Quantitative Analysis of White Matter Fiber Properties along Geodesic Paths

Diffusion Tensor Imaging (DTI) is becoming a routine magnetic resonance technique to study white matter properties and alterations of fiber integrity due to pathology. The advanced MRI technique needs postprocessing by adequate image processing and visualization tools. Analysis of DTI in clinical studies so far use manual definition of regions or interest or image matching followed by voxel-based analysis. This paper presents a novel concept that extracts major fiber bundles by tractography and provides a statistical analysis of diffusion properties along fibers, i.e. geodesic paths within the three-dimensional brain image. Fiber tracing thus serves as a sophisticated, efficient method for defining complex regions of interests along major fiber tracts not accessible otherwise. Fiber bundles extracted from a set of subjects are parametrized by arc-length and mapped to a common coordinate system centered at well-defined anatomical landmarks. The description of the methodology is guided by the example of measuring diffusion properties along the left and right cingulate. We also present preliminary results from an ongoing clinical neonatal study that studies early brain development.

[1]  Marko Wilke,et al.  Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study. , 2002, Radiology.

[2]  S. Maier,et al.  Microstructural Development of Human Newborn Cerebral White Matter Assessed in Vivo by Diffusion Tensor Magnetic Resonance Imaging , 1998, Pediatric Research.

[3]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[4]  Guido Gerig,et al.  Towards a shape model of white matter fiber bundles using diffusion tensor MRI , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[5]  Comparisons of Regional White Matter Diffusion in Healthy Neonates and Adults Using a 3t Head-only Mr Scanner , .

[6]  P. Basser,et al.  Estimation of the effective self-diffusion tensor from the NMR spin echo. , 1994, Journal of magnetic resonance. Series B.

[7]  R. Kikinis,et al.  Quantitative magnetic resonance imaging of brain development in premature and mature newborns , 1998, Annals of neurology.

[8]  Guido Gerig,et al.  Comparisons of regional white matter diffusion in healthy neonates and adults performed with a 3.0-T head-only MR imaging unit. , 2003, Radiology.

[9]  A. Snyder,et al.  Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging. , 1998, Radiology.

[10]  P. Basser,et al.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. , 1996, Journal of magnetic resonance. Series B.

[11]  A. D. de Crespigny,et al.  Compromised white matter tract integrity in schizophrenia inferred from diffusion tensor imaging. , 1999, Archives of general psychiatry.

[12]  Christos Davatzikos,et al.  A Framework for Callosal Fiber Distribution Analysis , 2002, NeuroImage.

[13]  John C. Gore,et al.  Case study: reconstruction, visualization and quantification of neuronal fiber pathways , 2001, Proceedings Visualization, 2001. VIS '01..

[14]  R. Skalko,et al.  Congenital asymmetry: report of 10 cases with associated developmental abnormalities. , 1969, Pediatrics.

[15]  Guido Gerig,et al.  Level-set evolution with region competition: automatic 3-D segmentation of brain tumors , 2002, Object recognition supported by user interaction for service robots.

[16]  Carl-Fredrik Westin,et al.  Processing and visualization for diffusion tensor MRI , 2002, Medical Image Anal..