Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord.

Magn Reson Imaging

Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.

Published: May 2024

AI Article Synopsis

  • Diffusion MRI of the spinal cord faces challenges due to geometric distortions and motion artifacts, which can lead to issues with image alignment and quality.
  • This study examines two key techniques: susceptibility corrections for better geometric alignment and cardiac triggering to reduce motion artifacts during imaging.
  • Results indicate that while susceptibility corrections improve alignment with high-contrast cerebrospinal fluid images, they do not necessarily enhance spinal cord geometry or matter contrast; however, skipping cardiac triggering does not compromise image quality and allows for quicker scans.

Article Abstract

Diffusion MRI of the spinal cord (SC) is susceptible to geometric distortion caused by field inhomogeneities, and prone to misalignment across time series and signal dropout caused by biological motion. Several modifications of image acquisition and image processing techniques have been introduced to overcome these artifacts, but their specific benefits are largely unproven and warrant further investigations. We aim to evaluate two specific aspects of image acquisition and processing that address image quality in diffusion studies of the spinal cord: susceptibility corrections to reduce geometric distortions, and cardiac triggering to minimize motion artifacts. First, we evaluate 4 distortion preprocessing strategies on 7 datasets of the cervical and lumbar SC and find that while distortion correction techniques increase geometric similarity to structural images, they are largely driven by the high-contrast cerebrospinal fluid, and do not consistently improve the geometry within the cord nor improve white-to-gray matter contrast. We recommend at a minimum to perform bulk-motion correction in preprocessing and posit that improvements/adaptations are needed for spinal cord distortion preprocessing algorithms, which are currently optimized and designed for brain imaging. Second, we design experiments to evaluate the impact of removing cardiac triggering. We show that when triggering is foregone, images are qualitatively similar to triggered sequences, do not have increased prevalence of artifacts, and result in similar diffusion tensor indices with similar reproducibility to triggered acquisitions. When triggering is removed, much shorter acquisitions are possible, which are also qualitatively and quantitatively similar to triggered sequences. We suggest that removing cardiac triggering for cervical SC diffusion can be a reasonable option to save time with minimal sacrifice to image quality.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11218893PMC
http://dx.doi.org/10.1016/j.mri.2024.01.008DOI Listing

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