Objective <p>To validate the automated analysis of magnetic resonance imaging (MRI) diffusion phantoms with an updated version of the magnetic resonance biomarker assessment software (MR-BIAS), an open-source tool initially developed for the analysis of MRI relaxometry phantoms.</p> Materials and methods <p>The updated MR-BIAS was validated against two published diffusion weighted MRI datasets: (i) a single-site study (<i>n</i> = 48) was used for validation of apparent diffusion coefficients (ADC) and to identify optimal region of interest (ROI) selection, and (ii) a multi-centre multi-vendor study including diffusion imaging from a shared benchmark protocol (<i>n</i> = 49) and site-specific protocols (<i>n</i> = 43). ADC analysis compared both datasets with ROIs manually matched to the original studies, and with automatically detected optimal ROIs.</p> Results <p>MR-BIAS ADC values were statistically equivalent (<i>p</i> &lt; 0.05) to original studies within tolerances (manual ROI, automatic ROI) for the single-site study (± 0.01, ± 6 μm<sup>2</sup>/s) and for the multi-vendor study for benchmark (± 4, ± 7 μm<sup>2</sup>/s) and site-specific (± 3, ± 6 μm<sup>2</sup>/s) protocols. The optimal ROI was a central cylinder (height = 10mm, diamete<i>r</i> = 10mm). MR-BIAS ADC summary metrics were comparable to those of the original studies.</p> Discussion <p>MR-BIAS can automatically and accurately perform ADC analysis of diffusion phantoms, making the software suitable for the quality assurance of multi-centre studies of multi-parametric MRI.</p>

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Open-source quality assurance for multi-parametric MRI: a diffusion analysis update for the magnetic resonance biomarker assessment software (MR-BIAS)

  • James C. Korte,
  • Stanley A. Norris,
  • Madeline E. Carr,
  • Lois Holloway,
  • Glenn D. Cahoon,
  • Ben Neijndorff,
  • Petra van Houdt,
  • Rick Franich

摘要

Objective

To validate the automated analysis of magnetic resonance imaging (MRI) diffusion phantoms with an updated version of the magnetic resonance biomarker assessment software (MR-BIAS), an open-source tool initially developed for the analysis of MRI relaxometry phantoms.

Materials and methods

The updated MR-BIAS was validated against two published diffusion weighted MRI datasets: (i) a single-site study (n = 48) was used for validation of apparent diffusion coefficients (ADC) and to identify optimal region of interest (ROI) selection, and (ii) a multi-centre multi-vendor study including diffusion imaging from a shared benchmark protocol (n = 49) and site-specific protocols (n = 43). ADC analysis compared both datasets with ROIs manually matched to the original studies, and with automatically detected optimal ROIs.

Results

MR-BIAS ADC values were statistically equivalent (p < 0.05) to original studies within tolerances (manual ROI, automatic ROI) for the single-site study (± 0.01, ± 6 μm2/s) and for the multi-vendor study for benchmark (± 4, ± 7 μm2/s) and site-specific (± 3, ± 6 μm2/s) protocols. The optimal ROI was a central cylinder (height = 10mm, diameter = 10mm). MR-BIAS ADC summary metrics were comparable to those of the original studies.

Discussion

MR-BIAS can automatically and accurately perform ADC analysis of diffusion phantoms, making the software suitable for the quality assurance of multi-centre studies of multi-parametric MRI.