MRI liver fat quantification in an oncologic population: the added value of complex chemical shift-encoded MRI

Giuseppe Corrias, Simone Krebs, Sarah Eskreis-Winkler, Davinia Ryan, Junting Zheng, Marinela Capanu, Luca Saba, Serena Monti, Maggie Fung, Scott Reeder, Lorenzo Mannelli

Research output: Contribution to journalArticlepeer-review


Introduction: Chemotherapy prolongs the survival of patients with advanced and metastatic tumors. Since the liver plays an active role in the metabolism of chemotherapy agents, hepatic injury is a common adverse effect. The purpose of this study is to compare a novel quantitative chemical shift encoded magnetic resonance imaging (CSE-MRI) method with conventional T1-weighted In and Out of phase (T1 IOP) MR for evaluating the reproducibility of the methods in an oncologic population exposed to chemotherapy. Materials and methods: This retrospective study was approved by the institutional review board with a waiver for informed consent. The study included patients who underwent chemotherapy, no suspected liver iron overload, and underwent upper abdomen MRI. Two radiologists independently draw circular ROIsin the liver parenchyma. The fat fraction was calculated from IOP imaging and measured from IDEAL-IQ fat fraction maps. Two different equations were used to estimate fat with IOP sequences. Intra-class correlation coefficient and repeatability coefficient were estimated to evaluate agreement between two readers on iron level and fat fraction measurement. Results: CSE-MRI showed a higher reliability in fat quantification compared with both IOP methods, with a substantially higher inter-reader agreement (0.961 vs 0.372). This has important clinical implications. Conclusion: The novel CSE-MRI method described here provides increased reproducibility and confidence in diagnosing hepatic steatosis in a oncologic clinical setting. IDEAL-IQ has been proved to be more reproducible than conventional IOP imaging.

Original languageEnglish
Pages (from-to)193-199
Number of pages7
JournalClinical Imaging
Publication statusPublished - Nov 1 2018


  • Chemotherapy
  • Fat fraction
  • Liver
  • Oncologic imaging
  • PDFF

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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