Semi-automated 3D segmentation of major tracts in the rat brain: comparing DTI with standard histological methods
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Researchers working with rodent models of neurological disease often require an accurate map of the anatomical organization of the white matter of the rodent brain. With the increasing popularity of small animal MRI techniques, including diffusion tensor imaging (DTI), there is considerable interest in rapid segmentation methods of neurological structures for quantitative comparisons. DTI-derived tractography allows simple and rapid segmentation of major white matter tracts, but the anatomic accuracy of these computer-generated fibers is open to question and has not been rigorously evaluated in the rat brain. In this study, we examine the anatomic accuracy of tractography-based segmentation in the adult rat brain. We analysed 12 major white matter pathways using semi-automated tractography-based segmentation alongside manual segmentation of Gallyas silver-stained histology sections. We applied four fiber-tracking algorithms to the DTI data—two integration methods and two deflection methods. In many cases, tractography-based segmentation closely matched histology-based segmentation; however different tractography algorithms produced dramatically different results. Results suggest that certain white matter pathways are more amenable to tractography-based segmentation than others. We believe that these data will help researchers decide whether it is appropriate to use tractography-based segmentation of white matter structures for quantitative DTI-based analysis of neurologic disease models.
KeywordsMRI DTI Automated segmentation Gallyas silver myelin staining
This work was supported by an Australia Fellowship awarded to Professor George Paxinos by the National Health and Medical Research Council (NHMRC) (466028) and the Duke Center for In Vivo Microscopy, an NIH/NCRR/NIBIB national Biomedical Technology Resource Center (P41 EB015897).
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