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Acar D, Ozcelik EU, Baykan B, Bebek N, Demiralp T, Bayram A. Diffusion tensor imaging in photosensitive and nonphotosensitive juvenile myoclonic epilepsy. Seizure 2024; 115:36-43. [PMID: 38183826 DOI: 10.1016/j.seizure.2023.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 11/27/2023] [Accepted: 12/22/2023] [Indexed: 01/08/2024] Open
Abstract
INTRODUCTION/BACKGROUND Juvenile myoclonic epilepsy (JME) syndrome is known to cause alterations in brain structure and white matter integrity. The study aimed to determine structural white matter changes in patients with JME and to reveal the differences between the photosensitive (PS) and nonphotosensitive (NPS) subgroups by diffusion tensor imaging (DTI) using the tract-based spatial statistics (TBSS) method. METHODS This study included data from 16 PS, 15 NPS patients with JME, and 41 healthy participants. The mean fractional anisotropy (FA) values of these groups were calculated, and comparisons were made via the TBSS method over FA values in the whole-brain and 81 regions of interest (ROI) obtained from the John Hopkins University White Matter Atlas. RESULTS In the whole-brain TBSS analysis, no significant differences in FA values were observed in pairwise comparisons of JME patient group and subgroups with healthy controls (HCs) and in comparison between JME subgroups. In ROI-based TBSS analysis, an increase in FA values of right anterior corona radiata and left corticospinal pathways was found in JME patient group compared with HC group. When comparing JME-PS patients with HCs, an FA increase was observed in the bilateral anterior corona radiata region, whereas when comparing JME-NPS patients with HCs, an FA increase was observed in bilateral corticospinal pathway. Moreover, in subgroup comparison, an increase in FA values was noted in corpus callosum genu region in JME-PS compared with JME-NPS. CONCLUSIONS Our results support the disruption in thalamofrontal white matter integrity in JME, and subgroups and highlight the importance of using different analysis methods to show the underlying microstructural changes.
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Affiliation(s)
- Dilan Acar
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Türkiye; Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Istanbul, Türkiye
| | - Emel Ur Ozcelik
- Departments of Neurology and Clinical Neurophysiology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye; Department of Neurology, Istanbul Kanuni Sultan Suleyman Training and Research Hospital, University of Health Sciences, Istanbul, Türkiye.
| | - Betül Baykan
- Departments of Neurology and Clinical Neurophysiology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye; Department of Neurology, Istanbul EMAR Medical Center, Istanbul, Türkiye
| | - Nerses Bebek
- Departments of Neurology and Clinical Neurophysiology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye
| | - Tamer Demiralp
- Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Türkiye
| | - Ali Bayram
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Türkiye; Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Istanbul, Türkiye
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Wang M, Cheng X, Shi Q, Xu B, Hou X, Zhao H, Gui Q, Wu G, Dong X, Xu Q, Shen M, Cheng Q, Xue S, Feng H, Ding Z. Brain diffusion tensor imaging reveals altered connections and networks in epilepsy patients. Front Hum Neurosci 2023; 17:1142408. [PMID: 37033907 PMCID: PMC10073437 DOI: 10.3389/fnhum.2023.1142408] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 02/28/2023] [Indexed: 04/11/2023] Open
Abstract
Introduction Accumulating evidence shows that epilepsy is a disease caused by brain network dysfunction. This study explored changes in brain network structure in epilepsy patients based on graph analysis of diffusion tensor imaging data. Methods The brain structure networks of 42 healthy control individuals and 26 epilepsy patients were constructed. Using graph theory analysis, global and local network topology parameters of the brain structure network were calculated, and changes in global and local characteristics of the brain network in epilepsy patients were quantitatively analyzed. Results Compared with the healthy control group, the epilepsy patient group showed lower global efficiency, local efficiency, clustering coefficient, and a longer shortest path length. Both healthy control individuals and epilepsy patients showed small-world attributes, with no significant difference between groups. The epilepsy patient group showed lower nodal local efficiency and nodal clustering coefficient in the right olfactory cortex and right rectus and lower nodal degree centrality in the right olfactory cortex and the left paracentral lobular compared with the healthy control group. In addition, the epilepsy patient group showed a smaller fiber number of edges in specific regions of the frontal lobe, temporal lobe, and default mode network, indicating reduced connection strength. Discussion Epilepsy patients exhibited lower global and local brain network properties as well as reduced white matter fiber connectivity in key brain regions. These findings further support the idea that epilepsy is a brain network disorder.
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Affiliation(s)
- Meixia Wang
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaoyu Cheng
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Qianru Shi
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Bo Xu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaoxia Hou
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Huimin Zhao
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qian Gui
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Guanhui Wu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaofeng Dong
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qinrong Xu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Mingqiang Shen
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qingzhang Cheng
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Shouru Xue
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hongxuan Feng
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
- *Correspondence: Hongxuan Feng,
| | - Zhiliang Ding
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
- Zhiliang Ding,
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Safri AA, Nassir CMNCM, Iman IN, Mohd Taib NH, Achuthan A, Mustapha M. Diffusion tensor imaging pipeline measures of cerebral white matter integrity: An overview of recent advances and prospects. World J Clin Cases 2022; 10:8450-8462. [PMID: 36157806 PMCID: PMC9453345 DOI: 10.12998/wjcc.v10.i24.8450] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 06/20/2022] [Accepted: 07/17/2022] [Indexed: 02/05/2023] Open
Abstract
Cerebral small vessel disease (CSVD) is a leading cause of age-related microvascular cognitive decline, resulting in significant morbidity and decreased quality of life. Despite a progress on its key pathophysiological bases and general acceptance of key terms from neuroimaging findings as observed on the magnetic resonance imaging (MRI), key questions on CSVD remain elusive. Enhanced relationships and reliable lesion studies, such as white matter tractography using diffusion-based MRI (dMRI) are necessary in order to improve the assessment of white matter architecture and connectivity in CSVD. Diffusion tensor imaging (DTI) and tractography is an application of dMRI that provides data that can be used to non-invasively appraise the brain white matter connections via fiber tracking and enable visualization of individual patient-specific white matter fiber tracts to reflect the extent of CSVD-associated white matter damage. However, due to a lack of standardization on various sets of software or image pipeline processing utilized in this technique that driven mostly from research setting, interpreting the findings remain contentious, especially to inform an improved diagnosis and/or prognosis of CSVD for routine clinical use. In this minireview, we highlight the advances in DTI pipeline processing and the prospect of this DTI metrics as potential imaging biomarker for CSVD, even for subclinical CSVD in at-risk individuals.
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Affiliation(s)
- Amanina Ahmad Safri
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Kelantan, Malaysia
| | - Che Mohd Nasril Che Mohd Nassir
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Kelantan, Malaysia
| | - Ismail Nurul Iman
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Kelantan, Malaysia
| | - Nur Hartini Mohd Taib
- Department of Radiology, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Kelantan, Malaysia
| | - Anusha Achuthan
- School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
| | - Muzaimi Mustapha
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian 16150, Kelantan, Malaysia
- Department of Neurosciences, Hospital Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia
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Fisher RS, Acharya JN, Baumer FM, French JA, Parisi P, Solodar JH, Szaflarski JP, Thio LL, Tolchin B, Wilkins AJ, Kasteleijn-Nolst Trenité D. Visually sensitive seizures: An updated review by the Epilepsy Foundation. Epilepsia 2022; 63:739-768. [PMID: 35132632 DOI: 10.1111/epi.17175] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 01/10/2022] [Accepted: 01/12/2022] [Indexed: 12/19/2022]
Abstract
Light flashes, patterns, or color changes can provoke seizures in up to 1 in 4000 persons. Prevalence may be higher because of selection bias. The Epilepsy Foundation reviewed light-induced seizures in 2005. Since then, images on social media, virtual reality, three-dimensional (3D) movies, and the Internet have proliferated. Hundreds of studies have explored the mechanisms and presentations of photosensitive seizures, justifying an updated review. This literature summary derives from a nonsystematic literature review via PubMed using the terms "photosensitive" and "epilepsy." The photoparoxysmal response (PPR) is an electroencephalography (EEG) phenomenon, and photosensitive seizures (PS) are seizures provoked by visual stimulation. Photosensitivity is more common in the young and in specific forms of generalized epilepsy. PS can coexist with spontaneous seizures. PS are hereditable and linked to recently identified genes. Brain imaging usually is normal, but special studies imaging white matter tracts demonstrate abnormal connectivity. Occipital cortex and connected regions are hyperexcitable in subjects with light-provoked seizures. Mechanisms remain unclear. Video games, social media clips, occasional movies, and natural stimuli can provoke PS. Virtual reality and 3D images so far appear benign unless they contain specific provocative content, for example, flashes. Images with flashes brighter than 20 candelas/m2 at 3-60 (particularly 15-20) Hz occupying at least 10 to 25% of the visual field are a risk, as are red color flashes or oscillating stripes. Equipment to assay for these characteristics is probably underutilized. Prevention of seizures includes avoiding provocative stimuli, covering one eye, wearing dark glasses, sitting at least two meters from screens, reducing contrast, and taking certain antiseizure drugs. Measurement of PPR suppression in a photosensitivity model can screen putative antiseizure drugs. Some countries regulate media to reduce risk. Visually-induced seizures remain significant public health hazards so they warrant ongoing scientific and regulatory efforts and public education.
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Affiliation(s)
- Robert S Fisher
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Jayant N Acharya
- Department of Neurology, Penn State Health, Hershey, Pennsylvania, USA
| | - Fiona Mitchell Baumer
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, USA
| | - Jacqueline A French
- NYU Comprehensive Epilepsy Center, Epilepsy Foundation, New York, New York, USA
| | - Pasquale Parisi
- Department of Neuroscience, Mental Health, and Sensory Organs, Sapienza University, Rome, Italy
| | - Jessica H Solodar
- American Medical Writers Association-New England Chapter, Boston, Massachusetts, USA
| | - Jerzy P Szaflarski
- Department of Neurology, Neurobiology and Neurosurgery, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, Alabama, USA
| | - Liu Lin Thio
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Benjamin Tolchin
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut, USA
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Yan R, Zhang H, Wang J, Zheng Y, Luo Z, Zhang X, Xu Z. Application value of molecular imaging technology in epilepsy. IBRAIN 2021; 7:200-210. [PMID: 37786793 PMCID: PMC10528966 DOI: 10.1002/j.2769-2795.2021.tb00084.x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/16/2021] [Accepted: 09/02/2021] [Indexed: 10/04/2023]
Abstract
Epilepsy is a common neurological disease with various seizure types, complicated etiologies, and unclear mechanisms. Its diagnosis mainly relies on clinical history, but an electroencephalogram is also a crucial auxiliary examination. Recently, brain imaging technology has gained increasing attention in the diagnosis of epilepsy, and conventional magnetic resonance imaging can detect epileptic foci in some patients with epilepsy. However, the results of brain magnetic resonance imaging are normal in some patients. New molecular imaging has gradually developed in recent years and has been applied in the diagnosis of epilepsy, leading to enhanced lesion detection rates. However, the application of these technologies in epilepsy patients with negative brain magnetic resonance must be clarified. Thus, we reviewed the relevant literature and summarized the information to improve the understanding of the molecular imaging application value of epilepsy.
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Affiliation(s)
- Rong Yan
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Hai‐Qing Zhang
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Jing Wang
- Prevention and Health Care, The Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Yong‐Su Zheng
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Zhong Luo
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Xia Zhang
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
| | - Zu‐Cai Xu
- Department of NeurologyThe Affiliated Hospital of Zunyi Medical UniversityZunyiGuizhouChina
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Yang Y, Zhang K, Yin X, Lei X, Chen X, Wang J, Quan Y, Yang L, Jia Z, Chen Q, Xian J, Lu Y, Huang Q, Zhang X, Feng H, Chen T. Quantitative Iron Neuroimaging Can Be Used to Assess the Effects of Minocycline in an Intracerebral Hemorrhage Minipig Model. Transl Stroke Res 2019; 11:503-516. [PMID: 31696415 DOI: 10.1007/s12975-019-00739-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 09/09/2019] [Accepted: 09/10/2019] [Indexed: 12/28/2022]
Abstract
Iron-mediated toxicity is a key factor causing brain injury after intracerebral hemorrhage (ICH). This study was performed to investigate the noninvasive neuroimaging method for quantifying brain iron content using a minipig ICH model and assess the effects of minocycline treatment on ICH-induced iron overload and brain injury. The minipig ICH model was established by injecting 2 ml of autologous blood into the right basal ganglia, which were then subjected to the treatments of minocycline and vehicle. Furthermore, the quantitative susceptibility mapping (QSM) was used to quantify iron content, and diffusion tensor imaging (DTI) was performed to evaluate white matter tract. Additionally, we also performed immunohistochemistry, Western blot, iron assay, Perl's staining, brain water content, and neurological score to evaluate the iron overload and brain injury. Interestingly, we found that the ICH-induced iron overload could be accurately quantified by the QSM. Moreover, the minocycline was quite beneficial for protecting brain injury by reducing the lesion volume and brain edema, preventing brain iron accumulation, downsizing ventricle enlargement, and alleviating white matter injury and neurological deficits. In summary, we suggest that the QSM be an accurate and noninvasive method for quantifying brain iron level, and the minocycline may be a promising therapeutic agent for patients with ICH.
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Affiliation(s)
- Yang Yang
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Kaiyuan Zhang
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Xuntao Yin
- Department of Radiology, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Xuejiao Lei
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Xuezhu Chen
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Ju Wang
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Yulian Quan
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Ling Yang
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Zhengcai Jia
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Qianwei Chen
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Jishu Xian
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Yongling Lu
- Clinical Research Center, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Qianying Huang
- Clinical Research Center, The Third Military Medical University (Army Military Medical University), Chongqing, China
| | - Xuan Zhang
- Department of Neurosurgery, No. 989 Hospital of Joint Logistic Force (the 150th central hospital) of PLA, Luoyang, Henan Province, China.
| | - Hua Feng
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China.
| | - Tunan Chen
- Department of Neurosurgery and Key Laboratory of Neurotrauma, Southwest Hospital, The Third Military Medical University (Army Military Medical University), Chongqing, China.
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Pillai RL, Chuan H, LaBella A, Mengru Z, Jie Y, Trivedi M, Weissman M, McGrath P, Fava M, Kurian B, Cooper C, McInnis M, Oquendo MA, Pizzagalli DA, Parsey RV, DeLorenzo C. Examining raphe-amygdala structural connectivity as a biological predictor of SSRI response. J Affect Disord 2019; 256:8-16. [PMID: 31158720 PMCID: PMC6750958 DOI: 10.1016/j.jad.2019.05.055] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2018] [Revised: 04/18/2019] [Accepted: 05/27/2019] [Indexed: 12/28/2022]
Abstract
BACKGROUND Our lab has previously found that structural integrity in tracts from the raphe nucleus (RN) to the amygdala, measured by fractional anisotropy (FA), predicts remission to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder (MDD). This could potentially serve as a biomarker for remission that can guide clinical decision-making. To enhance repeatability and reproducibility, we replicated our study in a larger, more representative multi-site sample. METHODS 64 direction DTI was collected in 144 medication-free patients with MDD from the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) study. We performed probabilistic tractography between the RN and bilateral amygdala and hippocampus and calculated weighted FA in these tracts. Patients were treated with either sertraline or placebo, and their change in Hamilton Depression Rating Scale (HDRS) score reported. Pretreatment weighted FA was compared between remitters and nonremitters, and correlation between FA and percent change in HDRS score was assessed. Exploratory moderator and voxel analyses were also performed. RESULTS Contrary to our hypotheses, FA was greater in nonremitters than in remitters in RN-left and right amygdala tracts (p = 0.02 and 0.01, respectively). Pretreatment FA between the raphe and left amygdala correlated with greater, not reduced, HDRS (r = 0.18, p = 0.04). This finding was found to be greater in the placebo group. Moderator and voxel analyses yielded no significant findings. CONCLUSIONS We found greater FA in nonremitters between the RN and amygdala than in remitters, and a correlation between FA and symptom worsening, particularly with placebo. These findings may help reveal more about the nature of MDD, as well as guide research methods involving placebo response.
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Affiliation(s)
| | - Huang Chuan
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, United States,Department of Radiology, Stony Brook University, Stony Brook, NY, United States,Corresponding author at: Department of Psychiatry, Stony Brook Medicine, HSC-T10-020, Stony Brook, NY 11794, United States., (C. Huang)
| | - Andrew LaBella
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States
| | - Zhang Mengru
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, United States
| | - Yang Jie
- Department of Family, Population, & Preventive Medicine, Stony Brook University, Stony Brook, NY, United States
| | - Madhukar Trivedi
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States
| | - Myrna Weissman
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University and the New York Psychiatric Institute, United States
| | - Patrick McGrath
- Department of Psychiatry, College of Physicians and Surgeons, Columbia University and the New York Psychiatric Institute, United States
| | - Maurizio Fava
- Department of Psychiatry, Harvard Medical School, United States
| | - Benji Kurian
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States
| | - Crystal Cooper
- Department of Psychiatry, University of Texas Southwestern Medical Center, United States
| | - Melvin McInnis
- Department of Psychiatry, University of Michigan, United States
| | - Maria A. Oquendo
- Department of Psychiatry, University of Pennsylvania, United States
| | | | - Ramin V. Parsey
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, United States
| | - Christine DeLorenzo
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, United States,Department of Psychiatry, Molecular Imaging and Neuropathology Division, Columbia University, New York, NY, United States
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Poleon S, Szaflarski JP. Photosensitivity in generalized epilepsies. Epilepsy Behav 2017; 68:225-233. [PMID: 28215998 DOI: 10.1016/j.yebeh.2016.10.040] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 10/26/2016] [Accepted: 10/29/2016] [Indexed: 11/24/2022]
Abstract
Photosensitivity, which is the hallmark of photosensitive epilepsy (PSE), is described as an abnormal EEG response to visual stimuli known as a photoparoxysmal response (PPR). The PPR is a well-recognized phenomenon, occurring in 2-14% of patients with epilepsy but its pathophysiology is not clearly understood. PPR is electrographically described as 2-5Hz spike, spike-wave, or slow wave complexes with frontal and paracentral prevalence. Diagnosis of PPR is confirmed using intermittent photic stimulation (IPS) as well as video monitoring. The PPR can be elicited by certain types of visual stimuli including flicker, high contrast gratings, moving patterns, and rapidly modulating luminance patterns which may be encountered during e.g., watching television, playing video games, or attending discotheques. Photosensitivity may present in different idiopathic (genetic) epilepsy syndromes e.g. juvenile myoclonic epilepsy (JME) as well as non-IGE syndromes e.g. severe myoclonic epilepsy of infancy. Consequently, PPR is present in patients with diverse seizure types including absence, myoclonic, and generalized tonic-clonic (GTC) seizures. Across syndromes, abnormalities in structural connectivity, functional connectivity, cortical excitability, cortical morphology, and behavioral and neuropsychological function have been reported. Treatment of photosensitivity includes antiepileptic drug administration, and the use of non-pharmacological agents, e.g. tinted or polarizing glasses, as well as occupational measures, e.g. avoidance of certain stimuli.
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Affiliation(s)
- Shervonne Poleon
- University of Alabama at Birmingham, Department of Neurology and UAB Epilepsy Center, Birmingham, AL, USA.
| | - Jerzy P Szaflarski
- University of Alabama at Birmingham, Department of Neurology and UAB Epilepsy Center, Birmingham, AL, USA
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Zhang Y, Gao Y, Zhou M, Wu J, Zee C, Wang D. A diffusional kurtosis imaging study of idiopathic generalized epilepsy with unilateral interictal epileptiform discharges in children. J Neuroradiol 2016; 43:339-45. [DOI: 10.1016/j.neurad.2016.05.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2016] [Revised: 05/02/2016] [Accepted: 05/04/2016] [Indexed: 12/22/2022]
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Aslan K, Bekci T, Gunbey HP, Bilgici MC, Incesu L. A unique combination of Dyke-Davidoff-Masson syndrome and Down syndrome: Diffusion tensor tractography findings. J Neuroradiol 2015; 43:227-30. [PMID: 26026193 DOI: 10.1016/j.neurad.2015.04.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2015] [Revised: 04/09/2015] [Accepted: 04/10/2015] [Indexed: 11/28/2022]
Affiliation(s)
- Kerim Aslan
- Department of Radiology, Faculty of Medicine, Ondokuz Mayis University, 55139 Kurupelit, Samsun, Turkey.
| | - Tumay Bekci
- Department of Radiology, Faculty of Medicine, Ondokuz Mayis University, 55139 Kurupelit, Samsun, Turkey.
| | - Hediye Pinar Gunbey
- Department of Radiology, Faculty of Medicine, Ondokuz Mayis University, 55139 Kurupelit, Samsun, Turkey.
| | - Meltem Ceyhan Bilgici
- Department of Radiology, Faculty of Medicine, Ondokuz Mayis University, 55139 Kurupelit, Samsun, Turkey.
| | - Lutfi Incesu
- Department of Radiology, Faculty of Medicine, Ondokuz Mayis University, 55139 Kurupelit, Samsun, Turkey.
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Laouchedi M, Galanaud D, Delmaire C, Fernandez-Vidal S, Messé A, Mesmoudi S, Oulebsir Boumghar F, Pélégrini-Issac M, Puybasset L, Benali H, Perlbarg V. Deafferentation in thalamic and pontine areas in severe traumatic brain injury. J Neuroradiol 2014; 42:202-11. [PMID: 24997478 DOI: 10.1016/j.neurad.2014.03.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2014] [Revised: 03/19/2014] [Accepted: 03/19/2014] [Indexed: 11/25/2022]
Abstract
PURPOSE Severe traumatic brain injury (TBI) is characterized mainly by diffuse axonal injuries (DAI). The cortico-subcortical disconnections induced by such fiber disruption play a central role in consciousness recovery. We hypothesized that these cortico-subcortical deafferentations inferred from diffusion MRI data could differentiate between TBI patients with favorable or unfavorable (death, vegetative state, or minimally conscious state) outcome one year after injury. METHODS Cortico-subcortical fiber density maps were derived by using probabilistic tractography from diffusion tensor imaging data acquired in 24 severe TBI patients and 9 healthy controls. These maps were compared between patients and controls as well as between patients with favorable (FO) and unfavorable (UFO) 1-year outcome to identify the thalamo-cortical and ponto-thalamo-cortical pathways involved in the maintenance of consciousness. RESULTS Thalamo-cortical and ponto-thalamo-cortical fiber density was significantly lower in TBI patients than in healthy controls. Comparing FO and UFO TBI patients showed thalamo-cortical deafferentation associated with unfavorable outcome for projections from ventral posterior and intermediate thalamic nuclei to the associative frontal, sensorimotor and associative temporal cortices. Specific ponto-thalamic deafferentation in projections from the upper dorsal pons (including the reticular formation) was also associated with unfavorable outcome. CONCLUSION Fiber density of cortico-subcortical pathways as measured from diffusion MRI tractography is a relevant candidate biomarker for early prediction of one-year favorable outcome in severe TBI.
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Affiliation(s)
- M Laouchedi
- Inserm U1146, CNRS UMR7371, laboratoire d'imagerie biomédicale, Sorbonne universités, UPMC université Paris 06 UMCR2, CHU Pitié-Salpêtrière, 91, boulevard de l'hôpital, 75634 Paris, France; ParIMed Team, LRPE, USTHB, Algiers, Algeria
| | - D Galanaud
- AP-HP, Pitié-Salpêtrière Hospital, Department of Neuroradiology, Paris, France
| | - C Delmaire
- CHRU de Lille, Department of Neuroradiology, Lille, France
| | - S Fernandez-Vidal
- Inserm and UPMC université Paris 06, UMR-S 975, CNRS, UMR 7225, centre de recherche de l'institut du cerveau et de la moelle épinière, Paris, France; Institut du cerveau et de la moelle épinière, centre de neuroimagerie de recherche, Paris, France
| | - A Messé
- Inserm U1146, CNRS UMR7371, laboratoire d'imagerie biomédicale, Sorbonne universités, UPMC université Paris 06 UMCR2, CHU Pitié-Salpêtrière, 91, boulevard de l'hôpital, 75634 Paris, France
| | - S Mesmoudi
- Inserm U1146, CNRS UMR7371, laboratoire d'imagerie biomédicale, Sorbonne universités, UPMC université Paris 06 UMCR2, CHU Pitié-Salpêtrière, 91, boulevard de l'hôpital, 75634 Paris, France; MATRICE Project University Paris 1 Panthéon-Sorbonne, Paris, France
| | | | - M Pélégrini-Issac
- Inserm U1146, CNRS UMR7371, laboratoire d'imagerie biomédicale, Sorbonne universités, UPMC université Paris 06 UMCR2, CHU Pitié-Salpêtrière, 91, boulevard de l'hôpital, 75634 Paris, France
| | - L Puybasset
- Inserm U1146, CNRS UMR7371, laboratoire d'imagerie biomédicale, Sorbonne universités, UPMC université Paris 06 UMCR2, CHU Pitié-Salpêtrière, 91, boulevard de l'hôpital, 75634 Paris, France; AP-HP, Pitié-Salpêtrière Hospital, Surgical Neuro-Intensive Care Unit, Paris, France
| | - H Benali
- Inserm U1146, CNRS UMR7371, laboratoire d'imagerie biomédicale, Sorbonne universités, UPMC université Paris 06 UMCR2, CHU Pitié-Salpêtrière, 91, boulevard de l'hôpital, 75634 Paris, France
| | - V Perlbarg
- Inserm U1146, CNRS UMR7371, laboratoire d'imagerie biomédicale, Sorbonne universités, UPMC université Paris 06 UMCR2, CHU Pitié-Salpêtrière, 91, boulevard de l'hôpital, 75634 Paris, France.
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Loizou CP, Petroudi S, Seimenis I, Pantziaris M, Pattichis CS. Quantitative texture analysis of brain white matter lesions derived from T2-weighted MR images in MS patients with clinically isolated syndrome. J Neuroradiol 2014; 42:99-114. [PMID: 24970463 DOI: 10.1016/j.neurad.2014.05.006] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2014] [Revised: 04/18/2014] [Accepted: 05/04/2014] [Indexed: 01/21/2023]
Abstract
INTRODUCTION This study investigates the application of texture analysis methods on brain T2-white matter lesions detected with magnetic resonance imaging (MRI) for the prognosis of future disability in subjects diagnosed with clinical isolated syndrome (CIS) of multiple sclerosis (MS). METHODS Brain lesions and normal appearing white matter (NAWM) from 38 symptomatic untreated subjects diagnosed with CIS as well as normal white matter (NWM) from 20 healthy volunteers, were manually segmented, by an experienced MS neurologist, on transverse T2-weighted images obtained from serial brain MR imaging scans (0 and 6-12 months). Additional clinical information in the form of the Expanded Disability Status Scale (EDSS), a scale from 0 to 10, which provides a way of quantifying disability in MS and monitoring the changes over time in the level of disability, were also provided. Shape and most importantly different texture features including GLCM and laws were then extracted for all above regions, after image intensity normalization. RESULTS The findings showed that: (i) there were significant differences for the texture futures extracted between the NAWM and lesions at 0 month and between NAWM and lesions at 6-12 months. However, no significant differences were found for all texture features extracted when comparing lesions temporally at 0 and 6-12 months with the exception of contrast (gray level difference statistics-GLDS) and difference entropy (spatial gray level dependence matrix-SGLDM); (ii) significant differences were found between NWM and NAWM for most of the texture features investigated in this study; (iii) there were significant differences found for the lesion texture features at 0 month for those with EDSS≤2 versus those with EDSS>2 (mean, median, inverse difference moment and sum average) and for the lesion texture features at 6-12 months with EDSS>2 and EDSS≤2 for the texture features (mean, median, entropy and sum average). It should be noted that whilst there were no differences in entropy at time 0 between the two groups, significant change was observed at 6-12 months, relating the corresponding features to the follow-up and disability (EDSS) progression. For the NAWM, significant differences were found between 0 month and 6-12 months with EDSS≤2 (contrast, inverse difference moment), for 6-12 months for EDSS>2 and 0 month with EDSS>2 (difference entropy) and for 6-12 months for EDSS>2 and EDSS≤2 (sum average); (iv) there was no significant difference for NAWM and the lesion texture features (for both 0 and 6-12 months) for subjects with no change in EDSS score versus subjects with increased EDSS score from 2 to 5 years. CONCLUSIONS The findings of this study provide evidence that texture features of T2 MRI brain white matter lesions may have an additional potential role in the clinical evaluation of MRI images in MS and perhaps may provide some prognostic evidence in relation to future disability of patients. However, a larger scale study is needed to establish the application in clinical practice and for computing shape and texture features that may provide information for better and earlier differentiation between normal brain tissue and MS lesions.
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Affiliation(s)
- C P Loizou
- Department of Computer Science, School of Sciences, Intercollege, 92, Ayias Phylaxeos Street, PO Box 51604, 3507 Limassol, Cyprus.
| | - S Petroudi
- Department of Computer Science, University of Cyprus, Nicosia, Cyprus.
| | - I Seimenis
- Medical Physics Laboratory, Medical School, Democritus University, Alexandroupolis, Greece.
| | - M Pantziaris
- Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.
| | - C S Pattichis
- Department of Computer Science, University of Cyprus, Nicosia, Cyprus.
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