Human brain atlas for automated region of interest selection in quantitative susceptibility mapping: application to determine iron content in deep gray matter structures

Neuroimage. 2013 Nov 15;82:449-69. doi: 10.1016/j.neuroimage.2013.05.127. Epub 2013 Jun 12.

Abstract

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a "deep gray matter parcellation map" (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established "white matter parcellation map" (WMPM) from the same subject's T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the "Everything Parcellation Map in Eve Space," also known as the "EvePM." It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting "almost perfect" agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray matter structures measured by Hallgren and Sourander (1958) allowed interpolation of the average iron concentration of several deep gray matter regions delineated in the EvePM.

Keywords: AIR; Algorithm for sparse linear equations and sparse least squares; Amg; Amygdala; Automated Image Registration; Body of the Corpus Callosum; Brain; CC; CCb; CCg; CCs; CN; COSMOS; CSF; CX; Calculation of Susceptibility through Multiple Orientation Sampling; Caudate Nucleus; Cerebrospinal Fluid; Corpus Callosum; Cortex; DGMPM; DN; Deep Gray Matter Parcellation Map (derived from QSM calculations); Deep gray matter; Dentate Nucleus; EC; ETAAS; Electro-thermal Atomic Absorption Spectroscopy; EvePM; External Capsule; GM; GP; GRE; Genu of the Corpus Callosum; Globus Pallidus; Gradient Recalled Echo; Gray Matter; Hip; Hippocampus; IC; INAA; Instrumental Neutron Activation Analysis; Internal Capsule; Iron; LDDMM; LSQR; LVL; Large Deformation Diffeomorphic Metric Mapping; Lateral Ventricle; MEDI; MRI; Magnetic Resonance Imaging; Morphology Enabled Dipole Inversion; PT; Put; Putamen; QSM; Quantitative Susceptibility Mapping; Quantitative magnetic susceptibility mapping; RN; ROI; RSO; Red Nucleus; Region of Interest; Regularized Single Orientation; SHARP; SN; SS; Sagittal Stratum; Segmentation; Sophisticated Harmonic Artifact Reduction for Phase data; Splenium of the Corpus Callosum; Stereotaxic atlas; Substantia Nigra; TH; TKD; TR; Th; Thalamic Radiations; Thalamus; Thresholded K-space Division; WKD; WM; WMPM; Weighted K-space partial Derivatives; White Matter; White Matter Parcellation Map (derived from previous T(1)-weighted and DTI measurements); “Everything” Parcellation Map with gray and white matter ROIs.

MeSH terms

  • Adult
  • Anatomy, Artistic*
  • Atlases as Topic*
  • Brain Chemistry*
  • Brain Mapping / methods*
  • Humans
  • Image Processing, Computer-Assisted
  • Iron / analysis*
  • Magnetic Resonance Imaging
  • Male
  • Software

Substances

  • Iron