The patients with disorders of consciousness (DOC) can be divided into vegetable state (VS), minimally conscious state (MCS). The aetiology of these clinical outcomes was varied and there were high rate of misdiagnosis. Diffusion tensor imaging (DTI) is a non-invasive technique to characterize the microstructures of brain tissue and brain white matter distributions[1, 2]. Previous DTI studies suggested that white matter microstructures in subcortical, thalamus, and brainstem were impaired in VS patients[3, 4]. However, few studies reported changes of brain white matter skeleton in DOC patients. In this study, we attempted to use the tract-based spatial statistics (TBSS) approach to examine the changes of diffusion parameters in whole brain white matter of DOC patients relative to healthy controls, and to detect the correlation between the diffusion parameters of white matters and clinical variables. Eighteen DOC patients (9VS/ 9MCS) of varying aetiology (11M/ 7F) were recruited from the Coma Recovery Unit, Centre for Hyperbaric Oxygen and Neurorehabilitaiton, Guangzhou Liuhuaqiao Hospital. The VS and MCS patients were diagnosed using the Coma Recovery Scale-Revised (CRS-R). We also enrolled 18 age- and gender-matched healthy subjects (10M/ 8F) as the controls. The protocols were approved by the Institutional Review Board of Guangzhou Liuhuaqiao Hospital. Written informed consent was obtained from each patient. All MR data were acquired on a 3T GE MRI scanner. DTI data were obtained using a spin-echo diffusion-weighted EPI sequence: 30 volumes, b=1000s/mm2 and 3 b0, TR/TE=17000/85.9ms, matrix = 256×256, FOV = 240mm×240mm, slice thickness = 2.4mm without gap, and 60 axial slices covering the whole brain. The T1-weighted 3D images were acquired using 3D FSPGR sequence: TR/TE=8.8/3.5ms, FOV=240mm×240mm, matrix size=256×256, thickness=1mm, 176 sagittal slices. DTI data were processed with FSL package. First, all images underwent eddy current distortion correction and then fitted a tensor model. Thus, we obtained the brain maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) for each subject. Second, we performed TBSS analysis on the whole brain FA maps across all subjects with the FSL/FDT[5]. For example, all FA images across subjects were co-registered to the FMRIB-58 FA template, and were averaged to generate a study-specific FA map with nonlinear coregistration. We created the mean FA skeleton for the present study. Third, the FA map of each subject was projected onto the mean FA skeleton. We conducted voxel-wised analysis with FA>0.2, removed covariates with GLM and carried out a non-parametric permutation test (5,000 repetitions). The same procedures were also conducted on the brain maps of MD, AD, and RD, respectively. The voxel-based threshold (p<0.05) was applied with multi-comparison correction (TFCE). Meanwhile, the ROI-based calculation was carried out to extract FA values that show differences in the white matters of each subject. Last, FA values of all 18 patients were used to carry out correlation analyses with the scores of CRS-R.Fig. 1 shows brain white matter with significant differences in FA, MD, AD, and RD maps between the DOC and HC groups (p<0.001, TFCE-corrected). We found the DOC group showed significantly decreased FA and AD, but increased MD and RD, in the tracts of corpus callosum, forceps minor and bilateral fronto-occipital fasciculus (Table 1). Meanwhile, we also detected no difference in FA values between MCS and VS (p = 0.0761). The results from the ROI-based correlation analyses revealed significant correlation (p < 0.05, corrected) between CRS-R scores of auditory, vision, motor and FA values of each DOC patients’ different white matters (Fig. 2).Our study revealed the alteration of brain white matter in the projection fibers, association fibers, and commissural fibers were correlated with the onset of DOC patients.Our findings may be useful for studying the pathophysiology, progression and treatment of DOC patients.