Imperial College London

DrGrahamCole

Faculty of MedicineNational Heart & Lung Institute

Honorary Clinical Senior Lecturer
 
 
 
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g.cole

 
 
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ICTEM buildingHammersmith Campus

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Summary

 

Publications

Publication Type
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104 results found

Kelshiker M, Seligman H, Howard JAMES, Rahman H, Foley M, Nowbar A, Rajkumar C, Shun-Shin M, Ahmad Y, Sen S, Al-Lamee R, Cole G, Hoole S, Morris P, Rigo F, Mayet J, Francis D, Petraco Ret al., 2022, Coronary flow reserve and cardiovascular outcomes: a systematic review and meta-analysis, European Heart Journal, Vol: 43, Pages: 1582-1593, ISSN: 0195-668X

Aims: This meta-analysis aims to quantify the association of reduced coronary flow with all3 cause mortality and major adverse cardiovascular events (MACE) across a broad range of patient groups and pathologies. Methods and Results: We systematically identified all studies between 1st January 2000 and1st August 2020, where coronary flow was measured and clinical outcomes were reported. The endpoints were all-cause mortality and MACE. Estimates of effect were calculated from published hazard ratios using a random-effects model. 79 studies, including 59,740 subjects were included. Abnormal coronary flow reserve (CFR) was associated with a higher incidence of all-cause mortality (HR 3.78, 95% CI 2.39-5.97) and a higher incidence of MACE (HR 3.42, 95% CI 2.92-3.99). Each 0.1-unit reduction in CFR was associated with a proportional increase in mortality (per 0.1 CFR unit HR 1.16, 95% CI 1.04-1.29) and MACE (per 0.1 CFR unit HR 1.08, 95% CI 1.04-1.11)). In patients with isolated coronary microvascular dysfunction, an abnormal CFR was associated with a higher incidence of mortality (HR 5.44, 95% CI 3.78-7.83) and MACE (HR 3.56, 95% CI 2.14-5.90). Abnormal CFR was also associated with a higher incidence of MACE in patients with acute coronary syndromes (HR 3.76, 95% CI 2.35-6.00), heart failure (HR 6.38, 95% CI 1.95-20.90), heart transplant (HR 3.32, 95% CI 2.34-4.71) and diabetes mellitus (HR 7.47, 95% CI 3.37-16.55). Conclusions: Reduced coronary flow is strongly associated with increased risk of all-cause mortality and MACE across a wide range of pathological processes. This finding supports recent recommendations that coronary flow should be measured more routinely in clinical practice to target aggressive vascular risk modification for individuals at higher risk

Journal article

Seraphim A, Dowsing B, Rathod KS, Shiwani H, Patel K, Knott KD, Zaman S, Johns I, Razvi Y, Patel R, Xue H, Jones DA, Fontana M, Cole G, Uppal R, Davies R, Moon JC, Kellman P, Manisty Cet al., 2022, Quantitative Myocardial Perfusion Predicts Outcomes in Patients With Prior Surgical Revascularization., J Am Coll Cardiol, Vol: 79, Pages: 1141-1151

BACKGROUND: Patients with previous coronary artery bypass graft (CABG) surgery typically have complex coronary disease and remain at high risk of adverse events. Quantitative myocardial perfusion indices predict outcomes in native vessel disease, but their prognostic performance in patients with prior CABG is unknown. OBJECTIVES: In this study, we sought to evaluate whether global stress myocardial blood flow (MBF) and perfusion reserve (MPR) derived from perfusion mapping cardiac magnetic resonance (CMR) independently predict adverse outcomes in patients with prior CABG. METHODS: This was a retrospective analysis of consecutive patients with prior CABG referred for adenosine stress perfusion CMR. Perfusion mapping was performed in-line with automated quantification of MBF. The primary outcome was a composite of all-cause mortality and major adverse cardiovascular events defined as nonfatal myocardial infarction and unplanned revascularization. Associations were evaluated with the use of Cox proportional hazards models after adjusting for comorbidities and CMR parameters. RESULTS: A total of 341 patients (median age 67 years, 86% male) were included. Over a median follow-up of 638 days (IQR: 367-976 days), 81 patients (24%) reached the primary outcome. Both stress MBF and MPR independently predicted outcomes after adjusting for known prognostic factors (regional ischemia, infarction). The adjusted hazard ratio (HR) for 1 mL/g/min of decrease in stress MBF was 2.56 (95% CI: 1.45-4.35) and for 1 unit of decrease in MPR was 1.61 (95% CI: 1.08-2.38). CONCLUSIONS: Global stress MBF and MPR derived from perfusion CMR independently predict adverse outcomes in patients with previous CABG. This effect is independent from the presence of regional ischemia on visual assessment and the extent of previous infarction.

Journal article

Ahmad Y, Kane C, Arnold AD, Cook C, Keene D, Shun-Shin M, Cole G, Al-Lamee R, Francis D, Howard Jet al., 2022, Randomized blinded placebo-controlled trials of renal sympathetic denervation for hypertension: a meta-analysis, Cardiovascular Revascularization Medicine, Vol: 34, Pages: 112-118, ISSN: 1553-8389

BackgroundThe efficacy of renal denervation has been controversial, but the procedure has now undergone several placebo-controlled trials. New placebo-controlled trial data has recently emerged, with longer follow-up of one trial and the full report of another trial (which constitutes 27% of the total placebo-controlled trial data). We therefore sought to evaluate the effect of renal denervation on ambulatory and office blood pressures in patients with hypertension.MethodsWe systematically identified all blinded placebo-controlled randomized trials of catheter-based renal denervation for hypertension. The primary efficacy outcome was ambulatory systolic blood pressure change relative to placebo. A random-effects meta-analysis was performed.Results6 studies randomizing 1232 patients were eligible. 713 patients were randomized to renal denervation and 519 to placebo. Renal denervation significantly reduced ambulatory systolic blood pressure (−3.52 mmHg; 95% CI −4.94 to −2.09; p < 0.0001), ambulatory diastolic blood pressure (−1.93 mmHg; 95% CI −3.04 to −0.83, p = 0.0006), office systolic blood pressure size (−5.10 mmHg; 95% CI −7.31 to −2.90, p < 0.0001) and office diastolic pressure (effect size −3.11 mmHg; 95% CI −4.43 to −1.78, p < 0.0001). Adverse events were rare and not more common with denervation.ConclusionsThe totality of blinded, randomized placebo-controlled data shows that renal denervation is safe and provides genuine reduction in blood pressure for at least 6 months post-procedure. If this effect continues in the long term, renal denervation might provide a life-long 10% relative risk reduction in major adverse cardiac events and 7.5% relative risk reduction in all-cause mortality.

Journal article

Zaman S, Petri C, Vimalesvaran K, Howard J, Bharath A, Francis D, Peters N, Cole GD, Linton Net al., 2022, Automatic diagnosis labeling of cardiovascular MRI by using semisupervised natural language processing of text reports, Radiology: Artificial Intelligence, Vol: 4, ISSN: 2638-6100

A semisupervised natural language processing (NLP) algorithm, based on bidirectional transformers, accurately categorized diagnoses from cardiac MRI text of radiology reports for the labeling of MR images; the model had a higher accuracy than traditional NLP models and performed faster labeling than clinicians.

Journal article

Thornton GD, Shetye A, Knight DS, Knott K, Artico J, Kurdi H, Yousef S, Antonakaki D, Razvi Y, Chacko L, Brown J, Patel R, Vimalesvaran K, Seraphim A, Davies R, Xue H, Kotecha T, Bell R, Manisty C, Cole GD, Moon JC, Kellman P, Fontana M, Treibel TAet al., 2021, Myocardial Perfusion Imaging After Severe COVID-19 Infection Demonstrates Regional Ischemia Rather Than Global Blood Flow Reduction, FRONTIERS IN CARDIOVASCULAR MEDICINE, Vol: 8, ISSN: 2297-055X

Journal article

Kellman P, Xue H, Chow K, Howard J, Chacko L, Cole G, Fontana Met al., 2021, Bright-blood and dark-blood phase sensitive inversion recovery late gadolinium enhancement and T1 and T2 maps in a single free-breathing scan: an all-in-one approach, JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE, Vol: 23, ISSN: 1097-6647

Journal article

Howard J, Zaman S, Francis D, Cole Get al., 2021, INTELLIGENT LOCALISERS: AN INTEGRATED TIME-SAVING DEEP LEARNING SOLUTION FOR THE PLANNING OF CINE IMAGING AND IDENTIFICATION OF UNEXPECTED FINDINGS FROM A SINGLE TRANSAXIAL STACK, Annual Meeting of the British-Society-of-Cardiovascular-Magnetic-Resonance (BSCMR), Publisher: BMJ PUBLISHING GROUP, Pages: A5-A6, ISSN: 1355-6037

Conference paper

Bachtiger P, Park S, Letchford E, Scott F, Barton C, Ahmed FZ, Cole G, Keene D, Plymen CM, Peters NSet al., 2021, Triage-HF plus: 12-month study of remote monitoring pathway for triage of heart failure risk initiated during the Covid-19 pandemic, Publisher: OXFORD UNIV PRESS, Pages: 3082-3082, ISSN: 0195-668X

Conference paper

Stowell C, Howard J, Cole G, Ananthan K, Demetrescu C, Pearce K, Rajani R, Sehmi J, Vimalesvaran K, Kanaganayagam S, Ghosh A, Chambers J, Rana B, Francis D, Shun-Shin Met al., 2021, Automated left ventricular dimension assessment using artificial intelligence, Publisher: OXFORD UNIV PRESS, Pages: 1-1, ISSN: 0195-668X

Conference paper

Stowell C, Howard J, Demetrescu C, Bhattacharyya S, Mangion K, Vimalesvaran K, Cole G, Rajani R, Sehmi J, Alzetani M, Zolgharni M, Rana B, Francis D, Shun-Shin Met al., 2021, Fully automated global longitudinal strain assessment using artificial intelligence developed and validated by a UK-wide echocardiography expert collaborative, Publisher: OXFORD UNIV PRESS, Pages: 2-2, ISSN: 0195-668X

Conference paper

Banerjee M, Chiew D, Patel K, Johns I, Chappell D, Linton N, Cole G, Francis D, Szram J, Ross J, Zaman Set al., 2021, The impact of artificial intelligence on clinical education: Perceptions of postgraduate trainee doctors in London (UK) and recommendations for trainers., BMC Medical Education, Vol: 21, Pages: 1-10, ISSN: 1472-6920

BackgroundArtificial intelligence (AI) technologies are increasingly used in clinical practice. Although there is robust evidence that AI innovations can improve patient care, reduce clinicians’ workload and increase efficiency, their impact on medical training and education remains unclear.MethodsA survey of trainee doctors’ perceived impact of AI technologies on clinical training and education was conducted at UK NHS postgraduate centers in London between October and December 2020. Impact assessment mirrored domains in training curricula such as ‘clinical judgement’, ‘practical skills’ and ‘research and quality improvement skills’. Significance between Likert-type data was analysed using Fisher’s exact test. Response variations between clinical specialities were analysed using k-modes clustering. Free-text responses were analysed by thematic analysis.Results210 doctors responded to the survey (response rate 72%). The majority (58%) perceived an overall positive impact of AI technologies on their training and education. Respondents agreed that AI would reduce clinical workload (62%) and improve research and audit training (68%). Trainees were skeptical that it would improve clinical judgement (46% agree, p=0.12) and practical skills training (32% agree, p<0.01). The majority reported insufficient AI training in their current curricula (92%), and supported having more formal AI training (81%).ConclusionsTrainee doctors have an overall positive perception of AI technologies’ impact on clinical training. There is optimism that it will improve ‘research and quality improvement’ skills and facilitate ‘curriculum mapping’. There is skepticism that it may reduce educational opportunities to develop ‘clinical judgement’ and ‘practical skills’. Medical educators should be mindful that these domains are protected as AI develops. We recommend that ‘Applied AI&r

Journal article

Rajkumar C, Shun-Shin M, Seligman H, Ahmad Y, Warisawa T, Cook C, Howard J, Ganesananthan S, Amarin L, Khan C, Ahmed A, Nowbar A, Foley M, Assomull R, Keenan N, Sehmi J, Keeble T, davies J, Tang K, Gerber R, Cole G, O'Kane P, Sharp A, Khamis R, Kanaganayagam G, Petraco R, Ruparelia N, Malik I, Nijjer S, Sen S, Francis D, Al-Lamee Ret al., 2021, Placebo-controlled efficacy of percutaneous coronary intervention for focal and diffuse patterns of stable coronary artery disease, Circulation: Cardiovascular Interventions, Vol: 14, Pages: 809-818, ISSN: 1941-7640

Background Physiological assessment with pressure wire pullback can characterize coronary artery disease (CAD) with a focal or diffuse pattern. However, the clinical relevance of this distinction is unknown. We use data from ORBITA to test if the pattern of CAD predicts the placebo-controlled efficacy of percutaneous coronary intervention (PCI) on stress echocardiography ischemia and symptom endpoints.Methods164 patients in ORBITA underwent blinded instantaneous wave-free ratio (iFR) pullback assessment prior to randomization. Focal disease was defined as 0.03 iFR unit drop within 15mm, rather than over a longer distance. Analyses were performed using regression modelling. ResultsIn the PCI arm (n=85), 48 were focal and 37 were diffuse. In the placebo arm (n=79), 35 were focal and 44 were diffuse. Focal stenoses were associated with significantly lower fractional flow reserve (FFR) and iFR values than diffusely diseased vessels (focal mean FFR and iFR 0.600.15 and 0.650.24, diffuse 0.780.10 and 0.880.08 respectively, p<0.0001). With adjustment for this difference, PCI for focal stenoses resulted in significantly greater reduction in stress echo ischemia than PCI for diffuse disease (p<0.05). The effect of PCI on between-arm pre-randomization-adjusted exercise time was 9.32 seconds (95% CI, -17.1 to 35.7s; p=0.487). When stratified for pattern of disease, there was no detectable difference between focal and diffuse CAD (Pinteraction=0.700). PCI improved Seattle Angina Questionnaire angina frequency score and freedom from angina more than placebo (p=0.034; p=0.0035). However, there was no evidence of interaction between the physiological pattern of CAD and these effects (Pinteraction=0.436; Pinteraction=0.908).ConclusionPCI achieved significantly greater reduction of stress echocardiography ischemia in focal compared to diffuse CAD. However, for symptom endpoints, no such difference was observed.

Journal article

Rosmini S, Seraphim A, Knott K, Brown JT, Knight DS, Zaman S, Cole G, Sado D, Captur G, Gomes AC, Zemrak F, Treibel TA, Cash L, Culotta V, O'Mahony C, Kellman P, Moon JC, Manisty Cet al., 2021, Non-invasive characterization of pleural and pericardial effusions using T1 mapping by magnetic resonance imaging, EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING, ISSN: 2047-2404

Journal article

Kotecha T, Knight DS, Moon JC, Cole GD, Fontana Met al., 2021, The evolution of cardiovascular COVID-19 research, EUROPEAN HEART JOURNAL, Vol: 42, Pages: 2953-2954, ISSN: 0195-668X

Journal article

Gorecka M, McCann GP, Berry C, Ferreira VM, Moon JC, Miller CA, Chiribiri A, Prasad S, Dweck MR, Bucciarelli-Ducci C, Dawson D, Fontana M, Macfarlane PW, McConnachie A, Neubauer S, Greenwood JPet al., 2021, Demographic, multi-morbidity and genetic impact on myocardial involvement and its recovery from COVID-19: protocol design of COVID-HEART-a UK, multicentre, observational study, JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE, Vol: 23, ISSN: 1097-6647

Journal article

Howard J, Stowell C, Cole G, Ananthan K, Camelia D, Pearce K, Rajani R, Sehmi J, Vimalesvaran K, Kanaganayagam G, McPhail E, Ghosh A, Chambers J, Singh A, Zolgharni M, Rana B, Francis D, Shun-Shin M, Howard J, Stowell C, Cole G, Ananthan K, Demetrescu C, Pearce K, Rajani R, Sehmi J, Vimalesvaran K, Kanaganayagam G, McPhail E, Ghosh A, Chambers J, Singh A, Zolgharni M, Rana B, Francis D, Shun-Shin Met al., 2021, Automated left ventricular dimension assessment using artificial intelligence developed and validated by a UK-wide collaborative, Circulation: Cardiovascular Imaging, Vol: 14, Pages: 405-415, ISSN: 1941-9651

Background: Echocardiography artificial intelligence (AI) requires training and validation to standards expected of humans. We developed an online platform and established the Unity Collaborative to build a dataset of expertise from 17 hospitals for training, validation, and standardisation of such techniques. Methods: The training dataset were 2056individual frames drawn at random from 1265parasternal long-axis video-loops of patients undergoing clinical echocardiography in 2015-2016. Nine experts labelled these images using our online platform. From this, we trained a convolutional neural network to identify key points. Subsequently, 13 experts labelled a validation dataset of the end-systolic and end-diastolic frame from100new video-loops, twice each. The 26-opinionconsensus was used as the reference standard. The primary outcome was “precision SD”, the standard deviation of difference between AI measurement and expert consensus. Results: In the validation dataset, the AI’s precision SD for left ventricular internal dimension was 3.5mm. For context, precision SD of individual expert measurements against the expert consensus was 4.4mm. Intraclass correlation coefficient (ICC) between AI and expert consensus was 0.926 (95% CI 0.904–0.944), compared with 0.817 (0.778–0.954) between individual experts and expert consensus. For interventricular septum thickness, precision SD was 1.8mm for AI (ICC 0.809; 0.729–0.967), versus 2.0 for individuals (ICC 0.641; 0.568–0.716). For posterior wall thickness, precision SD was 1.4mm for AI (ICC 0.535; 95% CI 0.379–0.661), versus 2.2mm for individuals(0.366; 0.288 to 0.462).We present all images and annotations. This highlights challenging cases, including poor image quality, tapered ventricles, and indistinct boundaries. Conclusions: Experts at multiple institutions successfully cooperated to build a collaborative AI. This performed as well as individual experts. Future echocardiogr

Journal article

Zaman S, Seligman H, Lloyd FH, Patel KT, Chappell D, O'Hare D, Cole GD, Francis DP, Petraco R, Linton NWFet al., 2021, Aerosolised fluorescein can quantify FFP mask faceseal leakage: a cost-effective adaptation to the existing point of care fit test, CLINICAL MEDICINE, Vol: 21, Pages: E263-E268, ISSN: 1470-2118

Journal article

Azarmehr N, Ye X, Howard JP, Lane ES, Labs R, Shun-Shin MJ, Cole GD, Bidaut L, Francis DP, Zolgharni Met al., 2021, Neural architecture search of echocardiography view classifiers, JOURNAL OF MEDICAL IMAGING, Vol: 8, ISSN: 2329-4302

Journal article

Lane ES, Azarmehr N, Jevsikov J, Howard JP, Shun-shin MJ, Cole GD, Francis DP, Zolgharni Met al., 2021, Multibeat echocardiographic phase detection using deep neural networks, COMPUTERS IN BIOLOGY AND MEDICINE, Vol: 133, ISSN: 0010-4825

Journal article

Levy S, Cole G, Pabari P, Dani M, Barton C, Mayet J, McDonagh T, Baxter J, Plymen Cet al., 2021, New horizons in cardiogeriatrics: geriatricians and heart failure care-the custard in the tart, not the icing on the cake, AGE AND AGEING, Vol: 50, Pages: 1064-1068, ISSN: 0002-0729

Journal article

Mikhail G, Khawaja SA, Mohan P, Jabbour R, Bampouri T, Bowsher G, Hassan AMM, Huq F, Baghdasaryan L, Wang B, Sethi A, Sen S, Petraco R, Ruparelia N, Nijjer S, Malik IS, Foale R, Bellamy M, Kooner J, Rana BS, Cole G, Sutaria N, Kanaganayagam G, Nihoyannopoulos P, Fox K, Plymen CM, Pabari P, Howard L, Davies R, Hajoi G, Lo Giudice F, Kanagaratnam P, Anderson J, Chukwuemeka A, Khamis R, Varnava A, Baker CSR, Francis D, Asaria P, Al-Lamee Ret al., 2021, COVID-19 and its impact on the cardiovascular system, Open Heart, Vol: 8, Pages: 1-9, ISSN: 2053-3624

Objectives: The clinical impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has varied across countries with varying cardiovascular manifestations. We review the cardiac presentations, in-hospital outcomes and development of cardiovascular complications in the initial cohort of SARS-CoV-2 positive patients at Imperial College Healthcare NHS Trust, United Kingdom.Methods: We retrospectively analysed 498 COVID-19 positive adult admissions to our institute from 7th March to 7th April 2020. Patient data was collected for baseline demographics, co-morbidities and in-hospital outcomes, especially relating to cardiovascular intervention.Results:Mean age was 67.4±16.1 years and 62.2%(n=310) were male. 64.1%(n=319) of our cohort had underlying cardiovascular disease (CVD) with 53.4%(n=266) having hypertension. 43.2%(n=215) developed acute myocardial injury. Mortality was significantly increased in those patients with myocardial injury (47.4% vs 18.4%,p<0.001). Only 4 COVID-19 patients had invasive coronary angiography,2 underwent percutaneous coronary intervention and 1 required a permanent pacemaker implantation. 7.0%(n=35) of patients had an inpatient echocardiogram. Acute myocardial injury (OR 2.39,1.31-4.40,p=0.005) and history of hypertension (OR 1.88 ,1.01-3.55,p=0.049) approximately doubled the odds of in-hospital mortality in patients admitted with COVID-19 after other variables had been controlled for.Conclusion:Hypertension, pre-existing CVD and acute myocardial injury were associated with increased in-hospital mortality in our cohort of COVID-19 patients. However, only a low number of patients required invasive cardiac intervention.

Journal article

Sweeney M, Cole GD, Pabari P, Hadjiphilippou S, Tayal U, Mayet J, Chapman N, Plymen CMet al., 2021, Urinary drug metabolite testing in chronic heart failure patients indicates high levels of adherence with life-prolonging therapies, ESC HEART FAILURE, Vol: 8, Pages: 2334-2337, ISSN: 2055-5822

Journal article

Cox-Smith A, Cooper T, Punjabi P, Barton C, Levy S, Plymen C, Cole Get al., 2021, LACK OF EVIDENCE FOR REDUCED EFFICACY OF MEDICAL THERAPY FOR HEART FAILURE IN OLDER ADULTS, Publisher: OXFORD UNIV PRESS, ISSN: 0002-0729

Conference paper

Kotecha T, Knight DS, Razvi Y, Kumar K, Vimalesvaran K, Thornton G, Patel R, Chacko L, Brown JT, Coyle C, Leith D, Shetye A, Ariff B, Bell R, Captur G, Coleman M, Goldring J, Gopalan D, Heightman M, Hillman T, Howard L, Jacobs M, Jeetley PS, Kanagaratnam P, Kon OM, Lamb LE, Manisty CH, Mathurdas P, Mayet J, Negus R, Patel N, Pierce I, Russell G, Wolff A, Xue H, Kellman P, Moon JC, Treibel TA, Cole GD, Fontana Met al., 2021, Patterns ofmyocardial injury in recovered troponin-positive COVID-19 patients assessed by cardiovascular magnetic resonance, EUROPEAN HEART JOURNAL, Vol: 42, Pages: 1866-1878, ISSN: 0195-668X

Journal article

Sivalokanathan S, Foley M, Cole G, Youngstein Tet al., 2021, Gastroenteritis and cardiogenic shock in a healthcare worker: a case report of COVID-19 myocarditis confirmed with serology, European Heart Journal: Case Reports, Vol: 5, Pages: 1-5, ISSN: 2514-2119

BackgroundCoronavirus disease 2019 (COVID-19) myocarditis is emerging as a component of the hyperactive inflammatory response secondary to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Isolated gastrointestinal symptoms are uncommon presenting features in adults with COVID-19 myocarditis. The availability of antibody testing is a valuable addition to the confirmation of COVID-19, when repeated reverse transcriptase–polymerase chain reaction of nasopharyngeal swabs are negative.Case summaryA young healthcare worker presented with dizziness and pre-syncope, 4 weeks after his original symptoms that included fever, lethargy, and diarrhoea. Despite 2 weeks of isolation, followed by a quiescent spell, his symptoms had returned. Shortly after, he presented in cardiogenic shock (left ventricular ejection fraction 25%), that required vasopressor support, at the height of the COVID-19 pandemic. Cardiac magnetic resonance imaging suggested florid myocarditis. Three nasopharyngeal swabs (Days 1, 3, and 5) were negative for SARS-CoV-2, but subsequent serology (Day 13) confirmed the presence of SARS-CoV-2 IgG. Treatment with intravenous immunoglobulin and glucocorticoids led to full recovery.DiscussionOur case study highlights the significance of the use of the available serological assays for diagnosis of patients presenting late with SARS-CoV-2. Importantly, it supports further research in the use of immunomodulatory drugs for the hyperinflammatory microenvironment induced by COVID-19.

Journal article

Naderi H, Robinson S, Swaans MJ, Bual N, Cheung W-S, Reid L, Shun-Shin M, Asaria P, Pabari P, Cole G, Kanaganayagam GS, Sutaria N, Bellamy M, Fox K, Nihoyannopoulos P, Petraco R, Al-Lamee R, Nijjer SS, Sen S, Ruparelia N, Baker C, Mikhail G, Malik I, Khamis R, Varnava A, Francis D, Mayet J, Rana Bet al., 2021, Adapting the role of handheld echocardiography during the COVID-19 pandemic: A practical guide, PERFUSION-UK, Vol: 36, Pages: 547-558, ISSN: 0267-6591

Journal article

Howard JP, Zaman S, Ragavan A, Hall K, Leonard G, Sutanto S, Ramadoss V, Razvi Y, Linton NF, Bharath A, Shun-Shin M, Rueckert D, Francis D, Cole Get al., 2020, Automated analysis and detection of abnormalities in transaxial anatomical cardiovascular magnetic resonance images: a proof of concept study with potential to optimize image acquisition, International Journal of Cardiovascular Imaging, Vol: 37, Pages: 1033-1042, ISSN: 1569-5794

The large number of available MRI sequences means patients cannot realistically undergo them all, so the range of sequences to be acquired during a scan are protocolled based on clinical details. Adapting this to unexpected findings identified early on in the scan requires experience and vigilance. We investigated whether deep learning of the images acquired in the first few minutes of a scan could provide an automated early alert of abnormal features. Anatomy sequences from 375 CMR scans were used as a training set. From these, we annotated 1500 individual slices and used these to train a convolutional neural network to perform automatic segmentation of the cardiac chambers, great vessels and any pleural effusions. 200 scans were used as a testing set. The system then assembled a 3D model of the thorax from which it made clinical measurements to identify important abnormalities. The system was successful in segmenting the anatomy slices (Dice 0.910) and identified multiple features which may guide further image acquisition. Diagnostic accuracy was 90.5% and 85.5% for left and right ventricular dilatation, 85% for left ventricular hypertrophy and 94.4% for ascending aorta dilatation. The area under ROC curve for diagnosing pleural effusions was 0.91. We present proof-of-concept that a neural network can segment and derive accurate clinical measurements from a 3D model of the thorax made from transaxial anatomy images acquired in the first few minutes of a scan. This early information could lead to dynamic adaptive scanning protocols, and by focusing scanner time appropriately and prioritizing cases for supervision and early reporting, improve patient experience and efficiency.

Journal article

Rajkumar C, Shun-Shin M, Seligman H, Ahmad Y, Warisawa T, Cook C, Howard J, Amarin L, Nowbar A, Foley M, Assomull R, Keenan N, Sehmi J, Keeble T, Davies J, Tang K, Gerber R, Cole G, O'Kane P, Sharp A, Khamis R, Kanaganayagam G, Petraco R, Ruparelia N, Malik I, Nijjer S, Sen S, Francis D, Al-Lamee Ret al., 2020, Placebo-Controlled Efficacy of Percutaneous Coronary Intervention for Focal and Diffuse Patterns of Stable Coronary Artery Disease: A Secondary Analysis From ORBITA, 32nd Annual Transcatheter Cardiovascular Therapeutics Symposium (TCT CONNECT), Publisher: ELSEVIER SCIENCE INC, Pages: B165-B165, ISSN: 0735-1097

Conference paper

Chatrath N, Kaza N, Pabari PA, Fox K, Mayet J, Barton C, Cole GD, Plymen CMet al., 2020, The effect of concomitant COVID-19 infection on outcomes in patients hospitalized with heart failure, ESC HEART FAILURE, Vol: 7, Pages: 4443-4447, ISSN: 2055-5822

Journal article

Howard JP, Tan J, Shun-Shin MJ, Mahdi D, Nowbar AN, Arnold AD, Ahmad Y, McCartney P, Zolgharni M, Linton NWF, Sutaria N, Rana B, Mayet J, Rueckert D, Cole GD, Francis DPet al., 2020, Improving ultrasound video classification: an evaluation of novel deep learning methods in echocardiography., J Med Artif Intell, Vol: 3

Echocardiography is the commonest medical ultrasound examination, but automated interpretation is challenging and hinges on correct recognition of the 'view' (imaging plane and orientation). Current state-of-the-art methods for identifying the view computationally involve 2-dimensional convolutional neural networks (CNNs), but these merely classify individual frames of a video in isolation, and ignore information describing the movement of structures throughout the cardiac cycle. Here we explore the efficacy of novel CNN architectures, including time-distributed networks and two-stream networks, which are inspired by advances in human action recognition. We demonstrate that these new architectures more than halve the error rate of traditional CNNs from 8.1% to 3.9%. These advances in accuracy may be due to these networks' ability to track the movement of specific structures such as heart valves throughout the cardiac cycle. Finally, we show the accuracies of these new state-of-the-art networks are approaching expert agreement (3.6% discordance), with a similar pattern of discordance between views.

Journal article

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