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Background: Advances in computational methodologies have enabled processing of large datasets originating from imaging studies. However, most imaging biomarkers suffer from a lack of direct links with underlying biology, as they are only observationally correlated with pathophysiology. Purpose(s): To develop and validate a novel AI-assisted image analysis platform, by applying quantitative radiotranscriptomics that quantifies cytokinedriven vascular inflammation from routine CT angiograms (CTA) performed as part of clinical care in COVID-19. Method(s): We used this platform to train the radiotranscriptomic signature C19-RS, derived from the perivascular space around the aorta and the internal mammary artery in routine chest CTAs, to best describe cytokinedriven vascular inflammation, defined using transcriptomic profiles from RNA sequencing data from human arterial biopsies (A). This signature was validated externally in 358 clinically indicated CT pulmonary angiograms from patients with or without COVID-19 from 3 different geographical regions. Result(s): First, 22 patients who had a CTA before the pandemic underwent repeat CTA <6 months post COVID-19 infection (B). Compared with 22 controls (matched for age, gender, and BMI) C19-RS was increased only in the COVID-19 group (C). Next, C19-RS was calculated in a cohort of 331 patients hospitalised during the pandemic, and was higher in COVID-19 positives (adjusted OR=2.97 [95% CI: 1.43-6.27], p=0.004, D). C19-RS had prognostic value for in-hospital mortality in COVID-19, with HR=3.31 ([95% CI: 1.49-7.33], p=0.003) and 2.58 ([95% CI: 1.10-6.05], p=0.028) in two testing cohorts respectively (E, F), adjusted for clinical factors and biochemical biomarkers of inflammation and myocardial injury. The corrected HR for in-hospital mortality was 8.24 [95% CI: 2.16-31.36], p=0.002 for those who received no treatment with dexamethasone, but only 2.27 [95% CI: 0.69-7.55], p=0.18 in those who received dexamethasone subsequently to the C19-RS based image analysis, suggesting that vascular inflammation may have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0.61, p=0.0003) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways. Conclusion(s): We present the first proof of concept study that combines transcriptomics with radiomics to provide a platform for the development of machine learning derived radiotranscriptomics analysis of routine clinical CT scans for the development of non-invasive imaging biomarkers. Application in COVID-19 produced C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation, that predicts inhospital mortality and identifies people who will have better response to anti-inflammatory treatments, allowing targeted therapy. This AI-assisted image analysis platform may have applications across a wide range of vascular diseases, from infections to autoimmune diseases.
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Background: CFTR modulators have led to improvements in CF outcomes, including FEV1, exacerbation frequency and body mass index (BMI). Despite positive outcomes, modulators have brought new challenges – particularly elevated BMI. For many, weight gain has been due to increased fat rather than muscle mass, making exercise a high priority. Exercise has always been an integral part of CF management. However, the COVID-19 pandemic has made it harder for patients to access exercise. This presented a service need to set up a platform where patients could safely exercise at home with support from a known physiotherapist. Objectives: To assess the feasibility and acceptability of a physiotherapyled online group exercise class for CF patients. Methods: In this pilot study, high and low intensity virtual exercise classes were delivered twice weekly over four weeks. Eight participants were recruited;five completed the study. The primary outcomes were (1) feasibility, assessed by means, resources and time needed to deliver the intervention and (2) acceptability, assessed by qualitative interviews with participants. FEV1, BMI, 60STS and psychosocial outcomes were also monitored. Results: Time, resources and equipment were all adequate to deliver the intervention within the service. Positive themes from interviews included: (1) Impact on health: improved fitness, (2) Motivation to exercise: feeling encouraged, supported and accountable, and (3) Convenience: saved time, money and ease of exercising at home. Some challenges patients reported were space, technical issues with equipment and missing face-to-face interaction. Conclusion: Virtual exercise classes for patients with CF are both feasible and acceptable, with patients reporting a positive impact on their fitness levels as well as reduced travel burden. Patients also stated that classes delivered by a familiar physiotherapist motivated them to exercise and instilled confidence that the exercises were safe and effective.Background: CFTR modulators have led to improvements in CF outcomes, including FEV1, exacerbation frequency and body mass index (BMI). Despite positive outcomes, modulators have brought new challenges – particularly elevated BMI. For many, weight gain has been due to increased fat rather than muscle mass, making exercise a high priority. Exercise has always been an integral part of CF management. However, the COVID-19 pandemic has made it harder for patients to access exercise. This presented a service need to set up a platform where patients could safely exercise at home with support from a known physiotherapist. Objectives: To assess the feasibility and acceptability of a physiotherapyled online group exercise class for CF patients. Methods: In this pilot study, high and low intensity virtual exercise classes were delivered twice weekly over four weeks. Eight participants were recruited;five completed the study. The primary outcomes were (1) feasibility, assessed by means, resources and time needed to deliver the intervention and (2) acceptability, assessed by qualitative interviews with participants. FEV1, BMI, 60STS and psychosocial outcomes were also monitored. Results: Time, resources and equipment were all adequate to deliver the intervention within the service. Positive themes from interviews included: (1) Impact on health: improved fitness, (2) Motivation to exercise: feeling encouraged, supported and accountable, and (3) Convenience: saved time, money and ease of exercising at home. Some challenges patients reported were space, technical issues with equipment and missing face-to-face interaction. Conclusion: Virtual exercise classes for patients with CF are both feasible and acceptable, with patients reporting a positive impact on their fitness levels as well as reduced travel burden. Patients also stated that classes delivered by a familiar physiotherapist motivated them to exercise and instilled confidence that the exercises were safe and effective.
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Background Evidence suggests that adverse outcomes in COVID-19 may be driven by a cytokine-induced vascular inflammatory response, caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). Aim We aimed to develop a non-invasive method for quantifying cytokine-driven vascular inflammation in patients with acute COVID-19 infection that could allow risk stratification. Methods We developed a platform for rapid development of novel imaging biomarkers of vascular inflammation, by applying quantitative radiotranscriptomics to images from standard Computed Tomography Angiography (CTA). We used this platform to train a radiotranscriptomic signature (C19-RS) from the perivascular space around the aorta and the internal mammary artery, visualized in routine chest CTAs, to best describe cytokine-driven vascular inflammation, defined using transcriptomic profiles from RNA sequencing data from human arterial biopsies. This signature was tested externally in 435 clinically indicated CT pulmonary angiograms (CTPAs) from patients with or without COVID-19 from 3 different geographical regions. Results COVID-19 patients were characterised by significantly higher C19-RS values (adjusted odds ratio of 2.97 [95%CI: 1.43-6.27], p=0.004), while patients infected with the new B.1.1.7 variant (“UK variant”) were also found to have higher C19-RS values compared to those with the original variant, evidence suggestive of higher degrees of vascular inflammation. C19-RS had prognostic value for in-hospital mortality in COVID-19, with hazard ratios of 3.31 ([95%CI: 1.49-7.33], p=0.003) and 2.58 ([95%CI: 1.10-6.05], p=0.028) in two external testing cohorts respectively, after correction for clinical factors and biochemical biomarkers of inflammation (WBC, CRP) and myocardial injury (troponin). Importantly, the corrected HR for in-hospital mortality was 8.24[95%CI: 2.16- 31.36], P=0.002 for those who received no treatment with dexamethasone, but only 2.27[95%CI: 0.69-7.55], p=0.18 in those who received dexamethasone after the test, suggesting that anti-inflammatory treatment may be modifying the natural history of COVID-19 infection by improving outcomes specifically in those patients with high vascular inflammation. Conclusions Our study introduces a new radiotranscriptomic signature, C19-RS, extracted from routine CTPAs, trained to detect cytokine-driven arterial inflammation, and demonstrates that vascular inflammation determined in this way has prognostic value in patients with COVID-19. The “UK variant” leads to higher vascular inflammation measured in this way, and the risk associated with COVID-19 arteritis is modifiable by dexamethasone.