Validation of a new t2∗ algorithm and its uncertainty value for cardiac and liver iron load determination from MRI magnitude images

Sebastian BidhulT, Christos G. Xanthis, Love Lindau LiljekvisT, Gerald Greil, Eike Nagel, Anthony H. Aletras, Einar Heiberg, Erik Hedström

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Purpose To validate an automatic algorithm for offline T2∗ measurements, providing robust, vendor-independent T2∗, and uncertainty estimates for iron load quantification in the heart and liver using clinically available imaging sequences. Methods A T2∗ region of interest (ROI)-based algorithm was developed for robustness in an offline setting. Phantom imaging was performed on a 1.5 Tesla system, with clinically available multiecho gradient-recalled-echo (GRE) sequences for cardiac and liver imaging. A T2∗ single-echo GRE sequence was used as reference. Simulations were performed to assess accuracy and precision from 2000 measurements. Inter- and intraobserver variability was obtained in a patient study (n = 23). Results Simulations: Accuracy, in terms of the mean differences between the proposed method and true T2∗ ranged from 0-0.73 ms. Precision, in terms of confidence intervals of repeated measurements, was 0.06-4.74 ms showing agreement between the proposed uncertainty estimate and simulations. Phantom study: Bias and variability were 0.26 ± 4.23 ms (cardiac sequence) and -0.23 ± 1.69 ms (liver sequence). Patient study: Intraobserver variability was similar for experienced and inexperienced observers (0.03 ± 1.44 ms versus 0.16 ± 2.33 ms). Interobserver variability was 1.0 ± 3.77 ms for the heart and -0.52 ± 2.75 ms for the liver. Conclusion The proposed algorithm was shown to provide robust T2∗ measurements and uncertainty estimates over the range of clinically relevant T2∗ values.

Original languageEnglish (US)
Pages (from-to)1717-1729
Number of pages13
JournalMagnetic resonance in medicine
Issue number4
StatePublished - Apr 1 2016


  • MRI relaxometry
  • iron-load
  • offline image processing
  • uncertainty estimation
  • validation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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