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Stefan K. Piechnik
Researcher at University of Oxford
Publications - 263
Citations - 15965
Stefan K. Piechnik is an academic researcher from University of Oxford. The author has contributed to research in topics: Magnetic resonance imaging & Population. The author has an hindex of 57, co-authored 249 publications receiving 12417 citations. Previous affiliations of Stefan K. Piechnik include Queen Mary University of London & John Radcliffe Hospital.
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Journal ArticleDOI
Myocardial T1 mapping and extracellular volume quantification: a Society for Cardiovascular Magnetic Resonance (SCMR) and CMR Working Group of the European Society of Cardiology consensus statement
James C. Moon,Daniel Messroghli,Peter Kellman,Stefan K. Piechnik,Matthew D. Robson,Martin Ugander,Peter D. Gatehouse,Andrew E. Arai,Matthias G. Friedrich,Stefan Neubauer,Jeanette Schulz-Menger,Jeanette Schulz-Menger,Erik B. Schelbert +12 more
TL;DR: This document provides recommendations for clinical and research T1 and ECV measurement, based on published evidence when available and expert consensus when not, and addresses controversies in the field.
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Continuous monitoring of cerebrovascular pressure reactivity allows determination of optimal cerebral perfusion pressure in patients with traumatic brain injury.
Luzius A. Steiner,Marek Czosnyka,Stefan K. Piechnik,Piotr Smielewski,Doris A. Chatfield,David K. Menon,John D. Pickard +6 more
TL;DR: Use of the criterion of minimal achievable PRx to guide future trials of CPP oriented treatment in head injured patients is proposed and could be identified in a majority of patients.
Journal ArticleDOI
Shortened Modified Look-Locker Inversion recovery (ShMOLLI) for clinical myocardial T1-mapping at 1.5 and 3 T within a 9 heartbeat breathhold
Stefan K. Piechnik,Vanessa M Ferreira,Vanessa M Ferreira,Erica Dall'Armellina,Lowri E. Cochlin,Andreas Greiser,Stefan Neubauer,Matthew D. Robson +7 more
TL;DR: In contrast to the original method, ShMOLLI showed no dependence on heart rates for long T1 values, with estimates characterized by a constant 4% underestimation for T1 = 800-2700 ms, and is an efficient method that generates immediate, high-resolution myocardial T1-maps in a short breath-hold with high precision.
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Noncontrast T1 mapping for the diagnosis of cardiac amyloidosis.
Theodoros D. Karamitsos,Stefan K. Piechnik,Sanjay M Banypersad,Marianna Fontana,Ntobeko A.B. Ntusi,Vanessa M Ferreira,Vanessa M Ferreira,Carol J. Whelan,Saul G. Myerson,Matthew D. Robson,Philip N. Hawkins,Stefan Neubauer,James C. Moon +12 more
TL;DR: Noncontrast T1 mapping has high diagnostic accuracy for detecting cardiac AL amyloidosis, correlates well with markers of systolic and diastolic dysfunction, and is potentially more sensitive for detecting early disease than LGE imaging.
Journal ArticleDOI
Automated cardiovascular magnetic resonance image analysis with fully convolutional networks
Wenjia Bai,Matthew Sinclair,Giacomo Tarroni,Ozan Oktay,Martin Rajchl,Ghislain Vaillant,Aaron M. Lee,Nay Aung,Elena Lukaschuk,Mihir M. Sanghvi,Filip Zemrak,Kenneth Fung,José Miguel Paiva,Valentina Carapella,Young Jin Kim,Hideaki Suzuki,Bernhard Kainz,Paul M. Matthews,Steffen E. Petersen,Stefan K. Piechnik,Stefan Neubauer,Ben Glocker,Daniel Rueckert +22 more
TL;DR: An automated analysis method based on a fully convolutional network achieves a performance on par with human experts in analysing CMR images and deriving clinically relevant measures.