Pneumomediastinum in COVID-19: a phenotype of severe COVID-19 pneumonitis? The results of the United Kingdom (POETIC) survey.

BACKGROUND: There is an emerging understanding that coronavirus disease 2019 (COVID-19) is associated with increased incidence of pneumomediastinum. We aimed to determine its incidence among patients hospitalised with COVID-19 in the United Kingdom and describe factors associated with outcome. METHODS: A structured survey of pneumomediastinum and its incidence was conducted from September 2020 to February 2021. United Kingdom-wide participation was solicited via respiratory research networks. Identified patients had SARS-CoV-2 infection and radiologically proven pneumomediastinum. The primary outcomes were to determine incidence of pneumomediastinum in COVID-19 and to investigate risk factors associated with patient mortality. RESULTS: 377 cases of pneumomediastinum in COVID-19 were identified from 58 484 inpatients with COVID-19 at 53 hospitals during the study period, giving an incidence of 0.64%. Overall 120-day mortality in COVID-19 pneumomediastinum was 195/377 (51.7%). Pneumomediastinum in COVID-19 was associated with high rates of mechanical ventilation. 172/377 patients (45.6%) were mechanically ventilated at the point of diagnosis. Mechanical ventilation was the most important predictor of mortality in COVID-19 pneumomediastinum at the time of diagnosis and thereafter (p<0.001) along with increasing age (p<0.01) and diabetes mellitus (p=0.08). Switching patients from continuous positive airways pressure support to oxygen or high flow nasal oxygen after the diagnosis of pneumomediastinum was not associated with difference in mortality. CONCLUSIONS: Pneumomediastinum appears to be a marker of severe COVID-19 pneumonitis. The majority of patients in whom pneumomediastinum was identified had not been mechanically ventilated at the point of diagnosis.

Tumour subregion analysis of colorectal liver metastases using semi-automated clustering based on DCE-MRI: Comparison with histological subregions and impact on pharmacokinetic parameter analysis.

PURPOSE: To use a novel segmentation methodology based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to define tumour subregions of liver metastases from colorectal cancer (CRC), to compare these with histology, and to use these to compare extracted pharmacokinetic (PK) parameters between tumour subregions. MATERIALS AND METHODS: This ethically-approved prospective study recruited patients with CRC and ≥1 hepatic metastases scheduled for hepatic resection. Patients underwent DCE-MRI pre-metastasectomy. Histological sections of resection specimens were spatially matched to DCE-MRI acquisitions and used to define histological subregions of viable and non-viable tumour. A semi-automated voxel-wise image segmentation algorithm based on the DCE-MRI contrast-uptake curves was used to define imaging subregions of viable and non-viable tumour. Overlap of histologically-defined and imaging subregions was compared using the Dice similarity coefficient (DSC). DCE-MRI PK parameters were compared for the whole tumour and histology-defined and imaging-derived subregions. RESULTS: Fourteen patients were included in the analysis. Direct histological comparison with imaging was possible in nine patients. Mean DSC for viable tumour subregions defined by imaging and histology was 0.738 (range 0.540-0.930). There were significant differences between Ktrans and kep for viable and non-viable subregions (p < 0.001) and between whole lesions and viable subregions (p < 0.001). CONCLUSION: We demonstrate good concordance of viable tumour segmentation based on pre-operative DCE-MRI with a post-operative histological gold-standard. This can be used to extract viable tumour-specific values from quantitative image analysis, and could improve treatment response assessment in clinical practice.

Magnitude-intrinsic water-fat ambiguity can be resolved with multipeak fat modeling and a multipoint search method.

PURPOSE: To develop a postprocessing algorithm for multiecho chemical-shift encoded water-fat separation that estimates proton density fat fraction (PDFF) maps over the full dynamic range (0-100%) using multipeak fat modeling and multipoint search optimization. To assess its accuracy, reproducibility, and agreement with state-of-the-art complex-based methods, and to evaluate its robustness to artefacts in abdominal PDFF maps. METHODS: We introduce MAGO (MAGnitude-Only), a magnitude-based reconstruction that embodies multipeak liver fat spectral modeling and multipoint optimization, and which is compatible with asymmetric echo acquisitions. MAGO is assessed first for accuracy and reproducibility on publicly available phantom data. Then, MAGO is applied to N = 178 UK Biobank cases, in which its liver PDFF measures are compared using Bland-Altman analysis with those from a version of the hybrid iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) algorithm, LiverMultiScan IDEAL (LMS IDEAL, Perspectum Diagnostics Ltd, Oxford, UK). Finally, MAGO is tested on a succession of high field challenging cases for which LMS IDEAL generated artefacts in the PDFF maps. RESULTS: Phantom data showed accurate, reproducible MAGO PDFF values across manufacturers, field strengths, and acquisition protocols. Moreover, we report excellent agreement between MAGO and LMS IDEAL for 6-echo, 1.5 tesla human acquisitions (bias = -0.02% PDFF, 95% confidence interval = ±0.13% PDFF). When tested on 12-echo, 3 tesla cases from different manufacturers, MAGO was shown to be more robust to artefacts compared to LMS IDEAL. CONCLUSION: MAGO resolves the water-fat ambiguity over the entire fat fraction dynamic range without compromising accuracy, therefore enabling robust PDFF estimation where phase data is inaccessible or unreliable and complex-based and hybrid methods fail.

Segmentation of Vasculature From Fluorescently Labeled Endothelial Cells in Multi-Photon Microscopy Images.

Vasculature is known to be of key biological significance, especially in the study of tumors. As such, considerable effort has been focused on the automated segmentation of vasculature in medical and pre-clinical images. The majority of vascular segmentation methods focus on bloodpool labeling methods; however, particularly, in the study of tumors, it is of particular interest to be able to visualize both the perfused and the non-perfused vasculature. Imaging vasculature by highlighting the endothelium provides a way to separate the morphology of vasculature from the potentially confounding factor of perfusion. Here, we present a method for the segmentation of tumor vasculature in 3D fluorescence microscopic images using signals from the endothelial and surrounding cells. We show that our method can provide complete and semantically meaningful segmentations of complex vasculature using a supervoxel-Markov random field approach. We show that in terms of extracting meaningful segmentations of the vasculature, our method outperforms both state-of-the-art method, specific to these data, as well as more classical vasculature segmentation methods.

Functional Parameters Derived from Magnetic Resonance Imaging Reflect Vascular Morphology in Preclinical Tumors and in Human Liver Metastases.

Purpose: Tumor vessels influence the growth and response of tumors to therapy. Imaging vascular changes in vivo using dynamic contrast-enhanced MRI (DCE-MRI) has shown potential to guide clinical decision making for treatment. However, quantitative MR imaging biomarkers of vascular function have not been widely adopted, partly because their relationship to structural changes in vessels remains unclear. We aimed to elucidate the relationships between vessel function and morphology in vivo Experimental Design: Untreated preclinical tumors with different levels of vascularization were imaged sequentially using DCE-MRI and CT. Relationships between functional parameters from MR (iAUC, K trans, and BATfrac) and structural parameters from CT (vessel volume, radius, and tortuosity) were assessed using linear models. Tumors treated with anti-VEGFR2 antibody were then imaged to determine whether antiangiogenic therapy altered these relationships. Finally, functional-structural relationships were measured in 10 patients with liver metastases from colorectal cancer.Results: Functional parameters iAUC and K trans primarily reflected vessel volume in untreated preclinical tumors. The relationships varied spatially and with tumor vascularity, and were altered by antiangiogenic treatment. In human liver metastases, all three structural parameters were linearly correlated with iAUC and K trans For iAUC, structural parameters also modified each other's effect.Conclusions: Our findings suggest that MR imaging biomarkers of vascular function are linked to structural changes in tumor vessels and that antiangiogenic therapy can affect this link. Our work also demonstrates the feasibility of three-dimensional functional-structural validation of MR biomarkers in vivo to improve their biological interpretation and clinical utility. Clin Cancer Res; 24(19); 4694-704. ©2018 AACR.

On the lubricity of transition metal dichalcogenides: an ab initio study.

Owing to specific characteristics engendered by their lamellar structures, transition metal dichalcogenides are posited as being some of the best dry lubricants available. Herein, we report a density functional investigation into the sliding properties and associated phenomena of these materials. Calculated potential energy and charge transfer profiles are used to highlight the dependence of shear strength on chemical composition and bilayer orientation (sliding direction). Furthermore, our calculations underscore the intrinsic relationship between incommensurate crystals and the oft-touted superlubric behaviour of molybdenum disulfide.

Comparison of linear and nonlinear implementation of the compartmental tissue uptake model for dynamic contrast-enhanced MRI.

PURPOSE: Fitting tracer kinetic models using linear methods is much faster than using their nonlinear counterparts, although this comes often at the expense of reduced accuracy and precision. The aim of this study was to derive and compare the performance of the linear compartmental tissue uptake (CTU) model with its nonlinear version with respect to their percentage error and precision. THEORY AND METHODS: The linear and nonlinear CTU models were initially compared using simulations with varying noise and temporal sampling. Subsequently, the clinical applicability of the linear model was demonstrated on 14 patients with locally advanced cervical cancer examined with dynamic contrast-enhanced magnetic resonance imaging. RESULTS: Simulations revealed equal percentage error and precision when noise was within clinical achievable ranges (contrast-to-noise ratio >10). The linear method was significantly faster than the nonlinear method, with a minimum speedup of around 230 across all tested sampling rates. Clinical analysis revealed that parameters estimated using the linear and nonlinear CTU model were highly correlated (ρ ≥ 0.95). CONCLUSION: The linear CTU model is computationally more efficient and more stable against temporal downsampling, whereas the nonlinear method is more robust to variations in noise. The two methods may be used interchangeably within clinical achievable ranges of temporal sampling and noise. Magn Reson Med 77:2414-2423, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Oncological image analysis.

Cancer is one of the world's major healthcare challenges and, as such, an important application of medical image analysis. After a brief introduction to cancer, we summarise some of the major developments in oncological image analysis over the past 20 years, but concentrating those in the authors' laboratories, and then outline opportunities and challenges for the next decade.

Pieces-of-parts for supervoxel segmentation with global context: Application to DCE-MRI tumour delineation.

Rectal tumour segmentation in dynamic contrast-enhanced MRI (DCE-MRI) is a challenging task, and an automated and consistent method would be highly desirable to improve the modelling and prediction of patient outcomes from tissue contrast enhancement characteristics - particularly in routine clinical practice. A framework is developed to automate DCE-MRI tumour segmentation, by introducing: perfusion-supervoxels to over-segment and classify DCE-MRI volumes using the dynamic contrast enhancement characteristics; and the pieces-of-parts graphical model, which adds global (anatomic) constraints that further refine the supervoxel components that comprise the tumour. The framework was evaluated on 23 DCE-MRI scans of patients with rectal adenocarcinomas, and achieved a voxelwise area-under the receiver operating characteristic curve (AUC) of 0.97 compared to expert delineations. Creating a binary tumour segmentation, 21 of the 23 cases were segmented correctly with a median Dice similarity coefficient (DSC) of 0.63, which is close to the inter-rater variability of this challenging task. A second study is also included to demonstrate the method's generalisability and achieved a DSC of 0.71. The framework achieves promising results for the underexplored area of rectal tumour segmentation in DCE-MRI, and the methods have potential to be applied to other DCE-MRI and supervoxel segmentation problems.

Improving In Vivo High-Resolution CT Imaging of the Tumour Vasculature in Xenograft Mouse Models through Reduction of Motion and Bone-Streak Artefacts.

INTRODUCTION: Preclinical in vivo CT is commonly used to visualise vessels at a macroscopic scale. However, it is prone to many artefacts which can degrade the quality of CT images significantly. Although some artefacts can be partially corrected for during image processing, they are best avoided during acquisition. Here, a novel imaging cradle and tumour holder was designed to maximise CT resolution. This approach was used to improve preclinical in vivo imaging of the tumour vasculature. PROCEDURES: A custom built cradle containing a tumour holder was developed and fix-mounted to the CT system gantry to avoid artefacts arising from scanner vibrations and out-of-field sample positioning. The tumour holder separated the tumour from bones along the axis of rotation of the CT scanner to avoid bone-streaking. It also kept the tumour stationary and insensitive to respiratory motion. System performance was evaluated in terms of tumour immobilisation and reduction of motion and bone artefacts. Pre- and post-contrast CT followed by sequential DCE-MRI of the tumour vasculature in xenograft transplanted mice was performed to confirm vessel patency and demonstrate the multimodal capacity of the new cradle. Vessel characteristics such as diameter, and branching were quantified. RESULTS: Image artefacts originating from bones and out-of-field sample positioning were avoided whilst those resulting from motions were reduced significantly, thereby maximising the resolution that can be achieved with CT imaging in vivo. Tumour vessels ≥ 77 µm could be resolved and blood flow to the tumour remained functional. The diameter of each tumour vessel was determined and plotted as histograms and vessel branching maps were created. Multimodal imaging using this cradle assembly was preserved and demonstrated. CONCLUSIONS: The presented imaging workflow minimised image artefacts arising from scanner induced vibrations, respiratory motion and radiopaque structures and enabled in vivo CT imaging and quantitative analysis of the tumour vasculature at higher resolution than was possible before. Moreover, it can be applied in a multimodal setting, therefore combining anatomical and dynamic information.

A copper(I)-arene complex with an unsupported η6 interaction.

Addition of PR3 (R=Ph or OPh) to [Cu(η(2)-Me6C6)2][PF6] results in the formation of [(η(6)-Me6C6)Cu(PR3)][PF6], the first copper-arene complexes to feature an unsupported η(6) arene interaction. A DFT analysis reveals that the preference for the η(6) binding mode is enforced by the steric clash between the methyl groups of the arene ligand and the phenyl rings of the phosphine co-ligand.

Computational cogitation of Cn@Al12 clusters.

A variety of novel Cn Al12 core-shell nanoclusters have been investigated using density functional calculations. A series of Cn cores (n=1-4) have been encapsulated by icosahedral Al12 , with characteristic physical properties (energetics and stabilities, ionisation energies, electron affinities) calculated for each cluster. Other isomers, with the Cn moiety bound externally to the Al12 shell, have also been studied. For both series, a peak in stability was found for n(C)=2, a characteristic that appears to be inextricably linked with the relaxation of the constituent parts upon dissociation. Analysis of trends for ionisation energies and electron affinities includes evaluation of contributions from the carbon and aluminium components, which highlights the effects of composition and morphology on cluster properties.

Communication: a density functional investigation of structure-property evolution in the tetrakis hexahedral C4Al14 nanocluster.

Nanoclusters are prime objects of study in modern nanotechnology and offer a variety of applications promoted by their properties tunable by size, shape, and composition. DFT calculations are employed to analyze structure, stability, and selected electronic properties of a core-shell C4Al14 species. With insertion of the carbon core, the original low-symmetry aluminum cluster is predicted to undergo a considerable reshaping and acquire a striking D4h tetrakis-hexahedral geometry, with proportions controlled by a near-degenerate spin state or charge. The system also becomes more stable to dissociation. Surprisingly, other properties such as ionisation energy and electron affinity do not change significantly, although still exhibit some interesting features including opposite variations for vertical and adiabatic values. The stability and property evolutions are analyzed in terms of contributions from reshaping of the shell and its further interaction with the core. The system thus has potential applications as a symmetric building unit and a molecular device for nano-electronics/spintronics.

Automated colorectal tumour segmentation in DCE-MRI using supervoxel neighbourhood contrast characteristics.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a powerful protocol for assessing tumour progression from changes in tissue contrast enhancement. Manual colorectal tumour delineation is a challenging and time consuming task due to the complex enhancement patterns in the 4D sequence. There is a need for a consistent approach to colorectal tumour segmentation in DCE-MRI and we propose a novel method based on detection of the tumour from signal enhancement characteristics of homogeneous tumour subregions and their neighbourhoods. Our method successfully detected 20 of 23 cases with a mean Dice score of 0.68 +/- 0.15 compared to expert annotations, which is not significantly different from expert inter-rater variability of 0.73 +/- 0.13 and 0.77 +/- 0.10. In comparison, a standard DCE-MRI tumour segmentation technique, fuzzy c-means, obtained a Dice score of 0.28 +/- 0.17.

Computer assisted detection of abnormal airway variation in CT scans related to paediatric tuberculosis.

Airway deformation and stenosis can be key signs of pathology such as lymphadenopathy. This study presents a local airway point distribution model (LA-PDM) to automatically analyse regions of the airway tree in CT scans and identify abnormal airway deformation. In our method, the airway tree is segmented and the centreline identified from each chest CT scan. Thin-plate splines, along with a local mesh alignment method for tubular meshes, are used to register the airways and develop point distribution models (PDM). Each PDM is then used to analyse and classify local regions of the airway. This LA-PDM method was developed using 89 training cases and evaluated on a 90 CT test set, where each set includes paediatric tuberculosis (TB) cases (with airway involvement) and non-TB cases (without airway involvement). The LA-PDM was able to accurately distinguish cases with airway involvement with an AUC of the ROC classification (and 95% confidence interval) of 0.87 (0.77-0.94) for the Trachea-LMB-RMB region and 0.81 (0.68-0.90) for the RMB-RUL-BI region - outperforming a comparison method based on airway cross-sectional features. This has the potential to assist and improve airway analysis from CT scans by detecting involved airways and visualising affected airway regions.

A computational study of 'Al-kanes' and 'Al-kenes'.

Two novel series of 'Al-kanes' (CnAl2n+2) and 'Al-kenes' (CnAl2n) have been studied theoretically in order to shed light on their structure, stability and properties. Density functional calculations suggest that the structures tend to be dictated by the constituent aluminium atoms, rather than the carbon backbone. This is the net effect of the aluminiums attempting to adopt preferred close-packed structures. Calculated energetics suggest a special stability of clusters with n(C) = 2 and 4 in both series and plausible interpretations are suggested.

Technical developments in postprocessing of paediatric airway imaging.

CT postprocessing allows more scan information to be viewed at one time allowing an accurate diagnosis to be made more efficiently, and is particularly important in paediatric practice where invasive clinical diagnostic tools can be replaced or at least assisted by modern postprocessing techniques. Four visualization techniques in clinical use are described in this paper including the advantages and disadvantages of each: multiplanar reformation, maximum and minimum intensity projections, shaded surface display and volume rendering. Volume-rendered internal visualization in the form of virtual endoscopy is also discussed. In addition, the clinical usefulness in paediatric practice of demonstrating airway compression and its causes are discussed. Advanced postprocessing techniques that must still find their way from the biomedical research environment into clinical use are introduced with specific reference to computer-aided diagnosis.

Extraction of airways from CT (EXACT'09).

This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part of the airway tree. Finally, the reference airway trees are constructed by taking the union of all correctly extracted branch segments. Fifteen airway tree extraction algorithms from different research groups are evaluated on a diverse set of twenty chest computed tomography (CT) scans of subjects ranging from healthy volunteers to patients with severe pathologies, scanned at different sites, with different CT scanner brands, models, and scanning protocols. Three performance measures covering different aspects of segmentation quality were computed for all participating algorithms. Results from the evaluation showed that no single algorithm could extract more than an average of 74% of the total length of all branches in the reference standard, indicating substantial differences between the algorithms. A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.

Identification of paediatric tuberculosis from airway shape features.

Clinical signs of paediatric pulmonary tuberculosis (TB) include stenosis and deformation of the airways. This paper presents two methods to analyse airway shape and detect airway pathology from CT images. Features were extracted using (1) the principal components of the airway surface mesh and (2) branch radius and orientation features. These methods were applied to a dataset of 61 TB and non-TB paediatric patients. Nested cross-validation of the support vector classifier found the sensitivity of detecting TB to be 86% and a specificity of 91% for the first 10 PCA modes while radius based features had a sensitivity of 86% and a specificity of 94%. These methods show the potential of computer assisted detection of TB and other airway pathology from airway shape deformation.

Structure-activity relationship refinement and further assessment of indole-3-glyoxylamides as a lead series against prion disease.

Structure-activity relationships within the indole-3-glyoxylamide series of antiprion agents have been explored further, resulting in discovery of several new compounds demonstrating excellent activity in a cell line model of prion disease (EC50 <10 nM). After examining a range of substituents at the para-position of the N-phenylglyoxylamide moiety, five-membered heterocycles containing at least two heteroatoms were found to be optimal for the antiprion effect. A number of modifications were made to probe the importance of the glyoxylamide substructure, although none were well tolerated. The most potent compounds did, however, prove largely stable towards microsomal metabolism, and the most active library member cured scrapie-infected cells indefinitely on administration of a single treatment. The present results thereby confirm the indole-3-glyoxylamides as a promising lead series for continuing in vitro and in vivo evaluation against prion disease.