Journal of Biophotonics

Cardiac amyloidosis is caused by deposits of misfolded proteins in the heart and can lead to heart failure. Histological confirmation typically involves staining tissue sections with Congo red and examining them under polarized light for apple-green birefringence; however, achieving an interpretable, label-free, and observer-independent assessment remains challenging. Here we show that Pearson kurtosis of channel intensities within the amide I window provides an interpretable, fitting-free contrast for cardiac amyloid in unstained human cardiac tissue sections from ten participants imaged by ultrabroadband multiplex coherent anti-Stokes Raman scattering (CARS). In a discovery participant, high-kurtosis regions corresponded with Congo red-positive tissue in two CARS-histology pairs of adjacent sections (descriptive spatial AUCs, 0.79 and 0.73). Across 15 fields from nine additional participants, field-level kurtosis values did not overlap between severe-deposition and Congo red-negative tissue fields. Among the descriptors examined, kurtosis showed the largest standardized participant-level separation. Exploratory multivariate curve resolution yielded a deposit-associated component with aromatic-residue features shared with reagent transthyretin. In one field from the discovery participant, the second harmonic generation (SHG) signal, acquired simultaneously with CARS, showed a broadly inverse spatial pattern relative to the amide I kurtosis map, revealing distinct tissue-architectural contrast. Together, these findings support a potential label-free approach to detecting cardiac amyloid deposits that combines amide I kurtosis derived from broadband CARS with SHG-derived architectural contrast.

The ultrastructure of endothelial cells (ECs) "in situ" is of great interest due to their involvement in many physiological processes. In some organs, these cells form transcellular pores or fenestrae, allowing for the rapid exchange of molecules between blood and interstitium. Despite their importance, no optical images of these dynamic morphological structures have yet been acquired in situ. Major obstacles to their in-situ imaging are the lack of specifical labels for fenestrae and their size well below the optical diffraction limit. Here, we report how we have overcome these challenges and managed to visualize the EC ultrastructure in situ in 25 {micro}m thick liver sections. To enable this, a lipophilic, fluorescent membrane dye was infused into the portal vein of murine livers to stain the sinusoidal ECs before the organ was harvested. Tissue sections were subsequently imaged using a novel, super-resolution optical-sectioning structured illumination microscope (OS-SIM), providing approx. 170 nm spatial resolution with significantly faster image acquisition compared to confocal microscopy.

Continuous wave diffuse correlation spectroscopy (cw-DCS) is a noninvasive optical technique to monitor the tissues blood flow changes. This technique measures the tissue blood flow index (BFI) by evaluating the decay rate of the autocorrelation function. The derived BFI is proportional to mean squared displacements of the red blood cells considered as the fast-dynamic scatterer component of tissue in time. However, biological tissue contains static scatterer component and slow-dynamic scatterer component which affect the decay rate of autocorrelation function and as a result the derived BFI. In this study, we assessed the fractional contribution of static, slow-dynamic and fast-dynamic scatterer components of a medium in the flow index derived by cw-DCS. The measurements performed on Agar-based phantom with tube showed that presence of static scatterer component and slow-dynamic scatterer component led to substantial underestimation ({approx} 123%) of the flow index derived by Siegert relation, compared to effective diffusion coefficient of fast-dynamic scatterers components derived by modified Siegert relation and bi-exponential model. The less underestimation was observed for the corresponding parameters obtained from the liquid phantom measurements ({approx} 25%) as well as during the forearm occlusion test and respiratory challenges ({approx} 16% - 26%).

Uniform, reproducible blood smears are critical for reliable hematological evaluation. Manual smear preparation, however, is user-dependent and introduces variability that limits quantitative microscopy. Here we developed BUsmear, a low-cost, 3D-printed, motorized blood smear device that prepares two smears simultaneously from a printed stage and a micro-motor drive with tunable linear velocity, controlled through a joystick-operated driver module. By spreading two slides in parallel with fully repeatable slide-to-slide motion, the device doubles throughput while eliminating operator-dependent motion artifacts, and can be fabricated on any benchtop 3D printer in under one day. To validate smear quality, we analyzed blood films from three donors together with a manual smear prepared by an expert from the blood of one of the same donors, giving a matched device-versus-manual pair. Automated Cellpose segmentation of 14,046 red blood cells across 12 bright-field fields showed that cell diameter was preserved and closely matched the expert smear (6.7-7.8 um across groups, within the 6.2-8.2 um human reference range; 6.7 vs 6.9 um in the matched pair), and that all films formed non-aggregated monolayers (Clark-Evans index of aggregation 1.04-1.24). Critically, red blood cells in the device films were markedly more circular than in the expert manual smear (mean eccentricity 0.405 vs 0.502; 0.443 vs 0.502 in the matched pair), with complete separation between the two methods at the level of whole fields of view. Because eccentricity reports smear-induced cell distortion, this indicates that a constant, mechanically controlled spreading velocity preserves red blood cell morphology better than skilled manual technique. BUsmear offers an accessible route to standardized smear geometry for quantitative analysis, including AI-based morphometry, and its low cost may be particularly advantageous in low-income countries with a high prevalence of malaria.

Abstract Background Advanced in vitro models of the human heart have become promising tools for studying cardiac diseases and drug discovery. Three-dimensional (3D) engineered heart tissues (EHTs) provide more adult cardiac tissue-like structural organization compared to traditional two-dimensional (2D) in vitro models with straightforward contractile readouts. However, the assessment of the architecture of EHTs, especially the quantification of cellular and tissue structural components, has remained poorly studied. Here we demonstrate the use of light-sheet microscopy for structural imaging of intact EHTs and provide quantification of the EHT cellular and subcellular structures. Methods We developed an in-house inverted selective plane illumination microscopy (iSPIM) platform and combined it with iterative indirect immunofluorescence (IT-IF) staining for better signal acquisition. We developed an image-processing and analysis pipeline dedicated to volumetric EHT analysis. Results With this integrated platform, we achieved volumetric imaging of intact EHTs and quantification of 3D tissue architecture, revealing aligned cardiomyocytes within the imaged volume and increasing cardiac nuclei content towards the core of the tissue. The developed methods allowed the detection of heterogeneities between tissue sections, demonstrating the sensitivity required for future disease modeling or maturation studies. Conclusions The developed integrated platform opens new possibilities for volumetric analysis and characterization of 3D tissue structure using iSPIM, providing new insights into EHT architecture and the use of EHTs as disease modeling tools.

Spatial frequency domain imaging (SFDI) has demonstrated the ability to provide early, quantitative assessment of burn wound severity. Previous studies using a research-grade SFDI platform showed that high-dimensional datasets incorporating multiple spatial frequencies and wavelengths can predict healing outcomes in controlled porcine models of graded burns. To assess the impact of reduced measurement dimensionality on diagnostic performance, we compared classifications derived from a research-grade SFDI system (Reflect RS) with those obtained using a simplified commercial SFDI platform (Clarifi RS). Both systems were used to image graded burns 24 hours after injury. Pixel-level classifiers were trained using regions defined by 28-day healing outcomes, and models based on the full Reflect dataset were compared with classifiers generated from reduced Reflect feature sets and datasets designed to mimic Clarifi acquisition features. Performance was evaluated using leave-one-subject-out validation. The full Reflect dataset achieved the highest classification performance, with mean F1 scores approaching 0.88. Although reducing the number of measured features decreased classification accuracy, simplified models and Clarifi-based datasets maintained F1 scores greater than 0.8 for binary classification. These findings indicate that dimensionality reduction produces a measurable but manageable loss in performance and support the development of clinically practical, application-specific SFDI systems for burn assessment.

SignificanceDiffuse Correlation Spectroscopy (DCS) is an established technique for non-invasive monitoring of Cerebral Blood Flow (CBF), but existing applications primarily measure CBF changes averaged over cortical tissue volumes. A method capable of targeting blood flow within a particular intracranial artery would expand the utility of DCS for vessel-specific cerebral perfusion monitoring and continuous bedside assessment. AimWe aim to investigate the feasibility of targeted, non-invasive monitoring of blood flow in the Anterior Cerebral Artery (ACA) using DCS through optimization of probe geometry and placement. ApproachA custom-built DCS system operating at 785 nm was used to probe ACA from the glabellar region. Source-detector (SD) separation, probe orientation, and probe location were systematically optimized using lower-limb motor tasks and a mental arithmetic task. The optimized configuration was evaluated using an ACA-mimicking multilayer phantom and validated in forty healthy volunteers during lower-limb activation tasks and postural changes. ResultsAn SD separation of 17 mm, vertical probe orientation, and glabellar placement provided the highest sensitivity to ACA-related blood flow changes. Phantom experiments demonstrated sensitivity to flow changes in a vessel located 45 mm beneath the scalp and showed that the frontal sinus, cerebrospinal fluid, and the absence of cortical tissue beneath the glabella along the longitudinal fissure together provide the best optical window for probing deep ACA flow. Using the optimized probe configuration, significant increases in relative CBF were observed during standing leg marching (66.4 {+/-} 38.6%) and supine leg crunches (39.4 {+/-} 32.2%) (p < 0.01), with consistent responses during supine-to-stand postural transitions. ConclusionThe proposed DCS approach enables targeted measurement of blood flow within the ACA territory. This technique provides a framework for continuous, non-invasive monitoring of ACA perfusion and has potential applications in cerebrovascular monitoring and stroke care.

Significance: Continuous, non-invasive monitoring of cardiovascular physiology provides critical information for clinical decision-making and patient care. Emerging optical sensors enable non-contact measurement of physiological parameters such as heart rate and respiratory rate, but current methods are limited in their ability to capture spatially resolved physiological waveforms. Aim: We aimed to extend the capabilities of non-contact cardiovascular monitoring by using an imaging-based approach from which spatially resolved physiological waveforms can be extracted and cardiovascular biomarkers can be derived in vivo. Approach: We implemented a digital holographic imaging sensor to continuously measure calibrated tissue motion for in vivo assessment of cardiovascular biomarkers in six adult male Sprague-Dawley rats, with validation against electrocardiographic and invasive arterial blood pressure measurements. Results: Heart rate and pulse arrival time-derived pulse wave velocity calculated from digital holographic imaging demonstrate strong agreement with reference-derived metrics (concordance correlation coefficient [&ge;] 0.98). Heart rate variability shows moderate agreement with reference-derived metrics (concordance correlation coefficient [&ge;] 0.59).

Mechanical stretchers are used to physically expand biological samples for microscopic studies of mechanobiology. Existing stretchers suffer from limited strain capacity and non-quantifiable forces, along with focus drift and feature-tracking limitations during microscopy. We develop an iris-based cell stretcher that applies isotropic equibiaxial force to achieve aerial strain of 1664% that corresponds to 4.2x linear expansion for Tensile Expansion Microscopy (TExM), a super-resolution method which increases sample size above the diffraction limit of light. The TExM stretcher uses 3D-printed, printed circuit board (PCB) and cost-effective parts, is portable and automated. We verify the performance of the TExM cell stretcher using image analysis, achieving ~90% mechanical precision, a maximum of four degrees of arm angular deviation, precise speed control down to 0.01 cm/sec, and an average expansion resolution of 3.98 x 10^-3 x. Integrated strain gauge sensors confirm equal application of force by each arm of the stretcher throughout expansion and finite-element simulation and planar-polariscope photoelastic imaging characterize the uniform substrate stress distribution while indicating high stress at the substrate gripping area. An AutoTracking software in communication with the stretcher hardware and microscope enables continuous autofocus and feature tracking during TExM and fiducial markers verify uniform equibiaxial stretch. The stretcher is demonstrated with fixed NIH 3T3 fibroblasts and live HeLa cells, observing ~4x cellular expansion of fixed cell size and separation of live cell clusters, highlighting the potential of TExM cell stretcher for biological imaging.

Objective: To develop and validate a dual-probe Diffuse Correlation Spectroscopy (DCS) system for non-invasive and simultaneous, monitoring of cerebral blood flow (CBF) in the bilateral Middle Cerebral Artery (MCA) territories, and expanding the utility of conventional DCS limited to cortical-volume-based CBF measurements to vessel-specific cerebral perfusion monitoring. Methods: A dual-probe DCS system was designed for non-invasive monitoring of MCA-specific perfusion. Probe placement and protocol optimization study has been performed using anatomical landmarks, motor and speech activation tasks in healthy volunteers. System stability and repeatability were further evaluated in a pilot cohort of 30 healthy (age, 25{+/-}7 years) participants using optimized probe position and protocol. A bilateral MCA ischemic Lacunar Infract stroke case report also validated the feasibility of the system in clinical settings. Results: Measurements demonstrated superior sensitivity towards MCA-territory perfusion at targeted probe locations compared to off-MCA positions. In pilot cohort, significant increase of 30.34 {+/-} 21.56% and 36.48 {+/-} 21.22% in rCBF corresponding to hand squeeze and speech task respectively showed reproducible physiological responsiveness of the system (p<0.001). Measurement done on a patient with bilateral MCA ischemic Lacunar Infract stroke showed a significant change of 30% during speech for both the MCAs but no significant change is observed for hand squeeze tasks. Conclusion: The custom built dual-probe DCS system enables non-invasive, operator-independent, targeted and continuous monitoring of rCBF within bilateral MCA territories. Significance: This approach enables the potential use of DCS system for bilateral and vessel-specific monitoring of cerebral perfusion in the MCA territories.

Background and Objective: High-speed and high-resolution retinal imaging using adaptive optics line confocal ophthalmoscopy (AOLCO) resolves individual red blood cells (erythrocytes) flowing through the smallest retinal capillaries, but quantifying their velocity first requires removing linear and nonlinear distortions caused by eye motion that may result in a displacement of tens to hundreds of pixels between frames. We present a computational pipeline that stabilizes AOLCO capillary video and measures erythrocyte velocity in true physical units, delivered as an interactive 3D Slicer extension and a batch command-line tool sharing one analysis core. Methods: Our video analysis pipeline has four stages: preprocessing, registration, postprocessing, and velocity measurement. During preprocessing, illumination is corrected, and closed-eye frames are identified. During registration, each frame is aligned to a reference frame using affine and, when needed, B-Spline registration, initialized by our robust and fast (GPU-based) translation-registration algorithm to accommodate large eye movements (e.g., microsaccades). During postprocessing, adjacent registered frames are differenced to suppress stationary structures, and a 2D projection of the frame-difference video reveals the capillary network. During velocity measurement, an operator manually identifies capillary segments on the 2D projection image. Spatiotemporal images are then generated along these segments from the frame-difference video, and blood-flow velocity curves are obtained from these images using the Radon transform. Results: We validate the velocimetry of the pipeline against synthetic ground-truth flow data, and the experiments show that the velocimetry recovers the speed within an error of 4% The GPU-based translation registration algorithm aligns the large eye motions (~90 um per frame on average) and runs about 3.6 x (100 Hz) to 38 x (400 Hz) faster than the baseline method. Across the full cohort (2344 videos, 57 subjects, 30 Hz to 400 Hz), our registration approach improves structural similarity (SSIM) of the video frames on every acquisition from 0.73 to 0.86. The recovered blood flow velocities are physiologically plausible, of the same order as published AO measurements. Conclusions: Our computational pipeline enables AOLCO velocimetry on the capillary-level.

Background Automated colonoscope navigation requires a way to determine where the lumen continues. One possible approach is to estimate the distance from the endoscope tip to the surrounding wall. However, adding a range sensor to a conventional colonoscope is technically difficult, and depth estimation from monocular endoscopic images remains challenging. We considered a simpler possibility. Because the light source of an endoscope is located close to the camera, distant regions of the lumen tend to appear darker than nearby walls. Aim To determine whether lumen direction can be estimated from image brightness alone in a patient-derived virtual colon, and to compare this estimate with one obtained from true wall distances. Methods A virtual colon was reconstructed from the author's CT colonography data (0.5 mm isotropic resolution). Endoluminal images were rendered at 342 positions along 1368 mm of the colonic centreline. At each position, the image was divided into 24 x 24 directional cells. Lumen direction was estimated from the darkness-weighted centroid of the largest connected component among the darkest 10% of cells. For comparison, the true distance from the virtual endoscope to the wall was obtained by ray casting, and a distance-based direction was calculated using the same method. Two illumination models were tested: a directional light without distance attenuation and a point source at the endoscope tip with distance attenuation. Results With point-source illumination, the brightness-based direction closely matched the distance-based direction, with a median angular difference of 2.5 degrees. Differences greater than 30 degrees occurred in 2.3% of frames. Within each frame, brightness and true wall distance were negatively correlated in all 342 frames (median Spearman rho = -0.770). Using the direction toward the centreline point 40 mm ahead as a fixed geometric reference, the median angular error was 6.6 degrees for the brightness-based estimator and 6.5 degrees for the distance-based estimator. The median frame-by-frame difference in error was -0.09 degrees. In contrast, the brightness cue failed under directional illumination without distance attenuation (median difference from the distance-based direction, 43.1 degrees). Conclusion In this patient-derived virtual colon, image brightness provided nearly the same lumen-direction information as exact wall distance when a point-source illumination model with distance attenuation was used. Exact metric distance was therefore not necessary for this specific navigation task. These findings suggest a simple, learning-free approach to semi-autonomous colonoscope steering based on image brightness and deterministic calculation.

The mechanical properties of red blood cell (RBC) membranes are critical to their function in oxygen delivery, and changes to these properties as RBCs age affect their journey around the circulatory system, including clearance by the spleen. Such changes can also have significant health effects,including in cardiovascular disease and on the interactions between RBCs and malaria parasites. The function of RBCs requires them to be very soft, which together with the small size of the cells brings the energy required for measurable deformation of the membrane into the range of typical thermal energies. Red Blood Cells can be observed to flicker under optical microscopy, and these shape fluctuations can be quantified and used to obtain key biophysical parameters such as the tension and bending modulus of the membrane. Typically the shape of the cell's equator is extracted, and the mean power spectrum is obtained by time-averaging the power present in the normal modes of the thermal fluctuations. Flickering spectroscopy has been used extensively on RBCs, but has so far been very low throughput and with some technical limitations. Here we address issues related to active versus passive fluctuations, focusing and optics, camera exposure and sampling, and fast contour detection. In combination with an automated imaging system it is possible to measure thousands of cells in one day, with no user input. We validate this new pipeline by chemical modification of RBC mechanics, and by comparison with simulated fluctuations including each confounding effect. The methods and codes for this robust flickering analysis will allow consistent measurements across labs.

This study presents a systematic investigation of the brain's own microwave emissions in the 0.85-5.0 GHz range, aiming to validate microwave encephalography (MWEG) as a novel tool for cognitive state assessment. Early experiments (2016-2019) using comparisons with background noise, a control phantom, and different antenna types confirmed the endogenous origin of the recorded signals. In a 2021 experiment (118 measurements on one subject, right and left occipital areas), we observed a significant functional hemispheric asymmetry: the number of "substantial spikes" was significantly higher in darkness for the right hemisphere (p<0.001) and higher in light for the left hemisphere (p<0.001). A 2025 group study (three subjects) confirmed the asymmetry (p<0.05 for right, p<0.01 for left). We describe the signal processing pipeline, including spike detection and statistical analysis. Two complementary mathematical models are presented: an energy-based model linking optical input to microwave emission via neural activity modes, and an information-based model interpreting spectral changes in terms of structural pattern overlap with memory engrams. An estimation of the physical dimensions of possible brain resonators (2-22 mm) is provided. The results are discussed in the context of hemispheric specialization and the information commutation theory. This work opens new perspectives for developing low cost, contactless brain monitoring systems.

This study aims to improve the detection performance of age-related macular degeneration (AMD) in low-quality retinal images. BackgroundAMD is a leading cause of vision loss among older adults globally, and accurate detection is crucial for clinical management. However, low-quality optical coherence tomography (OCT) images significantly compromise diagnostic accuracy. ObjectiveTo enhance AMD detection in low-quality images using noise-augmented data augmentation and an improved YOLO deep learning model. MethodsPublic datasets from UCSD and Duke University were utilized; the training dataset comprised 24,980 OCT images (high-quality and noise-augmented low-quality), while the testing dataset included 1,000 images (584 AMD, 416 normal). The model is based on the YOLOv8n framework, integrated with Squeeze-and-Excitation blocks (SEblock) and Adaptive Sparse Self-Attention (ASSA), with an additional 160x160 detection layer for detecting small lesions. Evaluation metrics included accuracy, sensitivity, specificity, and F2-score. ResultsThe proposed model achieved an accuracy of 99.02%, sensitivity of 98.17%, specificity of 100%, and an F2-score of 98.50% on the Duke dataset. Detection rates were significantly improved compared to traditional methods, particularly in low-quality images, with a detection rate of 89.60%, markedly superior to original YOLOv8n (55.10%) and classical models like ResNet50. ConclusionThe enhanced model, employing noise-augmented training data and improved attention mechanisms, demonstrates excellent AMD detection capabilities in low-quality OCT images, showing broad potential for clinical applications.

Background and Aims: Vibration-controlled transient elastography (VCTE) and two-dimensional shear-wave elastography (2D-SWE) are used to assess liver stiffness in metabolic dysfunction-associated steatotic liver disease (MASLD); patients may be assessed by different methods over time. Because 2D-SWE fibrosis cut-offs are not uniformly validated and no biopsy or magnetic resonance elastography reference is available, we asked whether switching methods moves patients across decision thresholds. We evaluated agreement and decision-threshold interchangeability between VCTE and 2D-SWE in MASLD with obesity. Methods: In a retrospective cross-sectional agreement study at a tertiary-care center, 317 consecutive adults with MASLD underwent same-day VCTE (FibroScan) and GE LOGIQ E9/E10 2D-SWE. Continuous agreement was assessed by Bland-Altman analysis; the categorical analysis compared binary clinical decision thresholds (VCTE [&ge;]8.0/[&ge;]10.0 kPa; 2D-SWE [&ge;]7.204/[&ge;]8.060 kPa) using Cohen {kappa} and McNemar tests. Prespecified sensitivity analyses and a post-hoc recalibration were performed; VCTE served as operational reference. Results: VCTE yielded higher values (geometric mean VCTE/2D-SWE ratio, 1.23; ratio limits of agreement, 0.64 2.40; intraclass correlation coefficient, 0.41). At the lower threshold, 71 of 117 VCTE-positive patients (61%) were below the 2D-SWE threshold versus 5 of 200 (2.5%) reclassified upward (agreement 76.0%; {kappa} 0.417; P<.001); the upper threshold was similar (38 of 63, 60%, vs 8 of 254, 3.1%). Discordance persisted across cut-offs; agreement worsened descriptively across BMI strata. Recalibration removed the directional asymmetry but not the discordance (agreement unchanged, 76.0%). Conclusions: In MASLD patients, switching from VCTE to 2D-SWE reclassified decision-threshold status in ~60% of VCTE-positive patients; recalibration removed the directional bias but not the disagreement. Follow-up should use the same elastography modality and, when possible, the same platform.

Point-of-care (POC) molecular detection has enabled rapid and accessible testing at or near the site of need, facilitating timely decision-making in clinical, field, and industrial settings. Despite these advancements, molecular detection platforms remain limited in their ability to prepare DNA from complex tissue matrices, restricting their applicability to a narrow range of sample types. To address sample preparation inefficiencies, focused ultrasound extraction (FUSE) has been developed for the rapid release of DNA from robust tissue matrices. FUSE disintegrates target tissue and releases DNA by delivering high pressure ultrasound pulses that generate a cavitation bubble cloud. In prior work, FUSE was performed using large, laboratory-based equipment. Here, a miniaturized FUSE device was designed and tested to enable POC DNA sample preparation. Design constraints were defined based on prior FUSE experiments, and based on these metrics, a 750 kHz cylindrical transducer was fabricated. The pressure output was measured, and high-speed optical imaging demonstrated that the transducer generated sustained cavitation within the defined focal region. The feasibility of DNA extraction from piscine and timber tissues was evaluated, and results show that the device can release DNA with quality suitable for PCR-based detection from both tissue types. These results demonstrate the potential of this device to rapidly extract DNA from complex samples and expand the applicability of molecular detection platforms.

The measurement of light received at the cornea of the eye is a paramount consideration for the understanding of the relation between environmental illumination and the non-image-forming effects of light. The field of view (FOV) at the cornea is less than a full hemisphere, because it is partially occluded by human facial morphology. The International Commission on Illumination (CIE) has defined a standard model of human FOV. A suitably designed physical occluder attached to the sensor (of a light meter) has been proposed as a means of incorporating the effect of human FOV when taking measurements. Similarly, when using simulation to predict light received at the cornea, a geometrical description of the occluder at the eye point(s) can be added to the 3D model of the scene. The first occluder model proposed to represent CIE human FOV was enumerated in terms of: the CIE definition; the radius of the occluder; and, the radius of the light sensor disc. We present a simpler model based only on the CIE definition and the occluder radius. Both models were tested using a virtual goniophotometer. Various sensor response functions describing the spatial sensitivity across the sensor disc, including several we characterized through laboratory measurements, were included in the test. For all functions considered, the performance of the simpler occluder model was equivalent to or better than the model first proposed.

Gas-bubble-enhanced focused ultrasound (FUSGB) is advancing clinically across a myriad of applications, including targeted drug delivery through transient blood-brain barrier opening (BBBO). Its broader translation requires a better understanding of the bioeffects that enable reproducible enhancement of barrier permeability while avoiding vascular injury, underscoring the need to clarify the relationship between acoustic exposure, bubble activity, and the biological response central to treatment optimization. These interactions are difficult to isolate in vivo, and acoustic reflections, geometry, and field distortion in conventional cultureware hinder quantitative in vitro studies. Herein, we present a theoretically and experimentally characterized ultrasound-transparent organ-on-chip device with >99.9% US transparency that enables quantitative in vitro modeling of the FUSGB procedure and study of BBBO. Furthermore, submicron bubbles (sMB, ~800nm) were fabricated and characterized. Acoustic dose-dependent subharmonic and broadband cavitation dose curves (SCD and BCD), as well as temporal responses, were studied. A 3-day accelerated Caco--2 surrogate barrier with a high TEER (~1200xcm2) was used to demonstrate US dose-dependent targeted barrier opening, visualized using an in vitro Evans Blue assay. Together, this study and its findings establish a foundation for quantitative in vitro modeling of FUS BBBO, as well as other US interactions in microphysiological systems, supporting systematic evaluation of procedural regimens, large-parameter-space optimization, acoustic safety window, and exposure conditions for brain drug delivery, and additionally enabling mechanistic insight into FUSGB BBBO.

Optical coherence tomography angiography (OCTA) has been extensively explored for the detection of pathological retinal changes arising in various ophthalmological diseases. Due to phase instability of conventional systems, most OCTA signal processing methods to date have relied on intensity-based averaging, despite the resulting lower contrast and dynamic range compared to coherent averaging approaches. In this work, we (1) present a novel computation pipeline that enables fully-coherent processing in any phase-stable or phase-unstable system, and (2) demonstrate the first angiography metric with integrated signal-to-noise ratio (SNR) correction and coherent spatiotemporal ensemble averaging effective in any OCT system. Our method does not rely on 2D en face projections or binarization to produce high-contrast en face views and it significantly enhances the contrast-to-noise ratio of computed OCTA volumes, particularly in regions with reduced SNR levels. Our OCTA volumes also have high cross-sectional quality, enabling the use of single-depth en face views and the localization of capillary paths in the axial dimension. We can now identify capillaries below the retinal pigment epithelium, near the lamina cribrosa in the optic cup, which was not previously possible due to low SNR. We also conducted an analysis of strategies for bias reduction in OCTA and developed the optimal method utilizing coherent spatiotemporal ensemble averaging. Because our method leverages coherent averaging across all dimensions, it provides flexibility in shaping the averaging kernel to target specific workflows. The value of this additional degree of freedom is illustrated in our vessel tracing investigations, in which the depth resolution was maximized by limiting coherent ensemble averaging to the two lateral dimensions even in presence of strong phase noise, enabling the identification of 3D features such as overlapping capillary paths.