Contact information
DPhil projects available
Myocardial functional T1 mapping – Advanced cardiac magnetic resonance imaging techniques
Stefan Piechnik
DSc, PhD, MScEE
Associate Professor of Biomedical Imaging
- Head of Advanced Cardiovascular Image Processing
I have approximately 30 years experience in interdisciplinary biomedical research, ranging from mathematical and biophysical modelling, measurement systems and methods design, direct clinical measurements, imaging and estimation using PET, SPECT, and MR, to clinical and self-assessment approaches. Applications include wide range of clinical specialties in Neurosciences (Neurosurgery, Neurology and Psychiatry), Dermatology, Cardiovascular and Internal Medicine. Over the course of my work I co-authored >100 research papers, attracting ~10'000 citations, resulting in a h-index of 53. My most recent focus is in the clinical application of CMR parametric tissue characterisation techniques, in particular T1 mapping.
Key publications
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Inflammatory bowel disease and myocarditis: T1-mapping the heart of the problem.
Journal article
Carande EJ. et al, (2017), Eur Heart J Cardiovasc Imaging, 18
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Splenic T1-mapping: a novel quantitative method for assessing adenosine stress adequacy for cardiovascular magnetic resonance.
Journal article
Liu A. et al, (2017), J Cardiovasc Magn Reson, 19
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Seeing Beyond the Obvious: Subclinical Cardiac Sarcoidosis Revealed by Cardiovascular Magnetic Resonance Mapping.
Journal article
Ferreira VM. and Piechnik SK., (2016), Circ Cardiovasc Imaging, 9
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Ultrafast Magnetic Resonance Imaging for Iron Quantification in Thalassemia Participants in the Developing World: The TIC-TOC Study (Thailand and UK International Collaboration in Thalassaemia Optimising Ultrafast CMR).
Journal article
Abdel-Gadir A. et al, (2016), Circulation, 134, 432 - 434
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Breast Milk Consumption in Preterm Neonates and Cardiac Shape in Adulthood.
Journal article
Lewandowski AJ. et al, (2016), Pediatrics, 138
Recent publications
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CMR Parametric Mapping as a Tool for Myocardial Tissue Characterization.
Journal article
Ferreira VM. and Piechnik SK., (2020), Korean Circ J, 50, 658 - 676
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Improving cardiac MRI convolutional neural network segmentation on small training datasets and dataset shift: A continuous kernel cut approach.
Journal article
Guo F. et al, (2020), Med Image Anal, 61
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PREDICTORS OF CLINICALLY SIGNIFICANT ATRIAL FIBRILLATION IN THE NHLBI HYPERTROPHIC CARDIOMYOPATHY REGISTRY (HCMR)
Conference paper
Kramer C. et al, (2020), JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 75, 676 - 676
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Association Between Recreational Cannabis Use and Cardiac Structure and Function.
Journal article
Khanji MY. et al, (2020), JACC Cardiovasc Imaging, 13, 886 - 888
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Fully Automated Myocardial Strain Estimation from Cardiovascular MRI-tagged Images Using a Deep Learning Framework in the UK Biobank.
Journal article
Ferdian E. et al, (2020), Radiol Cardiothorac Imaging, 2
ORCID
0000-0002-0268-5221