Abstract #3727

On the Importance of Using High-Resolution Atlases for Voxel-Based Morphometry of High-Resolution MRI Data: A Case-Control Study on Essential Tremor

Eric M Cameron^1,2, Jonathan P Dyke³, Elan D Louis^4,5,6, and Ulrike Dydak^1,2

¹School of Health Sciences, Purdue University, West Lafayette, IN, United States, ²Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States, ³Department of Radiology, Weill Cornell Medicine, New York, NY, United States, ⁴Department of Neurology, Yale School of Medicine, New Haven, CT, United States, ⁵Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, United States, ⁶Center for Neuroepidemiology and Clinical Neurological Research, Yale School of Medicine, New Haven, CT, United States

The use of a high resolution atlas for segmentation and normalization greatly improves the accuracy of voxel-based morphometry analysis of magnetic resonance images. An adjusted method including the high resolution atlas was compared to the default method with the standard resolution atlas in a case-control study on essential tremor to demonstrate the impact of higher resolution segmentation. After multiple comparison correction using extent cluster thresholding, the adjusted method showed bilaterally consistent results, while the default method showed some false positive results in peripheral regions of the brain. A high resolution atlas should be used to segment equally high resolution images.

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