• Camilo A Campo, Diego Hernando, Tilman Schubert, Candice A Bookwalter, Andrew J Van Pay, and Scott B Reeder.
• 1 Department of Radiology, Wisconsin Institutes for Medical Research, University of Wisconsin-Madison, 1111 Highland Ave, Madison, WI 53705.
• AJR Am J Roentgenol. 2017 Sep 1; 209 (3): 592-603.

ObjectiveThe purpose of this study was to evaluate the reproducibility (interreviewer agreement) and repeatability (intrareviewer agreement) of ROI sampling strategies to measure chemical shift-encoded (CSE) MRI-based liver proton density fat fraction (PDFF) and R2* (1 / T2*). A secondary purpose was to standardize ROI-based liver PDFF and R2* measurements by providing a compromise between measurement reproducibility and repeatability and time burden for image analysts.Materials And MethodsCSE data from two cohorts were retrospectively analyzed. Cohort A included 53 patients referred for abdominal MRI and healthy subjects recruited for a comparison study of CT and MRI. Cohort B included 37 patients with suspected liver iron overload. Three reviewers measured liver PDFF and R2* using previously reported ROI sampling strategies. Inter- and intrareviewer agreement of liver PDFF and R2* were evaluated using Bland-Altman analysis.ResultsAveraging largest-fit ROIs over the nine Couinaud segments resulted in the narrowest limits of agreement (LOA) for liver PDFF and R2* measurements in both cohorts. For PDFF, interreviewer agreement had mean LOA of ± 0.8% for cohort A and ± 1.7% for cohort B. Intrareviewer agreement was ± 0.5% for cohort A and ± 0.9% for cohort B. For R2* interre-viewer agreement had mean LOA of ± 3.0 s-1 for cohort A and ± 17.9 s-1 for cohort B. Intrare-viewer agreement was ± 2.6 s-1 for cohort A and ± 14.6 s-1 for cohort B. This approach was the most time-burdensome, requiring a mean ± SD of 149.7 ± 8.6 s per dataset.ConclusionFor improved reproducibility and repeatability of liver PDFF and R2* measurements, clinicians and researchers should sample as much area of the liver as possible using multiple large ROIs.

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