Biomedical optics express最新文献

Welcome to the 2024 Feature Issue on Diffuse Optical Spectroscopy: Technology and Applications in Biomedical Optics Express! This feature issue provides an exemplary sample of established and emerging DOS technologies as well as their biomedical applications through 27 contributed research papers and 1 invited review article. DOS researchers are inherently multidisciplinary, advancing topics spanning the basic theory of light-tissue interactions, computational modeling, technique and system development and preclinical and clinical applications. You will find this full range of topics represented in this feature issue.

We compared the peripheral refractive measurements of a recently proposed laser-scanning instrument with an established peripheral refractor. Two-dimensional refractive maps were obtained using both instruments for 18 young subjects with differing values of central refraction. The comparison shows a strong correlation between devices in the overlapping measurement area, with the new device extending the range of the explored retinal area to a 100-degree-diameter circular patch, compared to the 60°x35° rectangular area of the older peripheral refractor. Larger refractive maps exhibit trends that cannot be easily predicted from narrower scans. These results demonstrate that the new instrument can be a useful tool for assessing wide-angle peripheral optical data in the human eye.

We present ATLAS, a 512 × 512 single-photon avalanche diode (SPAD) array with embedded autocorrelation computation, implemented in 3D-stacked CMOS technology, suitable for single-photon correlation spectroscopy applications, including diffuse correlation spectroscopy (DCS). The shared per-macropixel SRAM architecture provides a 128 × 128 macropixel resolution, with parallel autocorrelation computation, with a minimum autocorrelation lag-time of 1 µs. We demonstrate the direct, on-chip computation of the autocorrelation function of the sensor, and its capability to resolve changes in decorrelation times typical of body tissue in real time, at long source-detector separations similar to those achieved by the current leading optical modalities for cerebral blood flow monitoring. Finally, we demonstrate the suitability for in-vivo measurements through cuff-occlusion and forehead cardiac signal measurements.

An experimental testbed was constructed to rigorously assess the fundamental limits of light-wave sensing-an economic, non-contact vitals monitoring approach previously reported. We improve the testbed using lock-in amplification and demonstrate that a photodetector and a commonplace array of infrared LEDs are sufficient to detect respiratory motion and quantify respiration rate up to 2.5 meters away. We propose a novel scattering model, from which we derive the performance limits of the light-wave sensing system in terms of a theoretical range resolution limited by the dynamic range of the system. Using a robotic breathing phantom, we experimentally assess, for the first time, the range resolution of the testbed system and compare this to theoretical predictions. This work also introduces a process for generating stochastic respiration patterns, which may prove broadly useful to the designers of breathing phantoms. Holistically exploring practical challenges and analytical models, this paper serves as a unique and comprehensive tutorial for understanding and designing light-wave sensing systems.

In this study, an in vitro comparison of the optical performances of three models (spherical, aberration-neutral, and aberration-correcting) of monofocal intraocular lenses (IOLs) is proposed. A comprehensive model is employed, encompassing a wide range of corneal models and aperture sizes, reflecting the high variability of corneal spherical aberrations (SA) and pupil sizes in both normal and postoperative refractive corneal surgery populations. Analysis of average through-focus modulation transfer function (MTF) curves reveals significant differences in optical performance attributable to pupil size and corneal SA. These differences depend on the IOL model and affects MTFmax (representing contrast at best focus), depth of focus, refractive error tolerance, and the effective power of the lens.

Retinal image quality assessment (RIQA) is crucial for diagnosing various eye diseases and ensuring the accuracy of diagnostic analyses based on retinal fundus images. Traditional deep convolutional neural networks (CNNs) for RIQA face challenges such as over-reliance on RGB image brightness and difficulty in differentiating closely ranked image quality categories. To address these issues, we introduced the Dual-Path Frequency-domain Cross-attention Network (DFC-Net), which integrates RGB images and contrast-enhanced images using contrast-limited adaptive histogram equalization (CLAHE) as dual inputs. This approach improves structure detail detection and feature extraction. We also incorporated a frequency-domain attention mechanism (FDAM) to focus selectively on frequency components indicative of quality degradations and a cross-attention mechanism (CAM) to optimize the integration of dual inputs. Our experiments on the EyeQ and RIQA-RFMiD datasets demonstrated significant improvements, achieving a precision of 0.8895, recall of 0.8923, F1-score of 0.8909, and a Kappa score of 0.9191 on the EyeQ dataset. On the RIQA-RFMiD dataset, the precision was 0.702, recall 0.6729, F1-score 0.6869, and Kappa score 0.7210, outperforming current state-of-the-art approaches.

Retinal vasculature is the only vascular system in the human body that can be observed in a non-invasive manner, with a phenotype associated with a wide range of ocular, cerebral, and cardiovascular diseases. OCT and OCT angiography (OCTA) provide powerful imaging methods to visualize the three-dimensional morphological and functional information of the retina. In this study, based on OCT and OCTA multimodal inputs, a multitask convolutional neural network model was built to realize 3D segmentation of retinal blood vessels and disease classification for different retinal diseases, overcoming the limitations of existing methods that can only perform 2D analysis of OCTA. Two hundred thirty sets of OCT and OCTA data from 109 patients, including 138,000 cross-sectional images in normal and diseased eyes (age-related macular degeneration, retinal vein occlusion, and central serous chorioretinopathy), were collected from four commercial OCT systems for model training, validation, and testing. Experimental results verified that the proposed method was able to achieve a DICE coefficient of 0.956 for 3D segmentation of blood vessels and an accuracy of 91.49% for disease classification, and further enabled us to evaluate the 3D reconstruction of retinal vessels, explore the interlayer connections of superficial and deep vasculatures, and reveal the 3D quantitative vessel characteristics in different retinal diseases.

Optical quality bioresorbable materials have been gaining interest in recent years for various interstitial biomedical/medical application. An example of this is when the implant gradually dissolves in the body, providing physiological information over extended periods of time, hence reducing the need for revision surgeries. This study reports for the first time the in-house fabrication of single mode (at 785 nm) calcium phosphate glass (CPG) based bioresorbable optical fibers and investigates their suitability for microvascular blood flow monitoring using diffuse correlation spectroscopy (DCS). Ex vivo experiments in liquid phantom and non-invasive in vivo experiments on the human forearm muscle were conducted using multimode and single mode CPG bioresorbable optical fibers. The retrieved flow index from the correlation curves acquired using CPG fibers was in good agreement with that obtained using standard silica (Si) fibers, both ex vivo and in vivo. The results demonstrate the potential of CPG optical fibers for further exploration.

3D cell cultures are widely used in biomedical research for the recapitulation of in vivo microenvironments. Viability assessment and monitoring of these intricate conformations remain an open problem as standard cell viability protocols based on colorimetry or microscopy are not directly applicable to intact 3D samples. Optical coherence tomography (OCT) has been explored extensively for subsurface structural and quasi-functional analysis of 3D cell cultures and tissue. Recent studies of dynamic OCT as a source of cellular contrast have found qualitative associations with necrosis in cell spheroids, suggesting potential as a viability marker. We present empirical and validated evidence for dynamic OCT as a quantitative indicator of cell viability in 3D cultures. We analysed over 240 MCF-7 cancer cell spheroids with dynamic OCT and corresponding viability measurements using the trypan blue exclusion assay. Significant effects of common reagents dimethyl sulfoxide (DMSO) and phosphate-buffered saline (PBS) on OCT readouts were noted. We proposed a regression-based OCT brightness normalisation technique that removed reagent-induced OCT intensity biases and helped improve correspondence to the viability assay. These results offer a quantitative biological foundation for further advances of dynamic OCT as a novel non-invasive modality for 3D culture monitoring.

Endotracheal tube (ETT) intubation is a medical procedure routinely used for achieving mechanical ventilation in critically ill patients. Appropriate ETT placement is crucial as undetected tube migration may cause multiple complications or even fatalities. Therefore, prompt detection of unplanned movement of the ETT and immediate action to restore proper placement are essential to ensure patient safety. Despite this necessity, there is not a widely adopted tool for real-time assessment of ETT displacement. We have developed a device, a dual-camera endotracheal tube or DC-ETT, to address this unmet clinical need. This device uses a near-infrared (NIR) LED and a side-firing optical fiber embedded in the side of an ETT to light up the tracheal tissue and a visible and NIR camera module for the displacement detection. The NIR camera tracks the movement of the NIR pattern on the skin, while the visible camera is used to correct the body movements. The efficacy of the DC-ETT was assessed in two piglets with a linear displacement sensor as reference. A mean discrepancy of less than 0.5 mm between the DC-ETT and reference sensor was observed within a displacement range of ±15 mm. The results suggest that the DC-ETT can potentially provide a simple and cost-effective solution for real-time monitoring of ETT displacements in operating rooms, intensive care units, and emergency departments.