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Native cardiac T1 Mapping: Standardized inline analysis of long and short axis at three identical 1.5 Tesla MRI scanners.

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BACKGROUND Interpretation of native T1 time values remains difficult due to limited hard- and software comparability and the lack of measurement recommendations for the number of slices and their orientation.… Click to show full abstract

BACKGROUND Interpretation of native T1 time values remains difficult due to limited hard- and software comparability and the lack of measurement recommendations for the number of slices and their orientation. To provide a standardized comparison of native T1 time values in short and long axis and to investigate the interscanner reproducibility. METHODS 78 cardiac MRIs in 26 healthy volunteers were performed with three structurally identical 1.5 T MRI scanners. A commercially available software package for T1 mapping with automatic in-line motion correction was used for analysis. On T1 mapping images regions of interest were manually placed in each of the 16 myocardial segments according to the AHA model in three short and three long axis. RESULTS A total of 2652 ROIs were drawn and 102 segments per volunteer were analysed. Interscanner reproducibility was high and the mean myocardial T1 time value for all evaluated segments was 996 ± 34 ms. Significant variations of T1 time values were found between heart segments in the same axis. Mean T1 time values were comparable between long and short axis but differed in 33% of corresponding short and long axis segments. CONCLUSIONS Native T1 time values in short and long axis are highly reproducible but can vary significantly between heart segments in the same axis. Comparability between corresponding short and long axis segments is limited. To get representative results native T1 time values should be obtained in more than one heart segment and for follow-up studies identical segments should be used to avoid a systematic bias.

Keywords: time; short long; time values; long axis; native time

Journal Title: European journal of radiology
Year Published: 2018

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