Journal of Biophotonics最新文献

Detection of radiation-induced changes of the brain white matter is important for brain neoplasms repeated surgery. We investigated the influence of irradiation on the scattering properties of the white matter using optical coherence tomography (OCT). Healthy Wistar rats undergone the irradiation of the brain right hemisphere. At seven time points from the irradiation procedure (2–14 weeks), an ex vivo OCT study was performed with subsequent calculation of attenuation coefficient values in the corpus callosum followed by immunohistochemical analysis. As a result, we discovered acute and early-delayed changes characterized by the edema of different severity, accompanied by a statistically significant decrease in attenuation coefficient values. In particular, these changes were found at 2 weeks after irradiation in the irradiated hemisphere, while at 6- and 12-week time points they affected both irradiated and contralateral hemisphere. Thus, radiation-induced changes occurring in white matter during the first 3 months after irradiation can be detected by OCT.

This study focuses on the use of cellular autofluorescence which visualizes the cell metabolism by monitoring endogenous fluorophores including NAD(P)H and flavins. It explores the potential of multispectral imaging of native fluorophores in melanoma diagnostics using excitation wavelengths ranging from 340 nm to 510 nm and emission wavelengths above 391 nm. Cultured immortalized cells are utilized to compare the autofluorescent signatures of two melanoma cell lines to one fibroblast cell line. Feature analysis identifies the most significant and least correlated features for differentiating the cells. The investigation successfully applies this analysis to pre-processed, noise-removed images and original background-corrupted data. Furthermore, the applicability of distinguishing melanomas and healthy fibroblasts based on their autofluorescent characteristics is validated using the same evaluation technique on patient cells. Additionally, the study tentatively maps the detected features to underlying biological processes. This research demonstrates the potential of cellular autofluorescence as a promising tool for melanoma diagnostics.

In acute intestinal ischemia, the progression of ischemia varies across different layers of intestinal tissue. We established a mouse model and used swept-source optical coherence tomography (OCT) to observe the intestinal ischemic process longitudinally in different tissue layers. Employing a method that combines asymmetric gradient filtering with adaptive weighting, we eliminated the vessel trailing phenomenon in OCT angiograms, reducing the confounding effects of superficial vessels on the imaging of deeper vasculature. We quantitatively assessed changes in vascular perfusion density (VPD), vessel length, and vessel average diameter across various intestinal layers. Our results showed a significant reduction in VPD in all layers during ischemia. The mucosa layer experienced the most significant impact, primarily due to disrupted capillary blood flow, followed by the submucosa layer, where vascular constriction or decreased velocity was the primary factor.

The only existing approach for assessing the risk of developing acute ischemic stroke (AIS) necessitates that individuals possess a strong understanding of their health status. Our research gathered compelling evidence in favor of our hypothesis, suggesting that the likelihood of developing AIS can be assessed by analyzing the green autofluorescence (AF) of the skin and fingernails. Utilizing machine learning-based analyses of AF images, we found that the area under the curve (AUC) for distinguishing subjects with three risk factors from those with zero, one, or two risk factors was 0.79, 0.76, and 0.75, respectively. Our research has revealed that green AF serves as an innovative biomarker for assessing the risk of developing AIS. Our method is objective, non-invasive, efficient, and economic, which shows great promise to boost a technology for screening natural populations for risk of developing AIS.

This article investigates an endoscopic approach that utilizes negative pressure to achieve laser-induced thermal coagulation limited to the esophageal wall's mucosal and superficial submucosal layers. The study was built upon a series of studies combining numerical simulation based on the Monte-Carlo technique and ex vivo porcine tissue experiments, including apparatus design and histology analysis. An endoscopy apparatus was developed using 3D printing to validate the tissue stretching-based approach. A fiber-pigtailed diode was used as the near-infrared source, emitting 208.8 W/cm² laser irradiance at 1.5 μm. Simulation results suggested that the approach successfully created a local heat well to prevent residual thermal effects (>65°C) from penetrating the deeper submucosal layer. Histology analysis of ex vivo tissues showed that at a fluence of 5.22 kJ/cm², the depth of thermal coagulation was reduced by half compared to the control. With further preclinical studies, including endoscopy apparatus design, the approach can be applied to the larger esophageal surface.

Drosophila model has been widely used to study cardiac functions, especially combined with optogenetics and optical coherence tomography (OCT) that can continuously acquire mass cross-sectional images of the Drosophila heart in vivo over time. It's urgent to quickly and accurately obtain dynamic Drosophila cardiac parameters such as heartbeat rate for cardiac function quantitative analysis through these mass cross-sectional images of the Drosophila heart. Here we present a deep-learning method that integrates U-Net and generative adversarial network architectures while incorporating residually connected convolutions for high-precision OCT image segmentation of Drosophila heart and dynamic cardiac parameter measurements for optogenetics-OCT-based cardiac function research. We compared our proposed network with the previous approaches and our segmentation results achieved the accuracy of intersection over union and Dice similarity coefficient higher than 98%, which can be used to better quantify dynamic heart parameters and improve the efficiency of Drosophila-model-based cardiac research via the optogenetics-OCT-based platform.

Several serum Raman spectroscopy (RS) studies have demonstrated its potential as an oral cancer screening tool. This study investigates influence of low tumour load (LTL) and high tumour load (HTL) on serum RS using hamster buccal pouch model of experimental oral carcinogenesis. Sera of untreated control, LTL, and HTL groups at week intervals during malignant transformation were employed. Serum Raman spectra were subjected to multivariate analyses—principal component analysis, principal component-based linear discriminant analysis (for stratification of study groups), and multivariate curve resolution-alternating least squares (MCR-ALS) (to comprehend biomolecular differences). Multivariate analysis revealed misclassifications between LTL and HTL at all week intervals. MCR-ALS components showed statistically significant abundances between control versus LTL and control versus HTL, but could not discern LTL and HTL. MCR-ALS components exhibited spectral mixtures of proteins, lipids, heme and nucleic acids. Thus, these findings support use of serum RS as a screening tool as varying tumour load is not a confounding factor influencing the technique.

Quantifying corneal elasticity after femtosecond laser-assisted in situ keratomileusis (FS-LASIK) procedure plays an important role in improving surgical safety and quality, since some latent complications may occur ascribing to changes in postoperative corneal biomechanics. Nevertheless, it is suggested that current research has been severely constrained due to the lack of an accurate quantification method to obtain postoperative corneal elasticity distribution. In this paper, an acoustic radiation force optical coherence elastography system combined with the improved phase velocity algorithm was utilized to realize elasticity distribution images of the in vivo rabbit cornea after FS-LASIK under various intraocular pressure levels. As a result, elasticity variations within and between the regions of interest could be identified precisely. This is the first time that elasticity imaging of in vivo cornea after FS-LASIK surgery was demonstrated, and the results suggested that this technology may hold promise in further exploring corneal biomechanical properties after refractive surgery.

Optoacoustic imaging enables the measurement of tissue oxygen saturation (sO₂) and blood perfusion while being utilized for detecting tumor microenvironments. Our aim was to employ multispectral optoacoustic tomography (MSOT) to assess immediate-early changes of hemoglobin level and sO₂ within breast tumors during diverse treatments. Mouse breast cancer models were allocated into four groups: control, everolimus (EVE), paclitaxel (PTX), and photodynamic therapy (PDT). Hemoglobin was quantified daily, as well as sO₂ and blood perfusion were verified by immunohistochemical (IHC) staining. MSOT showed a temporal window of enhanced oxygenation and improved perfusion in EVE and PTX groups, while sO₂ consistently remained below baseline in PDT. The same results were obtained for the IHC. Therefore, MSOT can monitor tumor hypoxia and indirectly reflect blood perfusion in a non-invasive and non-labeled way, which has the potential to monitor breast cancer progression early and enable individualized treatment in clinical practice.

Pancreatic intraepithelial neoplasia (PanIN) is the most common precursor lesion that has the potential to progress to invasive pancreatic cancer, and early and rapid detection may offer patients a chance for treatment before the development of invasive carcinoma. Therefore, the identification of PanIN holds significant clinical importance. In this study, we first used multiphoton microscopy (MPM) combining two-photon excitation fluorescence and second-harmonic generation imaging to label-free detect PanIN and attempted to differentiate between normal pancreatic ducts and different grades of PanIN. Then, we also developed an automatic image processing strategy to extract eight morphological features of collagen fibers from MPM images to quantify the changes in collagen fibers surrounding the ducts. Experimental results demonstrate that the combination of MPM and quantitative information can accurately identify normal pancreatic ducts and different grades of PanIN. This study may contribute to the rapid diagnosis of pancreatic diseases and may lay the foundation for further clinical application of MPM.