Biomedical optics express最新文献

Kidney transplantation remains the preferred treatment for patients with end-stage kidney disease. However, the ongoing shortage of donor organs continues to limit the availability of transplant treatments. Existing evaluation methods, such as the kidney donor profile index (KDPI) and pre-transplant donor biopsy (PTDB), have various limitations, including low discriminative power, invasiveness, and sampling errors, which reduce their effectiveness in organ quality assessment and contribute to the risk of unnecessary organ discard. In this study, we explored the dynamic optical coherence tomography (DOCT) as a label-free, non-invasive approach to monitor the viability of ex vivo mouse kidneys during static cold storage over 48 hours. The dynamic metrics logarithmic intensity variance (LIV), early OCT correlation decay speed (OCDS _e ), and late OCT correlation decay speed (OCDS _l ) were extracted from OCT signal fluctuations to quantify temporal and spatial tissue activity and deterioration. Our results demonstrate that DOCT provides complementary information relevant to tissue viability, in addition to the morphological assessment offered by conventional OCT imaging, showing potential to improve pre-transplant organ evaluation and clinic decision-making.

The transport of intensity equation (TIE) is a powerful phase imaging technique. However, its formulation fails to account for the off-axial transfer function due to the paraxial approximation. To address the resulting image degradation, we analyze TIE phase retrieval using the contrast transfer function (CTF) framework. The attenuation of high-frequency components, leading to the loss of fine structural details, is assessed and restored through Wiener deconvolution. Simulations and experiment results demonstrate significant enhancements in sharpness, contrast, and structural clarity. We showcase enhanced phase imaging of cheek cells, revealing finer subcellular details and achieving diffraction-limited performance, contributing to advances in super-resolution phase imaging.

We present a fully 3D-printed, broadband endomicroscopic objective optimized for near-infrared two-photon fluorescence imaging, featuring a compact, alignment-free design. The objective provides a numerical aperture of 0.6 in water immersion over a 200 µm field of view and maintains near diffraction-limited performance across the 720-950 nm excitation band. Monolithically fabricated with multi-material via two-photon polymerization (2PP), the three-element refractive objective achieves a 2 mm lens mechanical diameter, a mechanical housing diameter of 3 mm, and a total length of 2.1 mm with an approximately 10-hour build time. A self-aligning architecture integrates the printed half-housing with the optics to minimize assembly error, yielding sub-10 µm element decenter and <0.1° element tilt. Optical performance was validated using a resolution target and biological specimens, with broadband excitation behavior assessed by two-photon imaging of pollen grains across multiple excitation wavelengths, and with autofluorescence imaging of fresh mouse liver confirming feasibility for in situ tissue imaging. This work demonstrates the potential of fully printed broadband objectives for compact, high-performance endomicroscopy and integrated biomedical optics.

Ovulation is preceded by a critical physiological process known as cumulus expansion, during which the cumulus cell layer surrounding the oocyte undergoes structural remodeling. Despite the recognized importance of this process for reproductive success, live quantitative imaging of cumulus expansion has not been previously achieved due to limitations of current imaging technologies for deeply located ovaries. In this study, we employed intravital optical coherence tomography for three-dimensional visualization of mouse follicles containing cumulus-oocyte complexes (COC) within the physiological context of the ovary, both ex vivo and in vivo. This method enabled time-lapse measurement of cumulus layer thickness and COC volume. Longitudinal imaging in live mice revealed the physiological spatiotemporal dynamics of cumulus matrix expansion preceding ovulation. These findings establish a novel in vivo platform for dynamic investigation of previously inaccessible preovulatory processes within a physiological context.

Functional imaging in freely moving animals with genetically encoded voltage indicators (GEVIs) will open new capabilities for neuroscientists to study the behavioral relevance of neural activity with high spatial and temporal precision. However, miniaturization of an imaging system with sufficient collection efficiency to resolve the small changes in fluorescence yield from voltage spikes, as well as the development of efficient image sensors that are sufficiently fast to capture them, has proven challenging. We present a miniaturized microscope designed for voltage imaging, with a numerical aperture of 0.6, a 250 µm field of view, and a 1.3-1.6 mm working distance that weighs 16.4 g. We show it is capable of imaging in vivo voltage spikes from Voltron2 with a spike peak-to-noise ratio >3 at a framerate of 530 Hz.

We implement an integrated multi-electrode array on a silicon-nitride-based photonic integrated circuit for ex-vivo retinal characterization via optical stimulation. The interrogation beam formers, based on curved grating emitters and optical phased arrays, are designed to achieve transverse focusing with spot sizes in the 1-2 µm range to target single cells. The experimentally realized focusing optical phased arrays show suppressed side-lobes, with approximately 11.5% of the power in each side-lobe and ∼60% in the main lobe, reducing unintentional cellular excitation. Additional design refinement enables further suppression of the side-lobes to a few percent of the total power. Additionally, we demonstrate a compact design of meandered thermal phase shifters implemented across the array that allow push-pull steering in the transverse direction as well as focusing and defocusing of the beam, with a total of only four control signals. Transverse angular steering by ±5.1° and axial translation of the focal spot by 204 µm are demonstrated with tuning currents below 50 mA, together with longitudinal angular steering by 4.26° obtained by means of wavelength tuning in a ± 15 nm range centered on 525 nm.

Optoretinography (ORG) is a recent technique for assessing photoreceptor function by measuring their physiological responses to a flash of light. These responses induce changes in the optical properties of photoreceptors, which can be analyzed to evaluate cone photoreceptor health. Recent studies suggest that ORG could be a useful biomarker for detecting retinal pathologies. However, the ORG signal depends on various non-pathology-related factors that need to be taken into account for effective clinical translation. Here, we introduce a new ORG metric and mapping based on the percentage of cones responsive to the stimulus, and we study the effects of retinal eccentricity, color blindness, and age on intensity-based ORG (iORG) using an adaptive optics scanning laser ophthalmoscope (AOSLO).

Real-time multi-wavelength photoacoustic (PA) imaging has emerged as a powerful modality for investigating tumor vascular dynamics, offering non-invasive, high-resolution visualization of hemodynamic changes that are critical for cancer diagnosis and therapeutic monitoring. In this study, we present a custom integration of the Verasonics Vantage ultrasound platform with an optical parametric oscillator (OPO) laser system. The first part of the study provides a comprehensive review of the current literature on PA imaging using the Verasonics system, emphasizing its capabilities, limitations, and adaptability for advanced imaging applications. Building upon this foundation, we introduce a robust framework that leverages the Verasonics system in conjunction with the fast-tuning capabilities of the OPO laser to enable synchronized, multi-wavelength PA imaging. In the second part of the study, we demonstrate selected applications of the developed system, such as multi-wavelength spectral imaging of tumor vasculature and near-real-time monitoring of therapeutic response. These case studies highlight the system's capability to capture dynamic physiological changes and support functional, longitudinal assessments in complex pathological environments. Future directions include the exploration of alternative tunable laser sources and the integration of machine learning algorithms to enhance real-time image reconstruction and spectral unmixing. Collectively, this work establishes a versatile and scalable platform for advancing PA imaging in preclinical and translational cancer research.

Time-domain diffuse correlation spectroscopy (TD-DCS) is a non-invasive optical technique for measuring tissue blood flow. Recovering the blood flow index (αD _b) requires accurate modelling of the normalised electric field autocorrelation function (g ₁), and an optimised data processing approach to minimise noise. We quantitatively compared four modelling approaches for g ₁: (i) using momentum transfer (Y) and pathlengths (L) from Monte Carlo (MC) simulations, (ii) using L only, (iii) applying an analytical solution of the photon diffusion equation (DE) in time domain, and (iv) applying an analytical solution of the correlation diffusion equation (CDE) in steady state. The second and third approaches use solutions in near-infrared spectroscopy (NIRS) for modelling g ₁ in DCS by assuming Y = μ' _s L. We computed g ₁ curves using the first approach, considered the gold standard, and recovered αD _b using the other three approaches for various source-detector distances (ρ) and scattering coefficients (μ' _s). Also, we investigated how the correlator time bin width (T _bin), which is an adjustable parameter in data processing, affects the standard deviation of g ₁ (or the normalised intensity autocorrelation function g ₂). We used a more convenient version of the noise equation expressed as a function of g ₁ (or g ₂), which removes the need to know the decay rate. When using photons detected after ∼0.5 ns, all four approaches produced nearly identical g ₁ curves. Using all detected photons, the DE solution produced negligible errors (up to ∼2%) in the recovered αD _b across various ρ and μ' _s, while using L from MC simulations resulted in larger errors (up to ∼9% at ρ = 5 mm and ∼1.5% at ρ = 30 mm). The analysis of the probability distributions P(Y) and P(μ' _s L) explained these differences. As expected, the standard deviation of g ₁ (or g ₂) can be reduced during data processing by increasing T _bin. To achieve the lowest standard deviation, T _bin should be longer than the inverse of the photon count rate, indicating that the optimal T _bin may vary across different time gates. The results provide quantitative insights into modelling g ₁ (or g ₂), and provide a direct guideline for minimising the standard deviation of g ₁ (or g ₂) in data processing.

Diffuse correlation spectroscopy (DCS) is a promising, noninvasive, light-based method for continuous bedside monitoring of cerebral blood flow. However, its sensitivity to brain tissue is affected by extracerebral layers. Although layered-model analysis improves cerebral perfusion measurement accuracy, it requires precise knowledge of the properties of superficial layers. To address this challenge, we demonstrate a method for quantifying superficial blood flow dynamics and thickness using three-channel DCS measurements. The approach was validated via simulation and layered phantom experiments. Results demonstrated that an accurate superficial-layer blood flow index can be obtained by adjusting photon count rates at short separations. In turn, this enabled estimation of the superficial-layer thickness and the lower-layer blood flow index from DCS data acquired at two long source-detector separations.