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On the water–fat in-phase assumption for quantitative susceptibility mapping

  • Technical University of Munich
  • Philips Germany GmbH

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Purpose: To (a) define multi-peak fat model-based effective in-phase echo times for quantitative susceptibility mapping (QSM) in water–fat regions, (b) analyze the relationship between fat fraction, field map quantification bias and susceptibility bias, and (c) evaluate the susceptibility mapping performance of the proposed effective in-phase echoes in comparison to single-peak in-phase echoes and water–fat separation for regions where both water and fat are present. Methods: Effective multipeak in-phase echo times for a bone marrow and a liver fat spectral model were derived from a single voxel simulation. A Monte Carlo simulation was performed to assess the field map estimation error as a function of fat fraction for the different in-phase echoes. Additionally, a phantom scan and in vivo scans in the liver, spine, and breast were performed and evaluated with respect to quantification accuracy. Results: The use of single-peak in-phase echoes can introduce a worst-case susceptibility bias of (Formula presented.) ppm. The use of effective multipeak in-phase echoes shows a similar quantitative performance in the numerical simulation, the phantom and in all in vivo anatomies when compared to water–fat separation-based QSM. Conclusion: QSM based on the proposed effective multipeak in-phase echoes can alleviate the quantification bias present in QSM based on single-peak in-phase echoes. When compared to water–fat separation-based QSM the proposed effective in-phase echo times achieve a similar quantitative performance while drastically reducing the computational expense for field map estimation.

Original languageEnglish
Pages (from-to)1068-1082
Number of pages15
JournalMagnetic Resonance in Medicine
Volume89
Issue number3
DOIs
StatePublished - Mar 2023

Keywords

  • field map
  • in phase
  • quantitative susceptibility mapping
  • susceptibility

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