Journal of biophotonics最新文献

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.

The objective of the study was to evaluate the effect of photobiomodulation (PBM) with laser on the inflammatory process in an experimental in vitro model of ACO. The groups were: (1) human bronchial epithelial cells (BEAS-2B); (2) BEAS-2B cells treated with dexamethasone; (3) BEAS-2B cells irradiated with laser; (4) BEAS-2B cells stimulated with cigarette smoke extract (CSE) + House Dust Mite (HDM); (5) BEAS-2B cells stimulated with CSE + HDM and treated with dexamethasone; (6) BEAS-2B cells incubated with CSE + HDM and irradiated with laser. After 24 h, cytokines were quantified. There was a reduction in TNF-α, IL-1β, IL-6, IL-4, IL-5, IL-13, IL-17, IL-21, IL-23, and an increase in IL-10 and IFN-γ in cells from the laser-irradiated ACO group compared to only ACO group. With these results, we can suggest that photobiomodulation acts in the modulation of inflammation observed in ACO, and may be a treatment option.

Since both top and bottom illuminations are widely used in infrared transmission measurements, in this paper, we study the effects of different illuminations on the signatures in infrared microspectroscopy. By simulating a series of dielectric samples, we show that their extinction efficiency, $Q_{\mathrm{ext}}$ , remains unchanged when the direction of the incident plane wave is reversed, even though the field distributions both inside and outside of the sample may be dramatically different. We find features in $Q_{\mathrm{ext}}$ that are correlated with whispering gallery modes for one beam direction and correspond to completely different field distributions for the opposite beam direction. In addition, by linking the optical theorem and the reciprocity relation of far-field scattered field, we rigorously prove the invariance of $Q_{\mathrm{ext}}$ for arbitrary dielectric targets under opposite plane-wave illuminations. Furthermore, we show the difference in the apparent absorbance spectrum for opposite beam directions when considering numerical apertures.

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.

Otitis media (OM), a highly prevalent inflammatory middle-ear disease in children worldwide, is commonly caused by an infection, and can lead to antibiotic-resistant bacterial biofilms in recurrent/chronic OM cases. A biofilm related to OM typically contains one or multiple bacterial species. OCT has been used clinically to visualize the presence of bacterial biofilms in the middle ear. This study used OCT to compare microstructural image texture features from bacterial biofilms. The proposed method applied supervised machine-learning-based frameworks (SVM, random forest, and XGBoost) to classify multiple species bacterial biofilms from in vitro cultures and clinically-obtained in vivo images from human subjects. Our findings show that optimized SVM-RBF and XGBoost classifiers achieved more than 95% of AUC, detecting each biofilm class. These results demonstrate the potential for differentiating OM-causing bacterial biofilms through texture analysis of OCT images and a machine-learning framework, offering valuable insights for real-time in vivo characterization of ear infections.

In this study, we introduced a novel dual-laser multi-color imaging system. Integrated with a multi-channel filter wheel, this system compared three spectral decontamination algorithms (nonnegative matrix factorization [NMF], RCAN, and PICASSO) showcasing its efficacy in achieving four-color imaging with only two laser sources. Combined with a reliable image reconstruction algorithm, the spatial resolution of four channels super-resolution four-color images reached 130, 125, 133, and 132 nm, respectively. Lipid droplets, mitochondria, lysosomes, and nuclei from the mouse hepatocytes (AML12), human neuroblastoma cells (SH-SY5Y), mouse hippocampal neuronal cells (HT-22), and immortalized murine bone marrow-derived macrophages were imaged. At the same time, the chromatin condensation, nuclear contraction, DNA fragmentation, apoptotic body formation, as well as the fusion of Mito and Lyso involved in mitochondrial autophagy were observed in HT-22 and SH-SY5Y cells suffering oxidative stress. Our multi-color SIM imaging system establishes a powerful platform for dynamic organelle studies and other high-resolution investigations in live cells.

Photoacoustic computed tomography (PACT) has centimeter-level imaging ability and can be used to detect the human body. However, strong photoacoustic signals from skin cover deep tissue information, hindering the frontal display and analysis of photoacoustic images of deep regions of interest. Therefore, we propose a 2.5 D deep learning model based on feature pyramid structure and single-type skin annotation to extract the skin region, and design a mask generation algorithm to remove skin automatically. PACT imaging experiments on the human periphery blood vessel verified the correctness our proposed skin-removal method. Compared with previous studies, our method exhibits high robustness to the uneven illumination, irregular skin boundary, and reconstruction artifacts in the images, and the reconstruction errors of PACT images decreased by 20% ~ 90% with a 1.65 dB improvement in the signal-to-noise ratio at the same time. This study may provide a promising way for high-definition PACT imaging of deep tissues.

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.

Early invasive skin melanoma (EISM) associated with partial tumor invasion to the thin and optically complex papillary dermis (PD) represents a critical stage before the onset of metastasis. EISM lesions may be accompanied by angiogenesis, which can alter the PD's blood and fibril contents. A comprehensive understanding about these interconnected processes is essential for enhancing the efficacy of EISM optical evaluation methodologies. Employing a first-principles computational approach supported by measured data, we systematically assess the impact that angiogenesis can have on the EISM's spectral responses. Our findings indicate that these responses are discernibly affected by angiogenesis under distinct physiological conditions, with more substantial tissue alterations leading to accentuated spectral changes in the 550-600 nm region. Accordingly, we propose the use of a customized low-cost spectral index to monitor these processes. Furthermore, our investigation provides a high-fidelity in silico platform for interdisciplinary research on the photobiology of evolving skin melanomas.

Radiofrequency (RF) ablation is a minimally invasive therapy for atrial fibrillation. Conventional RF procedures lack intraoperative monitoring of ablation-induced necrosis, complicating assessment of completeness. While spectroscopic photoacoustic (sPA) imaging shows promise in distinguishing ablated tissue, multi-spectral imaging is challenging in vivo due to low imaging quality caused by motion. Here, we introduce a cardiac-gated sPA imaging (CG-sPA) framework to enhance image quality using a motion-gated averaging filter, relying on image similarity. Necrotic extent was calculated based on the ratio between spectral unmixed ablated tissue contrast and total tissue contrast, visualizing as a continuous color map to highlight necrotic area. The validation of the concept was conducted in both ex vivo and in vivo swine models. The ablation-induced necrotic lesion was successfully detected throughout the cardiac cycle through CG-sPA imaging. The results suggest the CG-sPA imaging framework has great potential to be incorporated into clinical workflow to guide ablation procedures intraoperatively.