Diffusion tensor imaging metrics in neonates - A comparison of manual region-of-interest analysis vs. tract-based spatial statistics

Youngseob Seo, Zhiyue J. Wang, Gareth Ball, Nancy K. Rollins

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Background: Diffusion tensor data can be analyzed using region-of-interest (ROI) analysis and tract-based spatial statistics (TBSS). There is essentially no literature validating or comparing these techniques in the neonate. Objective: The purpose of this study was to perform a direct comparison of fractional anisotropy (FA), axial diffusivity (AD) and radial diffusivity (RD) derived using manual ROI analysis and TBSS modified for use in neonates. Materials and methods: This study was IRB-approved. Thirty-nine infants, 32-49 weeks post-conception age, underwent MRI at 3 T. FA, AD and RD of the callosal genu (CG) and splenium (CS) and posterior limbs of both internal capsules (PLIC) were determined using both techniques. Pearson correlation (r) was used to estimate the concordance of tensor metrics derived from these techniques. Results: The r value for FA in the CG, CS and left and right PLIC was 0.88, 0.75, 0.78 and 0.35, respectively. The r value for axial/radial diffusivity in the CG, CS and left and right PLIC was 0.62/0.72, 0.76/0.64, 0.68/0.9 and 0.3/0.72, respectively. The variable concordance results from problems with spatial correspondence of ROI masks between the native space and the FA skeleton. Conclusion: Direct comparison between these methodologies shows tensor metrics varied with location and by degree, suggesting the two techniques do not provide consistently comparable results.

Original languageEnglish (US)
Pages (from-to)69-79
Number of pages11
JournalPediatric radiology
Volume43
Issue number1
DOIs
StatePublished - Jan 2013

Keywords

  • Comparison of diffusion tensor metrics
  • Diffusion tensor imaging
  • Manual ROI analysis
  • Tract-based spatial statistics

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Radiology Nuclear Medicine and imaging

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