Purpose: To develop and assess a method for the creation of templates for voxel-based analysis (VBA) and atlas-based approaches using quantitative magnetic susceptibility mapping (QSM).
Materials and methods: We studied four strategies for the creation of magnetic susceptibility brain templates, derived as successive extensions of the conventional template generation (CONV) based on only T1 -weighted (T1 w) images. One method that used only T1 w images involved a minor improvement of CONV (U-CONV). One method used only magnetic susceptibility maps as input for template generation (DIRECT), and the other two used a linear combination of susceptibility and T1 w images (HYBRID) and an algorithm that directly used both image modalities (MULTI), respectively. The strategies were evaluated in a group of N = 10 healthy human subjects and semiquantitatively assessed by three experienced raters. Template quality was compared statistically via worth estimates (WEs) obtained with a log-linear Bradley-Terry model.
Results: The overall quality of the templates was better for strategies including both susceptibility and T1 w contrast (MULTI: WE = 0.62; HYBRID: WE = 0.21), but the best method depended on the anatomical region of interest. While methods using only one modality resulted in lower WEs, lowest overall WEs were obtained when only T1 w images were used (DIRECT: WE = 0.12; U-CONV: WE = 0.05).
Conclusion: Template generation strategies that employ only magnetic susceptibility contrast or both magnetic susceptibility and T1 w contrast produce templates with the highest quality. The optimal approach depends on the anatomical structures of interest. The established approach of using only T1 w images (CONV) results in reduced image quality compared to all other approaches studied.
Level of evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1474-1484.
Keywords: T1-weighted imaging; magnetic resonance imaging (MRI); normalization; quantitative susceptibility mapping (QSM); template; voxel-based analysis (VBA).
© 2017 International Society for Magnetic Resonance in Medicine.