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Magn Reson Imaging. 2019 Oct;62:228-241. doi: 10.1016/j.mri.2019.07.009. Epub 2019 Jul 15.

Phase Image Texture Analysis for Motion Detection in Diffusion MRI (PITA-MDD).

Author information

1
Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States. Electronic address: nelsaid@iu.edu.
2
Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States.
3
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States.

Abstract

PURPOSE:

Pronounced spin phase artifacts appear in diffusion-weighted imaging (DWI) with only minor subject motion. While DWI data corruption is often identified as signal drop out in diffusion-weighted (DW) magnitude images, DW phase images may have higher sensitivity for detecting subtle subject motion.

METHODS:

This article describes a novel method to return a metric of subject motion, computed using an image texture analysis of the DW phase image. This Phase Image Texture Analysis for Motion Detection in dMRI (PITA-MDD) method is computationally fast and reliably detects subject motion from diffusion-weighted images. A threshold of the motion metric was identified to remove motion-corrupted slices, and the effect of removing corrupted slices was assessed on the reconstructed FA maps and fiber tracts.

RESULTS:

Using a motion-metric threshold to remove the motion-corrupted slices results in superior fiber tracts and fractional anisotropy maps. When further compared to a state-of-the-art magnitude-based motion correction method, PITA-MDD was able to detect comparable corrupted slices in a more computationally efficient manner.

CONCLUSION:

In this study, we evaluated the use of DW phase images to detect motion corruption. The proposed method can be a robust and fast alternative for automatic motion detection in the brain with multiple applications to inform prospective motion correction or as real-time feedback for data quality control during scanning, as well as after data is already acquired.

PMID:
31319127
PMCID:
PMC6697150
[Available on 2020-10-01]
DOI:
10.1016/j.mri.2019.07.009

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