Assessing the accuracy of CMRtools software for diagnosing liver iron overload in thalassemia patients: influencing factors and optimisation strategies.

BACKGROUND

CMRtools is a software package that can be used to measure T2* values to diagnose liver iron overload, however, its accuracy in terms is affected by multiple factors, including goodness-of-fit (R value), the number of echo time (TE) images, and the liver iron concentration (LIC). To investigate the effects of the R value, the number of TE images, and the LIC on the accuracy of CMRtools software for measuring T2* values to diagnose liver iron overload (LIO).

MATERIALS AND METHODS

CMRtools software was used to measure liver T2* values among 108 thalassemia patients via the truncation method, and the R values, the number of TE images, and T2* values were recorded. These values were subsequently converted into liver iron concentration (LIC) values. The LIC (derived from MRI-R2/FerriScan) was used as a reference, and the diagnostic accordance rate (DAR) was compared between R value subgroups, between TE image number subgroups, and between LIC subgroups.

RESULTS

The greater the R value was, the greater the standardized DAR (SDAR) was ( < 0.05). The SDAR are not identical between each TE image number subgroup ( > 0.05). However, the relationship between TE image number subgroups and SDAR was analysed using Spearman's correlation, and it was found to be positively correlated (  = 0.729,  = 0.017). The SDAR are not identical between each LIC subgroup ( > 0.05), furthermore, the relationship between LIC subgroup and SDAR was found irrelevant ( = 0.747).

CONCLUSION

The accuracy of CMRtools software for diagnosing LIO in patients with thalassemia can be improved by artificially controlling the number of TE images to be fitted and selecting higher R values.