OBJECTIVES: To assess the level of agreement and interchangeability among different software programs for calculation of T2 values for iron overload. METHODS: T2 images were analysed in 60 patients with thalassaemia major using the truncation method in three software programs. Levels of agreement were assessed using Pearson correlation and Bland-Altman plots. Categorical classification for levels of iron concentration by each software program was also compared. RESULTS: For the heart, all correlation coefficients were significant among the software programs (P < 0.001 for all coefficients). The mean differences and 95% limits of agreement were 0.2 (-4.73 to 5.0); 0.1 (-4.0 to 3.9); and -0.1 (-4.3 to 4.8). For the liver all correlations were also significant with P < 0.001. Bland-Altman plots showed differences of -0.02 (-0.7 to 0.6); 0.01 (-0.4 to 0.4); and -0.02 (-0.6 to 0.6). There were no significant differences in clinical classification among the software programs. CONCLUSIONS: All tools used in this study provided very good agreement among heart and liver T2 values. The results indicate that interpretation of T2 data is interchangeable with any of the software programs tested. KEY POINTS: Magnetic resonance imaging in iron overload assessment has become an essential tool. Post processing options to establish T2 values have not been compared. No differences were found on T2 of the liver or heart using 3 different techniques. Availability of these methods should allow more widespread interpretation of iron overload by MRI.
OBJECTIVES: To assess the level of agreement and interchangeability among different software programs for calculation of T2 values for iron overload. METHODS: T2 images were analysed in 60 patients with thalassaemia major using the truncation method in three software programs. Levels of agreement were assessed using Pearson correlation and Bland-Altman plots. Categorical classification for levels of iron concentration by each software program was also compared. RESULTS: For the heart, all correlation coefficients were significant among the software programs (P < 0.001 for all coefficients). The mean differences and 95% limits of agreement were 0.2 (-4.73 to 5.0); 0.1 (-4.0 to 3.9); and -0.1 (-4.3 to 4.8). For the liver all correlations were also significant with P < 0.001. Bland-Altman plots showed differences of -0.02 (-0.7 to 0.6); 0.01 (-0.4 to 0.4); and -0.02 (-0.6 to 0.6). There were no significant differences in clinical classification among the software programs. CONCLUSIONS: All tools used in this study provided very good agreement among heart and liver T2 values. The results indicate that interpretation of T2 data is interchangeable with any of the software programs tested. KEY POINTS: Magnetic resonance imaging in iron overload assessment has become an essential tool. Post processing options to establish T2 values have not been compared. No differences were found on T2 of the liver or heart using 3 different techniques. Availability of these methods should allow more widespread interpretation of iron overload by MRI.
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