On the confounding effect of temperature on chemical shift-encoded fat quantification

Authors

  • Diego Hernando,

    Corresponding author
    1. Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
    • Correspondence to: Diego Hernando, Ph.D., Department of Radiology, University of Wisconsin, WIMR 1115, 1111 Highland Avenue, Madison, WI 53792. E-mail: dhernando@wisc.edu

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  • Samir D. Sharma,

    1. Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
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  • Harald Kramer,

    1. Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
    2. Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital Munich, Munich, Germany
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  • Scott B. Reeder

    1. Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA
    2. Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
    3. Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
    4. Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA
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Abstract

Purpose

To characterize the confounding effect of temperature on chemical shift-encoded (CSE) fat quantification.

Methods

The proton resonance frequency of water, unlike triglycerides, depends on temperature. This leads to a temperature dependence of the spectral models of fat (relative to water) that are commonly used by CSE-MRI methods. Simulation analysis was performed for 1.5 Tesla CSE fat–water signals at various temperatures and echo time combinations. Oil–water phantoms were constructed and scanned at temperatures between 0 and 40°C using spectroscopy and CSE imaging at three echo time combinations. An explanted human liver, rejected for transplantation due to steatosis, was scanned using spectroscopy and CSE imaging. Fat–water reconstructions were performed using four different techniques: magnitude and complex fitting, with standard or temperature-corrected signal modeling.

Results

In all experiments, magnitude fitting with standard signal modeling resulted in large fat quantification errors. Errors were largest for echo time combinations near TEinit ≈ 1.3 ms, ΔTE ≈ 2.2 ms. Errors in fat quantification caused by temperature-related frequency shifts were smaller with complex fitting, and were avoided using a temperature-corrected signal model.

Conclusion

Temperature is a confounding factor for fat quantification. If not accounted for, it can result in large errors in fat quantifications in phantom and ex vivo acquisitions. Magn Reson Med 72:464–470, 2014. © 2013 Wiley Periodicals, Inc.

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