Dr Graham Cole is a Consultant Cardiologist and Honorary Senior Lecturer in Cardiology. His main interest is the rational use of cardiac imaging for clinical and research purposes.
His undergraduate training was at Gonville & Caius College, Cambridge where he achieved First Class Honours in Natural Sciences (Pathology) and was a Clinical Scholar. He achieved distinctions in all areas of his clinical finals and was awarded the Roger Morris prize for Surgery by Cambridge University. His postgraduate training was at the Hammersmith, Charing Cross, Guy's and St Thomas' Hospitals.
He was appointed to the North-West London training programme in Cardiology in 2008 and undertook a BHF-funded PhD with Professor Darrel Francis studying the high-precision quantification of cardiac function. He undertook fellowships in cardiac MRI at UCL/Barts and in cardiac CT at Guy's and St Thomas' Hospitals. He was appointed as a Consultant Cardiologist and Honorary Senior Lecturer at Imperial in 2018.
He is accredited in imaging and heart failure, is a high-volume CMR reporter (>1200 cases/year) and leads Cardiac MRI provision in the key areas of cardiomyopathy, heart failure, myocarditis and coronary artery disease.
et al., 2023, Comparison of methods for delivering cardiac resynchronization therapy: an acute electrical and haemodynamic within-patient comparison of left bundle branch area, His bundle, and biventricular pacing, Ep Europace, ISSN:1099-5129, Pages:1-8
et al., 2022, Coronary flow reserve and cardiovascular outcomes: a systematic review and meta-analysis, European Heart Journal, Vol:43, ISSN:0195-668X, Pages:1582-1593
et al., 2022, Quantitative Myocardial Perfusion Predicts Outcomes in Patients With Prior Surgical Revascularization, Journal of the American College of Cardiology, Vol:79, ISSN:0735-1097, Pages:1141-1151
et al., 2022, Randomized blinded placebo-controlled trials of renal sympathetic denervation for hypertension: a meta-analysis, Cardiovascular Revascularization Medicine, Vol:34, ISSN:1553-8389, Pages:112-118
et al., 2022, PAT-CNN: Automatic Segmentation and Quantification of Pericardial Adipose Tissue from T2-Weighted Cardiac Magnetic Resonance Images, Lecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol:13593 LNCS, ISSN:0302-9743, Pages:359-368