Effects of interpolation methods in spatial normalization of diffusion tensor imaging data on group comparison of fractional anisotropy Tzu-Cheng Chao a,b , Ming-Chung Chou a,c , Pinchen Yang d,e, ⁎ , Hsiao-Wen Chung a,c , Ming-Ting Wu b,f a Department of Electrical Engineering, National Taiwan University, Taipei 106, Taiwan b Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung 813, Taiwan c Department of Radiology, Tri-Service General Hospital, Taipei 100, Taiwan d Department of Psychiatry, Kaohsiung Medical University, Kaohsiung 807, Taiwan e Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan f School of Medicine, National Yang-Ming University, Taipei 112, Taiwan Received 7 March 2008; revised 9 September 2008; accepted 25 September 2008 Abstract This study investigated the effects on the measurement of fractional anisotropy (FA) during interpolation of diffusion tensor images in spatial normalization, which is required for voxel-based statistics. Diffusion tensor imaging data were obtained from nine male patients with attention deficit/hyperactivity disorder and nine age-matched control subjects. Regions of interest were selected from the genu of corpus callosum (GCC) and the right anterior corona radiata (RACR), with FA values measured before and after spatial normalization using two interpolation algorithms: linear and rotationally linear. Computer simulations were performed to verify the experimental findings. Between- group difference in FA was observed in the GCC and RACR before spatial normalization (Pb .00001). Interpolation reduced the measured FA values significantly (Pb .00001 for both algorithms) but did not affect the group difference in the GCC. For the RACR, the between-group difference vanished (P=.968) after linear interpolation but was relatively unaffected by using rotationally linear interpolation (P=.00001). FA histogram analysis and computer simulations confirmed these findings. This work suggests that caution should be exercised in voxel-based group comparisons as spatial normalization may affect the FA value in nonnegligible degrees, particularly in brain areas with predominantly crossing fibers. © 2009 Elsevier Inc. All rights reserved. 1. Introduction Diffusion tensor imaging (DTI) using magnetic resonance imaging (MRI) has become a popular noninvasive imaging technique in the examination of microstructures of brain tissues [1–3]. DTI can be used to assess fractional anisotropy (FA) of white matter track in the brain, with lower white matter FA values often indicating alterations in white matter fiber integrity [4]. Studies performing DTI analysis on psychiatric disorders suggested that there may be micro- structural changes in the white matter, as reflected by alterations in DTI indices [3]. However, the neurobiological changes in the white matter fibers due to psychiatric diseases are usually subtle compared with physiological injuries, causing detection difficulty on single subjects in the presence of finite signal-to-noise ratios [5,6]. For psychiatric dis- orders, therefore, group analysis via intersubject averaging of imaging data now plays an increasingly important role. Voxel-based statistical (VBS) analysis could be a useful tool in the unveiling of regional structural differences between groups of subjects in an unbiased manner [7]. Before the voxel-based analysis can be performed, the process of spatial normalization consisting of a series of image deformation procedures must be applied to transform the individual brain image onto a standard template. For morphological images, such as T1-weighted images, the normalization algorithm has been well developed, with free shareware programs easily accessible [8–10]. Spatial normalization of DTI, however, is more complicated in Available online at www.sciencedirect.com Magnetic Resonance Imaging 27 (2009) 681 – 690 ⁎ Corresponding author. Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan. Tel.: +886 7 3121101; fax: +886 7 3218309. E-mail address: pichya@cc.kmu.edu.tw (P. Yang). 0730-725X/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.mri.2008.09.004