Frontiers in Medicine (Sep 2024)
Assessing the accuracy of CMRtools software for diagnosing liver iron overload in thalassemia patients: influencing factors and optimisation strategies
Abstract
BackgroundCMRtools 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 (R2 value), the number of echo time (TE) images, and the liver iron concentration (LIC). To investigate the effects of the R2 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 methodsCMRtools software was used to measure liver T2* values among 108 thalassemia patients via the truncation method, and the R2 values, the number of TE images, and T2* values were recorded. These values were subsequently converted into liver iron concentration (LICT) values. The LICF (derived from MRI-R2/FerriScan) was used as a reference, and the diagnostic accordance rate (DAR) was compared between R2 value subgroups, between TE image number subgroups, and between LIC subgroups.ResultsThe greater the R2 value was, the greater the standardized DAR (SDAR) was (p < 0.05). The SDAR are not identical between each TE image number subgroup (p > 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 (rs = 0.729, p = 0.017). The SDAR are not identical between each LIC subgroup (p > 0.05), furthermore, the relationship between LIC subgroup and SDAR was found irrelevant (p = 0.747).ConclusionThe 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 R2 values.
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