Data Efficiency of Segment Anything Model for Optic Disc and Cup Segmentation

We investigated the performance of Segment Anything Model (SAM)—the first promptable foundation model for image segmentation—for optic disc (OD) and optic cup (OC) segmentation when fine-tuned on progressively smaller number of fundus images. Three different implementations of SAM with an input prompt were considered: (1) SAM with an OD/OC-centred bounding box (SAM GT); (2) SAM with a noise-added (e.g. displacement, size variation) bounding box (SAM Noise); and (3) SAM with an automatically predicted (using Faster R-CNN) bounding box (SAM Auto). Two popular pre-trained semantic segmentation models, DeepLabV3 with a MobileNetV3-Large backbone and DeepLabV3 with a ResNet-50 backbone were used as baseline models. For OD segmentation, ResNet-50 exhibited comparable if not higher data efficiency (i.e. good performance despite limited training data) than even the most optimal implementation of SAM (SAM GT), although SAM was evidently more robust to small training set sizes, e.g. 25, than MobileNetV3-Large and in eyes with more challenging OD morphologies, e.g. significant peri-papillary atrophy. For OC segmentation, however, SAM GT and SAM Noise consistently demonstrated higher data efficiency, particularly in eyes with relatively small cup-to-disc ratio and ill-defined OC margin

Compressed vessels bias red blood cell partitioning at bifurcations in a hematocrit-dependent manner:implications in tumor blood flow

The tumor microenvironment is abnormal and associated with tumor tissue hypoxia, immunosuppression, and poor response to treatment. One important abnormality present in tumors is vessel compression. Vessel decompression has been shown to increase survival rates in animal models via enhanced and more homogeneous oxygenation. However, our knowledge of the biophysical mechanisms linking tumor decompression to improved tumor oxygenation is limited. In this study, we propose a computational model to investigate the impact of vessel compression on red blood cell (RBC) dynamics in tumor vascular networks. Our results demonstrate that vessel compression can alter RBC partitioning at bifurcations in a hematocrit-dependent and flow rate–independent manner. We identify RBC focusing due to cross-streamline migration as the mechanism responsible and characterize the spatiotemporal recovery dynamics controlling downstream partitioning. Based on this knowledge, we formulate a reduced-order model that will help future research to elucidate how these effects propagate at a whole vascular network level. These findings contribute to the mechanistic understanding of hemodilution in tumor vascular networks and oxygen homogenization following pharmacological solid tumor decompression

Analyzing and Modeling the Performance of the HemeLB Lattice-Boltzmann Simulation Environment

We investigate the performance of the HemeLB lattice-Boltzmann simulator for cerebrovascular blood flow, aimed at providing timely and clinically relevant assistance to neurosurgeons. HemeLB is optimised for sparse geometries, supports interactive use, and scales well to 32,768 cores for problems with ~81 million lattice sites. We obtain a maximum performance of 29.5 billion site updates per second, with only an 11% slowdown for highly sparse problems (5% fluid fraction). We present steering and visualisation performance measurements and provide a model which allows users to predict the performance, thereby determining how to run simulations with maximum accuracy within time constraints.Comment: Accepted by the Journal of Computational Science. 33 pages, 16 figures, 7 table

Mathematical modelling of oxygen transport in a muscle-on-chip device

Muscle-on-chip devices aim to recapitulate the physiological characteristics of in vivo muscle tissue and so maintaining levels of oxygen transported to cells is essential for cell survival and for providing the normoxic conditions experienced in vivo. We use finite-element method numerical modelling to describe oxygen transport and reaction in a proposed three-dimensional muscle-on-chip bioreactor with embedded channels for muscle cells and growth medium. We determine the feasibility of ensuring adequate oxygen for muscle cell survival in a device sealed from external oxygen sources and perfused via medium channels. We investigate the effects of varying elements of the bioreactor design on oxygen transport to optimize muscle tissue yield and maintain normoxic conditions. Successful co-culturing of muscle cells with motor neurons can boost muscle tissue function and so we estimate the maximum density of seeded neurons supported by oxygen concentrations within the bioreactor. We show that an enclosed bioreactor can provide sufficient oxygen for muscle cell survival and growth. We define a more efficient arrangement of muscle and perfusion chambers that can sustain a predicted 50% increase in maximum muscle volume per perfusion vessel. A study of simulated bioreactors provides functions for predicting bioreactor designs with normoxic conditions for any size of perfusion vessel, muscle chamber and distance between chambers

On the preservation of vessel bifurcations during flow-mediated angiogenic remodelling

Copyright: © 2021 Edgar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.During developmental angiogenesis, endothelial cells respond to shear stress by migrating and remodelling the initially hyperbranched plexus, removing certain vessels whilst maintaining others. In this study, we argue that the key regulator of vessel preservation is cell decision behaviour at bifurcations. At flow-convergent bifurcations where migration paths diverge, cells must finely tune migration along both possible paths if the bifurcation is to persist. Experiments have demonstrated that disrupting the cells’ ability to sense shear or the junction forces transmitted between cells impacts the preservation of bifurcations during the remodelling process. However, how these migratory cues integrate during cell decision making remains poorly understood. Therefore, we present the first agent-based model of endothelial cell flow-mediated migration suitable for interrogating the mechanisms behind bifurcation stability. The model simulates flow in a bifurcated vessel network composed of agents representing endothelial cells arranged into a lumen which migrate against flow. Upon approaching a bifurcation where more than one migration path exists, agents refer to a stochastic bifurcation rule which models the decision cells make as a combination of flow-based and collective-based migratory cues. With this rule, cells favour branches with relatively larger shear stress or cell number. We found that cells must integrate both cues nearly equally to maximise bifurcation stability. In simulations with stable bifurcations, we found competitive oscillations between flow and collective cues, and simulations that lost the bifurcation were unable to maintain these oscillations. The competition between these two cues is haemodynamic in origin, and demonstrates that a natural defence against bifurcation loss during remodelling exists: as vessel lumens narrow due to cell efflux, resistance to flow and shear stress increases, attracting new cells to enter and rescue the vessel from regression. Our work provides theoretical insight into the role of junction force transmission has in stabilising vasculature during remodelling and as an emergent mechanism to avoid functional shunting.L.T.E, C.A.F, H.G., and M.O.B. would like to graciously acknowledge our funding as part of a Foundation Leducq Transatlantic Network of Excellence (17 CVD 03, https://www.mdc-berlin.de/leducq-attract). M.O.B is supported by grants from EPSRC (EP/R029598/1, EP/R021600/1). C.A.F was supported by European Research Council starting grant (679368), the Fundação para a Ciência e a Tecnologia funding (grants: PTDC/MED-PAT/31639/2017; PTDC/BIA-CEL/32180/2017; CEECIND/04251/2017). C.A.F. and M.O.B are supported by a grant from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 801423. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Applicability of oculomics for individual risk prediction: Repeatability and robustness of retinal Fractal Dimension using DART and AutoMorph

Purpose: To investigate whether Fractal Dimension (FD)-based oculomics could be used for individual risk prediction by evaluating repeatability and robustness. Methods: We used two datasets: Caledonia, healthy adults imaged multiple times in quick succession for research (26 subjects, 39 eyes, 377 colour fundus images), and GRAPE, glaucoma patients with baseline and follow-up visits (106 subjects, 196 eyes, 392 images). Mean follow-up time was 18.3 months in GRAPE, thus it provides a pessimistic lower-bound as vasculature could change. FD was computed with DART and AutoMorph. Image quality was assessed with QuickQual, but no images were initially excluded. Pearson, Spearman, and Intraclass Correlation (ICC) were used for population-level repeatability. For individual-level repeatability, we introduce measurement noise parameter {\lambda} which is within-eye Standard Deviation (SD) of FD measurements in units of between-eyes SD. Results: In Caledonia, ICC was 0.8153 for DART and 0.5779 for AutoMorph, Pearson/Spearman correlation (first and last image) 0.7857/0.7824 for DART, and 0.3933/0.6253 for AutoMorph. In GRAPE, Pearson/Spearman correlation (first and next visit) was 0.7479/0.7474 for DART, and 0.7109/0.7208 for AutoMorph (all p<0.0001). Median {\lambda} in Caledonia without exclusions was 3.55\% for DART and 12.65\% for AutoMorph, and improved to up to 1.67\% and 6.64\% with quality-based exclusions, respectively. Quality exclusions primarily mitigated large outliers. Worst quality in an eye correlated strongly with {\lambda} (Pearson 0.5350-0.7550, depending on dataset and method, all p<0.0001). Conclusions: Repeatability was sufficient for individual-level predictions in heterogeneous populations. DART performed better on all metrics and might be able to detect small, longitudinal changes, highlighting the potential of robust methods

Emergent cell-free layer asymmetry and biased haematocrit partition in a biomimetic vascular network of successive bifurcations

Blood is a vital soft matter, and its normal circulation in the human body relies on the distribution of red blood cells (RBCs) at successive bifurcations. Understanding how RBCs are partitioned at bifurcations is key for the optimisation of microfluidic devices as well as for devising novel strategies for diagnosis and treatment of blood-related diseases. We report the dynamics of RBC suspensions flowing through a biomimetic vascular network incorporating three generations of microchannels and two classical types of bifurcations at the arteriole level. Our microfluidic experiments with dilute and semidilute RBC suspensions demonstrate the emergence of excessive heterogeneity of RBC concentration in downstream generations upon altering the network's outflow rates. Through parallel simulations using the immersed-boundary-lattice-Boltzmann method, we reveal that the heterogeneity is attributed to upstream perturbations in the cell-free layer (CFL) and lack of its recovery between consecutive bifurcations owing to suppressed hydrodynamic lift under reduced flow conditions. In the dilute/semidilute regime, this perturbation dominates over the effect of local fractional flow at the bifurcation and can lead to inherently unfavourable child branches that are deprived of RBCs even for equal flow split. Our work highlights the importance of CFL asymmetry cascading down a vascular network, which leads to biased phase separation that deviates from established empirical predictions

Retinal Fractal Dimension Is a Potential Biomarker for Systemic Health-Evidence From a Mixed-Age, Primary-Care Population

PURPOSE: To investigate whether fractal dimension (FD), a retinal trait relating to vascular complexity and a potential "oculomics" biomarker for systemic disease, is applicable to a mixed-age, primary-care population.METHODS: We used cross-sectional data (96 individuals; 183 eyes; ages 18-81 years) from a university-based optometry clinic in Glasgow, Scotland, to study the association between FD and systemic health. We computed FD from color fundus images using Deep Approximation of Retinal Traits (DART), an artificial intelligence-based method designed to be more robust to poor image quality.RESULTS: Despite DART being designed to be more robust, a significant association (P &lt; 0.001) between image quality and FD remained. Consistent with previous literature, age was associated with lower FD (P &lt; 0.001 univariate and when adjusting for image quality). However, FD variance was higher in older patients, and some patients over 60 had FD comparable to those of patients in their 20s. Prevalent systemic conditions were significantly (P = 0.037) associated with lower FD when adjusting for image quality and age.CONCLUSIONS: Our work suggests that FD as a biomarker for systemic health extends to mixed-age, primary-care populations. FD decreases with age but might not substantially decrease in everyone. This should be further investigated using longitudinal data. Finally, image quality was associated with FD, but it is unclear whether this finding is measurement error caused by image quality or confounded by age and health. Future work should investigate this to clarify whether adjusting for image quality is appropriate.TRANSLATIONAL RELEVANCE: FD could potentially be used in regular screening settings, but questions around image quality remain.</p