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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
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Effect of scanner in longitudinal diffusion tensor imaging studies.

Hidemasa Takao1, Naoto Hayashi, Hiroyuki Kabasawa

  • 1Department of Radiology, Graduate School of Medicine, University of Tokyo, Hongo, Bunkyo-ku, Tokyo, Japan. takaoh-tky@umin.ac.jp

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|March 11, 2011
PubMed
Summary
This summary is machine-generated.

Longitudinal diffusion tensor imaging studies are affected by scanner variability and upgrades. Even identical scanners show bias, impacting results for fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD).

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Area of Science:

  • Neuroimaging
  • Diffusion Tensor Imaging (DTI)
  • Medical Physics

Background:

  • Longitudinal studies in neuroimaging require consistent scanner performance over time.
  • Scanner hardware drift, inter-scanner variability, and software upgrades can introduce biases.
  • Understanding these factors is crucial for accurate interpretation of longitudinal changes in white matter properties.

Purpose of the Study:

  • To assess the impact of scanner hardware drift, inter-scanner variability, and scanner upgrades on longitudinal diffusion tensor imaging (DTI) metrics.
  • To evaluate the effects on global and regional white matter fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD).
  • To analyze these effects using data from two identical 3.0-T scanners at a single institution.

Main Methods:

  • Longitudinal DTI data were acquired from 224 healthy subjects scanned twice, approximately one year apart.
  • Two identical 3.0-T scanners were used, with both undergoing a simultaneous software upgrade during the study.
  • Tract-based spatial statistics (TBSS) were employed to analyze changes in FA, AD, and RD, accounting for scanner combinations.

Main Results:

  • Significant inter-scanner variability (bias) was observed, affecting longitudinal DTI results despite using identical scanner models.
  • White matter FA, AD, and RD remained relatively stable when scanned on the same machine over time.
  • A significant effect of the scanner software upgrade was detected on longitudinal FA, AD, and RD measurements.

Conclusions:

  • Inter-scanner variability poses a significant challenge for longitudinal DTI studies, even with the same scanner model.
  • Scanner upgrades, including software-only updates, can introduce significant changes in longitudinal DTI data.
  • These findings highlight the need for careful calibration and consideration of scanner-related factors in longitudinal neuroimaging research.