| Computer # |
| 4183.
 | 17 | Motor and Cognitive Deficits Accompanied by Progressive Microstructural and Metabolic Deterioration in a Mouse Model of Parkinson’s Disease Ting-Chieh Chen1, Ssu-Ju Li1, Yu-Chun Lo2, Yi-Chen Lin1, Ching-Wen Chang1, Yao-Wen Liang1, Yun-Ting Liu1, Yi-Chun Lee3, Kai-Yun Chen2, and You-Yin Chen1,2
1Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan, 2PhD Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan, 3School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan Keywords: Parkinson's Disease, Parkinson's Disease Motivation: The MitoPark mouse model, induced by mitochondrial dysfunction, has been confirmed to exhibit both motor and cognitive impairments resembling Parkinson's disease. However, further research is needed to delve into the mechanisms underlying these changes. Goal(s): Ｗe aimed to explore age-related changes in behavioral performances, brain microstructure, and metabolic functions in MitoPark mice. Approach: Every four weeks, a battery of tests including behavioral assessments, DTI scanning, and respiratory assays were performed on 8-week-old experimental mice. Results: MitoPark mice showed progressive degeneration in both motor and cognitive functions and impairments of microstructure and energy metabolism in dopaminergic pathways with increasing age. Impact: Progressively deteriorating mitochondrial respiration and glycolysis, impaired neural integrity, and demyelination in dopaminergic pathways in MitoPark mice may provide potential mechanisms underlying motor and non-motor deficits during the aging process of Parkinson's disease. |
| 4184.
 | 18 | Superior cerebellar peduncle diffusivity differentiates progressive supranuclear palsy from other parkinsonian syndromes Jason Langley1, Kristy Hwang2, Amanda Goodwin3, Kelsey Tucker3, Xiaoping Hu1,4, and Daniel Huddleston3
1Center for Advanced Neuroimaging, University of California Riverside, Riverside, CA, United States, 2Long Beach VA, Long Beach, CA, United States, 3Department of Neurology, Emory University, Atlanta, GA, United States, 4Department of Bioengineering, University of California Riverside, Riverside, CA, United States Keywords: Parkinson's Disease, Parkinson's Disease, cerebellum Motivation: Overlapping clinical symptoms make differential diagnosis of typical and atypical parkinsonian syndromes difficult in the early stages of these diseases. Goal(s): Our goal was to assess atrophy in the superior cerebellar peduncle in progressive supranuclear palsy. Approach: A high-resolution DTI (voxel size=1.1×1.1×1.1 mm3) was used to derive diffusion metrics in the super cerebellar peduncle in a population of typical and atypical parkinsonian syndromes. Results: Application of this protocol found measures consistent with superior cerebellar peduncle atrophy (increased MD, decreased FA) in the progressive supranuclear palsy relative to the Parkinson’s disease and multiple systems atrophy- with predominant parkinsonian features groups. Impact: Overlapping clinical features makes differential diagnosis of
progressive supranuclear palsy from other parkinsonian syndromes difficult in
the early stages of these diseases. Our demonstration of superior cerebellar
peduncle atrophy in progressive supranuclear palsy suggests imaging markers may
aid differential diagnosis. |
| 4185.
 | 19 | Exploring the discrepancy of hippocampal subfield vulnerability and connectivity pattern between cognitive decline in PD and MCI patients Na Wang1, Pu-Yeh Wu2, and Xueling Liu1
1Radiology, Huashan Hospital, Fudan University, Shanghai, China, 2GE Healthcare, Beijing, China Keywords: Parkinson's Disease, Parkinson's Disease Motivation: Different vulnerabilities of hippocampal subfields in PD and MCI have been reported. Goal(s): To explore the discrepancy of hippocampal subfield atrophy and its FC pattern in HC, PDNCI, PDMCI, and MCI patients.
Approach: Volume of hippocampal subfields, and FC between impaired subfields and cortical regions were calculated to assess group differences. Results: PD groups had reduced volumes in CA2/3, CA4, and GC-DG subfields and increased FC in the visual network.MCI group exhibited decreased right CA4 volume and increased FC in the widespread visual network.PDMCI displayed enhanced FC in the DMN compared to PDNCI and decreased FC in the visual network relative to MCI. Impact: As cognitive decline advances in PD, FC alterations are prominent between the GC-DG+CA4 subfield and the DMN. Smaller hippocampal subfield and its widespread FC abnormalities in MCI relative to PDMCI may underscore the different progression mechanisms of the two diseases. |
| 4186.
 | 20 | Alterations in Static and Dynamic Functional Brain Connectivity in Drug-naïve Patients with Early Parkinson’s Disease Wenliang Fan1 and Fan Yang1
1Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China Keywords: Parkinson's Disease, fMRI (resting state), Brain Motivation: Long-term levodopa treatment can markedly change the brain connectivity network in Parkinson's disease(PD) patients. The changes of static and dynamic brain network in early PD remain unknown. Goal(s): To investigate the alterations in static and dynamic whole-brain connectivity in early PD patients who have never received dopaminergic therapy. Approach: A case-control study was performed. The static and dynamic functional connectivity were constructed and analysised. Results: PD patients showed alterations in the SMN, DGN, LBN, and VSN, which may be relevant to both motor and non-motor symptoms. LEiDA results showed that PD group displayed a shorter lifetime and lower probability than the HC group. Impact: The study offers neuroimaging evidence of static and dynamic brain functional connectivity changes in drug-naïve early Parkinson's disease patients. It identifies potential biomarkers for clinical Parkinson’s disease diagnosis and assessment. |
| 4187.
 | 21 | Millimetres Matter - Improving registration of DBS MRI using deep learning Sriranga Kashyap1, Jürgen Germann1,2,3, and Kâmil Uludağ1,4,5
1Krembil Brain Institute, University Health Network, Toronto, ON, Canada, 2Division of Neurosurgery, Toronto Western Hospital, Toronto, ON, Canada, 3Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, Canada, 4Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 5Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, Korea, Republic of Keywords: Parkinson's Disease, Software Tools Motivation: Precise electrode localisation in DBS surgery determines success or failure of neurostimulation and associated side-effects. Brainshift and electrode artefacts in post-op MRI complicate registration to pre-op data, impacting the study of immediate and longitudinal clinical outcomes.
Goal(s): To develop a new DBS MRI registration framework using deep learning and advanced image processing to overcome limitations of current approaches and improve registration. Approach: Post-op MRI is preprocessed to ameliorate artefacts and an artefact-free image is synthesised using deep learning and super resolution, followed by optimised non-linear registration. Results: Proposed method demonstrably outperforms standard approaches, reducing errors near electrodes and improved matching of brain regions. Impact: This work transforms DBS neuroimage processing offering a means for much improved electrode localisation and assessment of DBS outcomes. It's a promising step towards improved patient care and clinical success. Public availability of our tools will benefit the neuroimaging community. |
| 4188.
 | 22 | Investigating the Impact of Subthalamic Nucleus DBS Frequency on Motor Networks in Parkinson's Disease: An fMRI Study Anupa A Vijayakumari1, Jay L Alberts1, Benjamin L Walter1, Amber Rothe1, Sara Davidson1, Darrin Rothe2, Mark J Lowe1, and Pallab Bhattacharyya1
1Cleveland Clinic, Cleveland, OH, United States, 2Milwaukee School of Engineering, Milwaukee, WI, United States Keywords: Parkinson's Disease, Parkinson's Disease Motivation: Limited information is available on the impact of different deep brain stimulation (DBS) frequencies on motor task-related brain activity in Parkinson's disease (PD) patients with DBS implants in the subthalamic nucleus (STN). Goal(s): To investigate DBS frequency effects on brain activity during a motor task (force-tracking, FT). Approach: Using fMRI, we assessed FT-task-related brain activity in four PD patients with STN-DBS under three DBS conditions: off, high-frequency, and low-frequency. MDS-UPDRS-III scores measured motor impairment. Results: High-frequency DBS increased brain activation during FT and reduced MDS-UPDRS-III scores in PD patients compared to low-frequency DBS and DBS-off. Impact: These findings suggest that DBS in the STN has the potential to disrupt abnormal neural activations and restore the brain's capacity to generate and regulate normal patterns that are compromised in PD. |
| 4189.
 | 23 | Imaging α-synuclein protein aggregation by CEST-MRI for monitoring of synucleinopathies Julien Flament1, Alexis Fenyi1, Luc Bousset1, and Ronald Melki1
1Université Paris-Saclay, CEA, CNRS, MIRCen, Laboratoire des Maladies Neurodégénératives, Fontenay-aux-Roses, France, Fontenay-aux-Roses, France Keywords: Parkinson's Disease, CEST & MT Motivation: Misfolded proteins that aggregate in the brain are at the root of many neurodegenerative diseases. Goal(s): Our aim was to demonstrate that CEST can distinguish between soluble and aggregated forms, and that it is possible to monitor them in vivo. Approach: We optimized a CEST sequence in vitro on purified forms of α-synuclein and then injected them into the brain of mice to follow their propagation. Results: The CEST signal differ strongly depending on the protein conformation, and longitudinal tracking has enabled us to show that protein aggregates propagate in the brain on a scale of several months. Impact: CEST
imaging can distinguish proteins in soluble or aggregated form that are at the
root of many neurodegenerative diseases, making it possible to envisage CEST
imaging as a non-invasive diagnostic tool for these diseases. |
| 4190.
 | 24 | Loss of Neuromelanin in Parkinson’s Disease Correlates with Increased Iron Content within the Substantia Nigra Naying He1, Ying Wang2, Yida Wang3, Peng Wu4, Youmin Zhang1, Xinhui Wang1, Guang Yang3, Fuhua Yan1,5, and Ewart Mark Haacke1,6
1Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 2Radiology, Wayne State University, Detroit, MI, United States, 3Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China, 4Philips Healthcare, Shanghai, China, 5Faculty of Medical Imaging Technology, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China, 6Department of Biomedical Engineering, Wayne State University, Detroit, MI, United States Keywords: Parkinson's Disease, Parkinson's Disease, Neuromelanin MRI Motivation: Neuromelanin (NM) changes with iron content in the substantia nigra (SN) could provide a better understanding of the pathophysiology of PD. Goal(s): To evaluate changes in NM volume in the SN versus iron as a means of understanding NM degeneration and iron deposition in PD. Approach: We evaluated 342 healthy controls (HCs) and 558 PD patients with two different resolution datasets (Cohort 1 and 2) using magnetization transfer contrast imaging. Results: Both datasets show HCs with reasonable stable NM volumes in SN while the PD patients show a significant iron increase in the SN with loss of NM volume. Impact: A loss of NM volume with an increase of iron within SN demonstrates the association between NM depigmentation and iron elevation in PD, which provides insight into the role of NM and iron underlying PD pathophysiology. |
| 4191.
 | 25 | Quantitative N-Acetylaspartate and Creatine Metabolites in Cortical and Subcortical Regions in PD patients with cognitive impairment Ming ming Huang1, Hui Yu1, Xin yue Lv1, Kai AI2, Yong Jun Cheng3, and Bo Gao1
1Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang, China, 2Department of Clinical and Technical Support, Philips Healthcare, Xi'an, China, 3Department of Clinical and Technical Support, Philips Healthcare, Shanghai, China Keywords: Parkinson's Disease, Metabolism Motivation: N-acetylaspartate (NAA) and creatine (Cr) are two brain metabolites implicated in neuronal functions. The potential role of MRS as in vivo molecular imaging biomarker is controversial. Goal(s): Quantitative the concentration of NAA and tCr of posterior cingulate gyrus (PCC) and Thalamus (Tha) in Parkinson’s disease patients with (PDCI) and without mild cognitive impairment (PDN). Approach: Single voxel 1H-MRS technology combined with Lcmodel software were used. Results: Patients with PDCI showed significantly reduced concentrations of NAA and tCr both in PCC and left Tha regions. Both in PCC and left Tha, the reduction of NAA accompanying with decreasing of tCr. Impact: Comparison of PCC and Tha MRS profiles across cognitive impairment provides useful information for tracking cognitive decline in PD progress. Cortical (via PCC) and subcortical (via Tha) NAA and tCr are promising biomarkers in characterizing PD cognitive stage deficits. |
| 4192.
 | 26 | Radiomic features of substantia nigra based on multi-echo SWI susceptibility map can distinguish PD from atypical Parkinson syndrome Weiling Cheng1, Jiankun Dai2, and Fuqing Zhou1
1Department of Radiology, The First Affiliated Hospital, Nanchang University, Nanchang, China, 2MRI research, GE Healthcare, Beijing, China Keywords: Parkinson's Disease, Parkinson's Disease, atypical Parkinson syndrome, substantia nigra, susceptibility weighted imaging，radiomics Motivation: The ‘swallow tail’ sign (STS) of substantia nigra (SN) on SWI can distinguish PD from healthy subjects. However, it’s difficult to differentiate PD from APS by visually inspect the STS.
Goal(s): Discriminating PD from APS using the radiomic features of SN extracted from multi-echo SWI susceptibility map. Approach: 63 PD, 38 APS and 89 healthy controls were enrolled. Five classification models using radiomic features of SN were used and compared. Results: The size, shape, and texture characteristics of SN are the most important features, and
the light gradient-boosting machine model (LGBM) had the best performance in identifying PD, APS, and healthy subjects. Impact: PD and APS have similar clinical syndrome but were treated
differently. Our finding suggested LGBM based on radiomic features of SN can
differentiate PD from APS with high accuracy. It would help the treatment selection
for PD and APS patients. |
| 4193.
 | 27 | Genetic mechanisms underlying gray matter atrophy in Parkinson’s disease: a combined transcriptome and neuroimaging study Yi Ji1 and Xiangming Fang1
1The Affiliated Wuxi People's Hospital of Nanjing Medical University, WuXi, China Keywords: Parkinson's Disease, Neurodegeneration Motivation: Extensive research has shown prominent gray matter atrophy in patients with Parkinson's disease, yet its genetic mechanisms are largely unknown. Goal(s): We aimed to investigate the genetic mechanisms underlying gray matter atrophy in PD. Approach: We performed a comprehensive neuroimaging meta-analysis along with an independent dataset analysis. Utilizing the Allen Human Brain Atlas, we performed spatial association analyses linking transcriptome data to neuroimaging findings, along with gene functional feature analyses for the identified genes. Results: Our findings suggest that prominent gray matter atrophy in PD may be a consequence of intricate interactions among a diverse set of genes with various functional features. Impact: Our findings may offer unique insights into the genetic mechanisms underlying brain gray matter atrophy in Parkinson’s Disease through bridging the gap between microscale molecular function and macroscale brain architecture. |
| 4194.
 | 28 | 7 Tesla MRI in routine surgical planning for Deep Brain Stimulation for Parkinson’s Disease Matthijs H.S. de Buck1,2,3, Wietske van der Zwaag1,2, Yarit Wiggerts4, Niels Rijks4, Liza Afzali-Hashemi3, Matthan W.A. Caan5, Rob M.A. de Bie6, Pepijn van den Munckhof4, P. Richard Schuurman4, and Maarten Bot4
1Spinoza Centre for Neuroimaging, Amsterdam, Netherlands, 2Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, KNAW, Amsterdam, Netherlands, 3Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands, 4Department of Neurosurgery, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands, 5Department of Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands, 6Department of Neurology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands Keywords: Parkinson's Disease, Parkinson's Disease, Deep Brain Stimulation; Subthalamic Nucleus; Ultra-High Field MRI Motivation: Identifying the dorsolateral subthalamic nucleus (STN) for deep brain stimulation (DBS) in Parkinson’s disease (PD) can be challenging due to the size and double-oblique orientation. Goal(s): To evaluate the influence of 7T T2w-TSE and probabilistic tractography on STN target planning, micro-electrode recordings and motor improvement. Approach: We describe the implementation of 7T T2w-TSE and probabilistic tractography in 182 PD patients undergoing STN DBS at our centre from 2015-2022. Results: Implementation of 7T T2w-TSE for STN DBS enabled a refinement in targeting which can be used as basis for adding probabilistic subthalamic connectivity, in order to enhance clinical outcome of STN DBS. Impact: The extensive evaluation of 360 STNs has not been described previously and shows 7T T2w-TSE and probabilistic tractography can refine STN targeting and surgical efficiency in DBS for PD. |
| 4195.
 | 29 | The role of glymphatic system dysfunction in multiple system atrophy and its impact on disease-related pathological changes Boyu Chen1, Nana Zhang1,2, Yueluan Jiang3, Guoguang Fan MD，PhD1, Shenxia Zhang1, and Yuzi Fan Wang4
1Radiology, The First Hospital of China Medical University, Shenyang, China, 2Department of Radiology, The Second Hospital of Dlian Medical University, Dalian, China, 3MR Research Collaboration, Siemens Healthineers, Beijing, China, 4Department of Radiation Oncology, The First Hospital of China Medical University: The First Hospital of China Medical University, Shenyang, China Keywords: Parkinson's Disease, Neurodegeneration, DTI-ALPS Motivation: In the central nervous system, the dysfunction of " glymphatic system " potentially hinders α-synuclein clearance. Multiple system atrophy (MSA) as α-synucleinopathy diseases, the glymphatic system not been evaluated. Goal(s): ALPS-index has been proposed as a new techology to evaluate the glymphatic system function. Approach: - DTI-ALPS index to evaluate the glymphatic system function.
- Structural MRI features of each subject were extract.
- Group comparison, correlation analysis and granger causality test, mediation analysis were performed.
Results: MSA patients exhibited lower ALPS-index, and correlated with clinical symptoms and MSA-related neuropathological changes. The causality test indicated the ALPS-index changes may be the primary cause of the structural MRI changes. Impact: Changes
in glymphatic system status closely related to disease-related pathological in
patients with multiple system atrophy. |
| 4196.
 | 30 | Metabolic story of functional connectivity in Parkinson’s Disease- A multimodal imaging perspective. Priyanka Bhat1, S Senthil Kumaran1, Achal K Srivastava2, and Divya M Radhakrishnan2
1Nuclear Magnetic Resonance (NMR), AIIMS, New Delhi, India, 2Neurology, AIIMS, Delhi, India Keywords: Parkinson's Disease, Brain Connectivity, Functional Connectivity, Parkinson's Disease, Magnetic Resonance Spectriscopy Motivation: Cortical regions are consequential in non-invasive brain stimulation studies in Parkinson’s Disease. It is important to investigate the cortical connectivity and understand the status of cortical networks with respect to the metabolic profile in PD. Goal(s): This study explored the metabolic profile (using 1H-magnetic resonance spectroscopy-MRS) and functional connectivity (resting state functional MRI). Approach: Resting state functional MRI (with 360 dynamics), 3D T1, single voxel 1H-MRS (in bilateral primary motor areas) were assessed in PD and controls. Results: Perturbations in cortico-cortical networks with increased choline metabolites signify loss in neural integrity. Impact: This study explores the cortical connectivity correlates with neural biochemistry. PD related changes in the cortical connectivity could be due to loss in neural integrity in primary motor area. Multimodal studies could lay a groundwork for brain stimulation studies. |
| 4197.
 | 31 | Fractal Dimension as a T1 Measure for Multiparametric Investigation of Outcome Variance Following Deep Brain Stimulation in Parkinson’s Disease Devin Schoen1, Skyler Deutsch1, Sarah Wang2, Ian O. Bledsoe2, Jill L. Ostrem2, Philip A. Starr3, Doris D. Wang3, and Melanie A. Morrison1
1Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 2Neurology, University of California San Francisco, San Francisco, CA, United States, 3Neurological Surgery, University of California San Francisco, San Francisco, CA, United States Keywords: Parkinson's Disease, Parkinson's Disease, DBS, T1, multiparametric, fractal dimension, therapeutic outcomes, stimulation Motivation: Improved prognostic criteria are needed to better understand outcome variance in response to DBS for Parkinson's disease. Leveraging routinely collected T1-w MRI could offer accessible predictive biomarkers. Goal(s): In 129 patients, we sought to find features derivable from preoperative T1-w images to serve as informative biomarkers to explain variance in response to DBS. Approach: Employing regional analysis and regression techniques, we examined the relationships between fractal dimension (FD), regional volumes, and post-DBS treatment responses. Results: Analysis revealed distinct, significant correlations between FD and volumes with response to DBS, indicating their potential for complementary integration in a multi-parametric predictive tool. Impact: Fractal dimension and volume, metrics derived from T1-w MRI, correlate with DBS response variance in PD patients. Integration of multi-parametric T1-w imaging features into prediction models could aid clinicians in candidate selection and treatment planning to ultimately improve patient-centric outcomes. |
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