Zirun Wang¹, Martine Cleusix², Raoul Jenni², Philippe Conus³, Kim Q. Do², and Lijing Xin^1
1Animal imaging and technology core (AIT), Center for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ²Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, ³Service of General Psychiatry, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland

This study aims to investigate grey matter alterations in early psychosis patients (n = 44) compared to healthy control subjects (n=30). Morphometric analysis using MP2RAGE images at 7T. VBM did not reveal significant cluster after FWE (Family-Wise Error) corrections, but suggested grey matter reduction (uncorrected p<0.005) in the globus pallidus, right thalamus, left inferior temporal gyrus, left superior parietal, left paracentral lobule, left precuneus, right parietal lobe (postcentral gyrus) of patients compared to healthy subjects.

Emma Hiukka¹, Heta Helalari¹, Vesa Korhonen¹, and Vesa Kiviniemi^1
1Radiology, Oulu University, Oulu, Finland

The detection of functional alterations in psychotic subjects has proven to be a demanding task. In this study we used ultrafast fMRI to investigate physiological brain pulsations driving blood and CSF convection in psychotic brain. We detected dichotomized changes in opposing brain region pulsations between the upper frontal and lower posterior parts of the brain in all three major brain pulsations. The altered brain pulsations in psychotic brains may be connected to abnormal convection of metabolites via CSF and blood providing an physiological basis for the altered reality experiences in psychosis.

Marieke Van der Pluijm¹, Pascalle Nadine Reijers¹, Kenneth Wengler², Lieuwe De Haan¹, Jan Booij¹, Guillermo Horga², and Elsmarieke Van de Giessen^1
1Amsterdam UMC, Amsterdam, Netherlands, ²Columbia University Medical Center, New York, NY, United States

The current study assesses neuromelanin sensitive MRI (NM-MRI) as a potential biomarker for treatment resistance (TR) in first episode schizophrenia patients. NM-MRI is a novel MRI sequence, which indirectly measures dopamine synthesis. Research using positron emission tomography (PET) imaging suggest that TR patients show lower dopamine synthesis than responders. We acquired NM-MRI in 61 first episodes schizophrenia patients. Treatment response was determined during 6 months follow-up. TR patients showed significantly lower NM-MRI signal compared to responders. These findings are in line with previous PET studies and demonstrate the potential of NM-MRI as alternative and more accessible biomarker for TR.

Linnéa Andersson¹, Christoffer Rahm², Benny Liberg², Maria Ljungberg^1,3, and Isabella M. Björkman-Burtscher^4,5
1Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden, ²Department of Internal Medicine, Karolinska Institute, Stockholm, Sweden, ³Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, ⁴Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden, ⁵Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden

Fifty percent of all child sexual abuse (CSA) perpetrators are individuals with pedophilic disorder. The neural underpinnings of pedophilic disorder are unknown. We conducted a case-control study aiming to investigate functional connectivity alterations using independent component analysis on resting state fMRI data in search of biomarkers that can be used for preventing CSA. The results suggest there are functional connectivity alterations in several resting state networks in individuals with pedophilic disorder.

Faezeh Ghasemi^1,2, Hosna Tavakoli^3,4, Saeed Masoudnia ⁴, Narges Hoseini Tabatabaei⁵, Reza Rostami⁶, and Mohammad-Reza Nazem-Zadeh^4,7
1Medical Physics and Engineering, Shahid Beheshti University of Medical Sciences, Tehran, Iran (Islamic Republic of), ²Research Center for Biomedical Technologies and Robotics, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), ³cognitive neuroscience, Institute for Cognitive Science Studies, Tehran, Iran (Islamic Republic of), ⁴Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), ⁵Medical School, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), ⁶Department of Psychology, University of Tehran, Tehran, Iran (Islamic Republic of), ⁷Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of)

Accurate and specific diagnosis of mental disorders is very important for effective, customized, and personalized treatments, which would be made more possible based on individual neuroimaging data. In this study, we classified schizophrenia (SZ), bipolar disorder (BD), and attention deficit hyperactivity disorder (ADHD) cohorts, vs. healthy control (HC) cohort, using extracted graph features from Resting-State fMRI (rs-fMRI) images. The graph-based connectivity features of limbic, auditory, visual, and default mode networks were identified as the most separating features for the SZ, BD and, ADHD groups from the HC group among brain networks.

Jurjen Heij¹, Wietske van der Zwaag¹, Matthan W.A. Caan², Guido van Wingen³, and Moji Aghajani^4
1Spinoza Centre for Neuroimaging, Amsterdam, Netherlands, ²Department of Biomedical Engineering, Amsterdam UMC, Amsterdam, Netherlands, ³Department of Psychiatry, Amsterdam UMC, Amsterdam, Netherlands, ⁴Institute of Education and Child Studies, University of Leiden, Leiden, Netherlands

Large scale efforts are being employed to link Major Depressive Disorder (MDD) to cortical alterations in gray and white matter, though often, limited resolution prevents conclusions regarding the source. Here we used quantitative 7T MRI to explore the myeloarchitecture of the cortex in people suffering from MDD in order to unravel potential mechanisms underlying the psychopathology of MDD. We find altered T1-profiles in the rostral ACC, lateral PFC and OFC in MDD compared to healthy controls, indicating changes in cortical myeloarchitecture. Overall, cortical T1 values were higher in MDD, suggesting lower cortical myelination. 

Rouslan Sitnikov^1,2, Mikael Tiger³, and Johan Lundberg^3
1Neuroradiology, Karolinska University Hospital, Stockholm, Sweden, ²Clinical Neuroscience, MR Center, Karolinska Institutet, Stockholm, Sweden, ³Centre for Psychiatry Research, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden

Background:  The glutamate N-methyl-D-aspartate receptor antagonist ketamine has a rapid antidepressant effect in major depressive disorder (MDD) patients. Though, the ketamine's possible mechanism of action has been debated the main hypothesis was focused around glutamate.

Methods:  A proton short-echo MR Spectroscopy  was utilised to examined three brain regions Anterior Cingulate Cortex, Hippocampus and Raphe nuclei before and 24-hours after treatment. 28 Selective Serotonin Reuptake Inhibitor resistant MDD patients  were  randomized to double blind monotherapy with 0.5 mg/kg ketamine or placebo infusion.

Results:  glutamate correlates with depression symptoms severity in ACC and HC in opposing ways in ketamine group.

Xipeng Yue¹, Yan Bai¹, Ge Zhang¹, Yu Shen¹, Xianchang Zhang², and Meiyun Wang*^1
1Henan Provincial People’s Hospital, Zhengzhou, China, ²MR Collaboration, Siemens Healthineers Ltd., Beijing, China

Conventional static functional connectivity analysis does not capture transient and atypical changes in functional connectivity between neural networks in the autism spectrum disorder (ASD) patients. In this study, we evaluated rsfMRI data of 108 adult ASD patients by dynamic functional network connectivity (dFNC) analysis using sliding time window correlation and K-means clustering methods. Our results showed that higher dwell time and altered functional connectivity between multiple nodes in FNC state 2 correlated with clinical ASD scores. Therefore, our study demonstrates that aberrant and transient functional connectivity changes between neural networks in ASD patients can be evaluated by dFNC analysis.