Metabolic dysfunction and microvascular abnormality may contribute to the pathogenesis of schizophrenia. Most previous studies of cerebral perfusion in schizophrenia measured total cerebral blood volume (CBV) and cerebral blood flow (CBF) in the brain, which reflect the ensemble signal from the arteriolar, capillary, and venular compartments of the microvasculature. As the arterioles are the most actively regulated blood vessels among these compartments, they may be the most sensitive component of the microvasculature to metabolic disturbances. In this study, we adopted the inflow-based vascular-space-occupancy (iVASO) MRI approach to investigate alterations in the volume of small arterial (pial) and arteriolar vessels (arteriolar cerebral blood volume [CBVa]) in the brain of schizophrenia patients. The iVASO approach was extended to 3-dimensional (3D) whole brain coverage, and CBVa was measured in the brains of 12 schizophrenia patients and 12 matched controls at ultra-high magnetic field (7T). Significant reduction in grey matter (GM) CBVa was found in multiple areas across the whole brain in patients (relative changes of 14%-51% and effect sizes of 0.7-2.3). GM CBVa values in several regions in the temporal cortex showed significant negative correlations with disease duration in patients. GM CBVa increase was also found in a few brain regions. Our results imply that microvascular abnormality may play a role in schizophrenia, and suggest GM CBVa as a potential marker for the disease. Further investigation is needed to elucidate whether such effects are due to primary vascular impairment or secondary to other causes, such as metabolic dysfunction.

No abstract

Contributors Jun Hua conducted data collection, data analysis and interpretation, drafting of the article, revision of the article, and final approval. Nicholas I.S. Blair conducted the functional MRI data analysis. Adrian Paez contributed to data analysis and revision of the article. Ann Choe contributed to data interpretation and revision of the article. Anita D. Barber contributed to data interpretation and revision of the article. Allison Brandt contributed to the collection and analysis of the clinical data, and revision of the article. Issel Anne L. Lim contributed to data collection. Feng Xu contributed to data interpretation and revision of the article. Vidyulata Kamath contributed to data interpretation and revision of the article. James J. Pekar contributed to study design, data interpretation and revision of the article. Peter C.M. van Zijl contributed to study design, data interpretation, and revision of the article. Christopher A. Ross contributed to study design, data interpretation, and revision of the article. Russell L. Margolis contributed to study design, data analysis and interpretation, drafting of the article, revision of the article, and final approval. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Conflict of interest Equipment used in the study was manufactured by Philips. Peter C.M. van Zijl receives grant support from Philips, is a paid lecturer for Philips, and is the inventor of technology that is licensed to Philips. This arrangement has been approved by Johns Hopkins in accordance with its conflict of interest policies.

W ith MRI, magnetic susceptibility effects can cause significant image artifacts such as signal reduction and image distortion, especially when using echo-planar imaging (EPI). Such susceptibility artifacts are commonly seen in the presence of metallic objects. Dental fillings and orthodontic braces containing various metals can cause large artifacts extending from the facial region into the brain at EPI (1-3). Orthodontic treatments have become increasingly accessible and are commonly performed in the United States and around the world (see https://www.aaoinfo.org). Furthermore, susceptibility artifacts often affect patients undergoing MRI examinations (4,5), especially in regions close to surgical resection cavities, calcified structures, hemorrhages,

BackgroundThe thalamus, a critical node in which multiple cerebral circuits converge, is organized into multiple subnuclei, classified as either first-order (receiving peripheral sensory input) or higher-order (receiving input primarily from the cortex). Higher-order nuclei are of particular salience in psychotic disorders, as they appear to control cortico-cortical information transmission, possibly through regulation of neuronal synchrony. Substantial evidence has demonstrated abnormalities of thalamo-cortical connectivity in schizophrenia, generally with hyperconnectivity with sensorimotor and temporal cortices and hypoconnectivity with frontal regions. We took advantage of the spatial resolution of 7T (voxels of 3.375 mm3 vs 27 mm3 at 3T) to preliminarily assess resting state connectivity between specific thalamic nuclei and cortical regions in schizophrenia.MethodsResting state fMRI scans were obtained for 14 SCZ patients (mean age 39.5, mean disease duration 18.8 years) and 14 matched controls (smoking, age, sex) using a Phillps 7T imaging system, with GRE EPI (TR/TE/FA=2000/22ms/60º, voxel=2.5mm iso, 54 slices, 7min. Data analysis was carried out with SPM8 / Matlab6. Preprocessing included realignment, slice time correction, co-registration, segmentation, normalization; nuisance removal (CompCor), regression of global mean and motion parameters; spatially smoothing (5mm kernel) and temporal filtering (0.01-0.1Hz). Seed-based analysis was carried out using thalamic sub-regions as described in the Oxford Thalamic Connectivity Atlas (seven regions based on anatomic connectivity rather than histology), and whole brain connectivity maps (z values) to each seed were calculated. Second-level t-tests were performed to examine differential connectivity between SCZ patients and controls (thresholded at a voxel-level of p<.001 and multiple-comparisons corrected at a cluster-level threshold of p<.05). Effect size was estimated with Cohen’s d. The IBASPM116 atlas was used to identify anatomical regions within the significant clusters.ResultsBoth reduced and enhanced functional connectivity between the thalamus and multiple brain regions were observed. Statistically significant differences between scz and controls were detected in 47 regions, with particularly strong differences between scz and control in thalamo-temporal cortex connectivity, consistent with previous results at 3T. The same analysis was performed but with seeds placed in each of the seven thalamic subregions defined by the Oxford thalamic connectivity atlas. Enhanced connectivity was observed between all thalamic sub-regions and the motor cortex. Enhanced connectivity to the temporal cortex was detected in several thalamic sub-regions, but not sub-region 7, which has the highest anatomical connection probability in controls. Reduced functional connectivity in SCZ was detected between thalamic sub-regions 4, 6, and 7, and prefrontal and cingulate cortex.DiscussionOur results provide preliminary evidence of changes in resting state thalamo-cortica...