A method for calibrating diffusion gradients in diffusion tensor imaging

J Comput Assist Tomogr. 2007 Nov-Dec;31(6):984-93. doi: 10.1097/rct.0b013e31805152fa.

Abstract

Objective: To calibrate and correct the gradient errors including gradient amplitude scaling errors, background/imaging gradients, and residual gradients in diffusion tensor imaging (DTI).

Methods: A calibration protocol using an isotropic phantom was proposed. Gradient errors were estimated by using linear regression analyses on quadratic functions of diffusion gradients along 3 orthogonal directions. A 6-element total effective scaling vector is generated from the calibration protocol to retrospectively correct gradient errors in DTI experiments.

Results: The accuracy of the calibration protocol was within 1% or less in estimating gradient scaling errors. On both the brain study and the computer simulations, the retrospective correction minimized undesirable estimate biases of DTI measurements due to gradient errors.

Conclusion: The protocol and retrospective correction are shown to be effective. The method may be used for prospective correction if actual diffusion-gradient waveforms are available. The methodology is expandable to general diffusion imaging schemes.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Anisotropy
  • Brain / anatomy & histology
  • Calibration
  • Computer Simulation
  • Diffusion Magnetic Resonance Imaging / statistics & numerical data*
  • Echo-Planar Imaging / statistics & numerical data
  • Humans
  • Image Processing, Computer-Assisted / statistics & numerical data*
  • Linear Models
  • Models, Theoretical
  • Monte Carlo Method
  • Phantoms, Imaging