Details of Atypical Antipsychotic Drugs for Schizophrenia Patients. Resting-State Functional MR Imaging Data Acquisition and

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1 RSNA, /radiol Appendix E1 Details of Atypical Antipsychotic Drugs for Schizophrenia Patients After baseline assessment, all patients were treated with atypical antipsychotic drugs, with dosing and drug selection determined by the treating psychiatrist. Treatment at 1-year follow-up consisted of risperidone (in 13 cases), at a mean dose of 2.67 mg/d ± 1.87; quetiapine (in four cases), at a mean dose of mg/d ± ; clozapine (in three cases), at a mean dose of mg/d ± 26.13; olanzapine (in two cases), at a mean dose of 4.66 mg/d ± 5.7; sulpiride (in two cases), at a mean dose of 438 mg/d ± 347.9; and aripiprazole (in one case), at a mean dose of 20 mg/d. The number of patients who were treated with the different drugs exceeds the total number of patients because some patients received more than one medication. The dosage of antipsychotic medication at 1-year follow-up was converted to chlorpromazine equivalent dosages, with the mean (standard deviation) dose of mg/d ± (35). Resting-State Functional MR Imaging Data Acquisition and Preprocessing All subjects underwent rfmr imaging with a 3-T MR imaging system (Excite; GE Healthcare, Milwaukee, Wis) and an eight-channel phased-array head coil. The daily quality assurance protocol was used to establish the stability of the MR imaging system by using a water phantom. During imaging, subjects were instructed to relax with their eyes closed and without falling asleep or directed, systematic thought (which was confirmed by a self-report of subjects immediately after the experiment). Page 1 of 11

2 Before imaging, all participants were instructed not to think of anything in particular and keep their eyes closed during rfmr imaging; afterward, we asked participants the following questions: (a) Were you awake during imaging? (b) Did you keep your eyes closed during imaging? (c) Were you thinking of anything specific during imaging? Nevertheless, we acknowledge that we had no way of knowing for sure what subjects were thinking about during imaging. MR images that were sensitized to changes in BOLD signal levels were obtained with a gradient-echo echoplanar imaging sequence and the following parameters: repetition time/echo time, 2000/30 msec; flip angle, 90 ; section thickness, 5 mm, with no intersection gaps; matrix size, 64 64; field of view, mm 2 ; and voxel size, mm 3. Each brain volume comprised 30 axial sections, and each functional run contained 200 image volumes that were preceded by five dummy volumes, resulting in a total imaging time of 410 sec. For each participant, the first five dummy volumes were discarded to allow for imager stabilization and the subject s adaptation to the environment; the remaining gradient-echo echoplanar imaging functional images were section-time corrected, realigned to the middle volume, and realigned by using a six-parameter (rigid body) linear transformation. We used the Friston 24-parameter model to regress out head motion effects from the realigned data on the basis of recent reports in which higher-order models demonstrated benefits in removing head motion effects (36 38). White matter and cerebrospinal fluid signals were regressed out. In addition, linear trend was also included as a regressor, since BOLD signal can demonstrate low-frequency drift. After that, all functional images were spatially normalized to the Montreal Neurologic Institute template, and each voxel was resampled to mm 3, and a spatial smoothing transformation was conducted with an 8-mm full-width half-maximum Gaussian kernel. Page 2 of 11

3 In the present study, the head translation movement of all participants was less than 1.5 mm, and the rotation was less than 1.5. Moreover, recommended by previous studies, the mean framewise displacement of head motion was computed and used as a covariate in all group functional voxel-wise analyses, which derived with Jenkinson relative root mean square algorithm and considered the voxel-wise differences in motion in its derivation (17,18,37). At baseline, the framewise displacement of patients and control subjects was mm ± and mm ± 0.018, respectively. At 1-year follow-up, the framewise displacement of patients and control subjects was mm ± and mm ± 0.03, respectively, and there was no group (ie, patients and control subjects) by time (ie, baseline and 1-year follow-up) interaction (P =.444), main effect of group (P =.44), or main effect of time (P =.581). ALFF Calculation ALFF was calculated by using Data Processing Assistant for Resting-State fmr imaging (DPARSF) software (15). ALFF is proportional to the strength or intensity of low-frequency oscillations and is thought to reflect spontaneous neural activity (6). In brief, after the preprocessing that was previously mentioned, the time series for each voxel was transformed to the frequency domain without band-pass filtering, and the power spectrum was obtained. Then, the power spectrum was square root transformed and averaged across Hz at each voxel. The averaged square root of power in this frequency band was taken as the ALFF (15). Then, with the standardization procedure, the individual ALFF map was normalized by the individual s global mean ALFF; more specifically, the mean across voxels for ALFF map was calculated, and the value at each voxel was divided by the mean individually. FC Analysis Page 3 of 11

4 By focusing on connectivity with regions in which group-by-time interaction in regional ALFF was observed, we proceeded in a hypothesis-driven manner to test for altered FC with broader brain circuitry specifically involving regions in which altered regional activity was demonstrated. FC was examined by using a seed voxel correlation approach to establish the circuitry implications of the alterations in regional function. After band-pass filtering ( Hz), a reference time series for each seed was extracted by averaging the rfmr imaging time series of voxels within each seed region. Pearson correlation analyses were performed between each seed time series and the filtered time series from brain voxels outside the seed regions in a voxel-wise manner. The correlation coefficients between the time course of seed regions and every other brain voxel were transformed to z values by using the Fisher r-to-z transformation to improve normality and facilitate statistical analysis. For the patients and control subjects groups at both time-points, individual z value maps of FC were analyzed with a random effect one-sample t test to identify voxels that showed significant positive and negative correlations to the time course of seed regions. The significance level for each group at each time point was set at uncorrected P <.001. For two-way analysis of variance with a repeated measures design that compared patients and control subjects over time, the FC comparison was restricted to voxels with significant positive or negative correlations in both patients and control subjects at baseline and 1-year follow-up by using an explicit mask from the union set of one-sample t test results of the two groups at both time points. References 1. Meyer-Lindenberg A. From maps to mechanisms through neuroimaging of schizophrenia. Nature 2010;468(7321): Page 4 of 11

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9 36. Friston KJ, Williams S, Howard R, Frackowiak RS, Turner R. Movement-related effects in fmri time-series. Magn Reson Med 1996;35(3): Yan CG, Cheung B, Kelly C, et al. A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. Neuroimage 2013;76: Satterthwaite TD, Elliott MA, Gerraty RT, et al. An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage 2013;64: Table E1. 95% CIs of the Difference in the Range of Values that Showed Significant Group-by-Time Interaction and Main Effects of Group or Time Value Patients and Controls at Patients at Baseline and Patients and Controls at Baseline Follow-up Follow-up ALFF Group-by-time interaction Right inferior parietal lobule 0.141, , Right orbitofrontal cortex 0.103, , Right occipital gyrus 0.162, , Main effect of group Right precuneus 0.366, , Right ventral medial PFC 0.222, , Left ventral medial PFC 0.215, , Left thalamus 0.123, , Right thalamus 0.088, , Right amygdala 0.152, , Left precuneus 0.151, , FC Page 9 of 11

10 Group-by-time interaction Between bilateral IPLs 0.004, , Main effect of group Between right OFC and right DM PFC 0.086, , Note. Data are 95% confidence intervals of the difference. Follow-up was performed at 1 year. DM = dorsal medial. Table E2. Shapiro-Wilk Test to Justify the Assumption of Normality of Values that Showed Significant Group-by-Time Interaction and Main Effects of Group or Time Value Statistic DF P Value. ALFF Group-by-time interaction Right inferior parietal lobule Right orbitofrontal cortex Right occipital gyrus Main effect of group Right precuneus * Right ventral medial PFC * Left ventral medial PFC <.001* Left thalamus <.001* Right thalamus * Right amygdala * Left precuneus FC Group-by-time interaction Page 10 of 11

11 Between bilateral IPLs Main effect of group Between right OFC and right DM PFC Note. Data are Shapiro-Wilk test results. DF = degree of freedom, DM = dorsal medial. * Data tested were not from a normally distributed population. Page 11 of 11