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Automated adaptive preconditioner for quantitative susceptibility mapping.

Zhe Liu1,2, Yan Wen1,2, Pascal Spincemaille2

  • 1Department of Biomedical Engineering, Cornell University, Ithaca, New York.

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|August 13, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an automated adaptive preconditioner for quantitative susceptibility mapping (QSM) reconstruction. This method enhances accuracy and image quality across various anatomies.

Keywords:
QSMcardiachemorrhagepreconditioningtotal field inversion

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Area of Science:

  • Medical Imaging
  • Biophysics
  • Computational Science

Background:

  • Quantitative Susceptibility Mapping (QSM) is crucial for medical imaging.
  • Accurate QSM reconstruction faces challenges with artifacts and varying susceptibility ranges.
  • Developing robust and efficient QSM algorithms is an ongoing research area.

Purpose of the Study:

  • To develop an automated adaptive preconditioner for QSM reconstruction.
  • To improve susceptibility quantification accuracy and image quality.
  • To enable high-quality QSM across diverse anatomical regions and susceptibility ranges.

Main Methods:

  • Utilized total field to rapidly generate an approximate susceptibility map.
  • Averaged and trended the map to create a spatially varying preconditioning distribution.
  • Reconstructed QSM using total field inversion with the automated adaptive preconditioner.
  • Validated against empirical methods in simulations, brain imaging (healthy and hemorrhage patients), and cardiac imaging (healthy subjects).

Main Results:

  • The automated adaptive preconditioner demonstrated the fastest convergence in reducing QSM Root Mean Square Error (RMSE) in simulations.
  • Effectively suppressed hemorrhage-associated artifacts while preserving brain tissue contrast.
  • Yielded cardiac chamber oxygenation values consistent with established literature.
  • Outperformed empirical preconditioners in accuracy and artifact reduction.

Conclusions:

  • The developed automated adaptive preconditioner enables high-quality QSM reconstruction from total field data.
  • This method is effective for imaging various anatomies with dynamic susceptibility ranges.
  • It offers improved accuracy and image quality compared to existing methods.