Antonio Maria Chiarelli¹, Eleonora Patitucci², Hannah Chandler², Valentina Tomassini^1,3,4,5, Michael Germuska^2,6, and Richard Wise^1,2
1Department of Neuroscience, Imaging and Clinical Sciences, University G. D'Annunzio of Chieti Pescara, Chieti Scalo, Italy, ²CUBRIC, School of Psychology, Cardiff University, Cardiff, United Kingdom, ³Helen Durham Centre for Neuroinflammation, University Hospital of Wales, Cardiff, United Kingdom, ⁴MS Centre, Neurology Unit, “SS. Annunziata” University Hospital, Chieti, Italy, ⁵Division of Psychological Medicine and Clinical Neurosciences, University Hospital of Wales, Cardiff, United Kingdom, ⁶School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom

Dysfunction of energy supply or usage may be present in Multiple Sclerosis. We investigated the use of a simple oxygen diffusion model to infer mitochondrial oxygen tension from dual-calibrated fMRI (dc-fMRI) data. We observed a significant reduction of grey matter CBF and CMRO₂ in people with MS but no significant difference in OEF or BOLD-sensitive blood volume. Assuming no substantial tissue or vascular remodelling in MS, these results imply, within a simple flow-diffusion model of oxygen from capillaries into the tissue, an elevated partial pressure of oxygen at the mitochondria which may indicate mitochondrial dysfunction.

Geon-Ho Jahng¹, Kyung Mi Lee², Sang Tae Kim³, Soonchan Park¹, Sue Min Jung⁴, Hak Young Rhee⁵, Chang-Woo Ryu¹, and Eui Jong Kim^2
1Radiology, Kyung Hee University Hospital at Gangdong, Seoul, Korea, Republic of, ²Radiology, Kyung Hee University Hospital, Seoul, Korea, Republic of, ³Surgery & Neurology, Bundang Hospital, Seongnam city, Korea, Republic of, ⁴Biomedical Engineering, Kyung Hee University, Yongin-si, Korea, Republic of, ⁵Neurology, Kyung Hee University Hospital at Gangdong, Seoul, Korea, Republic of

To report the values of a battery of blood inflammatory biomarkers from cognitive normal (CN) to Alzheimer’s disease (AD) in our reasonably sized patient cohort and to evaluate the association between gray matter volume (GMV) loss in AD and plasma levels of blood biomarkers, we included 38 elderly CN elderly, 40 mild cognitive impairment (MCI), and 33 AD subjects and obtained blood biomarkers and GMV. We found that GMV was negatively associated with the levels of IL1b, P-tau, and T-tau. There were no significant associations between brain tissue volumes and the levels of mAβ, NLRP3, miR155, oAβ, and Nogo-A.

Caitlin F Fowler^1,2, Dana Goerzen², Gabriel A Devenyi^2,3, Dan Madularu⁴, M Mallar F Chakravarty^1,2,3, and Jamie Near^2,5
1Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada, ²Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada, ³Psychiatry, McGill University, Montreal, QC, Canada, ⁴Center for Translational Neuroimaging, Northeastern University, Boston, MA, United States, ⁵Physical Studies Research Platform, Sunnybrook Research Institute, Toronto, ON, Canada

Alzheimer’s disease is a progressive neurodegenerative disorder with a decades-long pre-symptomatic phase, substantiating the need for prodromal biomarker development and early intervention. We employed longitudinal magnetic resonance imaging and spectroscopy in conjunction with behavioural testing to characterize the chronological order of appearance and progression of multiple facets of disease pathology in the TgF344-AD rat model. The TgF344-AD rat demonstrated impaired spatial reference memory by 4 months of age, followed by neurochemical abnormalities by 10 months and major structural changes by 16 months, most of which recapitulated documented changes in brain structure and tissue chemistry in human Alzheimer’s disease patients. 

Xiuwei Fu¹, Yu Zhang², Tongtong Li², Yuanyuan Chen³, Xianchang Zhang⁴, and Hongyan Ni^5
1Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China, ²Department of Radiology, First Central Clinical institution, Tianjin Medical University, Tianjin, China, ³Institute of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China, ⁴MR Collaboration, Siemens Healthineers Ltd., Beijing, China, ⁵Department of Radiology, Tianjin First Central Hospital, Tianjin, China

This study investigated the changes in brain microstructure in patients with amnestic mild cognitive impairment (aMCI) using neurite orientation dispersion and density imaging (NODDI) combined with machine learning. Neurite density index (NDI) was significantly decreased in white matter, orientation dispersion index (ODI) was significantly decreased in gray matter, and volume fraction of isotropic water molecules (Viso) was significantly increased in the aMCI group. Further correlation and receiver operating characteristic (ROC) curve analyses showed NODDI may reflect the clinical cognitive status of aMCI. NODDI combined with a machine learning algorithm could be a promising alternative for early diagnosis of MCI.

Kiwamu Matsuoka^1,2, Kosei Hirata¹, Naomi Kokubo¹, Kenji Tagai¹, Hironobu Endo¹, Keisuke Takahata¹, Hitoshi Shinotoh¹, Maiko Ono¹, Chie Seki¹, Kazunori Kawamura³, Ming-Rong Zhang³, Hitoshi Shimada^1,4, Yuhei Takado¹, and Makoto Higuchi^1
1Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba-shi, Japan, ²Department of Psychiatry, Nara Medical University, Kashihara-shi, Japan, ³Department of Advanced Nuclear Medicine Sciences, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba-shi, Japan, ⁴Department of Functional Neurology & Neurosurgery, Center for Integrated Human Brain Science, Brain Research Institute, Niigata University, Niigata-shi, Japan

Glutamatergic neurons and cingulate cortices have crucial roles in the cognitive dysfunction of Alzheimer's disease (AD). This study aimed to evaluate regional vulnerabilities of the glutamatergic system in AD at the level of the cingulate gyrus in relation to tau and amyloid-β (Aβ) depositions. Combining MRSI and PET, we found that the glutamatergic system in the posterior cingulate cortex (PCC) is vulnerable to tau deposits but not Aβ from the early stage of AD, and glutamate in the PCC region may be a marker of disease progression in AD.

Siwei Liu¹, Xiao Luo², Yeerfan Jiaerken², Joanna Su Xian Chong¹, Hee Youn Shim¹, Minming Zhang², and Juan Helen Zhou^1
1National University of Singapore, Singapore, Singapore, ²Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

Subjective cognitive decline (SCD) is a risk factor for dementia. However, multiple pathologies, including amyloid deposition, cerebrovascular pathology, and depression, contribute to the heterogeneity in SCD. We included 170 non-demented elderly with 2-years follow-up to examine brain structural abnormalities in SCD. We found progressive and stable SCD individuals differed in deep white matter hyperintensities and temporoparietal grey matter atrophy. We used multi-model brain and behavioural factors to predict cognitive impairment and dementia progression. Periventricular white matter hyperintensities mediated the effect of amyloid accumulation on cognitive decline and disease severity, while depressive symptoms directly predicted disease severity.

Koichi Oshio¹, Masao Yui², Seiko Shimizu², Shinya Yamada^3,4, Madoka Nakajima⁴, Chihiro Akiba⁵, Hideki Bandai⁵, and Masakazu Miyajima^6
1Department of Radiology, Juntendo University, Tokyo, Japan, ²Canon Medical Systems Corporation, Otawara, Japan, ³Neurosurgery, Kugayama Hospital, Tokyo, Japan, ⁴Department of Neurosurgery, Juntendo University, Tokyo, Japan, ⁵Department of Neurosurgery, Juntendo Tokyo Koto Geriatric Medical Center, Tokyo, Japan, ⁶Department of Neurosurgery, Junterndo Tokyo Koto Geriatric Medical Center, Tokyo, Japan

A method to visualize possible waste clearance pathway in the brain was proposed earlier. The method is based on an assumption that there exist water containing macromolecules along the clearance pathway, and this water can be visualized using T2 component analysis. Preliminary results of this method applied for Alzheimer patients, as well as healthy volunteers, are presented. Distinct differences between the patients and healthy volunteers were observed. It is expected that this method can be a powerful tool for understanding the patho-physiology of the Alzheimer disease.

Yihan Wu^1,2, Huaying Cai³, Linhui Ni³, Guocan Han⁴, Zhiyong Zhao¹, and Dan Wu^1
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, Hangzhou, China, ²College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China, Hangzhou, China, ³Department of Neurology, Neuroscience Center, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China,, Hangzhou, China, ⁴Department of Radiology, Neuroscience Center, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China, Hangzhou, China

The present study aimed to explore functional and structural alterations in hippocampus and its subfields in post-stroke dementia (PSD). We collected resting-state fMRI and DTI data from 24 PSD patients, 36 post-stroke nondemented (PSND) patients and 21 normal controls (NC). Comparisons between groups found that PSD patients showed subfield-specific changes in the microstructures of hippocampus compared with the other two groups. Moreover, we not only found more PSD-related changes of functional connectivity with cortical regions in the subfields than entire hippocampus, but also revealed the different contributions of subfields on the connectivity changes of entire hippocampus.

Zhe Zhang^1,2, Chenyang Gao³, Wanlin Zhu^1,2, Yingkui Zhang^1,2, Qingle Kong⁴, Decai Tian³, Jing Jing^1,2, and Yongjun Wang^1,2,3
1Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, ²China National Clinical Research Center for Neurological Diseases, Beijing, China, ³Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, ⁴MR Collaboration, Siemens Healthineers Ltd., Beijing, China

Accurate visualization and evaluation of the MS lesions is an essential step for clinical practice. FLAWS-MP2RAGE has been proposed and applied at ultra-high field to better visualize both white matter and gray matter lesions. This work proposed the optimized method, tailored FLAWS(tFLAWS)-MP2RAGE, using a new image combination method for better lesion contrast. Results of MS patients showed higher lesion CNR of tFLAWS-MP2RAGE compared with conventional FLAWS-MP2RAGE and MPRAGE methods. This method might be a potential tool for lesion detection and evaluation at UHF for MS and other brain diseases.

Jiaxin Li¹, Yueqin Hu², Xue Feng ³, Weiying Dai⁴, Craig H. Meyer³, David C. Alsop⁵, and Li Zhao^1
1College of Biomedical Engineering & Instrument, Zhejiang University, Hangzhou, China, ²Psychology, Beijing Normal University, Beijing, China, ³Biomedical Engineering, University of Virginia, Charlottesville, VA, United States, ⁴Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, United States, ⁵Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States

Alzheimer’s disease (AD) may be caused by the dysfunction of glymphatic system, in which anatomic changes of the choroid plexus may be associated with reduced CSF production. Our previous work showed significantly increased choroid plexus volume in AD patients compared to healthy controls. However, contributions of the lateral ventricle volume were not investigated. Here, the lateral ventricle and choroid plexus were segmented using two cascaded deep learning models and the volumes were measured on 733 subjects. Increased lateral ventricle volume was found in AD patients, similar to previous studies. More importantly, choroid plexus volume showed a unique contribution to AD.

Wenli Li¹, Miao Zhang², Rong Guo^3,4, Yudu Li^3,4, Yibo Zhao^3,4, Jialin Hu¹, Yaoyu Zhang¹, Zhi-Pei Liang^3,4, and Yao Li^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, ³Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁴Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States

The default mode network (DMN) is the first large-scale system disrupted in Alzheimer’s disease (AD). However, the functional and metabolic changes in the DMN subsystems of AD patients are not yet fully understood. This study investigated the coupled functional and metabolic changes of the DMN subsystems by combining high-resolution 3D MRSI, resting-state fMRI, and ¹⁸F-FDG PET on a hybrid PET/MR scanner. Our results showed that the DMN subsystems have distinct functional and metabolic associations and contributions to cognitive decline in AD patients. Our findings may provide useful insights into the system-level pathophysiology of AD.

Natsuki Ikemitsu¹, Yuki Kanazawa², Akihiro Haga², Hiroaki Hayashi³, Yuki Matsumoto², and Masafumi Harada^2
1Graduate school of Health Science, Tokushima University, Tokushima, Japan, ²Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan, ³Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa, Japan

To classify healthy subjects or patients with Alzheimer's disease (AD) using three-dimensional T₁w data, we developed a machine learning system which can capture morphology features and determine atrophy of brain tissue in early-stage AD. Deep learning, a support vector machine (SVM), and 3D convolutional neural networks (3DCNN) were performed. The accuracies of SVM and deep learning based on volume values were comparable and greatly exceeded the accuracy of 3DCNN. It was found that atrophic features were more considerable than morphological features in early-stage AD.

Khazar Ahmadi¹, Joana B. Pereira^1,2, Danielle van Westen^1,3, Markus Nilsson⁴, Nicola Spotorno¹, and Oskar Hansson^1,5
1Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden, ²Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden, ³Diagnostic Radiology, Lund University, Lund, Sweden, ⁴Department of Medical Radiation Physics, Lund University, Lund, Sweden, ⁵Memory Clinic, Skåne University Hospital, Malmö, Sweden

Fixel-based analysis (FBA) enables investigation of micro- and macrostructural damage in white matter (WM) fiber bundles. However, the link between microscopic changes in fiber density (FD) and macroscopic morphological alterations in fiber cross-section (FC) with the pathological hallmarks of Alzheimer’s disease (AD) including regional tau and amyloid-β (Aβ) accumulation has not been explored yet. Here, we show that reduction in FC in the AD continuum is closely connected with tau tangles in contrast to Aβ pathology.

Fan Huang¹, Jonathan D. Rohrer², Hui Zhang³, and Martina Bocchetta^2
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom, ³Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, United Kingdom

Emma Muñoz-Moreno¹, Raul Tudela^2,3, Xavier López-Gil¹, and Guadalupe Soria^4,5
1Magnetic Resonance Imaging Core Facility, IDIBAPS, Barcelona, Spain, ²CIBER-BBN, Barcelona, Spain, ³Universitat de Barcelona, Barcelona, Spain, ⁴Laboratory of Surgical Neuroanatomy, Universitat de Barcelona, Barcelona, Spain, ⁵Institute of Neurosciences, Universitat de Barcelona, Barcelona, Spain

β-amyloid plaques and neuroinflammation, two of the pathological processes associated to Alzehimer's disease (AD) are not visible by conventional MRI. However, its presence may induce image changes that can be evaluated using texture analysis. We evaluated the potential of texture analysis of conventional MRI to characterize these changes. T2-weighted MRI of a transgenic rat model of AD were acquired and texture measures in hippocampus were correlated with inmunohistochemical quantification of plaques and microglia, showing significant correlation. Coherently, significant differences in the texture measures were found between transgenic and control animals, pointing to the potential of texture analysis as AD biomarker.