Combination of complex‐based and magnitude‐based multiecho water‐fat separation for accurate quantification of fat‐fraction

Abstract

Multipoint water–fat separation techniques rely on different water–fat phase shifts generated at multiple echo times to decompose water and fat. Therefore, these methods require complex source images and allow unambiguous separation of water and fat signals. However, complex-based water–fat separation methods are sensitive to phase errors in the source images, which may lead to clinically important errors. An alternative approach to quantify fat is through “magnitude-based” methods that acquire multiecho magnitude images. Magnitude-based methods are insensitive to phase errors, but cannot estimate fat-fraction greater than 50%. In this work, we introduce a water–fat separation approach that combines the strengths of both complex and magnitude reconstruction algorithms. A magnitude-based reconstruction is applied after complex-based water–fat separation to removes the effect of phase errors. The results from the two reconstructions are then combined. We demonstrate that using this hybrid method, 0–100% fat-fraction can be estimated with improved accuracy at low fat-fractions.

Optimized in-phase and opposed-phase MR imaging for accurate detection of small fat or water fractions: theoretical considerations and experimental application in emulsions

“…However, if this knowledge is not given a rugged method described in [49] can be easily applied to reveal the dominating signal fraction.…”

Characterizing active and inactive brown adipose tissue in adult humans using PET-CT and MR imaging

“…The MRI reconstruction and water-fat image separation steps were performed using a robust hybrid magnitude-and complex-based method (65). Prior to analysis, the first echo of each four-echo train was discarded to avoid potential phase contamination by eddy currents in the complex water-fat signal (26).…”

Association between novel MRI‐estimated pancreatic fat and liver histology‐determined steatosis and fibrosis in non‐alcoholic fatty liver disease

“…A magnitude-based technique was applied to echo sequences to avoid phase errors, which can adversely affect fat quantification. 31, 32 This algorithm is applied to the source images using custom analysis software developed at the UCSD Liver Imaging Group to generate a PDFF parametric map depicting fat quantity and distribution throughout the pancreas and liver. This method provides a more direct measure of liver fat content than prior MR techniques that relied on measurements of the image signal fat-fraction.…”