Quantification of accuracy and precision of multi-center DTI measurements: a diffusion phantom and human brain study

Neuroimage. 2011 Jun 1;56(3):1398-411. doi: 10.1016/j.neuroimage.2011.02.010. Epub 2011 Feb 18.

Abstract

The inter-site and intra-site variability of system performance of MRI scanners (due to site-dependent and time-variant variations) can have significant adverse effects on the integration of multi-center DTI data. Measurement errors in accuracy and precision of each acquisition determine both the inter-site and intra-site variability. In this study, multiple scans of an identical isotropic diffusion phantom and of the brain of a traveling human volunteer were acquired at MRI scanners from the same vendor and with similar configurations at three sites. We assessed the feasibility of multi-center DTI studies by direct quantification of accuracy and precision of each dataset. Accuracy was quantified via comparison to carefully constructed gold standard datasets while precision (the within-scan variability) was estimated by wild bootstrap analysis. The results from both the phantom and human data suggest that the inter-site variation in system performance, although relatively small among scanners of the same vendor, significantly affects DTI measurement accuracy and precision and therefore the effectiveness for the integration of multi-center DTI measurements. Our results also highlight the value of a DTI-specific phantom in identifying and quantifying measurement errors due to site-dependent variations in the system performance, and its usefulness for quality assurance/quality control in multi-center DTI studies. In addition, we observed that the within-scan variability of each data acquisition, as assessed by wild bootstrap analysis, is of the same magnitude as the inter-site and intra-site variability. We propose that by weighing datasets based on their variability, as evaluated by wild bootstrap analysis, one can improve the quality of the dataset. This approach will provide a more effective integration of datasets from multi-center DTI studies.

Publication types

  • Multicenter Study
  • Research Support, N.I.H., Extramural

MeSH terms

  • Brain / anatomy & histology*
  • Brain Mapping / methods
  • Data Interpretation, Statistical
  • Databases, Factual
  • Diffusion Tensor Imaging / instrumentation
  • Diffusion Tensor Imaging / methods*
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Multicenter Studies as Topic
  • Phantoms, Imaging*
  • Reproducibility of Results
  • Young Adult