• Bálint Kincses, Tamás Spisák, Péter Faragó, András Király, Nikoletta Szabó, Dániel Veréb, Krisztián Kocsis, Bence Bozsik, Eszter Tóth, László Vécsei, and Zsigmond Tamás Kincses.
• Department of Neurology, University of Szeged, Szeged, Hungary.
• J Neuroimaging. 2020 Jul 1; 30 (4): 512-522.

Background And PurposeDiffusion tensor imaging (DTI) is a promising approach to detect the underlying brain pathology. These alterations can be seen in several diseases such as multiple sclerosis. Tract-based spatial statistics (TBSS) is an easy to use and robust way for analyzing diffusion data. The effect of acquisition parameters of DTI on TBSS has not been evaluated, especially the number of diffusion encoding directions (NDED), which is directly proportional with scan time.MethodsWe analyzed a large set of DTI data of healthy controls (N = 126) and multiple sclerosis patients (N = 78). The highest NDED (60 directions) was reduced and a tensor calculation was done separately for every subset. We calculated the mean and standard deviation of DTI parameters under the white matter mask. Moreover, the FMRIB Software Library TBSS pipeline was used on DTI images with 15, 30, 45, and 60 directions to compare differences between groups. Mean DTI parameters were compared between groups as a function of NDED.ResultsThe mean value of FA and AD decreased with increasing number of directions. This was more pronounced in areas with smaller FA values. RD and MD were constant. The skeleton size reduced with elevating NDED along with the number of significant voxels. The TBSS analysis showed significant differences between groups throughout the majority of the skeleton and the group difference was associated with NDED.ConclusionOur results suggested that results of TBSS depended on the NDED, which should be considered when comparing DTI data with varying protocols.© 2020 The Authors. Journal of Neuroimaging published by Wiley Periodicals LLC on behalf of American Society of Neuroimaging.

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