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Comparison of accuracy between FSL's FIRST and Freesurfer for caudate nucleus and putamen segmentation.

ABSTRACT: Although several methods have been developed to automatically delineate subcortical gray matter structures from MR images, the accuracy of these algorithms has not been comprehensively examined. Most of earlier studies focused primarily on the hippocampus. Here, we assessed the accuracy of two widely used non-commercial programs (FSL-FIRST and Freesurfer) for segmenting the caudate and putamen. T1-weighted 1 mm³ isotropic resolution MR images were acquired for thirty healthy subjects (15 females). Caudate nucleus and putamen were segmented manually by two independent observers and automatically by FIRST and Freesurfer (v4.5 and v5.3). Utilizing manual labels as reference standard the following measures were studied: Dice coefficient (D), percentage volume difference (PVD), absolute volume difference as well as intraclass correlation coefficient (ICC) for consistency and absolute agreement. For putamen segmentation, FIRST achieved higher D, lower PVD and higher ICC for absolute agreement with manual tracing than either version of Freesurfer. Freesurfer overestimated the putamen, while FIRST was not statistically different from manual tracing. The ICC for consistency with manual tracing was similar between the two methods. For caudate segmentation, FIRST and Freesurfer performed more similarly. In conclusion, Freesurfer and FIRST are not equivalent when comparing to manual tracing. FIRST was superior for putaminal segmentation.

SUBMITTER: Perlaki G

PROVIDER: S-EPMC5445091 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Neuronal networks are regulated by three-dimensional spatial and structural properties. Despite robust evidence of functional implications in the modulation of cognition, little is known about the three-dimensional internal organization of cholinergic networks in the forebrain. Cholinergic networks in the forebrain primarily occur in subcortical nuclei, specifically the septum, nucleus basalis, globus pallidus, nucleus accumbens, and the caudate-putamen. Therefore, the present investigation analyzed the three-dimensional spatial organization of 14,000 cholinergic neurons that expressed choline acetyltransferase (ChAT) in these subcortical nuclei of the mouse forebrain. Point process theory and graph signal processing techniques identified three topological principles of organization. First, cholinergic interneuronal distance is not uniform across brain regions. Specifically, in the septum, globus pallidus, nucleus accumbens, and the caudate-putamen, the cholinergic neurons were clustered compared with a uniform random distribution. In contrast, in the nucleus basalis, the cholinergic neurons had a spatial distribution of greater regularity than a uniform random distribution. Second, a quarter of the caudate-putamen is composed of axonal bundles, yet the spatial distribution of cholinergic neurons remained clustered when axonal bundles were accounted for. However, comparison with an inhomogeneous Poisson distribution showed that the nucleus basalis and caudate-putamen findings could be explained by density gradients in those structures. Third, the number of cholinergic neurons varies as a function of the volume of a specific brain region but cell body volume is constant across regions. The results of the present investigation provide topographic descriptions of cholinergic somata distribution and axonal conduits, and demonstrate spatial differences in cognitive control networks. The study provides a comprehensive digital database of the total population of ChAT-positive neurons in the reported structures, with the x,y,z coordinates of each neuron at micrometer resolution. This information is important for future digital cellular atlases and computational models of the forebrain cholinergic system enabling models based on actual spatial geometry.

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Comparison of accuracy between FSL's FIRST and Freesurfer for caudate nucleus and putamen segmentation.

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