Biomedical optics express最新文献

We present the use of stimulated Brillouin scattering spectroscopy to achieve rapid measurements of cell biomechanics in a flow cytometer setup. Specifically, our stimulated Brillouin scattering flow cytometry can acquire at a rate of 200 Hz, with a spectral acquisition time of 5 ms, which marks a 10x improvement compared to previous demonstrations of spontaneous Brillouin scattering flow cytometry. We experimentally validate our stimulated Brillouin scattering flow cytometer by measuring cell populations of normal breast epithelial cells and metastatic breast epithelial cancer cells.

Optical coherence tomography angiography (OCTA) has significantly advanced the study and diagnosis of eye diseases. However, current clinical OCTA systems and software tools lack comprehensive quantitative analysis capabilities, limiting their full clinical utility. This paper introduces the OCTA Retinal Vessel Analyzer (OCTA-ReVA), a versatile open-source platform featuring a user-friendly graphical interface designed for the automated extraction and quantitative analysis of OCTA features. OCTA-ReVA includes traditional established OCTA features based on binary vascular image processing, such as blood vessel density (BVD), foveal avascular zone area (FAZ-A), blood vessel tortuosity (BVT), and blood vessel caliber (BVC). Additionally, it introduces new features based on blood perfusion intensity processing, such as perfusion intensity density (PID), vessel area flux (VAF), and normalized blood flow index (NBFI), which provide deeper insights into retinal perfusion conditions. These additional capabilities are crucial for the early detection and monitoring of retinal diseases. OCTA-ReVA demystifies the intricate task of retinal vasculature quantification, offering a robust tool for researchers and clinicians to objectively evaluate eye diseases and enhance the precision of retinal health assessments.

This study showcases the multifunctionality of a single-shot quantitative phase microscopy (QPM) system for comprehensive cell analysis. The system captures four high-contrast images in one shot, enabling tasks like cell segmentation, measuring cell confluence, and estimating cell mass. We demonstrate the usability of the QPM system in routine biological workflows, showing how its integration with computational algorithms enables automated, precise analysis, achieving accuracy scores between 85% and 97% across samples with varying cell densities, even those with low signal-to-noise ratios. This cost-effective tool operates under low-intensity light and resists vibrations, making it highly versatile for researchers in both optical and biological fields.

Label-free optical biosensors have become powerful tools in the study of biomolecular interactions without the need for labels. High throughput and low detection limit are desirable for rapid and accurate biomolecule detection. The oblique-incidence reflectivity difference (OI-RD) technique is capable of detecting thousands of biomolecular interactions in a high-throughput mode, specifically for biomolecules larger than 1000 Da. In order to enhance the detection capability of OI-RD for small molecules (typically < 500 Da), we have developed a three-dimensional biochip that utilized carboxymethyl chitosan (CMCS) functionalized slides. By investigating various factors such as sonication time, protein immobilization time, CMCS molecular weight, and glutaraldehyde (GA) functionalization time, we have achieved a detection limit of 6.8 pM for avidin (68 kDa). Furthermore, accurate detection of D-biotin with a molecular weight of 244 Da has also been achieved. This paper presents an effective solution for achieving both high throughput and low detection limits using the OI-RD technique in the field of biomolecular interaction detection.

Optical diffraction tomography (ODT) enables label-free and morphological 3D imaging of biological samples using refractive-index (RI) contrast. To accomplish this, ODT systems typically capture multiple angular-specific scattering measurements, which are used to computationally reconstruct a sample's 3D RI. Standard ODT systems employ scanning mirrors to generate angular illuminations. However, scanning mirrors are limited to illuminating the sample from only one angle at a time. Furthermore, when operated at high speeds, these mirrors may exhibit mechanical instabilities that compromise image quality and measurement speed. Recently, newer ODT systems have been introduced that utilize digital-micromirror devices (DMD), spatial light modulators (SLMs), or LED arrays to achieve switchable angle-scanning with no physically-scanning components. However, these systems associate with power inefficiencies and/or spurious diffraction orders that can also limit imaging performance. In this work, we developed a novel non-interferometric ODT system that utilizes a fully switchable module for angle scanning composed of a DMD and microlens array (MLA). Compared to other switchable ODT systems, this module enables each illumination angle to be generated fully independently from every other illumination angle (i.e., no spurious diffraction orders) while also optimizing the power efficiency based on the required density of illumination angles. We validate the quantitative imaging capability of this system using calibration microspheres. We also demonstrate its capability for imaging multiple-scattering samples by imaging an early-stage zebrafish embryo.

This paper investigates the theoretical capability of near-infrared spectroscopy (NIRS) systems to accurately measure changes in the oxidation state of cerebral cytochrome-c-oxidase (CCO) alongside the hemoglobins, for a deeper understanding of NIRS limitations. Concentration changes of oxy and deoxyhemoglobin (HbO and HbR) indicate the oxygen status of blood vessels and correlate with several other physiological parameters across different pathologies. The oxidation state of CCO indicates cellular energy usage efficiency through oxidative metabolism, potentially serving as a biomarker for brain and other tissue disorders. This study employs an analytical model based on the diffusion equation and statistical analyses to explore the dependency of estimated concentration changes on various systematic parameters, such as choice of wavelengths, spectral bandwidth, and uncertainties in extinction coefficient (ε) and differential pathlength factor (DPF). When there is a 10% uncertainty in DPF and ε, errors were found to be highly dependent on the number of discrete wavelengths, but not on their bandwidth if appropriate considerations are taken to account for it.

We measured the average group refractive index (RI) of 120 isolated lenses from 120 human donors (age: 0.03 to 61 years). The average group RI was calculated from a measurement of the optical thickness of the lens using optical coherence tomography and the apparent window shift of the test chamber caused by the lens. The estimated measurement uncertainty was ±0.004. The group RI at 880 nm was converted to phase RI at 589 nm using the dispersion equation of water and protein. From 2 to 61 years, the mean value of the RI was 1.415 ± 0.002 (group index at 880 nm) and 1.406 ± 0.002 (phase index at 589 nm) independent of age (p = 0.774). Two lenses from donors of age 0.33 and 3 months had significantly lower RI (group index: 1.405 and 1.403; phase index: 1.396 and 1.394). From age 2 to 61, the average lens RI is constant with age within the measurement uncertainty (±0.004).

Fluorescence fluctuation-based super-resolution microscopy (FF-SRM) is an economical and widely applicable technique that significantly enhances the spatial resolution of fluorescence imaging by capitalizing on fluorescence intermittency. However, each variant of FF-SRM imaging has inherent limitations. This study proposes a super-resolution reconstruction strategy (synSRM) by synergizing multiple variants of the FF-SRM approach to address the limitations and achieve high-quality and high-resolution imaging. The simulation and experimental results demonstrate that, compared to images reconstructed using single FF-SRM algorithms, by selecting suitable synSRM routes according to various imaging conditions, further improvements of the spatial resolution and image reconstruction quality can be obtained for super-resolution fluorescence imaging.

The classic multiple instance learning (MIL) paradigm is harnessed for weakly-supervised whole slide image (WSI) classification. The spatial position relationship located between positive tissues is crucial for this task due to the small percentage of these tissues in billions of pixels, which has been overlooked by most studies. Therefore, we propose a framework called TDT-MIL. We first serially connect a convolutional neural network and transformer for basic feature extraction. Then, a novel dual-channel spatial positional encoder (DCSPE) module is designed to simultaneously capture the complementary local and global positional information between instances. To further supplement the spatial position relationship, we construct a convolutional triple-attention (CTA) module to attend to the inter-channel information. Thus, the spatial positional and inter-channel information is fully mined by our model to characterize the key pathological semantics in WSI. We evaluated TDT-MIL on two publicly available datasets, including CAMELYON16 and TCGA-NSCLC, with the corresponding classification accuracy and AUC up to 91.54%, 94.96%, and 90.21%, 94.36%, respectively, outperforming state-of-the-art baselines. More importantly, our model possesses a satisfactory capability in solving the imbalanced WSI classification task using an ingenious but interpretable structure.