Re-evaluation of a novel approach for quantitative myocardial oedema detection by analysing tissue inhomogeneity in acute myocarditis using T2-mapping
- 290 Downloads
To re-evaluate a recently suggested approach of quantifying myocardial oedema and increased tissue inhomogeneity in myocarditis by T2-mapping.
Cardiac magnetic resonance data of 99 patients with myocarditis were retrospectively analysed. Thirthy healthy volunteers served as controls. T2-mapping data were acquired at 1.5 T using a gradient-spin-echo T2-mapping sequence. T2-maps were segmented according to the 16-segments AHA-model. Segmental T2-values, segmental pixel-standard deviation (SD) and the derived parameters maxT2, maxSD and madSD were analysed and compared to the established Lake Louise criteria (LLC).
A re-estimation of logistic regression models revealed that all models containing an SD-parameter were superior to any model containing global myocardial T2. Using a combined cut-off of 1.8 ms for madSD + 68 ms for maxT2 resulted in a diagnostic sensitivity of 75% and specificity of 80% and showed a similar diagnostic performance compared to LLC in receiver-operating-curve analyses. Combining madSD, maxT2 and late gadolinium enhancement (LGE) in a model resulted in a superior diagnostic performance compared to LLC (sensitivity 93%, specificity 83%).
The results show that the novel T2-mapping-derived parameters exhibit an additional diagnostic value over LGE with the inherent potential to overcome the current limitations of T2-mapping.
• A novel quantitative approach to myocardial oedema imaging in myocarditis was re-evaluated.
• The T2-mapping-derived parameters maxT2 and madSD were compared to traditional Lake-Louise criteria.
• Using maxT2 and madSD with dedicated cut-offs performs similarly to Lake-Louise criteria.
• Adding maxT2 and madSD to LGE results in further increased diagnostic performance.
• This novel approach has the potential to overcome the limitations of T2-mapping.
KeywordsMyocarditis T2 mapping Oedema imaging Tissue inhomogeneity Lake Louise criteria
Akaike information criterion
Area under the curve
Body surface area
Balanced steady-state free-precession
Coronary artery disease
Cardiovascular magnetic resonance
Early gadolinium enhancement ratio
Gradient Spin Echo T2 mapping sequence
Late gadolinium enhancement
Lake Louise criteria
Mean absolute deviation
MAD of segmental pixel-SD values
Loge-transformed version of madSD
MAD of segmental T2 values
Maximum segmental pixel-SD value
Maximum segmental T2 value
Maximum likelihood estimator
Segmental pixel-standard deviation of T2 values
Receiver operating curve
Region of interest
- T2 BB
T2 black blood
Compliance with ethical standards
The scientific guarantor of this publication is Dr. Bettina Baeßler.
Conflict of interest
The authors of this manuscript declare relationships with the following companies: Dr. Stehning and Dr. Schnackenburg are employees of Philips Research and Philips Healthcare, respectively.
The authors state that this work has not received any funding.
Statistics and biometry
Dr. Frank Schaarschmidt kindly provided statistical advice for this manuscript.
Written informed consent was obtained from all healthy volunteers in this study.
Written informed consent for the patients was waived by the Institutional Review Board due to the retrospective nature of the patient study.
Institutional Review Board approval was obtained.
Study subjects or cohorts overlap
Some study subjects or cohorts have been previously reported in Baeßler B, Schaarschmidt F, Dick A, et al (2015) Mapping tissue inhomogeneity in acute myocarditis: a novel analytical approach to quantitative myocardial enema imaging by T2-mapping. J Cardiovasc Magn Reson: Official Journal of the Society for Cardiovascular Magnetic Resonance 17:115. doi: 10.1186/s12968-015-0217-y.
• diagnostic or prognostic study
• performed at one institution
- 14.Caforio ALP, Pankuweit S, Arbustini E et al (2013) Current state of knowledge on aetiology, diagnosis, management, and therapy of myocarditis: a position statement of the European Society of Cardiology Working Group on Myocardial and Pericardial Diseases. Eur Heart J. doi: 10.1093/eurheartj/eht210 Google Scholar
- 22.R Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing. Available via http://www.R-project.org/. Accessed 08 March 2017
- 23.Wickham H, Chang W (2016) ggplot2: an implementation of the Grammar of Graphics. Available via http://ggplot2.tidyverse.org. Accessed 08 March 2017.
- 24.Grosjean P, Ibanez F, Etienne M (2002) Pastecs: package for analysis of space-time ecological series. Available via http://www.sciviews.org/pastecs. Accessed 08 March 2017
- 25.Maindonald JH, Braun WJ (2015) DAAG: data analysis and graphics data and functions. Available via http://www.stats.uwo.ca/DAAG. Accessed 08 March 2017
- 26.Liaw A, Wiener M, Breiman L, Cutler A (2015) randomForest: Breiman and Cutler's random forests for classification and regression. Available via https://www.stat.berkeley.edu/~breiman/RandomForests/. Accessed 08 March 2017
- 27.Therneau T, Atkinson B, Ripley B (2015) Recursive partitioning and regression trees. Available via http://www.R-project.org/. Accessed 08 March 2017
- 28.Breiman L, Friedman J, Stone CJ, Olshen RA (1984) Classification and regression trees, 1st edn. Chapman and Hall/CRC, BelmontGoogle Scholar
- 29.Sing T, Sander O, Beerenwinkel N, Lengauer T (2015) ROCR: visualizing the performance of scoring classifiers. Available via http://rocr.bioinf.mpi-sb.mpg.de/. Accessed 08 March 2017
- 33.Moon JC, Messroghli DR, Kellman P et al (2013) 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. J Cardiovasc Magn Reson. doi: 10.1186/1532-429X-15-92 Google Scholar
- 40.Cooper LT, Baughman KL, Feldman AM et al (2007) The role of endomyocardial biopsy in the management of cardiovascular disease: a scientific statement from the American Heart Association, the American College of Cardiology, and the European Society of Cardiology Endorsed by the Heart Failure Society of America and the Heart Failure Association of the European Society of Cardiology. Eur Heart J. doi: 10.1093/eurheartj/ehm456 PubMedGoogle Scholar