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Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.

IntroductionOur hospital redeployed healthcare professionals to implement a telephone-based Virtual Covid Ward (VCW) during the COVID-19 pandemic. Standardised clinical assessment included numeric (0 – 10) rating scales (NRS) for breathlessness and cough, and pulse oximetry.Aims and objectivesTo assess staff experience of routine breathlessness documentation by surveying feedback on the clinical effectiveness of assessment tools used in the VCW.MethodsData were obtained from an anonymous online survey distributed to VCW staff, summarised in themes and analysed with descriptive statistics.Results9/19 VCW staff completed the survey; 9 female; 5 nurses, 3 physiotherapists, 1 Operating Department Practitioner; 8 were senior, 1 junior. 100% had acute or respiratory medicine experience, 66% had experience in remote assessments. 100% reported absence of breathlessness at rest the most reassuring sign when discharging patients. 100% confidence when assessing breathlessness over the phone. 100% felt breathlessness was a ‘red flag’. 66% found the breathlessness NRS useful and 67% found the cough NRS useful. 89% believed patients’ responses were meaningful at least half the time. 78% believed patients overestimated the breathlessness score at least half of the time and 55% believed patients underestimated respiratory distress.ConclusionVCW staff were confident in assessing patients remotely and using the NRS. Staff found assessment of breathlessness useful in predicting adverse patient outcomes, but were less confident using the NRS (0–10) rating scale to quantify breathlessness was clinically valuable.

Extracellular vesicles (EVs) are nano-sized, natural, cell-derived vesicles that contain the same nucleic acids, proteins, and lipids as their source cells. Thus, they can serve as natural carriers for therapeutic agents and drugs, and have many advantages over conventional nanocarriers, including their low immunogenicity, good biocompatibility, natural blood – brain barrier penetration, and capacity for gene delivery. This review first introduces the classification of EVs and then discusses several currently popular methods for isolating and purifying EVs, EVs-mediated drug delivery, and the functionalization of EVs as carriers. Thereby, it provides new avenues for the development of EVs-based therapeutic strategies in different fields of medicine. Finally, it highlights some challenges and future perspectives with regard to the clinical application of EVs. Graphical Abstract Highlights Various current techniques for isolating extracellular vesicles are reviewed, and their advantages and disadvantages are compared. An overview of the strategies used for the modification of extracellular vesicles and their application as delivery systems or therapeutic agents in different diseases is provided. Several challenges in the clinical application of extracellular vesicles-based nanoplatforms are discussed, along with solutions for their implementation as a promising therapeutic tool.

Curcumin is a bioactive compound that is extracted from Curcuma longa and that is known for its antimicrobial properties. Curcuminoids are the main constituents of curcumin that exhibit antioxidant properties. It has a broad spectrum of antibacterial actions against a wide range of bacteria, even those resistant to antibiotics. Curcumin has been shown to be effective against the microorganisms that are responsible for surgical infections and implant-related bone infections, primarily Staphylococcus aureus and Escherichia coli. The efficacy of curcumin against Helicobacter pylori and Mycobacterium tuberculosis, alone or in combination with other classic antibiotics, is one of its most promising antibacterial effects. Curcumin is known to have antifungal action against numerous fungi that are responsible for a variety of infections, including dermatophytosis. Candidemia and candidiasis caused by Candida species have also been reported to be treated using curcumin. Life-threatening diseases and infections caused by viruses can be counteracted by curcumin, recognizing its antiviral potential. In combination therapy with other phytochemicals, curcumin shows synergistic effects, and this approach appears to be suitable for the eradication of antibiotic-resistant microbes and promising for achieving co-loaded antimicrobial pro-regenerative coatings for orthopedic implant biomaterials. Poor water solubility, low bioavailability, and rapid degradation are the main disadvantages of curcumin. The use of nanotechnologies for the delivery of curcumin could increase the prospects for its clinical application, mainly in orthopedics and other surgical scenarios. Curcumin-loaded nanoparticles revealed antimicrobial properties against S. aureus in periprosthetic joint infections.

All patients admitted with COVID-19 pneumonia should have a chest X-ray (CXR) at 6–12 weeks as per British Thoracic Society (BTS). Our study firstly aims to report our compliance with these recommendations. Secondly, we aim to quantify CXR changes on follow up, and also on alternative investigations that may be more sensitive. We also analyse mortality data between the first two waves.Our study is a single-centre retrospective audit of 1759 COVID-19 positive patients admitted to a district general hospital in the UK, over a 50-week period, between March 2020 and February 2021. Mortality data was gathered over a period of 5 weeks around the peaks of each wave to give comparable populations. CXRs were analysed by an appropriately trained physician, and this was used to give a subjective rating of COVID severity.Our results demonstrated that there was a significant difference between the mortality data and survival between the first and second wave. Additionally, our data aligns with other comparable studies demonstrating radiological changes at follow-up in both CXRs and Computerised Tomography (CT) scans. These studies concluded that CXRs are cost-efficient in monitoring ongoing COVID-related changes and support BTS recommendations. One study showed that for monitoring of ongoing long-term sequelae of COVID, CT scans were more sensitive as reinforced by our study, although logistically challenging.1 Abstract P162 Table 1Comparison of CXR changes between initial CXR and follow-up CXRWe found 4.5% of patients received a follow-up CXR in 6–12 weeks. This study demonstrates that awareness and compliance with BTS guidelines falls short, supported by similar studies. Additionally, monitoring could be improved through the use of machine learning and universal CXR scoring tools to stratify CXR severity, which could reduce clinician workload and the need for CT scans.2 ReferencesX. Han, Y. Fan, O. Alwalid, N. Li, X. Jia, M. Yuan, Y. Li, Y. Cao, J. Gu, H. Wu and H. Shi, ‘Six-month Follow-up Chest CT Findings after Severe COVID-19 Pneumonia,’ Radiology, vol. 299, no. 1, pp. E177-E186, April 2021.J. Cohen, L. Dao, K. Roth, P. Morrison, Y. Bengio, A. Abbasi, B. Shen, H. Mahsa, M. Ghassemi, H. Li and T. Duong, ‘Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning,’ Cureus, vol. 12, no. 7, p. e9448, 28 July 2020.

IntroductionPneumothorax is a rare but important complication of COVID-19.1 Although barotrauma may account for some cases, many affected patients have not received positive-pressure ventilatory (PPV) support1. The pathophysiology of COVID-pneumothorax is challenging to investigate because imaging data exist in diverse silos and only 0.97% of patients admitted for COVID-19 experience this complication.1 To provide mechanistic insight, we used artificial intelligence at scale to identify cases for detailed analysis from 4 large imaging datasets across 26 centres in 7 countries.MethodsA convolutional neural network was trained to detect pneumothorax on chest x-rays (CXRs) using the open-source CheXpert dataset, which includes 17,313 pneumothoraces. Testing was performed on labelled subsamples of the COVID-19 datasets. After running the model on all COVID-positive CXRs, predicted pneumothoraces were reviewed and the incidence of COVID-pneumothorax was estimated. Available CTs for patients with pneumothorax were assessed by radiologists. Radiology reports were used to curate additional CTs for two datasets.Results and DiscussionQuantitative results are summarised in figure 1. Adjusting for model sensitivity, the estimated incidence of COVID-pneumothorax was 0.97%, consistent with previous research.1 45 pneumothorax patients with CTs were identified; however, 13 unrelated to COVID-19, and 9 iatrogenic cases (except barotrauma) were excluded. Almost all remaining patients displayed diffuse, moderate-to-severe pneumonitis.Most pneumothoraces in patients on PPV were likely related to an interplay of barotrauma and COVID-19, with an acute lung injury pattern on CT. A high proportion demonstrated emphysema and three patients developed cystic abnormalities. One case followed a cavitating pulmonary infarction secondary to pulmonary embolism.Patients who had not received PPV, or had but were stepped down, developed pneumothoraces later in the disease. CT showed patterns consistent with the absorption stage of COVID-19, where consolidation is reduced but ground glass opacification persists with development of irregular bronchial dilatation. Such pneumothoraces perhaps represent increased parenchymal resistance.Abstract P164 Figure 1ConclusionThere are multiple mechanisms of COVID-pneumothorax. Barotrauma in patients with acute lung injury is most common, whilst pneumothorax in the absence of PPV most commonly occurs in the sub-acute, absorption stage of the disease.ReferenceMarciniak SJ, et al. COVID-19 Pneumothorax in the United Kingdom. ERJ 2021.Please refer to page A215 for declarations of interest related to this abstract.