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Abstract #2713

Assessment of Accuracy, Repeatability, Reproducibility & Robustness of Fat Quantification in a Water-Fat Phantom

Huanzhou Yu1, Catherine D. G. Hines2, Ann Shimakawa1, Charles A. McKenzie3, Scott B. Reeder4, Jean H. Brittain5

1Global Applied Science Laboratory, GE Healthcare, Menlo Park, CA, United States; 2Departments of Radiology, Biomedical Engineering, University of Wisconsin, Madison, WI, United States; 3Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada; 4Departments of Radiology, Medical Physics, Biomedical Engineering, University of Wisconsin, Madison, WI, United States; 5Global Applied Science Laboratory, GE Healthcare, Madison, WI, United States


In this work, we assess the performance of an IDEAL-based fat quantification method in a water-fat phantom with fat-fractions ranging from 0 to 100%. Assessment of the ground truth in phantoms allows evaluation of accuracy. By repeating the scans on the same scanner and different scanners, precision including repeatability and reproducibility are also evaluated. Finally, robustness is studied by changing a variety of imaging parameters. We demonstrate that quantitative IDEAL is highly accurate, repeatable, reproducible and robust. It has potential to offer an accurate and precise MR imaging method to measure fat-fraction in a 0~100% range, independent of imaging parameters.

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