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The development of strategies to combat hepatic disease and augment tissue regeneration has created a need for methods to assess regional liver function. Liver perfusion imaging has the potential to fulfil this need, across a range of hepatic diseases, alongside the assessment of therapeutic response. In this study, the feasibility of hepatic arterial spin labelling (HASL) was assessed for the first time in mice at 9.4 T, its variability and repeatability were evaluated, and it was applied to a model of colorectal liver metastasis. Data were acquired using flow-sensitive alternating inversion recovery-arterial spin labelling (FAIR-ASL) with a Look-Locker readout, and analysed using retrospective respiratory gating and a T1-based quantification. This study shows that preclinical HASL is feasible and exhibits good repeatability and reproducibility. Mean estimated liver perfusion was 2.2 ± 0.8 mL/g/min (mean ± standard error, n = 10), which agrees well with previous measurements using invasive approaches. Estimates of the variation gave a within-session coefficient of variation (CVWS) of 7%, a between-session coefficient of variation (CVBS) of 9% and a between-animal coefficient of variation (CVA) of 15%. The within-session Bland-Altman repeatability coefficient (RCWS) was 18% and the between-session repeatability coefficient (RCBS) was 29%. Finally, the HASL method was applied to a mouse model of liver metastasis, in which significantly lower mean perfusion (1.1 ± 0.5 mL/g/min, n = 6) was measured within the tumours, as seen by fluorescence histology. These data indicate that precise and accurate liver perfusion estimates can be achieved using ASL techniques, and provide a platform for future studies investigating hepatic perfusion in mouse models of disease. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Hepatic metastases are arterially supplied, resulting in an elevated hepatic perfusion index (HPI). The purpose of this study was to use dynamic contrast-enhanced (DCE) MR imaging to quantify the HPI of metastases and the liver before and after treatment with a novel antiangiogenic drug. Ten patients with known metastatic liver disease underwent DCE-MR studies. HPIs of metastases and whole liver were derived using regions of interest (ROIs) and calculated on a pixel-by-pixel basis from quantified changes in gadopentetate dimeglumine (Gd-DTPA) concentration. The HPI measurement error prior to treatment was derived by the Bland-Altman analysis. The median HPI before and after treatment with antiangiogenic drug BIBF 1120 were compared using the Wilcoxon signed rank test. Prior to treatment, the median HPI of metastases, 0.75 +/- 0.14, was significantly higher than that of the whole liver, 0.66 +/- 0.16 (p < 0.01). Bland-Altman reproducibility coefficients of the median HPI from metastases and whole liver were 13.0 and 5.1% respectively. The median HPI of metastases decreased significantly at 28 days after treatment with BIBF 1120 (p < 0.05). This pilot study demonstrates that HPI determined using quantified Gd-DTPA concentration is reproducible and may be useful for monitoring antiangiogenic treatment response of hepatic metastases. [ABSTRACT FROM AUTHOR]

Disruption of retinal vasculature is linked to various diseases, including diabetic retinopathy and macular degeneration, leading to vision loss. We present here a novel algorithmic approach that generates highly realistic digital models of human retinal blood vessels, based on established biophysical principles, including fully-connected arterial and venous trees with a single inlet and outlet. This approach, using physics-informed generative adversarial networks (PI-GAN), enables the segmentation and reconstruction of blood vessel networks with no human input and which out-performs human labelling. Segmentation of DRIVE and STARE retina photograph datasets provided near state-of-the-art vessel segmentation, with training on only a small (n = 100) simulated dataset. Our findings highlight the potential of PI-GAN for accurate retinal vasculature characterization, with implications for improving early disease detection, monitoring disease progression, and improving patient care., (© 2024. The Author(s).)

We present a 3D discrete-continuum model to simulate blood pressure in large microvascular tissues in the absence of known capillary network architecture. Our hybrid approach combines a 1D Poiseuille flow description for large, discrete arteriolar and venular networks coupled to a continuum-based Darcy model, point sources of flux, for transport in the capillary bed. We evaluate our hybrid approach using a vascular network imaged from the mouse brain medulla/pons using multi-fluorescence high-resolution episcopic microscopy (MF-HREM). We use the fully-resolved vascular network to predict the hydraulic conductivity of the capillary network and generate a fully-discrete pressure solution to benchmark against. Our results demonstrate that the discrete-continuum methodology is a computationally feasible and effective tool for predicting blood pressure in real-world microvascular tissues when capillary microvessels are poorly defined., (© 2024 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.)

Background: Carcinogenesis is driven by interactions between genetic mutations and the local tumor microenvironment. Recent research has identified hundreds of cancer driver genes; however, these studies often include a mixture of different molecular subtypes and ecological niches and ignore the impact of the immune system., Results: In this study, we compare the landscape of driver genes in tumors that escaped the immune system (escape +) versus those that did not (escape -). We analyze 9896 primary tumors from The Cancer Genome Atlas using the ratio of non-synonymous to synonymous mutations (dN/dS) and find 85 driver genes, including 27 and 16 novel genes, in escape - and escape + tumors, respectively. The dN/dS of driver genes in immune escaped tumors is significantly lower and closer to neutrality than in non-escaped tumors, suggesting selection buffering in driver genes fueled by immune escape. Additionally, we find that immune evasion leads to more mutated sites, a diverse array of mutational signatures and is linked to tumor prognosis., Conclusions: Our findings highlight the need for improved patient stratification to identify new therapeutic targets for cancer treatment., (© 2024. The Author(s).)

Missions into Deep Space are planned this decade. Yet the health consequences of exposure to microgravity and galactic cosmic radiation (GCR) over years-long missions on indispensable visceral organs such as the kidney are largely unexplored. We performed biomolecular (epigenomic, transcriptomic, proteomic, epiproteomic, metabolomic, metagenomic), clinical chemistry (electrolytes, endocrinology, biochemistry) and morphometry (histology, 3D imaging, miRNA-ISH, tissue weights) analyses using samples and datasets available from 11 spaceflight-exposed mouse and 5 human, 1 simulated microgravity rat and 4 simulated GCR-exposed mouse missions. We found that spaceflight induces: 1) renal transporter dephosphorylation which may indicate astronauts' increased risk of nephrolithiasis is in part a primary renal phenomenon rather than solely a secondary consequence of bone loss; 2) remodelling of the nephron that results in expansion of distal convoluted tubule size but loss of overall tubule density; 3) renal damage and dysfunction when exposed to a Mars roundtrip dose-equivalent of simulated GCR., (© 2024. The Author(s).)

Though the earliest stages of oncogenesis, post initiation, are not well understood, it is generally appreciated that a successful transition from a collection of dysregulated cells to an aggressive tumour requires complex ecological interactions between cancer cells and their environment. One key component of tumorigenesis is immune evasion. To investigate the interplay amongst the ecological behaviour of mutualism and immune evasion, we used a computational simulation framework. Sensitivity analyses of the growth of a virtual tumour implemented as a 2D-hexagonal lattice model suggests tumour survival depends on the interplay between growth rates, mutualism and immune evasion. In 60% of simulations, cancer clones with low growth rates, but exhibiting mutualism were able to evade the immune system and continue progressing suggesting that tumours with equivalent growth rates and no mutualism are more likely to be eliminated than tumours with mutualism. Tumours with faster growth rates showed a lower dependence upon mutualism for progression. Geostatistical analysis showed decreased spatial heterogeneity over time for polyclonal tumours with a high division rate. Overall, these results suggest that in slow growing tumours, mutualism is critical for early tumorigenesis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Gourmet, Walker-Samuel and Mallick.)

Structural changes to microvascular networks are increasingly highlighted as markers of pathogenesis in a wide range of disease, e.g. Alzheimer's disease, vascular dementia and tumour growth. This has motivated the development of dedicated 3D imaging techniques, alongside the creation of computational modelling frameworks capable of using 3D reconstructed networks to simulate functional behaviours such as blood flow or transport processes. Extraction of 3D networks from imaging data broadly consists of two image processing steps: segmentation followed by skeletonisation. Much research effort has been devoted to segmentation field, and there are standard and widely-applied methodologies for creating and assessing gold standards or ground truths produced by manual annotation or automated algorithms. The Skeletonisation field, however, lacks widely applied, simple to compute metrics for the validation or optimisation of the numerous algorithms that exist to extract skeletons from binary images. This is particularly problematic as 3D imaging datasets increase in size and visual inspection becomes an insufficient validation approach. In this work, we first demonstrate the extent of the problem by applying 4 widely-used skeletonisation algorithms to 3 different imaging datasets. In doing so we show significant variability between reconstructed skeletons of the same segmented imaging dataset. Moreover, we show that such a structural variability propagates to simulated metrics such as blood flow. To mitigate this variability we introduce a new, fast and easy to compute super metric that compares the volume, connectivity, medialness, bifurcation point identification and homology of the reconstructed skeletons to the original segmented data. We then show that such a metric can be used to select the best performing skeletonisation algorithm for a given dataset, as well as to optimise its parameters. Finally, we demonstrate that the super metric can also be used to quickly identify how a particular skeletonisation algorithm could be improved, becoming a powerful tool in understanding the complex implication of small structural changes in a network., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Vascularization is driven by morphogen signals and mechanical cues that coordinately regulate cellular force generation, migration, and shape change to sculpt the developing vascular network. However, it remains unclear whether developing vasculature actively regulates its own mechanical properties to achieve effective vascularization. We engineered tissue constructs containing endothelial cells and fibroblasts to investigate the mechanics of vascularization. Tissue stiffness increases during vascular morphogenesis resulting from emergent interactions between endothelial cells, fibroblasts, and ECM and correlates with enhanced vascular function. Contractile cellular forces are key to emergent tissue stiffening and synergize with ECM mechanical properties to modulate the mechanics of vascularization. Emergent tissue stiffening and vascular function rely on mechanotransduction signaling within fibroblasts, mediated by YAP1. Mouse embryos lacking YAP1 in fibroblasts exhibit both reduced tissue stiffness and develop lethal vascular defects. Translating our findings through biology-inspired vascular tissue engineering approaches will have substantial implications in regenerative medicine.

Complex interactions between the physical environment and phenotype of a tumour, and genomics, transcriptomics, proteomics and epigenomics, are increasingly known to have a significant influence on cancer development, progression and evolution. For example, mechanical stress can alter both genome maintenance and histone modifications, which consequently affect transcription and the epigenome. Increased stiffness has been linked to genetic heterogeneity and is responsible for heterochromatin accumulations. Stiffness thereby leads to deregulation in gene expression, disrupts the proteome and can impact angiogenesis. Several studies have shown how the physics of cancer can influence diverse cancer hallmarks such as resistance to cell death, angiogenesis and evasion from immune destruction. In this review, we will explain the role that physics of cancer plays in cancer evolution and explore how multiomics are being used to elucidate the mechanisms underpinning them., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Gourmet and Walker-Samuel.)

Episcopic imaging using techniques such as High Resolution Episcopic Microscopy (HREM) and its variants, allows biological samples to be visualized in three dimensions over a large field of view. Quantitative analysis of episcopic image data is undertaken using a range of methods. In this systematic review, we look at trends in quantitative analysis of episcopic images and discuss avenues for further research. Papers published between 2011 and 2022 were analyzed for details about quantitative analysis approaches, methods of image annotation and choice of image processing software. It is shown that quantitative processing is becoming more common in episcopic microscopy and that manual annotation is the predominant method of image analysis. Our meta-analysis highlights where tools and methods require further development in this field, and we discuss what this means for the future of quantitative episcopic imaging, as well as how annotation and quantification may be automated and standardized across the field.

Aims: The adapter protein p130Cas, encoded by the Bcar1 gene, is a key regulator of cell movement, adhesion, and cell cycle control in diverse cell types. Bcar1 constitutive knockout mice are embryonic lethal by embryonic days (E) 11.5-12.5, but the role of Bcar1 in embryonic development remains unclear. Here, we investigated the role of Bcar1 specifically in cardiovascular development and defined the cellular and molecular mechanisms disrupted following targeted Bcar1 deletions., Methods and Results: We crossed Bcar1 floxed mice with Cre transgenic lines allowing for cell-specific knockout either in smooth muscle and early cardiac tissues (SM22-Cre), mature smooth muscle cells (smMHC-Cre), endothelial cells (Tie2-Cre), second heart field cells (Mef2c-Cre), or neural crest cells (NCC) (Pax3-Cre) and characterized these conditional knock outs using a combination of histological and molecular biology techniques. Conditional knockout of Bcar1 in SM22-expressing smooth muscle cells and cardiac tissues (Bcar1SM22KO) was embryonically lethal from E14.5-15.5 due to severe cardiovascular defects, including abnormal ventricular development and failure of outflow tract (OFT) septation leading to a single outflow vessel reminiscent of persistent truncus arteriosus. SM22-restricted loss of Bcar1 was associated with failure of OFT cushion cells to undergo differentiation to septal mesenchymal cells positive for SMC-specific α-actin, and disrupted expression of proteins and transcription factors involved in epithelial-to-mesenchymal transformation (EMT). Furthermore, knockout of Bcar1 specifically in NCC (Bcar1PAX3KO) recapitulated part of the OFT septation and aortic sac defects seen in the Bcar1SM22KO mutants, indicating a cell-specific requirement for Bcar1 in NCC essential for OFT septation. In contrast, conditional knockouts of Bcar1 in differentiated smooth muscle, endothelial cells, and second heart field cells survived to term and were phenotypically normal at birth and postnatally., Conclusion: Our work reveals a cell-specific requirement for Bcar1 in NCC, early myogenic and cardiac cells, essential for OFT septation, myocardialization and EMT/cell cycle regulation and differentiation to myogenic lineages., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Advances in biological imaging have accelerated our understanding of human physiology in both health and disease. As these advances have developed, the opportunities gained by integrating with cutting-edge mathematical models have become apparent yet remain challenging. Combined imaging-modelling approaches provide unprecedented opportunity to correlate data on tissue architecture and function, across length and time scales, to better understand the mechanisms that underpin fundamental biology and also to inform clinical decisions. Here we discuss the opportunities and challenges of such approaches, providing literature examples across a range of organ systems. Given the breadth of the field we focus on the intersection of continuum modelling and in vivo imaging applied to the vasculature and blood flow, though our rationale and conclusions extend widely. We propose three key research pillars (image acquisition, image processing, mathematical modelling) and present their respective advances as well as future opportunity via better integration. Multidisciplinary efforts that develop imaging and modelling tools concurrently, and share them open-source with the research community, provide exciting opportunity for advancing these fields., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Nanoparticles have the potential to increase the efficacy of anticancer drugs whilst reducing off-target side effects. However, there remain uncertainties regarding the cellular uptake kinetics of nanoparticles which could have implications for nanoparticle design and delivery. Polymersomes are nanoparticle candidates for cancer therapy which encapsulate chemotherapy drugs. Here we develop a mathematical model to simulate the uptake of polymersomes via endocytosis, a process by which polymersomes bind to the cell surface before becoming internalised by the cell where they then break down, releasing their contents which could include chemotherapy drugs. We focus on two in vitro configurations relevant to the testing and development of cancer therapies: a well-mixed culture model and a tumour spheroid setup. Our mathematical model of the well-mixed culture model comprises a set of coupled ordinary differential equations for the unbound and bound polymersomes and associated binding dynamics. Using a singular perturbation analysis we identify an optimal number of ligands on the polymersome surface which maximises internalised polymersomes and thus intracellular chemotherapy drug concentration. In our mathematical model of the spheroid, a multiphase system of partial differential equations is developed to describe the spatial and temporal distribution of bound and unbound polymersomes via advection and diffusion, alongside oxygen, tumour growth, cell proliferation and viability. Consistent with experimental observations, the model predicts the evolution of oxygen gradients leading to a necrotic core. We investigate the impact of two different internalisation functions on spheroid growth, a constant and a bond dependent function. It was found that the constant function yields faster uptake and therefore chemotherapy delivery. We also show how various parameters, such as spheroid permeability, lead to travelling wave or steady-state solutions., Competing Interests: RJS and SWS would like to acknowledge generous support form the Rosetrees Trust (https://rosetreestrust.co.uk) (M601). SDW’s commercial affiliation did not play a role in the study (he only moved to this role when all work was complete). The commercial affiliation of SDW does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Objectives: Effects of liver disease on portal venous (PV), hepatic arterial (HA), total liver blood flow (TLBF), and cardiac function are poorly understood. Terlipressin modulates PV flow but effects on HA, TLBF, and sepsis/acute-on-chronic liver failure (ACLF)-induced haemodynamic changes are poorly characterised. In this study, we investigated the effects of terlipressin and sepsis/ACLF on hepatic haemodynamics and cardiac function in a rodent cirrhosis model using caval subtraction phase-contrast (PC) MRI and cardiac cine MRI., Methods: Sprague-Dawley rats (n = 18 bile duct-ligated (BDL), n = 16 sham surgery controls) underwent caval subtraction PCMRI to estimate TLBF and HA flow and short-axis cardiac cine MRI for systolic function at baseline, following terlipressin and lipopolysaccharide (LPS) infusion, to model ACLF., Results: All baseline hepatic haemodynamic/cardiac systolic function parameters (except heart rate and LV mass) were significantly different in BDL rats. Following terlipressin, baseline PV flow (sham 181.4 ± 12.1 ml/min/100 g; BDL 68.5 ± 10.1 ml/min/100 g) reduced (sham - 90.3 ± 11.1 ml/min/100 g, p < 0.0001; BDL - 31.0 ± 8.0 ml/min/100 g, p = 0.02), sham baseline HA flow (33.0 ± 11.3 ml/min/100 g) increased (+ 92.8 ± 21.3 ml/min/100 g, p = 0.0003), but BDL baseline HA flow (83.8 ml/min/100 g) decreased (- 34.4 ± 7.5 ml/min/100 g, p = 0.11). Sham baseline TLBF (214.3 ± 16.7 ml/min/100 g) was maintained (+ 2.5 ± 14.0 ml/min/100 g, p > 0.99) but BDL baseline TLBF (152.3 ± 18.7 ml/min/100 g) declined (- 65.5 ± 8.5 ml/min/100 g, p = 0.0004). Following LPS, there were significant differences between cohort and change in HA fraction (p = 0.03) and TLBF (p = 0.01) with BDL baseline HA fraction (46.2 ± 4.6%) reducing (- 20.9 ± 7.5%, p = 0.03) but sham baseline HA fraction (38.2 ± 2.0%) remaining unchanged (+ 2.9 ± 6.1%, p > 0.99). Animal cohort and change in systolic function interactions were significant only for heart rate (p = 0.01) and end-diastolic volume (p = 0.03)., Conclusions: Caval subtraction PCMRI and cardiac MRI in a rodent model of cirrhosis demonstrate significant baseline hepatic haemodynamic/cardiac differences, failure of the HA buffer response post-terlipressin and an altered HA fraction response in sepsis, informing potential translation to ACLF patients., Key Points: Caval subtraction phase-contrast and cardiac MRI demonstrate: • Significant differences between cirrhotic/non-cirrhotic rodent hepatic blood flow and cardiac systolic function at baseline. • Failure of the hepatic arterial buffer response in cirrhotic rodents in response to terlipressin. • Reductions in hepatic arterial flow fraction in the setting of acute-on-chronic liver failure.

Noninvasive measurements of liver perfusion and fibrosis in cirrhotic small animals can help develop treatments for haemodynamic complications of liver disease. Here, we measure liver perfusion in cirrhotic rodents using flow-sensitive alternating inversion recovery arterial spin labelling (FAIR ASL), evaluating agreement with previously validated caval subtraction phase-contrast magnetic resonance imaging (PCMRI) total liver blood flow (TLBF). Baseline differences in cirrhotic rodents and the haemodynamic effects of acute inflammation were investigated using FAIR ASL and tissue T1. Sprague-Dawley rats (nine bile duct ligated [BDL] and ten sham surgery controls) underwent baseline hepatic FAIR ASL with T1 measurement and caval subtraction PCMRI (with two-dimensional infra-/supra-hepatic inferior vena caval studies), induction of inflammation with intravenous lipopolysaccharide (LPS) and repeat liver FAIR ASL with T1 measurement after ~90 minutes. The mean difference between FAIR ASL hepatic perfusion and caval subtraction PCMRI TLBF was -51 ± 30 ml/min/100 g (Bland-Altman 95% limits-of-agreement ±258 ml/min/100 g). The FAIR ASL coefficient of variation was smaller than for caval subtraction PCMRI (29.3% vs 50.1%; P = .03). At baseline, FAIR ASL liver perfusion was lower in BDL rats (199 ± 32 ml/min/100 g vs sham 316 ± 24 ml/min/100 g; P = .01) but liver T1 was higher (BDL 1533 ± 50 vs sham 1256 ± 18 ms; P = .0004). Post-LPS FAIR ASL liver perfusion response differences were observed between sham/BDL rats (P = .02), approaching significance in sham (+78 ± 33 ml/min/100 g; P = .06) but not BDL rats (-49 ± 40 ml/min/100 g; P = .47). Post-LPS differences in liver tissue T1 were nonsignificant (P = .35). FAIR ASL hepatic perfusion and caval subtraction PCMRI TLBF agreement was modest, with significant baseline FAIR ASL liver perfusion and tissue T1 differences in rodents with advanced cirrhosis compared with controls. Following inflammatory stress, differences in hepatic perfusion response were detected between cirrhotic/control animals, but liver T1 was unaffected. Findings underline the potential of FAIR ASL in the assessment of vasoactive treatments for patients with chronic liver disease and inflammation., (© 2020 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Introduction: To combine numerical simulations, in vitro and in vivo experiments to evaluate the feasibility of measuring diffusion exchange across the cell membrane with diffusion exchange spectroscopy (DEXSY)., Methods: DEXSY acquisitions were simulated over a range of permeabilities in nerve tissue and yeast substrates. In vitro measurements were performed in a yeast substrate and in vivo measurements in mouse tumor xenograft models, all at 9.4 T., Results: Diffusion exchange was observed in simulations over a physiologically relevant range of cell permeability values. In vitro and in vivo measures also provided evidence of diffusion exchange, which was quantified with the Diffusion Exchange Index (DEI)., Conclusions: Our findings provide preliminary evidence that DEXSY can be used to make in vivo measurements of diffusion exchange and cell membrane permeability., (© 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

Cancer cells differ in size from those of their host tissue and are known to change in size during the processes of cell death. A noninvasive method for monitoring cell size would be highly advantageous as a potential biomarker of malignancy and early therapeutic response. This need is particularly acute in brain tumours where biopsy is a highly invasive procedure. Here, diffusion MRI data were acquired in a GL261 glioma mouse model before and during treatment with Temozolomide. The biophysical model VERDICT (Vascular Extracellular and Restricted Diffusion for Cytometry in Tumours) was applied to the MRI data to quantify multi-compartmental parameters connected to the underlying tissue microstructure, which could potentially be useful clinical biomarkers. These parameters were compared to ADC and kurtosis diffusion models, and, measures from histology and optical projection tomography. MRI data was also acquired in patients to assess the feasibility of applying VERDICT in a range of different glioma subtypes. In the GL261 gliomas, cellular changes were detected according to the VERDICT model in advance of gross tumour volume changes as well as ADC and kurtosis models. VERDICT parameters in glioblastoma patients were most consistent with the GL261 mouse model, whilst displaying additional regions of localised tissue heterogeneity. The present VERDICT model was less appropriate for modelling more diffuse astrocytomas and oligodendrogliomas, but could be tuned to improve the representation of these tumour types. Biophysical modelling of the diffusion MRI signal permits monitoring of brain tumours without invasive intervention. VERDICT responds to microstructural changes induced by chemotherapy, is feasible within clinical scan times and could provide useful biomarkers of treatment response.

Heterogeneity of lymphatic vessels during embryogenesis is critical for organ-specific lymphatic function. Little is known about lymphatics in the developing kidney, despite their established roles in pathology of the mature organ. We performed three-dimensional imaging to characterize lymphatic vessel formation in the mammalian embryonic kidney at single-cell resolution. In mouse, we visually and quantitatively assessed the development of kidney lymphatic vessels, remodeling from a ring-like anastomosis under the nascent renal pelvis; a site of VEGF-C expression, to form a patent vascular plexus. We identified a heterogenous population of lymphatic endothelial cell clusters in mouse and human embryonic kidneys. Exogenous VEGF-C expanded the lymphatic population in explanted mouse embryonic kidneys. Finally, we characterized complex kidney lymphatic abnormalities in a genetic mouse model of polycystic kidney disease. Our study provides novel insights into the development of kidney lymphatic vasculature; a system which likely has fundamental roles in renal development, physiology and disease., Competing Interests: DJ, DM, MK, NP, KP, NM, CW, RC, PW, PH, CR, SW, PR, AW, PS, DL No competing interests declared, (© 2019, Jafree et al.)

Cancers exhibit spatially heterogeneous, unique vascular architectures across individual samples, cell-lines and patients. This inherently disorganised collection of leaky blood vessels contribute significantly to suboptimal treatment efficacy. Preclinical tools are urgently required which incorporate the inherent variability and heterogeneity of tumours to optimise and engineer anti-cancer therapies. In this study, we present a novel computational framework which incorporates whole, realistic tumours extracted ex vivo to efficiently simulate vascular blood flow and interstitial fluid transport in silico for validation against in vivo biomedical imaging. Our model couples Poiseuille and Darcy descriptions of vascular and interstitial flow, respectively, and incorporates spatially heterogeneous blood vessel lumen and interstitial permeabilities to generate accurate predictions of tumour fluid dynamics. Our platform enables highly-controlled experiments to be performed which provide insight into how tumour vascular heterogeneity contributes to tumour fluid transport. We detail the application of our framework to an orthotopic murine glioma (GL261) and a human colorectal carcinoma (LS147T), and perform sensitivity analysis to gain an understanding of the key biological mechanisms which determine tumour fluid transport. Finally we mimic vascular normalization by modifying parameters, such as vascular and interstitial permeabilities, and show that incorporating realistic vasculatures is key to modelling the contrasting fluid dynamic response between tumour samples. Contrary to literature, we show that reducing tumour interstitial fluid pressure is not essential to increase interstitial perfusion and that therapies should seek to develop an interstitial fluid pressure gradient. We also hypothesise that stabilising vessel diameters and permeabilities are not key responses following vascular normalization and that therapy may alter interstitial hydraulic conductivity. Consequently, we suggest that normalizing the interstitial microenvironment may provide a more effective means to increase interstitial perfusion within tumours., Competing Interests: The authors have declared that no competing interests exist.

Purpose: This preclinical study investigated the use of QSM MRI to noninvasively measure venous oxygen saturation (SvO2) in the hepatic and portal veins., Methods: QSM data were acquired from a cohort of healthy mice (n = 10) on a 9.4 Tesla MRI scanner under normoxic and hyperoxic conditions. Susceptibility was measured in the portal and hepatic veins and used to calculate SvO2 in each vessel under each condition. Blood was extracted from the inferior vena cava of 3 of the mice under each condition, and SvO2 was measured with a blood gas analyzer for comparison. QSM data were also acquired from a cohort of mice bearing liver tumors under normoxic conditions. Susceptibility was measured, and SvO2 calculated in the portal and hepatic veins and compared to the healthy mice. Statistical significance was assessed using a Wilcoxon matched-pairs signed rank test (normoxic vs. hyperoxic) or a Mann-Whitney test (healthy vs. tumor bearing)., Results: SvO2 calculated from QSM measurements in healthy mice under hyperoxia showed significant increases of 15% in the portal vein (P < 0.05) and 21% in the hepatic vein (P < 0.01) versus normoxia. These values agreed with inferior vena cava measurements from the blood gas analyzer (26% increase). SvO2 in the hepatic vein was significantly lower in the colorectal liver metastases cohort (30% ± 11%) than the healthy mice (53% ± 17%) (P < 0.05); differences in the portal vein were not significant., Conclusion: QSM is a feasible tool for noninvasively measuring SvO2 in the liver and can detect differences due to increased oxygen consumption in livers bearing colorectal metastases., (© 2018 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

Proteasome inhibitors (PIs) are now standard of care for several cancers, and noninvasive biomarkers of treatment response are critically required for early patient stratification and treatment personalization. The present study evaluated whether chemical exchange (CEST) magnetic resonance imaging (MRI) can provide measurements that can be used as the noninvasive biomarkers of proteasome inhibition, alongside diffusion MRI and relaxometry. The sensitivity of human colorectal carcinoma cells to the PI Ixazomib was assessed via in vitro and in vivo dose-response experiments. Acute in vivo response to Ixazomib was assessed at three dosing concentrations, using CEST MRI (amide, amine, hydroxyl signals), diffusion MRI (ADC) and relaxometry (T 1 , T 2 ). These responses were further evaluated with the known histological markers for Ixazomib and Bradford assay ex vivo. The CEST signal from amides and amines increased in proportion to Ixazomib dose in colorectal cancer xenografts. The cell lines differed in their sensitivity to Ixazomib, which was reflected in the MRI measurements. A mild stimulation in tumor growth was observed at low Ixazomib doses. Our results identify CEST MRI as a promising method for safely and noninvasively monitoring disrupted tumor protein homeostasis induced by proteasome inhibitor treatment, and for stratifying sensitivity between tumor types.

Understanding the uptake of a drug by diseased tissue, and the drug's subsequent spatiotemporal distribution, are central factors in the development of effective targeted therapies. However, the interaction between the pathophysiology of diseased tissue and individual therapeutic agents can be complex, and can vary across tissue types and across subjects. Here, we show that the combination of mathematical modelling, high-resolution optical imaging of intact and optically cleared tumour tissue from animal models, and in vivo imaging of vascular perfusion predicts the heterogeneous uptake, by large tissue samples, of specific therapeutic agents, as well as their spatiotemporal distribution. In particular, by using murine models of colorectal cancer and glioma, we report and validate predictions of steady-state blood flow and intravascular and interstitial fluid pressure in tumours, of the spatially heterogeneous uptake of chelated gadolinium by tumours, and of the effect of a vascular disrupting agent on tumour vasculature.