Dr Nav Chahal is a consultant cardiologist at London Northwest Health NHS Trust; an Honorary Consultant at Royal Brompton Hospital and an Honorary Senior Clinical Lecturer at the National Heart and Lung Institute, Imperial College London.
His PhD explored potential mechanisms underlying the increased risk of cardiovascular disease amongst Indian Asian and European white individuals recruited into the LOLIPOP (London Life Sciences Prospective Population) study. He has written several papers on the role of non-invasive imaging as an epidemiological tool for detecting subclinical disease, on ethnicity-related differences in cardiac function and on the role of stress imaging in the assessment of valvular disease.
In 2011 he was appointed as the advanced cardiac imaging fellow at The Royal Brompton Hospital and has developed extensive experience of performing stress echocardiography, transoesophageal echocardiography, cardiovascular MRI and cardiac CT.
His clinical research is currently focused on refining the assessment of valvular heart disease and chest pain with rest echocardiography, stress echocardiography and cardiac MRI. He has also established collaboration with the department of bioengineering at Imperial College, exploring techniques for quantifying myocardial blood flow and carotid plaque neovascularisation using ultrasonography.
Chahal NS, Senior R, 2021, Severe Patient-Prosthesis Mismatch Compelling Entity or an Epiphenomenon of Low Flow?, Circulation-cardiovascular Imaging, Vol:14, ISSN:1941-9651
Chahal N, Senior R, 2020, Assessing systolic function in aortic stenosis: the earlier the better?, Heart, Vol:106, ISSN:1355-6037, Pages:1200-1201
et al., 2019, Low transvalvular flow rate predicts mortality in patients with low-gradient aortic stenosis following aortic valve intervention, Jacc: Cardiovascular Imaging, Vol:12, ISSN:1936-878X, Pages:1715-1724
et al., 2018, High frame rate contrast echocardiography –in human demonstration, Jacc: Cardiovascular Imaging, Vol:11, ISSN:1936-878X, Pages:923-924
et al., 2018, Fully automatic myocardial segmentation of contrast echocardiography sequence using random forests guided by shape model, Ieee Transactions on Medical Imaging, Vol:37, ISSN:0278-0062, Pages:1081-1091