| Coronary artery anomalies overview: the normal and the abnormal ADM Villa, E Sammut, A Nair, R Rajani, R Bonamini, A Chiribiri World journal of radiology 8 (6), 537, 2016 | 436 | 2016 |
| Myocardial tissue characterization by cardiac magnetic resonance imaging using T1 mapping predicts ventricular arrhythmia in ischemic and non–ischemic cardiomyopathy patients … Z Chen, M Sohal, T Voigt, E Sammut, C Tobon-Gomez, N Child, ... Heart Rhythm 12 (4), 792-801, 2015 | 132 | 2015 |
| Prognostic value of quantitative stress perfusion cardiac magnetic resonance EC Sammut, ADM Villa, G Di Giovine, L Dancy, F Bosio, T Gibbs, ... JACC: Cardiovascular Imaging 11 (5), 686-694, 2018 | 113 | 2018 |
| Studying dynamic myofiber aggregate reorientation in dilated cardiomyopathy using in vivo magnetic resonance diffusion tensor imaging C Von Deuster, E Sammut, L Asner, D Nordsletten, P Lamata, CT Stoeck, ... Circulation: Cardiovascular Imaging 9 (10), e005018, 2016 | 101 | 2016 |
| Estimation of passive and active properties in the human heart using 3D tagged MRI L Asner, M Hadjicharalambous, R Chabiniok, D Peresutti, E Sammut, ... Biomechanics and modeling in mechanobiology 15, 1121-1139, 2016 | 88 | 2016 |
| Stem cell therapy for heart diseases AM Mozid, S Arnous, EC Sammut, A Mathur British medical bulletin 98 (1), 143-159, 2011 | 88 | 2011 |
| Deep‐learning‐based preprocessing for quantitative myocardial perfusion MRI CM Scannell, M Veta, ADM Villa, EC Sammut, J Lee, M Breeuwer, ... Journal of Magnetic Resonance Imaging 51 (6), 1689-1696, 2020 | 83 | 2020 |
| Analysis of passive cardiac constitutive laws for parameter estimation using 3D tagged MRI M Hadjicharalambous, R Chabiniok, L Asner, E Sammut, J Wong, ... Biomechanics and modeling in mechanobiology 14, 807-828, 2015 | 69 | 2015 |
| Microvascular ischemia in hypertrophic cardiomyopathy: new insights from high-resolution combined quantification of perfusion and late gadolinium enhancement ADM Villa, E Sammut, N Zarinabad, G Carr-White, J Lee, N Bettencourt, ... Journal of cardiovascular magnetic resonance 18 (1), 4, 2016 | 65 | 2016 |
| Non-invasive model-based assessment of passive left-ventricular myocardial stiffness in healthy subjects and in patients with non-ischemic dilated cardiomyopathy M Hadjicharalambous, L Asner, R Chabiniok, E Sammut, J Wong, ... Annals of biomedical engineering 45, 605-618, 2017 | 55 | 2017 |
| A prospective evaluation of cardiovascular magnetic resonance measures of dyssynchrony in the prediction of response to cardiac resynchronization therapy M Sohal, SG Duckett, X Zhuang, W Shi, M Ginks, A Shetty, E Sammut, ... Journal of Cardiovascular Magnetic Resonance 16 (1), 58, 2014 | 53 | 2014 |
| Prevalence of myocardial crypts in a large retrospective cohort study by cardiovascular magnetic resonance N Child, T Muhr, E Sammut, D Dabir, EA Ucar, T Bueser, J Gill, ... Journal of Cardiovascular Magnetic Resonance 16 (1), 66, 2014 | 53 | 2014 |
| A U-shaped type II contraction pattern in patients with strict left bundle branch block predicts super-response to cardiac resynchronization therapy T Jackson, M Sohal, Z Chen, N Child, E Sammut, J Behar, S Claridge, ... Heart rhythm 11 (10), 1790-1797, 2014 | 52 | 2014 |
| Noninvasive assessment of LV contraction patterns using CMR to identify responders to CRT M Sohal, A Shetty, S Duckett, Z Chen, E Sammut, S Amraoui, ... JACC: Cardiovascular Imaging 6 (8), 864-873, 2013 | 52 | 2013 |
| Focal but not diffuse myocardial fibrosis burden quantification using cardiac magnetic resonance imaging predicts left ventricular reverse modeling following cardiac … Z Chen, M Sohal, E Sammut, N Child, T Jackson, S Claridge, M Cooklin, ... Journal of cardiovascular electrophysiology 27 (2), 203-209, 2016 | 50 | 2016 |
| Age-related changes in intraventricular kinetic energy: a physiological or pathological adaptation? J Wong, R Chabiniok, A Devecchi, N Dedieu, E Sammut, T Schaeffter, ... American Journal of Physiology-Heart and Circulatory Physiology 310 (6 …, 2016 | 40 | 2016 |
| Patient-specific modeling for left ventricular mechanics using data-driven boundary energies L Asner, M Hadjicharalambous, R Chabiniok, D Peressutti, E Sammut, ... Computer Methods in Applied Mechanics and Engineering 314, 269-295, 2017 | 36 | 2017 |
| Combined identification of septal flash and absence of myocardial scar by cardiac magnetic resonance imaging improves prediction of response to cardiac resynchronization therapy M Sohal, S Amraoui, Z Chen, E Sammut, T Jackson, M Wright, M O’Neill, ... Journal of Interventional Cardiac Electrophysiology 40, 179-190, 2014 | 34 | 2014 |
| Biophysical modeling to determine the optimization of left ventricular pacing site and AV/VV delays in the acute and chronic phase of cardiac resynchronization therapy AWC Lee, A Crozier, ER Hyde, P Lamata, M Truong, M Sohal, T Jackson, ... Journal of cardiovascular electrophysiology 28 (2), 208-215, 2017 | 33 | 2017 |
| Impact of COVID‐19 on inpatient referral of acute heart failure: a single‐centre experience from the south‐west of the UK G Doolub, C Wong, L Hewitson, A Mohamed, F Todd, L Gogola, ... ESC heart failure 8 (2), 1691-1695, 2021 | 31 | 2021 |
