Geometric distortion evaluation using a multi-orientated water-phantom at 0.2 T MRI

Jochi Jao1, Mingye Cheng2, Hsintien Lee2

  • 1Department of Medical Imaging and Radiological Sciences, College of Health Sciences, Kaohsiung Medical University, 100, Shih-Chuan First Rd., Kaohsiung City, 80708, Taiwan, R.O.C.

Insights

Magnetic Resonance Imaging (MRI) geometric distortion, caused by magnetic field inhomogeneity, can hinder lesion diagnosis. This study quanties distortion using a novel phantom, correlating it with off-center positions and signal variations.

Area of Science:

  • Medical Imaging Physics
  • Radiological Sciences
  • Biomedical Engineering

Background:

  • Magnetic Resonance Imaging (MRI) is a vital diagnostic tool, but suffers from geometric distortion.
  • Distortion is exacerbated by magnetic field inhomogeneity and off-center imaging, impacting clinical accuracy.
  • Accurate lesion characterization is crucial for effective disease diagnosis and treatment planning.

Purpose of the Study:

  • To evaluate and quantify geometric distortion in MRI.
  • To investigate the relationship between distortion, off-center positions, and signal intensity variations.
  • To assess distortion across different imaging planes (axial, coronal, sagittal).

Main Methods:

  • Utilized an innovative multi-oriented water phantom for distortion assessment.
  • Measured image distortion ratios in axial, coronal, and sagittal planes.
  • Correlated distortion levels with varying off-center magnetic field positions and signal intensity changes.

Main Results:

  • Quantified image distortion ratios across multiple orientations.
  • Established correlations between geometric distortion severity and off-center imaging distances.
  • Demonstrated the influence of signal intensity variations on distortion measurements.

Conclusions:

  • Geometric distortion in MRI is significantly influenced by magnetic field inhomogeneity and lesion location.
  • The developed multi-oriented phantom effectively evaluates off-center distortion.
  • Understanding and quantifying distortion is essential for improving MRI diagnostic reliability, particularly in low-field applications.