Yijun Leng^1,2, Xueling Liu², Daoying Geng^1,2,3, Fengtao Liu⁴, Pu-Yeh Wu⁵, Yuxin Li^2,3, and Liqin Yang^2,3
1Academy for Engineering & Technology, Fudan University, Shanghai, China, ²Department of Radiology, Huashan Hospital, Shanghai, China, ³Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China, ⁴Department of Neurology, Huashan Hospital, Shanghai, China, ⁵GE Healthcare, Beijing, China

For differential diagnosis between PD and atypical parkinsonisms, we designed a stratified automated method based on SVM and multi-modality MRI, including T1WI, QSM and DTI. 163 patients (96 PD, 27 MSA, 40 PSP) and 65 healthy controls were recruited. Features including volume, cortical thickness, magnetic susceptibility, FA and MD of 124 ROIs were calculated for SVM classification. The result showed that SVM classification based on susceptibility enabled accurate differentiation of patients with parkinsonian disorders and controls, and classification of PD, MSA and PSP was allowed by using T1 and DTI.

Song'an Shang¹, Weiqiang Dou², and Jingtao Wu^3
1Nanjing First Hospital, Nanjing Medical University, Nanjing, China, ²GE Healthcare, MR Research China, Beijing, China, ³Clinical Medical College, Yangzhou University, Yangzhou, China

Cognitive deficits are prominent non-motor symptoms in Parkinson’s disease (PD) and have been involved with neurovascular unit. However, sufficient neuroimaging studies are lacked investigating the associated modulating mechanisms. This study aimed to identify the contribution of neurovascular decoupling to the pathogenesis of cognitive decline in PD by integrating informative data obtained from the blood oxygen level-dependent and arterial-spin-labeling approaches. The involvement of neurovascular decoupling in cognitive impairment in PD is regionally specific and most prominent in the visual-spatial cortices, which could potentially provide a complementary understanding for the pathophysiological mechanisms underlying cognitive deficits in PD.

xiu Cheng¹, jun Wang¹, pengfei Zhang¹, jing Zhang¹, kai Ai², and wanjun Hu^1
1Lanzhou University Second Hospital, Lanzhou, China, ²Philips Healthcare, Xi'an, China

To investigate the structural and functional alterations of cerebellum in patients with Parkinson's disease (PD) using voxel-based morphometry and resting-state functional MRI. We analyzed alterations gray matter volume (GMV), regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF) in the cerebellum of PD patients. Furthermore, the correlation analysis between GMV, ALFF, ReHo values and clinical scale scores was performed. Our results showed that the structure and function of the cerebellum of PD patients are significantly different from healthy controls (HC), and these changes are significantly correlated with clinical scales scores, which suggested that the cerebellum plays an important role in PD.

Yu Shen¹, Yan Bai¹, Xianchang Zhang², Yaping Wu¹, Yu Luo¹, Zhun Huang¹, Xipeng Yue¹, Menghuan Zhang¹, and Meiyun Wang^1
1Henan Provincial People's Hospital, Zhengzhou, China, ²MR Collaboration, Siemens Healthineers Ltd, Beijing, China

Quantitative R1(1/T1) imaging has been proposed as surrogate imaging biomarkers for myelin content in cortical gray matter. This study, using high resolution T1 maps generated by MP2RAGE sequence, quantified gray matter myelin in Parkinson’s disease (PD) patients and compared the values with those in healthy controls. The results revealed that myelin (represented by R1) was significantly decreased in PD in several cortical and subcortical brain areas, which may be anatomic evidence for the spectrum of symptoms in PD, such as deficits of memory, mood, and cognition. Myelin quantification based on MP2RAGE-T1 mapping may be a valuable biomarker for characterizing PD.

Thomas Welton^1,2, Amadis Aliya Ong³, Septian Hartono^1,2, Yao-Chia Shih⁴, Amanda Lee³, Eng-King Tan^1,5, and Ling Ling Chan^1,3
1National Neuroscience Institute, Singapore, Singapore, ²Duke-NUS Graduate Medical School, Singapore, Singapore, ³Diagnostic Radiology, Singapore General Hospital, Singapore, Singapore, ⁴Graduate Institute of Medicine, Yuan Ze University, Taiwan, Taiwan, ⁵Neurology, Singapore General Hospital, Singapore, Singapore

Differential diagnosis of essential tremor and Parkinson’s disease can be challenging due to overlapping clinical presentations, but these diseases differ in neuropathological features, which may be detected using diffusion spectrum imaging. We identified parts of a tremor-related cerebello-thalamo-cortical network based on diffusion spectrum imaging that differed among a cohort comprising essential tremor and Parkinson’s patients, and healthy-controls. The patient groups had minimally-overlapping areas of abnormal microstructure in the tremor-network, and these were significantly correlated with clinical and kinetic measures of tremor severity. A future DSI-based marker of tremor-network microstructure may aid in differential diagnosis of essential tremor and Parkinson’s disease.

Jingwen Chen¹, Cheng Zhou¹, Jingjing Wu¹, Tao Guo¹, Xueqin Bai¹, Haoting Wu¹, Xiaocao Liu¹, Jiaqi Wen¹, Zhengye Cao¹, Yong Zhang², Xiaojun Guan¹, Xiaojun Xu¹, and Minming Zhang^1
1Radiology, The second affiliated hospital, Zhejiang University school of medicine, Hangzhou, China, ²GE Healthcare, Shanghai, China

It has been overlooked in clinical that there exists a complex relationship between laterality and motor symptoms in Parkinson’s disease (PD) and these factors may influence their motor and nonmotor symptoms in together. Here we found PD with left-side akinetic/rigid (L-AR) signs performed worst in clinical manifestations. And the underlying brain structure alterations was revealed severer damage in anterior cingulate and its connected fibers of right hemisphere by a multimodal imaging approach including cortical thickness and diffusion-weighted MRI measures. 

mingrui qu¹, bingbing gao¹, yuhan jiang¹, yangyingqiu liu¹, yuan li¹, qingwei song¹, and yanwei miao^1
1the First Affiliated Hospital of Dalian Medical University, Dalian, China

Cognitive impairment is very common in patients with Parkinson’s disease (PD). The amygdala in the limbic system of midbrain has been proved to play a unique role in cognitive function. However, there are almost no studies on changes in amygdala structure, especially the volume of amygdala subregions, in PD patients. In this study, automated volumetry of amygdala subregions in PD patients was performed and compared with healthy controls, and found that PD patients have amygdala subregions atrophy, especially in bilateral accessory basal nucleus, bilateral cortical nucleus and right medial nucleus.

Destaw Bayabil Mekbib¹, Weiying Dai², Miao Cai³, Xiaoli Liu³, and Li Zhao^1
1Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China, ²Computer Science, Binghamton Univeristy, State University of New York, Binghamton, NY, United States, ³Neurology, Zhejiang Hospital, Hangzhou, China

Resting-state fMRI plays an increasing role in understanding the neural mechanisms of Parkinson's disease (PD). However, neural network alterations, regional and global signal associations are not fully understood in PD patients. Here, we studied the whole-brain neural networks including the inter-network and their correlations with the global fluctuation in 37 PD patients and 20 healthy controls. Our findings revealed that the visual cortex had reduced neural network connectivity in PD patients and altered connections from default mode network to other networks. Weaker correlations were observed between the global signal and regional networks in the PD patients than healthy controls.

Xuanxuan Li¹, Yiping Lu¹, Pu-Yeh Wu², Tonggang Yu³, and Bo Yin^1
1Huashan Hospital, Fudan University, Shanghai, China, ²GE Healthcare, Beijing, China, ³Shanghai Gamma Hospital, Huashan Hospital, Fudan University, Shanghai, China

The aim of this study is to adopt machine learning and deep learning methods to predict the risk of post-GKS edema for meningiomas. 595 multicenter cases were included to train and validate 38 random survival forest (RSF) and DeepSurv models. The RSF model incorporating clinical, semantic, and ADC radiomic features achieved the best performance with a C-index of 0.861 in internal validation, and 0.780 in external validation. The derived nomogram had excellent discrimination and calibration. The proposed RSF model with a nomogram represents a non-invasive and cost-effective tool to predict post-GKS edema risks, thus facilitates personalized decision-making in meningioma treatment.

Jiaqi Wen¹, Xiaojun Guan¹, Tao Guo¹, Jingjing Wu¹, Xueqin Bai¹, Cheng Zhou¹, Haoting Wu¹, Xiaocao Liu¹, Jingwen Chen¹, Zhengye Cao¹, Yong Zhang², Luyan Gu³, Jiali Pu³, Baorong Zhang³, Minming Zhang¹, and Xiaojun Xu^1
1Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China, ²GE Healthcare, Shanghai, China, Shanghai, China, ³Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

In Parkinson’s disease (PD), nigral iron deposition exacerbates a-synuclein aggregation. In our study, we divided PD and normal controls (NC) into high iron group and normal iron group according to the median of nigral magnetic susceptibility of NC, respectively. ICA method was applied to separate brain large-scale networks. The PD*iron interaction effect on brain functional networks were investigated by mixed effect analysis. We found that PD disease status specifically moderates the effect of nigral iron deposition on the function of some regions in BGN and VN, which partially mediates the relationship between nigral iron deposition and disease severity.

Caixia Fu¹, Youmin Zhang², Qing Li³, Wei Liu¹, Naying He², Yu Liu², Daniel Polak⁴, E. Mark Haacke ⁵, and Fuhua Yan^2
1MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, ²Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, ³MR Collaborations, Siemens Healthineers Ltd., Shanghai, China, ⁴MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany, ⁵Department of Radiology, Wayne State University, Detroit, MI, United States

In this work, Wave-CAIPI accelerated 3D SWI has been used to achieve whole brain imaging in about 3min 30s. Both short-TE and long-TE protocols were compared for the detection of the Nigrosome-1(N1) sign. The phase-mask formula and number of phase mask multiplications were adjusted to explorer their influence on the contrast-to-noise (CNR) of the N1 sign relative to adjacent tissues. The result showed that long-TE protocol had better CNR and made it easier to recognize the N1 sign. The adjusted phase-mask formula with an increased number of phase mask multiplications also helped to improve the CNR of the N1 sign. 

Song'an Shang¹, Weiqiang Dou², and Jingtao Wu^3
1Nanjing First Hospital, Nanjing Medical University, Nanjing, China, ²GE Healthcare, MR Research China, Beijing, China, ³Clinical Medical College, Yangzhou University, Yangzhou, China

For Parkinson’s disease (PD), the time-varying properties of functional coherence and their coupling to regional perfusion are rarely elucidated. We aimed to investigate early disruption of dynamic regional homogeneity (dReho) pattern and neurovascular coupling (NC) in PD patients before onset of cognitive impairment and their classification performance. PD patients at early stage exhibited an impaired dynamic pattern of neuronal synchronization and disrupted NC. The features of CBF/dReho provided robust performance in differentiating PD from healthy controls. With this findings, the insights into early pathophysiological mechanism underlying PD from regional dynamic pattern and NC were reinforced.

Hui Huang¹, Siyu Yuan¹, Miao Zhang², Wei Liu³, Yibo Zhao^4,5, Rong Guo^4,5, Yudu Li^4,5, Lihong Tang¹, Zhi-Pei Liang^4,5, Yao Li¹, and Jie Luo^1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ²Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, ³Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, ⁴Department of Electrical and Computer Engineering, University of Illinois at Urbana Champaign, Urbana, IL, United States, ⁵Beckman Institute for Advanced Sciences and Technology, University of Illinois at Urbana Champaign, Urbana, IL, United States

Accurate detection of the epileptogenic zone for surgical planning often relies on stereo-electroencephalography, which is limited by low spatial sampling. Development of noninvasive brain high resolution imaging to better identify epileptogenic zone is of great value. This study aimed to investigate the imaging signature for detection of epileptogenic zones among features extracted from structural, functional, and metabolic imaging using hybrid PET/MR scanner. Our results highlighted the value of combination between metabolic and functional imaging features.   

Lekai Luo¹, Lizhou Chen¹, Qian Li¹, Ning He², Yuanyuan Li², Wanfang You¹, Yuxia Wang¹, Yaxuan Wang¹, John A. Sweeney^1,3, Lanting Guo², Qiyong Gong¹, and Fei Li^1
1Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, ²Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China, ³Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States

Sparse canonical correlation analysis (sCCA) was used to delineate multivariate relationship between dynamic functional connectivity (dFC) and behavior or cognition scores in a cohort of children with and without Attention-Deficit/Hyperactivity Disorder (ADHD). We identified four distinct patterns of dFC, each corresponded to a specific dimension of behavior (inattention/hyperactivity, somatization) or cognitive function (inhibition and flexibility, fluency and memory). Altered dFC within the default mode network (DMN) and between DMN and sensorimotor network (SMN) were common to all dimensions.