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Xie Y, Gao C, Wu B, Peng L, Wu J, Lang L. Morphologic brain network predicts levodopa responsiveness in Parkinson disease. Front Aging Neurosci 2023; 14:990913. [PMID: 36688150 PMCID: PMC9849367 DOI: 10.3389/fnagi.2022.990913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 10/18/2022] [Indexed: 01/06/2023] Open
Abstract
Background The levodopa challenge test (LCT) has been routinely used in Parkinson disease (PD) evaluation and predicts the outcome of deep brain stimulation (DBS). Guidelines recommend that patients with an improvement in Unified Parkinson's Disease Rating Scale (UPDRS)-III score > 33% in the LCT receive DBS treatment. However, LCT results are affected by many factors, and only provide information on the immediate effectiveness of dopamine. The aim of the present study was to investigate the relationship between LCT outcome and brain imaging features of PD patients to determine whether the latter can be used to identify candidates for DBS. Methods A total of 38 PD patients were enrolled in the study. Based on improvement in UPDRS-III score in the LCT, patients were divided into low improvement (PD-LCT-L) and high improvement (PD-LCT-H) groups. Each patient's neural network was reconstructed based on T1-weighted magnetic resonance imaging data using the Jensen-Shannon divergence similarity estimation method. The network was established with the multiple kernel support vector machine technique. We analyzed differences in individual morphologic brain networks and their global and local metrics to determine whether there were differences in the connectomes of PD-LCT-L and PD-LCT-H groups. Results The 2 groups were similar in terms of demographic and clinical characteristics. Mean ± SD levodopa responsiveness was 26.52% ± 3.47% in the PD-LCT-L group (N = 13) and 58.66% ± 4.09% in the PD-LCT-H group (N = 25). There were no significant differences between groups in global and local metrics. There were 43 consensus connections that were affected in both groups; in PD-LCT-L patients, most of these connections were decreased whereas those related to the dorsolateral superior frontal gyrus and left cuneus were significantly increased. Conclusion Morphologic brain network assessment is a valuable method for predicting levodopa responsiveness in PD patients, which can facilitate the selection of candidates for DBS.
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Affiliation(s)
- Yongsheng Xie
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Chunyan Gao
- Department of Nursing, Huashan Hospital, Fudan University, Shanghai, China
| | - Bin Wu
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Liling Peng
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai, China
| | - Jianjun Wu
- Department of Neurology and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China
| | - Liqin Lang
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
- National Center for Neurological Disorders, Shanghai, China
- Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, China
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Kang SH, Kim J, Lee J, Koh SB. Mild cognitive impairment is associated with poor gait performance in patients with Parkinson’s disease. Front Aging Neurosci 2022; 14:1003595. [PMID: 36268193 PMCID: PMC9577227 DOI: 10.3389/fnagi.2022.1003595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 09/20/2022] [Indexed: 11/18/2022] Open
Abstract
Cognitive impairment may be commonly accompanied by gait disturbance in patients with Parkinson’s disease (PD). However, it is still controversial whether gait disturbance is associated with mild cognitive impairment (MCI) and which cognitive function has a more important effect on specific gait parameter. Our objective was to investigate the association of gait parameters with MCI and the correlation between performance on comprehensive neuropsychological tests and gait parameters in PD patients. We enrolled 257 patients with de novo PD (111 PD-normal cognition and 146 PD-MCI). All patients underwent comprehensive neuropsychological tests and gait evaluation using the GAITRite system. We used logistic regression analysis and partial correlation to identify the association between gait parameters and MCI and correlations between neuropsychological performance and gait parameters. Gait velocity (odds ratio [OR] = 0.98, 95% confidence interval [CI] = 0.97−0.99) and stride length (OR = 0.98; 95% CI = 0.97−0.99) were associated with MCI in patients with PD. Specifically, gait velocity, stride length, and double support ratio were only associated with attention and frontal-executive function performance in patients with PD. Our findings provide insight into the relationship between gait disturbance and MCI in patients with PD. Furthermore, the evaluation of gait disturbance is necessary for PD patients with cognitive impairment.
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Shih YC, Tseng WYI, Montaser-Kouhsari L. Recent advances in using diffusion tensor imaging to study white matter alterations in Parkinson's disease: A mini review. Front Aging Neurosci 2022; 14:1018017. [PMID: 36910861 PMCID: PMC9992993 DOI: 10.3389/fnagi.2022.1018017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 12/26/2022] [Indexed: 02/24/2023] Open
Abstract
Parkinson's disease (PD) is the second most common age-related neurodegenerative disease with cardinal motor symptoms. In addition to motor symptoms, PD is a heterogeneous disease accompanied by many non-motor symptoms that dominate the clinical manifestations in different stages or subtypes of PD, such as cognitive impairments. The heterogeneity of PD suggests widespread brain structural changes, and axonal involvement appears to be critical to the pathophysiology of PD. As α-synuclein pathology has been suggested to cause axonal changes followed by neuronal degeneration, diffusion tensor imaging (DTI) as an in vivo imaging technique emerges to characterize early detectable white matter changes due to PD. Here, we reviewed the past 5-year literature to show how DTI has helped identify axonal abnormalities at different PD stages or in different PD subtypes and atypical parkinsonism. We also showed the recent clinical utilities of DTI tractography in interventional treatments such as deep brain stimulation (DBS). Mounting evidence supported by multisite DTI data suggests that DTI along with the advanced analytic methods, can delineate dynamic pathophysiological processes from the early to late PD stages and differentiate distinct structural networks affected in PD and other parkinsonism syndromes. It indicates that DTI, along with recent advanced analytic methods, can assist future interventional studies in optimizing treatments for PD patients with different clinical conditions and risk profiles.
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Affiliation(s)
- Yao-Chia Shih
- Graduate Institute of Medicine, Yuan Ze University, Taoyuan, Taiwan
| | - Wen-Yih Isaac Tseng
- AcroViz Inc., Taipei, Taiwan.,Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
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Zhang L, Shen Q, Liao H, Li J, Wang T, Zi Y, Zhou F, Song C, Mao Z, Wang M, Cai S, Tan C. Aberrant Changes in Cortical Complexity in Right-Onset Versus Left-Onset Parkinson's Disease in Early-Stage. Front Aging Neurosci 2021; 13:749606. [PMID: 34819848 PMCID: PMC8606890 DOI: 10.3389/fnagi.2021.749606] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 10/05/2021] [Indexed: 11/17/2022] Open
Abstract
There is increasing evidence to show that motor symptom lateralization in Parkinson’s disease (PD) is linked to non-motor features, progression, and prognosis of the disease. However, few studies have reported the difference in cortical complexity between patients with left-onset of PD (LPD) and right-onset of PD (RPD). This study aimed to investigate the differences in the cortical complexity between early-stage LPD and RPD. High-resolution T1-weighted magnetic resonance images of the brain were acquired in 24 patients with LPD, 34 patients with RPD, and 37 age- and sex-matched healthy controls (HCs). Cortical complexity including gyrification index, fractal dimension (FD), and sulcal depth was analyzed using surface-based morphometry via CAT12/SPM12. Familywise error (FWE) peak-level correction at p < 0.05 was performed for significance testing. In patients with RPD, we found decreased mean FD and mean sulcal depth in the banks of the left superior temporal sulcus (STS) compared with LPD and HCs. The mean FD in the left superior temporal gyrus (STG) was decreased in RPD compared with HCs. However, in patients with LPD, we did not identify significantly abnormal cortical complex change compared with HCs. Moreover, we observed that the mean FD in STG was negatively correlated with the 17-item Hamilton Depression Scale (HAMD) among the three groups. Our findings support the specific influence of asymmetrical motor symptoms in cortical complexity in early-stage PD and reveal that the banks of left STS and left STG might play a crucial role in RPD.
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Affiliation(s)
- Lin Zhang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Qin Shen
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Haiyan Liao
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Junli Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Tianyu Wang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China.,Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yuheng Zi
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Fan Zhou
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Chendie Song
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhenni Mao
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Min Wang
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Sainan Cai
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Changlian Tan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China
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