Xiaoyu Wang¹, Mengxuan Li¹, Miaomiao Wang¹, Congcong Liu¹, Xianjun Li¹, and Jian Yang^1
1Radiology, The first afflicted hospital of Xi'an Jiaotong University, Xi'an, China

Incidental white matter lesions (IWMLs) is a common disease in children with an incidence rate between 1.9% - 20%. Locating the brain lesions that might be related to the decline in verbal comprehension by overlapping lesion-associated networks can help define the possible response lesion. Our finding would help pediatricians to recognize the significant IWMLs that could potentially cause language delay in children. Thus, an early intervention can be applied to prevent the occurrence and progression of verbal comprehension decline in children.

Stefan Eggenreich¹, Lukas Pirpamer¹, Michael Khalil¹, Christian Enzinger¹, and Stefan Ropele^1
1Department of Neurology, Medical University of Graz, Graz, Austria

Various diffusion-based approaches were suggested for the characterization of lesional tissue in MS-patients. The multi-compartment spherical mean technique (SMT) has been proposed as a way to investigate microscopic diffusion properties in multiple water compartments. However, the potential of SMT for lesion characterization remains unclear. We investigated diffusion-based SMT properties in active and chronic lesions in 58 MS patients and related them to conventional diffusion tensor imaging (DTI). We found that SMT allows a more specific characterization of MS-lesions than DTI and provide evidence that SMT can be considered as a sensitive and robust measure for myelin content in MS patients.

Yangyingqiu Liu¹, Weiwei Wang¹, Yuhan Jiang¹, Ailian Liu¹, and Yanwei Miao^1
1Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China

Volume of hippocampal subfields in patients with type 2 diabetes mellitus(T2DM) was quantitatively assessed, and its’correlation to white matter hyperintensity (WMH) grade was also analyzed. The results show that the severity of WMH in T2DM patients may affect the atrophy of hippocampal subfields.

Huiru Li¹, Huawei Zhang¹, Li Yin², Zhiyun Jia¹, and Qiyong Gong^1
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan Universit, Chengdu, China, ²Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China

In this study, we used 5 machine learning algorithms with structural and diffusion MRI to classify suicidal risk in depressed patients and the best performance was acquired by support vector machine. In addition, the most important 10 features were most located in fronto-temporal–parietal regions. This study found a classification model using MRI data can help diagnosis and assess suicidal risk in depressed patients.

Bei Wang¹, Cen Guo², He Wang^1,3, Yan Han², and Ying-Hua Chu^4
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, ²Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China, ³Human Phenome Institute, Fudan University, Shanghai, China, ⁴MR Collaboration, Siemens Healthineers Ltd., Shanghai, China

With the help of 7T Imaging, we investigated the association between the thalamic anterior vascularization patterns and emotions, including depression and anxiety. Cerebral small vessel diseases were considered as a risk factor for emotional performance. The thalamic anterior vascularization pattern was found association with depression and anxiety in subjects without CSVD burden. In the CSVD group, the thalamic volume and cortex thickness in pars triangularis, rostral middle frontal and superior frontal were found significantly correlated with both HAMD and HAMA test scores. It suggests the pathway of the thalamus regulating emotion changes with the development of CSVD.

Weijie Bao¹, Lingxiao Cao¹, Ruohan Feng^1,2, Yingxue Gao¹, Hailong Li¹, Xinyue Hu¹, Hui Qiu¹, Kaili Liang¹, Zilin Zhou¹, and Xiaoqi Huang^1,3
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, ²Department of radiology, the Thrid Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China, Mianyang, China, ³Psychoradiology Research Unit of the Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, Sichuan, China, Chengdu, China

Evidence has emerged to suggest the important role of cortical gyrification morphology in adult major depressive disorder (MDD). However, little is known about how the altered cortical gyrification contribute to adolescent patients who is at a critical period of brain development. We address this gap by examining the difference of local gyrification index (LGI) between adolescent MDD patients and HCs. We found that MDD patients showed significant increased LGI in the left PCC and bilateral lingual gyrus, which characterize the neurobiological mechanisms of adolescent MDD and may be important to understand the developmental effect of this disorder.

Kun Qin¹, Du Lei², Ziyu Zhu², and Qiyong Gong^1
1West China Hospital of Sichuan University, Chengdu, China, ²University of Cincinnati College of Medicine, Cincinnati, OH, United States

Few previous studies considered brain network architecture when establishing machine learning models to identify major depressive disorder (MDD). Based on a large, multi-site dataset including 1586 participants, this study aimed to use novel graph convolution network (GCN) to distinguish MDD patients from controls, identify MDD subtypes and characterize related network disruption. We found that GCN enabled excellent classification performance of over 80% accuracy. Besides, shared and distinct disrupted network patterns were identified in first-episode drug-naive and recurrent patients. These findings support the feasibility and effectiveness of network-based GCN classier, illustrating the utility of GCN for detecting disrupted network topology.

Yagmur Karakus Aydos¹, Dicle Dovencioglu², Kader Karlı Oguz³, Pınar Ozdemir⁴, Melis Pehlivanturk Kızılkan⁵, Nuray Kanbur⁵, Dilek Unal¹, Kevser Nalbant¹, Fusun Cetin Cuhadaroglu¹, and Devrim Akdemir^1
1Child and Adolescent Psychiatry, Hacettepe University, Ankara, Turkey, ²Psychology, Middle East Technical University, Ankara, Turkey, ³Radiology, Hacettepe University& Bilkent University UMRAM, Ankara, Turkey, ⁴Bioistatistics, Hacettepe University, Ankara, Turkey, ⁵Adolescent Health, Hacettepe University, Ankara, Turkey

Body image disorder is the core symptom of Anorexia Nervosa (AN). Our research focuses on a group of adolescent patients diagnosed with AN to investigate neurobiological aspects of body image distortion, comparing the results with healthy control (HC) and major depression (MD) groups. We planned a block-design task in fMRI by using participants' original and distorted overweight and underweight images. We applied General Linear Models (GLM) for whole-brain analyses and examined correlations of the findings with behavioral data. As a result, AN patients differentiated when evaluating their underweight images. However, all adolescents had similar activations for overweight conditions. 

Shilong Tang¹ and Lisa Nie^2
1Children's Hospital of Chongqing Medical University, Chongqing, China, ²GE Healthcare, MR Research China, Beijing, Beijing, China

Purpose: To explore the application of quantitative magnetic resonance imaging in the diagnosis of autism in children. Methods:  All the children were scanned using head MRI conventional sequences, 3D-T1,DKI, ESWAN and 3D-pcASL sequences. The QSM, CBF and brain microstructure of each brain area were compared between the groups, and correlations were analyzed. Results: The frontal lobe, temporal lobe and hippocampal regions may be the first areas to show microstructural changes in autistic children . Conclusion: Quantitative magnetic resonance imaging can shows the abnormal changes of brain microstructural in children with autism .

Zibin Yang¹, Shu Xiao¹, Long Qian², and Ying Wang^1
1Medical Imaging Center, First Affiliated Hospital of Jinan, Guangzhou, China, ²GE Healthcare, Beijing, China, Beijing, China

Numerous neuroimaging studies have revealed abnormalities in specific brain regions in obsessive-compulsive disorder (OCD), but results have been inconsistent. We conducted a whole-brain voxel-wise meta-analysis on resting-state functional imaging and VBM studies between OCD patients and HCs by using Seed-based d Mapping (SDM) software. The meta-analysis demonstrated that OCD exhibits similar abnormalities in both function and structure in the prefrontal and insula. Few regions exhibited only functional or only structural abnormalities in OCD. These results expand the current understanding of functional and structural brain abnormalities in OCD patients, which would provide additional potential targets for therapeutic intervention.

Suming Zhang ¹, Xinyu Hu², Xuan Bu², Hailong Li¹, LingXiao Cao², Jing Liu², KaiLi Liang², Xue Li³, and Xiaoqi Huang^2
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu City, China, ²Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, ChengDu City, China, ³College of Physics, Sichuan University,Chengdu, China, Chengdu City, China

We investigated the alteration of white matter in obsessive compulsive disorder from voxel-level, tractography-level and connectome-level by combining analysis of TBSS, AFQ and graph theory. TBSS and AFQ revealed widespread changes in WM.  Network-based statistic (NBS) analysis demonstrated decreased structural connectivity in patients mainly comprising frontal, temporal, limbic areas, which belong to DMN, FPN, limbic, SMN and VAN network. Along with regions commonly described in the CSTC model of pathophysiology, our results indicate an involvement of white matter in frontal-temporal and limbic regions to differentiate OCD patients and healthy controls, supporting their importance for neurobiological alterations in OCD.

Qikai Qin^1,2, Miao Zhang³, Biao Li^3,4, and Garth John Thompson^1
1iHuman Institute, ShanghaiTech University, Shanghai, China, ²School of Life Science and Technology, ShanghaiTech University, Shanghai, China, ³Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, ⁴Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Ruijin Center, Shanghai, China

Locating epileptic foci is critical for surgery in drug-resistant epilepsy. However, conventional methods (MRI, PET, SEEG) often cannot provide sufficient information alone. We have developed a new method, relative oxygen-glucose index (OGI), based on simultaneous PET and calibrated fMRI, which we used as a biomarker to locate epileptic foci during inter-ictal period. Relative OGI reflects aerobic glycolysis relative to global levels, which is useful as many diseases are characterized by metabolic pathway alterations. In this study, we not only demonstrate its potential in foci localization in epilepsy, but also distinguish temporal-lobe and extra-temporal-lobe epilepsy based on their different pathogenesis.

Yucai Bai¹, Jian LI¹, Xiaocheng Wei², Yaoxing Ma¹, and Bing Chen^1
1General Hospital of Ningxia Medical University, Ningxia yinchuan, China, ²GE Healthcare, Beijing, China

The purpose of this study is to explore the value of different quantitative parameters derived from Synthetic MRI and combined with DWI in the diagnosis of hippocampal sclerosis. It was concluded that the values of T1, T2 and ADC in the hippocampal sclerosis were significantly higher than those in the normal control group .In addition, the AUC of the combined model of T2 and ADC was 0.96, which was higher than that of ADC (AUC 0.884) or T2 alone (AUC 0.952). Its sensitivity, specificity, positive predictive value and negative predictive value were 0.95,0.91,0.81,0.98 respectively.

Yizhi Yuan^1,2, Yuting Wang^2,3, Jingping Mou³, Lan Mei^2,3, Chunyang Liu³, and Lihua Qiu^1,2,3
1Department of Radiology, Chengdu Medical College, Chengdu, China, ²Department of Radiology, The Second People’s Hospital of Yibin, Yibin, China, ³Department of Radiology, Southwest Medical University, Luzhou, China

Dynamic functional connectivity (dFC) is a newly developed analysis strategies which could provide novel understandings of the pathophysiological mechanisms of neuropsychiatric disease. 45 adolescents diagnosed with IGE and 32 well-matched healthy controls completed this study using dynamic functional connectivity (dFC). The decreased dFC between two seed regions(MCC and ParaHipp) and PCC and IPL were part of default mode network(DMN). The impaired DMN in adolescent IGE patients suggest dFC might be more sensitive to reflect the changes of brain function in the early stage of disease and dFC analysis was a promising avenue to deepen our understanding of this disease. 

Robert Elton Smith^1,2, Eric Pierre¹, Graeme Jackson^1,2,3, and David Vaughan^1,2,4
1Florey Institute of Neuroscience & Mental Health, Heidelberg, Australia, ²Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Australia, ³Department of Medicine, Austin Health, Heidelberg, Australia, ⁴Department of Neurology, Austin Health, Heidelberg, Australia

We evaluate the utility of a recently-proposed method tailored for the removal of Gibbs ringing artifacts in 3D MRI data, by applying it to high-resolution isotropic T2-weighted data acquired during the Australian Epilepsy Project (AEP) pilot. The filter is highly effective at removing this known artifact whilst preserving pathological detail. We therefore encourage its uptake in not only the radiological assessment of the Epilepsies, but any 3D imaging context where the manifestation of Gibbs ringing may be detrimental. 

William Tackett¹, Dawn Mechanic-Hamilton¹, Sandhitsu Das², Kathryn Davis¹, and John Detre^1,2
1Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States, ²Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

Surgery to treat mesial temporal lobe epilepsy (TLE) offers freedom from seizures but risks postsurgical memory decline. Lateralizing memory function is essential for mitigating the risk of resecting “eloquent” cortex. Memory laterality has traditionally been assessed using the Wada test, but it is invasive and poses its own risks. The noninvasive method of functional magnetic resonance imaging (fMRI) has become a possible alternative. However, questions remain about fMRI’s reliability in lateralizing memory. Our group has shown that a scene memory task is capable of activating hippocampus and lateralizing memory function. Here, we present an improved version of that experimental paradigm.