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Automated truncation method for myocardial T2* measurement in thalassemia
Author(s) -
He Taigang,
Zhang Jun,
Carpenter JohnPaul,
Feng Yanqiu,
Smith Gillian C.,
Pennell Dudley J.,
Firmin David N.
Publication year - 2013
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.23780
Subject(s) - reproducibility , truncation (statistics) , thalassemia , computer science , software , population , data mining , nuclear medicine , artificial intelligence , biomedical engineering , pattern recognition (psychology) , medicine , mathematics , statistics , machine learning , programming language , environmental health
Purpose: To propose an automated truncation method for myocardial T2* measurement and evaluate this method on a large population of patients with iron loading in the heart and scanned at multiple magnetic resonance imaging (MRI) centers. Materials and Methods: A total of 550 thalassemia patients were scanned at 20 international centers using a variety of MR scanners (Siemens, Philips, or GE). A single mid‐ventricular short axis slice was imaged. All patient data were anonymized before the T2* were measured by expert observers using standard techniques. These same datasets were then retrospectively processed using the proposed automated truncation method by another independent observer and the resulting T2* measurements were compared with those of expert readings. Results: The T2* measurements using the automated method showed good agreement with those measured by expert observers using standard techniques ( P = 0.95) with a low coefficient of variation (1.6%). Conclusion: This study demonstrates feasibility and good reproducibility of a new automated truncation method for myocardial T2* measurement. This approach simplifies the overall analysis and can be easily incorporated into T2* analysis software to facilitate further development of a fully automated myocardial tissue iron quantification. J. Magn. Reson. Imaging 2013;37:479–483. © 2012 Wiley Periodicals, Inc.