical fiber probe and capable of performing real-time autofluorescence lifetime imaging at a macroscopic scale, under bright background conditions. We validate and demonstrate the practicality of this technology to discriminate healthy against neoplastic tissue in freshly excised tumor biopsies. The capability of delineating tumor margins through processing the fluorescence decays in the phasors domain was demonstrated on four different types of cancer, highlighting the broad range of potential clinical applications for the proposed approach. The presented results suggest that our autofluorescence lifetime imaging probe, together with phasor analysis, can offer a real-time tool to observe lifetime contrast on tissues and, thus, is a suitable candidate for improving in situ tissue diagnostics during surgery.

In this article we present the novel spectroscopy method supported with machine learning for real-time detection of infectious agents in wastewater. In the case of infectious diseases, wastewater monitoring can be used to detect the presence of inflammation biomarkers, such as the proposed C-reactive protein, for monitoring inflammatory conditions and mass screening during epidemics for early detection in communities of concern, such as hospitals, schools, and so on. The proposed spectroscopy method supported with machine learning for real-time detection of infectious agents will eliminate the need for time-consuming processes, which contribute to reducing costs. The spectra in range 220-750 nm were used for the study. We achieve accuracy of our prediction model up to 68% with using only absorption spectrophotometer and machine learning. The use of such a set makes the method universal, due to the possibility of using many different detectors.

Optical clearing agents (OCAs) are substances that temporarily modify tissue's optical properties, enabling better imaging and light penetration. This study aimed to assess the impact of OCAs on the nail bed and blood using in vivo and in vitro optical methods. In the in vivo part, OCAs were applied to the nail bed, and optical coherence tomography and optical digital capillaroscopy were used to evaluate their effects on optical clearing and capillary blood flow, respectively. In the in vitro part, the collected blood samples were incubated with the OCA and blood aggregation properties were estimated using diffuse light scattering techniques. The results indicate that OCAs significantly influence the optical properties of the nail bed and blood microrheology. These findings suggest that OCAs hold promise for improving optical imaging and diagnostics, particularly for nail bed applications, and can modify blood microrheology.

The broadband absorption coefficient spectrum of the rabbit lung presents some particular characteristics that allow the identification of the chromophores in this tissue. By performing a weighted combination of the absorption spectra of water, hemoglobin, DNA, proteins and the pigments melanin and lipofuscin, it was possible to obtain a good match to the experimental absorption spectrum of the lung. Such reconstruction provided reasonable information about the contents of the tissue components in the lung tissue, and allowed to identify a similar accumulation of melanin and lipofuscin.