Biomedical optics express最新文献

We present a novel portable in vivo confocal ophthalmoscope (PICO) designed to enable non-contact imaging of the cornea and anterior segment of the eye. PICO uses a broadband light source and diffraction gratings to acquire two-dimensional confocal images without any beam scanning mechanisms. A dry objective lens with a long working distance was used to image the external eye without making physical contact with the cornea or ocular surface. Lateral resolution of 2.2-2.7 μm and axial resolution of 8.1 μm were achieved with PICO when imaging ex vivo animal corneas, and provided reliable signal levels when images were acquired at high speeds of 100-135 frames/sec. The resulting images enable clear visualization of characteristic cellular morphological details of the cornea, including epithelial cells, corneal nerve fibers, stromal keratocytes, and endothelial cells. These preliminary results from high-speed PICO imaging of animal corneas merit further evaluation of the prototype device for in vivo human corneal imaging.

Quantitative pathology remains limited due to the need for chemical staining and subjective interpretation of tissue features. Autofluorescence imaging offers a label-free alternative; however, high-dimensional excitation-emission datasets pose challenges for visualization and reproducible analysis. Here, we present Dimensionality Reduction for Enhanced Autofluorescence Microscopy (DREAM), a method that condenses multi-excitation emission spectra into a compact, information-rich format using phasor-based tools. Applied to unstained esophageal tissue samples, DREAM enables high-contrast visualizations that distinguish key histological structures without the need for exogenous labeling. Quantitative assessments across multiple datasets show DREAM improves colorfulness, sharpness, and consistency over single-laser acquisitions, supporting its potential to advance objective, label-free diagnostics through enhanced spectral visualization.

The formation of intracellular vacuoles in mammalian cells is associated with different dysfunctions, e.g., autophagy, lysosomal storage diseases, and cellular stress. We introduce a pipeline for high-throughput, label-free analysis of adherent cells and vacuoles using Fourier ptychographic microscopy (FPM). In fact, by tailoring the Cellpose model to the case of FPM phase-contrast imaging, we segment and characterize more than 3 × 10⁴ cells and more than 10⁵ vacuoles. We tune the platform using cells engineered to express various types of vacuoles. In pathological cells, our platform can identify distinct subpopulations within the same patient-derived line. By analyzing their content, the platform could yield clues about their origin and machinery, as well as screen conditions highlighted by vacuole formations.

Quantitative analysis of viscoelastic alterations in oral submucous fibrosis (OSF) provides crucial insights for monitoring disease progression and preventing malignant transformation. We developed a piezoelectric-based optical coherence elastography (OCE) system for real-time, in vivo quantitative assessment of OSF progression. In our experimental model, sixteen rats were systematically divided into four groups representing progressive fibrosis stages. Phase-sensitive OCE measurements captured distinctive elastic wave propagation patterns across all experimental groups. Comprehensive analysis of phase velocity dispersion curves and wave attenuation enabled the extraction of quantitative viscoelastic parameters that reflect fundamental tissue changes. Results demonstrated significant biomechanical alterations with disease progression, most notably a nearly four-fold increase in Young's modulus from normal tissue (32.6 ± 3.9 kPa) to severe fibrosis (121.1 ± 9.9 kPa), accompanied by more than doubled viscosity coefficients (0.52 ± 0.06 Pa·s to 1.27 ± 0.15 Pa·s). Particularly significant was the loss factor (G"/G') pattern, which exhibited a non-monotonic trend-decreasing from 0.30 in control specimens to 0.18 in moderate fibrosis groups before slightly increasing to 0.20 in severe fibrosis groups. The viscoelastic parameters quantified by OCE may facilitate more precise staging of OSF and potentially provide early indicators for assessing progression risk toward malignancy.

Drusen are a hallmark biomarker of age-related macular degeneration (AMD), with their size, number, and morphology (type) closely linked to disease severity and progression. Accurate segmentation and classification of drusen from optical coherence tomography (OCT) images are essential for objective AMD assessment and monitoring. In this work, we present a deep learning framework that combines a convolutional neural network for automated drusen segmentation with a dedicated classification module to distinguish four clinically relevant, distinct drusen types based on segmentation output. We evaluated our approach on a comprehensive dataset and achieved a mean Dice score of 0.74 ± 0.21 for voxel-wise segmentation accuracy and a critical success index of 0.69 ± 0.24 for drusen count accuracy. This method demonstrates substantial improvements in the quantitative drusen analysis and offers a promising tool for enhanced AMD diagnosis and tracking of disease progression.

Photoacoustic imaging (PAI) combines optical contrast with acoustic detection to enable high-resolution, molecular imaging at clinically relevant depths. This review outlines the current status and future potential of contrast-enhanced PAI in human applications. We begin by discussing regulatory considerations surrounding both imaging devices and exogenous contrast agents, highlighting safety concerns, lack of standardized validation protocols, and barriers to the approval of novel agents. To accelerate clinical adoption, many studies have focused on repurposing FDA-approved agents such as indocyanine green, methylene blue, and clofazimine, which offer favorable optical properties and known safety profiles. We then review clinical applications of contrast-enhanced PAI across organ systems. In lymphatic imaging, PAI enables noninvasive visualization of lymphatic vessels and sentinel lymph nodes. Prostate imaging benefits from improved tumor delineation, and vascular applications leverage PAI to assess oxygen saturation and vascular remodeling. In gastrointestinal and hepatic imaging, PAI supports functional assessment and lesion detection with enhanced contrast. Emerging applications in neuro-oncology demonstrate the potential of PAI for intraoperative guidance and brain tumor imaging. Compared to fluorescence imaging, PAI provides deeper penetration and quantifiable contrast. Studies using both approved and investigational agents, including gold nanorods and targeted dye conjugates, highlight advances in imaging tumor margins. Progress in transcranial PAI and molecular probe design continues to broaden its capabilities. Together, these developments underscore the expanding clinical utility of contrast-enhanced PAI for real-time, functional, and molecular imaging.

Keratoconus is an ophthalmopathy characterized by a central thinning that commonly causes irregular astigmatism and high myopia. However, the diagnostic standards of keratoconus have not yet been well established clinically and mainly rely on macro characteristics measured through corneal topography. To describe the micro changes conveyed by collagen microstructures in the corneal stroma and provide a new insight for keratoconus, we developed a quantitative diagnostic method combining macro-micro information via in vivo optical coherence tomography (OCT). A comparison experiment was designed to confirm the feasibility of characterizing collagen organization using OCT. Macro variables, including heterogeneity in curvature and thickness of cornea, and micro variables of collagen fiber alignment, were calculated and weighted to define the keratoconus potential index (KPI) as a quantitative measure for diagnosing keratoconus and mapping disease risks of 104 participants, which showed excellent diagnostic power (with an area under the curve of 0.991) in keratoconus detection.

Optoretinography (ORG) is a label-free imaging of the light-evoked changes in the retina associated with alterations in the cell shape and refractive indices. Its most precise version, the phase-resolved optical coherence tomography (pOCT), exhibited sensitivity of about 10 nm in vivo, limited by the signal-to-noise ratio and accuracy of the tissue registration. While it is yet insufficient for the detection of single action potentials, which are about 1 nm in amplitude, it enables monitoring slower and larger deformations in other retinal layers. In response to a single flash delivered to the dark-adapted retina, photoreceptor outer segments (OS) exhibit rapid (millisecond-scale) contraction, reaching tens of nm in cones and hundreds of nm in rods. This effect can be explained by changes in the membrane tension due to hyperpolarization of the OS discs-that is, the intradiscal space becoming more negatively charged-during the early receptor potential induced by opsins isomerization. In cones, such contraction is followed by a slower elongation by hundreds of nm during hundreds of ms. The proposed underlying mechanisms include osmotic influx of water, swelling of the cone opsin and disc membranes, and conformational changes in phosphodiesterase (PDE6) during phototransduction. ORG also reveals slow deformations in the subretinal space (SRS) and retinal pigment epithelium (RPE), likely induced by light-evoked ionic and osmotic shifts, as well as in the inner plexiform layer (IPL) and ganglion cell layer (GCL). ORG has a high potential as a non-invasive, label-free, and objective assay of retinal health, co-registered with structural images in the same OCT machine. To realize its promise in basic science and clinical assessment of diseases and therapies, its underlying mechanisms need to be delineated. This review summarizes current understanding of the physiological mechanisms behind the ORG.

Pancreatic cancer remains one of the deadliest cancers due to the lack of effective early detection tools. While deep neural networks (DNNs) have shown promise in tumor segmentation, electronic accelerators suffer from power inefficiency and latency. To address this, we propose MediONN-a photonic neural network system implemented on an integrated chip, optimized for 3D medical image segmentation. MediONN integrates a 4×4 photonic neural processor within a hierarchical 3D optical computation framework. To improve training convergence, we introduce a segmentation-specific Gaussian weight initialization strategy, along with 3D optical convolutional layers for volumetric feature extraction. Unlike prior photonic systems focused on classification, MediONN is the first to demonstrate optical neural networks (ONNs) directly applied to 3D segmentation. On the NIH pancreas CT dataset, MediONN achieves a Dice similarity coefficient (DSC) of 0.5215 (2D) and 0.5302 (3D), with peak DSCs of 0.5919 (2D) and 0.8788 (3D). Comprehensive evaluation metrics confirm MediONN's segmentation accuracy is comparable to electronic counterparts, while offering significant gains in computational speed and energy efficiency. These results highlight the scalability and biomedical potential of integrated photonic ONNs.

This study evaluated optical coherence tomography angiography (OCTA) for monitoring gingival vascular changes during induced inflammation and resolution. Twelve healthy participants abstained from brushing for 14 days, followed by 14 days of resumed oral hygiene. Vascular changes were quantified using vessel area density (VAD), vessel skeleton density (VSD), and vessel diameter index (VDI). VSD showed minimal change, whereas VAD increased by 13.6% and VDI by 10.1% at peak inflammation (P < 0.01). Participants were classified as high or low responders based on their gingival response. OCTA enabled site-specific, noninvasive assessment of gingival inflammation, detecting early microvascular alterations during disease progression.