Premium
Multipeak fat‐corrected complex R2* relaxometry: Theory, optimization, and clinical validation
Author(s) -
Hernando Diego,
Kramer J. Harald,
Reeder Scott B.
Publication year - 2013
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.24593
Subject(s) - robustness (evolution) , confounding , noise (video) , relaxometry , mathematics , range (aeronautics) , statistics , computer science , algorithm , artificial intelligence , magnetic resonance imaging , chemistry , medicine , radiology , spin echo , materials science , biochemistry , image (mathematics) , gene , composite material
Purpose To develop R2* mapping techniques corrected for confounding factors and optimized for noise performance. Theory and Methods Conventional R2* mapping is affected by two key confounding factors: noise‐related bias and the presence of fat in tissue. Noise floor effects introduce bias in magnitude‐based reconstructions, particularly at high R2* values. The presence of fat, if uncorrected, introduces severe protocol‐dependent bias. In this work, the bias/noise properties of different R2* mapping reconstructions (magnitude‐ and complex‐fitting, fat‐uncorrected, and fat‐corrected) are characterized using Cramer‐Rao Bound analysis, simulations, and in vivo data. A framework for optimizing the choice of echo times is provided. Finally, the robustness of liver R2* mapping in the presence of fat is evaluated in 28 subjects. Results Fat‐corrected R2* mapping removes fat‐related bias without noise penalty over a wide range of R2* values. Complex nonlinear least‐squares fitted and fat‐corrected R2* reconstructions that account for the spectral complexity of fat provide robust R2* estimates with low bias and optimized noise performance over a wide range of echo times combinations and R2* values. Conclusion The use of complex fitting and fat‐correction improves the robustness, noise performance, and accuracy of R2* measurements, and are necessary to establish R2* as quantitative imaging biomarker in the liver. Magn Reson Med 70:1319–1331, 2013. © 2013 Wiley Periodicals, Inc.