Int J Comput Assist Radiol Surg - Automated segmentation of basal ganglia and deep brain structures in MRI of Parkinson's disease.

Tópicos

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Resumo

RPOSE: Template-based segmentation techniques have been developed to facilitate the accurate targeting of deep brain structures in patients with movement disorders. Three template-based brain MRI segmentation techniques were compared to determine the best strategy for segmenting the deep brain structures of patients with Parkinson's disease.METHODS: T1-weighted and T2-weighted magnetic resonance (MR) image templates were created by averaging MR images of 57 patients with Parkinson's disease. Twenty-four deep brain structures were manually segmented on the templates. To validate the template-based segmentation, 14 of the 24 deep brain structures from the templates were manually segmented on 10 MR scans of Parkinson's patients as a gold standard. We compared the manual segmentations with three methods of automated segmentation: two registration-based approaches, automatic nonlinear image matching and anatomical labeling (ANIMAL) and symmetric image normalization (SyN), and one patch-label fusion technique. The automated labels were then compared with the manual labels using a Dice-kappa metric and center of gravity. A Friedman test was used to compare the Dice-kappa values and paired t tests for the center of gravity.RESULTS: The Friedman test showed a significant difference between the three methods for both thalami (p?<?0.05) and not for the subthalamic nuclei. Registration with ANIMAL was better than with SyN for the left thalamus and was better than the patch-based method for the right thalamus.CONCLUSION: Although template-based approaches are the most used techniques to segment basal ganglia by warping onto MR images, we found that the patch-based method provided similar results and was less time-consuming. Patch-based method may be preferable for the subthalamic nucleus segmentation in patients with Parkinson's disease.

Resumo Limpo

rpose templatebas segment techniqu develop facilit accur target deep brain structur patient movement disord three templatebas brain mri segment techniqu compar determin best strategi segment deep brain structur patient parkinson diseasemethod tweight tweight magnet reson mr imag templat creat averag mr imag patient parkinson diseas twentyfour deep brain structur manual segment templat valid templatebas segment deep brain structur templat manual segment mr scan parkinson patient gold standard compar manual segment three method autom segment two registrationbas approach automat nonlinear imag match anatom label anim symmetr imag normal syn one patchlabel fusion techniqu autom label compar manual label use dicekappa metric center graviti friedman test use compar dicekappa valu pair t test center gravityresult friedman test show signific differ three method thalami p subthalam nuclei registr anim better syn left thalamus better patchbas method right thalamusconclus although templatebas approach use techniqu segment basal ganglia warp onto mr imag found patchbas method provid similar result less timeconsum patchbas method may prefer subthalam nucleus segment patient parkinson diseas

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