AIMS: To determine the optimal T1 mapping approach to assess myocardial fibrosis at 3T. METHODS AND RESULTS: T1 mapping was performed at 3T using the modified look-locker-inversion sequence in 20 healthy volunteers and 20 patients with aortic stenosis (AS). Pre- and post-contrast myocardial T1, the partition coefficient (λ; ΔRmyocardium/ΔRblood, where ΔR = 1/post-contrast T1 - 1/pre-contrast T1), and extracellular volume fraction [ECV; λ (1 - haematocrit)] were assessed. After establishing the optimal time point and myocardial region for analysis, we compared the reproducibility of these T1 measures and their ability to differentiate asymptomatic patients with AS from healthy volunteers. There was no segmental variation across the ventricle in any of the T1 measures evaluated. λ and ECV did not vary with time, while post-contrast T1 was relatively constant between 15 and 30 min. Thus, mid-cavity myocardium at 20 min was used for subsequent analyses. ECV displayed excellent intra-, inter-observer, and scan-rescan reproducibility [intra-class correlation coefficients (ICC) 1.00, 0.97, and 0.96, respectively], as did λ (ICC 0.99, 0.94, 0.93, respectively). Moreover, ECV and λ were both higher in patients with AS compared with controls (ECV 28.3 ± 1.7 vs. 26.0 ± 1.6%, P < 0.001; λ 0.46 ± 0.03 vs. 0.44 ± 0.03, P = 0.02), with the former offering improved differentiation. In comparison, scan-rescan reproducibilities for pre- and post-contrast myocardial T1 were only modest (ICC 0.72 and 0.56) with no differences in values observed between cases and controls (both P> 0.05). CONCLUSIONS: ECV appears to be the most promising measure of diffuse myocardial fibrosis at 3T based upon its superior reproducibility and ability to differentiate disease from health.
AIMS: To determine the optimal T1 mapping approach to assess myocardial fibrosis at 3T. METHODS AND RESULTS: T1 mapping was performed at 3T using the modified look-locker-inversion sequence in 20 healthy volunteers and 20 patients with aortic stenosis (AS). Pre- and post-contrast myocardial T1, the partition coefficient (λ; ΔRmyocardium/ΔRblood, where ΔR = 1/post-contrast T1 - 1/pre-contrast T1), and extracellular volume fraction [ECV; λ (1 - haematocrit)] were assessed. After establishing the optimal time point and myocardial region for analysis, we compared the reproducibility of these T1 measures and their ability to differentiate asymptomatic patients with AS from healthy volunteers. There was no segmental variation across the ventricle in any of the T1 measures evaluated. λ and ECV did not vary with time, while post-contrast T1 was relatively constant between 15 and 30 min. Thus, mid-cavity myocardium at 20 min was used for subsequent analyses. ECV displayed excellent intra-, inter-observer, and scan-rescan reproducibility [intra-class correlation coefficients (ICC) 1.00, 0.97, and 0.96, respectively], as did λ (ICC 0.99, 0.94, 0.93, respectively). Moreover, ECV and λ were both higher in patients with AS compared with controls (ECV 28.3 ± 1.7 vs. 26.0 ± 1.6%, P < 0.001; λ 0.46 ± 0.03 vs. 0.44 ± 0.03, P = 0.02), with the former offering improved differentiation. In comparison, scan-rescan reproducibilities for pre- and post-contrast myocardial T1 were only modest (ICC 0.72 and 0.56) with no differences in values observed between cases and controls (both P> 0.05). CONCLUSIONS: ECV appears to be the most promising measure of diffuse myocardial fibrosis at 3T based upon its superior reproducibility and ability to differentiate disease from health.
Authors: Manuel D Cerqueira; Neil J Weissman; Vasken Dilsizian; Alice K Jacobs; Sanjiv Kaul; Warren K Laskey; Dudley J Pennell; John A Rumberger; Thomas Ryan; Mario S Verani Journal: Circulation Date: 2002-01-29 Impact factor: 29.690
Authors: Martin Ugander; Abiola J Oki; Li-Yueh Hsu; Peter Kellman; Andreas Greiser; Anthony H Aletras; Christopher T Sibley; Marcus Y Chen; W Patricia Bandettini; Andrew E Arai Journal: Eur Heart J Date: 2012-01-24 Impact factor: 29.983
Authors: Nathan Mewton; Chia Ying Liu; Pierre Croisille; David Bluemke; João A C Lima Journal: J Am Coll Cardiol Date: 2011-02-22 Impact factor: 24.094
Authors: Christopher T Sibley; Radwa A Noureldin; Neville Gai; Marcelo Souto Nacif; Songtao Liu; Evrim B Turkbey; James O Mudd; Rob J van der Geest; João A C Lima; Marc K Halushka; David A Bluemke Journal: Radiology Date: 2012-10-22 Impact factor: 11.105
Authors: Daniel R Messroghli; Kevin Walters; Sven Plein; Patrick Sparrow; Matthias G Friedrich; John P Ridgway; Mohan U Sivananthan Journal: Magn Reson Med Date: 2007-07 Impact factor: 3.737
Authors: Sacha Bull; Steven K White; Stefan K Piechnik; Andrew S Flett; Vanessa M Ferreira; Margaret Loudon; Jane M Francis; Theodoros D Karamitsos; Bernard D Prendergast; Matthew D Robson; Stefan Neubauer; James C Moon; Saul G Myerson Journal: Heart Date: 2013-01-24 Impact factor: 5.994
Authors: Francesco Sardanelli; Simone Schiaffino; Moreno Zanardo; Francesco Secchi; Paola Maria Cannaò; Federico Ambrogi; Giovanni Di Leo Journal: Eur Radiol Date: 2019-05-02 Impact factor: 5.315
Authors: Frank Kramer; Hani N Sabbah; James J Januzzi; Faiez Zannad; J Peter van Tintelen; Erik B Schelbert; Raymond J Kim; Hendrik Milting; Richardus Vonk; Brien Neudeck; Richard Clark; Klaus Witte; Wilfried Dinh; Burkert Pieske; Javed Butler; Mihai Gheorghiade Journal: Heart Fail Rev Date: 2017-05 Impact factor: 4.214
Authors: Partho P Sengupta; Sirish Shrestha; Nobuyuki Kagiyama; Yasmin Hamirani; Hemant Kulkarni; Naveena Yanamala; Rong Bing; Calvin W L Chin; Tania A Pawade; David Messika-Zeitoun; Lionel Tastet; Mylène Shen; David E Newby; Marie-Annick Clavel; Phillippe Pibarot; Marc R Dweck Journal: JACC Cardiovasc Imaging Date: 2021-05-19