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Yuzkan S, Hasimoglu O, Balsak S, Mutlu S, Karagulle M, Kose F, Altinkaya A, Tugcu B, Kocak B. Utility of diffusion tensor imaging and generalized q-sampling imaging for predicting short-term clinical effect of deep brain stimulation in Parkinson's disease. Acta Neurochir (Wien) 2024; 166:217. [PMID: 38748304 PMCID: PMC11096246 DOI: 10.1007/s00701-024-06096-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 04/16/2024] [Indexed: 05/18/2024]
Abstract
PURPOSE To assess whether diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) metrics could preoperatively predict the clinical outcome of deep brain stimulation (DBS) in patients with Parkinson's disease (PD). METHODS In this single-center retrospective study, from September 2021 to March 2023, preoperative DTI and GQI examinations of 44 patients who underwent DBS surgery, were analyzed. To evaluate motor functions, the Unified Parkinson's Disease Rating Scale (UPDRS) during on- and off-medication and Parkinson's Disease Questionnaire-39 (PDQ-39) scales were used before and three months after DBS surgery. The study population was divided into two groups according to the improvement rate of scales: ≥ 50% and < 50%. Five target regions, reported to be affected in PD, were investigated. The parameters having statistically significant difference were subjected to a receiver operating characteristic (ROC) analysis. RESULTS Quantitative anisotropy (qa) values from globus pallidus externus, globus pallidus internus (qa_Gpi), and substantia nigra exhibited significant distributional difference between groups in terms of the improvement rate of UPDRS-3 scale during on-medication (p = 0.003, p = 0.0003, and p = 0.0008, respectively). In ROC analysis, the best parameter in predicting DBS response included qa_Gpi with a cut-off value of 0.01370 achieved an area under the ROC curve, accuracy, sensitivity, and specificity of 0.810, 73%, 62.5%, and 85%, respectively. Optimal cut-off values of ≥ 0.01864 and ≤ 0.01162 yielded a sensitivity and specificity of 100%, respectively. CONCLUSION The imaging parameters acquired from GQI, particularly qa_Gpi, may have the ability to non-invasively predict the clinical outcome of DBS surgery.
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Affiliation(s)
| | - Ozan Hasimoglu
- Department of Neurosurgery, University of Health Sciences, Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey
| | - Serdar Balsak
- Department of Radiology, Bezmialem Vakif University Hospital, Istanbul, Turkey
| | - Samet Mutlu
- Department of Radiology, University of Health Sciences, Basaksehir Cam and Sakura City Hospital, Basaksehir, Istanbul, 34480, Turkey
| | - Mehmet Karagulle
- Department of Radiology, University of Health Sciences, Basaksehir Cam and Sakura City Hospital, Basaksehir, Istanbul, 34480, Turkey
| | - Fadime Kose
- Department of Radiology, University of Health Sciences, Basaksehir Cam and Sakura City Hospital, Basaksehir, Istanbul, 34480, Turkey
| | - Ayca Altinkaya
- Department of Neurosurgery, University of Health Sciences, Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey
| | - Bekir Tugcu
- Department of Neurosurgery, University of Health Sciences, Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey
| | - Burak Kocak
- Department of Radiology, University of Health Sciences, Basaksehir Cam and Sakura City Hospital, Basaksehir, Istanbul, 34480, Turkey.
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Weng JC, Chuang YC, Zheng LB, Lee MS, Ho MC. Assessment of brain connectome alterations in male chronic smokers using structural and generalized q-sampling MRI. Brain Imaging Behav 2022; 16:1761-1775. [PMID: 35294980 DOI: 10.1007/s11682-022-00647-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/30/2022] [Indexed: 11/26/2022]
Abstract
An association has been shown between chronic cigarette smoking and structural abnormalities in the brain areas related to several functions relevant to addictive behavior. However, few studies have focused on the structural alternations of chronic smoking by using magnetic resonance imaging (MRI). Also, it remains unclear how structural alternations are associated with tobacco-dependence severity and the positive/negative outcome expectances. The q-sampling imaging (GQI) is an advanced diffusion MRI technique that can reconstruct more precise and consistent images of complex oriented fibers than other methods. We aimed to use GQI to evaluate the impact of the neurological structure caused by chronic smoking. Sixty-seven chronic smokers and 43 nonsmokers underwent a MRI scan. The tobacco dependence severity and the positive/negative outcome expectancies were assessed via self-report. We used GQI with voxel-based statistical analysis (VBA) to evaluate structural brain and connectivity abnormalities. Graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also performed to identify the structural network differences among groups. Chronic smokers had smaller GM and WM volumes in the bilateral frontal lobe and bilateral frontal region. The GM/WM volumes correlated with dependence severity and outcome expectancies in the brain areas involving high-level functions. Chronic smokers had shape changes in the left hippocampal head and tail and the inferior brain stem. Poorer WM integrity in chronic smokers was found in the left middle frontal region, the right superior fronto-occipital fasciculus, the right temporal region, the left parahippocampus, the left anterior internal capsule, and the right inferior parietal region. WM integrity correlated with dependence severity and outcome expectancies in brain areas involving high-level functions. Chronic smokers had decreased local segregation and global integration among the brain regions and networks. Our results provide further evidence indicating that chronic smoking may be associated with brain structure and connectivity changes.
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Affiliation(s)
- Jun-Cheng Weng
- Department of Medical Imaging and Radiological Sciences, Graduate Institute of Artificial Intelligence, Chang Gung University, 33302, Taoyuan, Taiwan
- Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University, Chang Gung Memorial Hospital at Linkou, 33302, Taoyuan, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, 61363, Chiayi, Taiwan
| | - Yu-Chen Chuang
- Department of Medical Imaging and Radiological Sciences, Graduate Institute of Artificial Intelligence, Chang Gung University, 33302, Taoyuan, Taiwan
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, 10051, Taipei, Taiwan
| | - Li-Bang Zheng
- Department of Medical Imaging and Radiological Sciences, Graduate Institute of Artificial Intelligence, Chang Gung University, 33302, Taoyuan, Taiwan
| | - Ming-Shih Lee
- Department of Medical Laboratory and Biotechnology, Chung Shan Medical University, 40201, Taichung, Taiwan
- Clinical Laboratory, Chung Shan Medical University Hospital, 40201, Taichung, Taiwan
| | - Ming-Chou Ho
- Department of Psychology, Chung Shan Medical University, 40201, Taichung, Taiwan.
- Clinical Psychological Room, Chung Shan Medical University Hospital, 40201, Taichung, Taiwan.
- Department of Psychology, Chung Shan Medical University, No.110, Sec. 1, Chien-Kuo N. Road, 402, Taichung, Taiwan.
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Weng JC, Kao TW, Huang GJ, Tyan YS, Tseng HC, Ho MC. Evaluation of structural connectivity changes in betel-quid chewers using generalized q-sampling MRI. Psychopharmacology (Berl) 2017; 234:1945-55. [PMID: 28342092 DOI: 10.1007/s00213-017-4602-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2016] [Accepted: 03/13/2017] [Indexed: 12/17/2022]
Abstract
RATIONALE Betel quid (BQ) is a common addictive substance in many Asian countries. However, few studies have focused on the influences of BQ on the brain. It remains unclear how BQ can affect structural brain abnormalities in BQ chewers. OBJECTIVES We aimed to use generalized q-sampling imaging (GQI) to evaluate the impact of the neurological structure of white matter caused by BQ. METHODS The study population comprised 16 BQ chewers, 15 tobacco and alcohol controls, and 17 healthy controls. We used GQI with voxel-based statistical analysis (VBA) to evaluate structural brain and connectivity abnormalities in the BQ chewers compared to the tobacco and alcohol controls and the healthy controls. Graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also performed to identify the structural network differences among the three groups. RESULTS Using GQI, we found increases in diffusion anisotropy in the right anterior cingulate cortex (ACC), the midbrain, the bilateral angular gyrus, the right superior temporal gyrus (rSTG), the bilateral superior occipital gyrus, the left middle occipital gyrus, the bilateral superior and inferior parietal lobule, and the bilateral postcentral and precentral gyrus in the BQ chewers when compared to the tobacco and alcohol controls and the healthy controls. In GTA and NBS analyses, we found more connections in connectivity among the BQ chewers, particularly in the bilateral anterior cingulum. CONCLUSIONS Our results provided further evidence indicating that BQ chewing may lead to brain structure and connectivity changes in BQ chewers.
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Tyan YS, Liao JR, Shen CY, Lin YC, Weng JC. Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI. Neuroimage Clin 2017; 15:376-382. [PMID: 28580294 PMCID: PMC5447512 DOI: 10.1016/j.nicl.2017.05.014] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2017] [Revised: 04/27/2017] [Accepted: 05/21/2017] [Indexed: 01/01/2023]
Abstract
The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences. The GQI-based structural connectomic study provides a new piece of the puzzle regarding gender differences. Male brains exhibit better intrahemispheric communication, and female exhibit better interhemispheric communication. The network organization of teenage male brains is more local and more segregated than teenage female brains.
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Affiliation(s)
- Yeu-Sheng Tyan
- Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan; Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan; School of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Jan-Ray Liao
- Graduate Institute of Communication Engineering, National Chung Hsing University, Taichung, Taiwan; Department of Electrical Engineering, National Chung Hsing University, Taichung, Taiwan
| | - Chao-Yu Shen
- Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan; Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan; Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Yu-Chieh Lin
- Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan
| | - Jun-Cheng Weng
- Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan; Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan.
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Chen VCH, Shen CY, Liang SHY, Li ZH, Tyan YS, Liao YT, Huang YC, Lee Y, McIntyre RS, Weng JC. Assessment of abnormal brain structures and networks in major depressive disorder using morphometric and connectome analyses. J Affect Disord 2016; 205:103-111. [PMID: 27423425 DOI: 10.1016/j.jad.2016.06.066] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2016] [Revised: 06/14/2016] [Accepted: 06/15/2016] [Indexed: 01/11/2023]
Abstract
BACKGROUND It is hypothesized that the phenomenology of major depressive disorder (MDD) is subserved by disturbances in the structure and function of brain circuits; however, findings of structural abnormalities using MRI have been inconsistent. Generalized q-sampling imaging (GQI) methodology provides an opportunity to assess the functional integrity of white matter tracts in implicated circuits. METHODS The study population was comprised of 16 outpatients with MDD (mean age 44.81±2.2 years) and 30 age- and gender-matched healthy controls (mean age 45.03±1.88 years). We excluded participants with any other primary mental disorder, substance use disorder, or any neurological illnesses. We used T1-weighted 3D MRI with voxel-based morphometry (VBM) and vertex-wise shape analysis, and GQI with voxel-based statistical analysis (VBA), graph theoretical analysis (GTA) and network-based statistical (NBS) analysis to evaluate brain structure and connectivity abnormalities in MDD compared to healthy controls correlates with clinical measures of depressive symptom severity, Hamilton Depression Rating Scale 17-item (HAMD) and Hospital Anxiety and Depression Scale (HADS). RESULTS Using VBM and vertex-wise shape analyses, we found significant volumetric decreases in the hippocampus and amygdala among subjects with MDD (p<0.001). Using GQI, we found decreases in diffusion anisotropy in the superior longitudinal fasciculus and increases in diffusion probability distribution in the frontal lobe among subjects with MDD (p<0.01). In GTA and NBS analyses, we found several disruptions in connectivity among subjects with MDD, particularly in the frontal lobes (p<0.05). In addition, structural alterations were correlated with depressive symptom severity (p<0.01). LIMITATIONS Small sample size; the cross-sectional design did not allow us to observe treatment effects in the MDD participants. CONCLUSIONS Our results provide further evidence indicating that MDD may be conceptualized as a brain disorder with abnormal circuit structure and connectivity.
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Affiliation(s)
- Vincent Chin-Hung Chen
- School of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Chao-Yu Shen
- Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan; Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan
| | - Sophie Hsin-Yi Liang
- School of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Psychiatry, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Zhen-Hui Li
- Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan
| | - Yeu-Sheng Tyan
- Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan; Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan
| | - Yin-To Liao
- Department of Psychiatry, Chung Shan Medical University, Taichung, Taiwan
| | - Yin-Chen Huang
- Department of Neurosurgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Yena Lee
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Canada
| | - Roger S McIntyre
- Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Jun-Cheng Weng
- Department of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan; Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan.
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