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Wang Y, Chen H, Wang C, Liu J, Miao P, Wei Y, Wu L, Wang X, Wang P, Zhang Y, Cheng J, Fan S, Sun G. Static and dynamic interactions within the triple-network model in stroke patients with multidomain cognitive impairments. Neuroimage Clin 2024; 43:103655. [PMID: 39146837 DOI: 10.1016/j.nicl.2024.103655] [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: 04/26/2024] [Revised: 07/23/2024] [Accepted: 08/07/2024] [Indexed: 08/17/2024]
Abstract
BACKGROUND Internal capsule strokes often result in multidomain cognitive impairments across memory, attention, and executive function, typically due to disruptions in brain network connectivity. Our study examines these impairments by analyzing interactions within the triple-network model, focusing on both static and dynamic aspects. METHODS We collected resting-state fMRI data from 62 left (CI_L) and 56 right (CI_R) internal capsule stroke patients, along with 57 healthy controls (HC). Using independent component analysis to extract the default mode (DMN), executive control (ECN), and salience networks (SAN), we conducted static and dynamic functional network connectivity analyses (DFNC) to identify differences between stroke patients and controls. For DFNC, we used k-means clustering to focus on temporal properties and multilayer network analysis to examine integration and modularity Q, where integration represents dynamic interactions between networks, and modularity Q measures how well the network is divided into distinct modules. We then calculated the correlations between SFNC/DFNC properties with significant inter-group differences and cognitive scales. RESULTS Compared to HC, both CI_L and CI_R patients showed increased static FCs between SAN and DMN and decreased dynamic interactions between ECN and other networks. CI_R patients also had heightened static FCs between SAN and ECN and maintained a state with strongly positive FNCs across all networks in the triple-network model. Additionally, CI_R patients displayed decreased modularity Q. CONCLUSION These findings highlight that stroke can result in the disruption of static and dynamic interactions in the triple network model, aiding our understanding of the neuropathological basis for multidomain cognitive deficits after internal capsule stroke.
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Affiliation(s)
- Yingying Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Hongxu Chen
- Cardiff University Brain Research Imaging Centre, United Kingdom
| | - Caihong Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingchun Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Peifang Miao
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ying Wei
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Luobing Wu
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xin Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Peipei Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Siyuan Fan
- Cardiovascular Center, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Guifang Sun
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Henan Province 450052, China.
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Liu J, Wang C, Zhang Y, Guo J, Miao P, Wei Y. Cortical structure reorganization and correlation with attention deficit in subcortical stroke: An underlying pattern analysis. Neuroimage Clin 2024; 42:103612. [PMID: 38692208 PMCID: PMC11067530 DOI: 10.1016/j.nicl.2024.103612] [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: 12/02/2023] [Revised: 04/13/2024] [Accepted: 04/25/2024] [Indexed: 05/03/2024]
Abstract
BACKGROUND Subcortical stroke may significantly alter the cerebral cortical structure and affect attention function, but the details of this process remain unclear. The study aimed to investigate the neural substrates underlying attention impairment in patients with subcortical stroke. MATERIALS AND METHODS In this prospective observational study, two distinct datasets were acquired to identify imaging biomarkers underlying attention deficit. The first dataset consisted of 86 patients with subcortical stroke, providing a cross-sectional perspective, whereas the second comprised 108 patients with stroke, offering longitudinal insights. All statistical analyses were subjected to false discovery rate correction upon P < 0.05. RESULTS In the chronic-stage data, the stroke group exhibited significantly poorer attention function compared with that of the control group. The cortical structure analysis showed that patients with stroke exhibited decreased cortical thickness of the precentral gyrus and surface area of the cuneus, along with an increase in various frontal, occipital, and parietal cortices regions. The declined attention function positively correlated with the superior frontal gyrus cortical thickness and supramarginal gyrus surface area. In the longitudinal dataset, patients with stroke showed gradually increasing cortical thickness and surface area within regions of obvious structural reorganization. Furthermore, deficient attention positively correlated with supramarginal gyrus surface area both at the subacute and chronic stages post-stroke. CONCLUSIONS Subcortical stroke can elicit dynamic reorganization of cortical areas associated with attention impairment. Moreover, the altered surface area of the supramarginal gyrus is a potential neuroimaging biomarker for attention deficits.
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Affiliation(s)
- Jingchun Liu
- Departments of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Caihong Wang
- Departments of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China; Department of MRI, The First Affiliated Hospital of Zhengzhou University, Henan 450052, China
| | - Yujie Zhang
- Departments of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jun Guo
- Department of Radiology, Tianjin University Huanhu Hospital & Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Peifang Miao
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Henan 450052, China
| | - Ying Wei
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Henan 450052, China
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Kim CW, Kim Y, Kim HH, Choi JY. The aspect of structural connectivity in relation to age-related gait performance. PSYCHORADIOLOGY 2023; 3:kkad028. [PMID: 38666123 PMCID: PMC10917373 DOI: 10.1093/psyrad/kkad028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/05/2023] [Accepted: 11/24/2023] [Indexed: 04/28/2024]
Affiliation(s)
- Cheol-Woon Kim
- Department of Physical Education, Korea University,, 02841, Seoul, Republic of Korea
| | - Yechan Kim
- Department of Biomedical Engineering, Yonsei University,, 26493, Wonju, Republic of Korea
| | - Hyun-Ho Kim
- Department of Biomedical Engineering, Yonsei University,, 26493, Wonju, Republic of Korea
| | - Joon Yul Choi
- Department of Biomedical Engineering, Yonsei University,, 26493, Wonju, Republic of Korea
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Wang C, Liu J, Guo J, Han S, Miao P, Wei Y, Wang Y, Wang X, Li Z, Xue K, Wang K, Cheng J. Dynamic brain activity states of memory impairment in stroke patients with varying motor outcomes. Front Aging Neurosci 2023; 15:1294009. [PMID: 38046468 PMCID: PMC10690823 DOI: 10.3389/fnagi.2023.1294009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 11/02/2023] [Indexed: 12/05/2023] Open
Abstract
Introduction The objective of this study was to characterize the alteration patterns of dynamic spatiotemporal activity in chronic subcortical stroke patients with varying motor outcomes, while investigating the imaging indicators relevant to the assessment of potential cognitive deficits in these patients. Methods A total of 136 patients and 88 normal controls were included in the analysis of static and dynamic intrinsic brain activity, determined by amplitude of low-frequency fluctuations. Results The findings unveiled that subcortical stroke patients exhibited significantly aberrant temporal dynamics of intrinsic brain activity, involving regions within multiple brain networks. These spatiotemporal patterns were found to be contingent upon the side of the lesion. In addition, these aberrant metrics demonstrated potential in discerning cognitive deficits in stroke patients with memory impairment, with the dynamic indices exerting more influence than the static ones. The observe findings may indicate that subcortical stroke can trigger imbalances in the segregation and integration of spatiotemporal patterns across the entire brain with multi-domain networks, especially in patients with poor motor outcomes. Conclusion It suggests that the temporal dynamics indices of intrinsic brain activity could serve as potential imaging indicators for assessing cognitive impairment in patients with chronic subcortical stroke, which may be associated with the motor outcomes.
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Affiliation(s)
- Caihong Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan, China
| | - Jingchun Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jun Guo
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Shaoqiang Han
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan, China
| | - Peifang Miao
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan, China
| | - Ying Wei
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan, China
| | - Yingying Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan, China
| | - Xin Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan, China
| | - Zhen Li
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kangkang Xue
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan, China
| | - Kaiyu Wang
- MR Research China, GE Healthcare, Beijing, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, Henan, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, Henan, China
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Chen S, Zhang X, Chen X, Zhou Z, Cong W, Chong K, Xu Q, Wu J, Li Z, Lin W, Shan C. The assessment of interhemispheric imbalance using functional near-infrared spectroscopic and transcranial magnetic stimulation for predicting motor outcome after stroke. Front Neurosci 2023; 17:1231693. [PMID: 37655011 PMCID: PMC10466792 DOI: 10.3389/fnins.2023.1231693] [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: 05/30/2023] [Accepted: 08/02/2023] [Indexed: 09/02/2023] Open
Abstract
Objective To investigate changes in interhemispheric imbalance of cortical excitability during motor recovery after stroke and to clarify the relationship between motor function recovery and alterations in interhemispheric imbalance, with the aim to establish more effective neuromodulation strategies. Methods Thirty-one patients underwent assessments of resting motor threshold (RMT) using transcranial magnetic stimulation (TMS); the cortical activity of the primary motor cortex (M1), premotor cortex (PMC), and supplementary motor area (SMA) using functional near-infrared spectroscopy (fNIRS); as well as motor function using upper extremity Fugl-Meyer (FMA-UE). The laterality index (LI) of RMT and fNIRS were also calculated. All indicators were measured at baseline(T1) and 1 month later(T2). Correlations between motor function outcome and TMS and fNIRS metrics at baseline were analyzed using bivariate correlation. Results All the motor function (FMA-UE1, FMA-UE2, FMA-d2) and LI-RMT (LI-RMT1 and LI-RMT2) had a moderate negative correlation. The higher the corticospinal excitability of the affected hemisphere, the better the motor outcome of the upper extremity, especially in the distal upper extremity (r = -0.366, p = 0.043; r = -0.393, p = 0.029). The greater the activation of the SMA of the unaffected hemisphere, the better the motor outcome, especially in the distal upper extremity (r = -0.356, p = 0.049; r = -0.367, p = 0.042). There was a significant moderate positive correlation observed between LI-RMT2 and LI-SMA1 (r = 0.422, p = 0.018). The improvement in motor function was most significant when both LI-RMT1 and LI-SMA1 were lower. Besides, in patients dominated by unaffected hemisphere corticospinal excitability during motor recovery, LI-(M1 + SMA + PMC)2 exhibited a significant moderate positive association with the proximal upper extremity function 1 month later (r = 0.642, p = 0.007). Conclusion The combination of both TMS and fNIRS can infer the prognosis of motor function to some extent. Which can infer the role of both hemispheres in recovery and may contribute to the development of effective individualized neuromodulation strategies.
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Affiliation(s)
- Songmei Chen
- Department of Rehabilitation Medicine, Shanghai No.3 Rehabilitation Hospital, Shanghai, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiaolin Zhang
- Department of Rehabilitation Medicine, Shanghai No.3 Rehabilitation Hospital, Shanghai, China
| | - Xixi Chen
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhiqing Zhou
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Weiqin Cong
- Department of Rehabilitation Medicine, Shanghai No.3 Rehabilitation Hospital, Shanghai, China
| | - KaYee Chong
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Qing Xu
- Department of Rehabilitation Medicine, Shanghai No.3 Rehabilitation Hospital, Shanghai, China
| | - Jiali Wu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhaoyuan Li
- Department of Rehabilitation Medicine, Shanghai No.3 Rehabilitation Hospital, Shanghai, China
| | - Wanlong Lin
- Department of Rehabilitation Medicine, Shanghai No.3 Rehabilitation Hospital, Shanghai, China
| | - Chunlei Shan
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Center of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
- Institute of rehabilitation, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Salvalaggio S, Turolla A, Andò M, Barresi R, Burgio F, Busan P, Cortese AM, D’Imperio D, Danesin L, Ferrazzi G, Maistrello L, Mascotto E, Parrotta I, Pezzetta R, Rigon E, Vedovato A, Zago S, Zorzi M, Arcara G, Mantini D, Filippini N. Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach. Front Aging Neurosci 2023; 15:1205063. [PMID: 37469951 PMCID: PMC10352609 DOI: 10.3389/fnagi.2023.1205063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 06/19/2023] [Indexed: 07/21/2023] Open
Abstract
Background Stroke is a debilitating disease affecting millions of people worldwide. Despite the survival rate has significantly increased over the years, many stroke survivors are left with severe impairments impacting their quality of life. Rehabilitation programs have proved to be successful in improving the recovery process. However, a reliable model of sensorimotor recovery and a clear identification of predictive markers of rehabilitation-induced recovery are still needed. This article introduces the cross-modality protocols designed to investigate the rehabilitation treatment's effect in a group of stroke survivors. Methods/design A total of 75 stroke patients, admitted at the IRCCS San Camillo rehabilitation Hospital in Venice (Italy), will be included in this study. Here, we describe the rehabilitation programs, clinical, neuropsychological, and physiological/imaging [including electroencephalography (EEG), transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI) techniques] protocols set up for this study. Blood collection for the characterization of predictive biological biomarkers will also be taken. Measures derived from data acquired will be used as candidate predictors of motor recovery. Discussion/summary The integration of cutting-edge physiological and imaging techniques, with clinical and cognitive assessment, dose of rehabilitation and biological variables will provide a unique opportunity to define a predictive model of recovery in stroke patients. Taken together, the data acquired in this project will help to define a model of rehabilitation induced sensorimotor recovery, with the final aim of developing personalized treatments promoting the greatest chance of recovery of the compromised functions.
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Affiliation(s)
- Silvia Salvalaggio
- IRCCS San Camillo Hospital, Venice, Italy
- Padova Neuroscience Center, Università degli Studi di Padova, Padua, Italy
| | - Andrea Turolla
- Department of Biomedical and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum – Università di Bologna, Bologna, Italy
- Unit of Occupational Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | | | | | | | | | - Anna Maria Cortese
- Department of Rehabilitation Medicine, AULSS 3 Serenissima, Venice, Italy
| | | | | | | | | | - Eleonora Mascotto
- Department of Physical Medicine and Rehabilitation, Venice Hospital, Venice, Italy
| | | | | | | | - Anna Vedovato
- General Hospital San Camillo of Treviso, Treviso, Italy
| | - Sara Zago
- IRCCS San Camillo Hospital, Venice, Italy
| | - Marco Zorzi
- IRCCS San Camillo Hospital, Venice, Italy
- Padova Neuroscience Center, Università degli Studi di Padova, Padua, Italy
- Department of General Psychology, University of Padova, Padua, Italy
| | | | - Dante Mantini
- IRCCS San Camillo Hospital, Venice, Italy
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
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Liu J, Wang C, Qin W, Guo J, Han T, Cheng J, Yu C. Dynamic reorganization of cortical structure in multi-domain regions after capsular and pontine stroke. J Cereb Blood Flow Metab 2023; 43:1130-1141. [PMID: 37150601 PMCID: PMC10291451 DOI: 10.1177/0271678x231159954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 12/21/2022] [Accepted: 01/30/2023] [Indexed: 02/24/2023]
Abstract
Subcortical stroke may cause widespread structural changes to the cerebral cortex in multiple domains; however, the details of this process remain unclear. In this prospective observational study, we acquired two datasets to investigate the effect of lesion location on cortical structure. One was cross-sectional, comprising 269 patients with chronic stroke, either capsular stroke (CS) or pontine stroke (PS), and the other was longitudinal, comprising 119 patients with CS or PS. In the chronic-stage data, both CS and PS exhibited reduced cortical thickness in the precentral gyrus and increased cortical thickness and area in the frontal, temporal, occipital and insular cortices. Cortical thicknesses were correlated with motor outcomes in the precentral and lingual gyri, and early impairment of the corticospinal tract was associated with cortical thickness in the middle frontal gyrus. In the longitudinal dataset, CS showed gradually decreasing cortical thickness in the precentral gyrus, and both CS and PS showed gradually increasing cortical thickness and area in regions with significant structural reorganization. Subcortical stroke can therefore cause complex cortical structural changes in multi-domain regions involved in motor, primary and higher cognitive areas and have different evolution patterns depending on the subcortical level of the lesion affecting the motor pathways.
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Affiliation(s)
- Jingchun Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Caihong Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jun Guo
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Tong Han
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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Wróbel PP, Guder S, Feldheim JF, Graterol Pérez JA, Frey BM, Choe CU, Bönstrup M, Cheng B, Rathi Y, Pasternak O, Thomalla G, Gerloff C, Shenton ME, Schulz R. Altered microstructure of the contralesional ventral premotor cortex and motor output after stroke. Brain Commun 2023; 5:fcad160. [PMID: 37265601 PMCID: PMC10231803 DOI: 10.1093/braincomms/fcad160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 03/17/2023] [Accepted: 05/15/2023] [Indexed: 06/03/2023] Open
Abstract
Cortical thickness analyses have provided valuable insights into changes in cortical brain structure after stroke and their association with recovery. Across studies though, relationships between cortical structure and function show inconsistent results. Recent developments in diffusion-weighted imaging of the cortex have paved the way to uncover hidden aspects of stroke-related alterations in cortical microstructure, going beyond cortical thickness as a surrogate for cortical macrostructure. We re-analysed clinical and imaging data of 42 well-recovered chronic stroke patients from 2 independent cohorts (mean age 64 years, 4 left-handed, 71% male, 16 right-sided strokes) and 33 healthy controls of similar age and gender. Cortical fractional anisotropy and cortical thickness values were obtained for six key sensorimotor areas of the contralesional hemisphere. The regions included the primary motor cortex, dorsal and ventral premotor cortex, supplementary and pre-supplementary motor areas, and primary somatosensory cortex. Linear models were estimated for group comparisons between patients and controls and for correlations between cortical fractional anisotropy and cortical thickness and clinical scores. Compared with controls, stroke patients exhibited a reduction in fractional anisotropy in the contralesional ventral premotor cortex (P = 0.005). Fractional anisotropy of the other regions and cortical thickness did not show a comparable group difference. Higher fractional anisotropy of the ventral premotor cortex, but not cortical thickness, was positively associated with residual grip force in the stroke patients. These data provide novel evidence that the contralesional ventral premotor cortex might constitute a key sensorimotor area particularly susceptible to stroke-related alterations in cortical microstructure as measured by diffusion MRI and they suggest a link between these changes and residual motor output after stroke.
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Affiliation(s)
- Paweł P Wróbel
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - Stephanie Guder
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - Jan F Feldheim
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - José A Graterol Pérez
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - Benedikt M Frey
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - Chi-un Choe
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - Marlene Bönstrup
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
- Department of Neurology, University Medical Center, Leipzig 04103, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - Yogesh Rathi
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston 02115, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston 02115, MA, USA
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston 02115, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston 02115, MA, USA
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston 02115, MA, USA
- Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston 02115, MA, USA
| | - Robert Schulz
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20251, Germany
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Karakis R, Gurkahraman K, Mitsis GD, Boudrias MH. DEEP LEARNING PREDICTION OF MOTOR PERFORMANCE IN STROKE INDIVIDUALS USING NEUROIMAGING DATA. J Biomed Inform 2023; 141:104357. [PMID: 37031755 DOI: 10.1016/j.jbi.2023.104357] [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: 11/15/2022] [Revised: 02/24/2023] [Accepted: 04/01/2023] [Indexed: 04/11/2023]
Abstract
The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have been used as potential biomarkers of motor recovery, with limited accuracy up to date. To address this, the present study aimed to develop a deep learning model based on structural brain images obtained from stroke participants and healthy volunteers. The following inputs were used in a multi-channel 3D convolutional neural network (CNN) model: fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps obtained from Diffusion Tensor Imaging (DTI) images, white and gray matter intensity values obtained from Magnetic Resonance Imaging, as well as demographic data (e.g., age, gender). Upper limb motor function was classified into "Poor" and "Good" categories. To assess the performance of the DL model, we compared it to more standard machine learning (ML) classifiers including k-nearest neighbor, support vector machines (SVM), Decision Trees, Random Forests, Ada Boosting, and Naïve Bayes, whereby the inputs of these classifiers were the features taken from the fully connected layer of the CNN model. The highest accuracy and area under the curve values were 0.92 and 0.92 for the 3D-CNN and 0.91 and 0.91 for the SVM, respectively. The multi-channel 3D-CNN with residual blocks and SVM supported by DL was more accurate than traditional ML methods to classify upper limb motor impairment in the stroke population. These results suggest that combining volumetric DTI maps and measures of white and gray matter integrity can improve the prediction of the degree of motor impairment after stroke. Identifying the potential of recovery early on after a stroke could promote the allocation of resources to optimize the functional independence of these individuals and their quality of life.
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Affiliation(s)
- Rukiye Karakis
- Department of Software Engineering, Faculty of Technology, Sivas Cumhuriyet University, Turkey
| | - Kali Gurkahraman
- Department of Computer Engineering, Faculty of Engineering, Sivas Cumhuriyet University, Turkey
| | - Georgios D Mitsis
- Department of Bioengineering, Faculty of Engineering, McGill University, Montreal, QC, Canada
| | - Marie-Hélène Boudrias
- School of Physical and Occupational Therapy, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada; BRAIN Laboratory, Jewish Rehabilitation Hospital, Site of Centre for Interdisciplinary Research of Greater Montreal (CRIR) and CISSS-Laval, QC, Canada.
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10
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Neuroplasticity Following Stroke from a Functional Laterality Perspective: A fNIRS Study. Brain Topogr 2023; 36:283-293. [PMID: 36856917 DOI: 10.1007/s10548-023-00946-z] [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: 12/09/2022] [Accepted: 02/14/2023] [Indexed: 03/02/2023]
Abstract
To explore alterations of resting-state functional connectivity (rsFC) in sensorimotor cortex following strokes with left or right hemiplegia considering the lateralization and neuroplasticity. Seventy-three resting-state functional near-infrared spectroscopy (fNIRS) files were selected, including 26 from left hemiplegia (LH), 21 from right hemiplegia (RH) and 26 from normal controls (NC) group. Whole-brain analyses matching the Pearson correlation were used for rsFC calculations. For right-handed normal controls, rsFC of motor components (M1 and M2) in the left hemisphere displayed a prominent intensity in comparison with the right hemisphere (p < 0.05), while for stroke groups, this asymmetry has disappeared. Additionally, RH rather than LH showed stronger rsFC between left S1 and left M1 in contrast to normal controls (p < 0.05), which correlated inversely with motor function (r = - 0.53, p < 0.05). Regarding M1, rsFC within ipsi-lesioned M1 has a negative correlation with motor function of the affected limb (r = - 0.60 for the RH group and - 0.43 for the LH group, p < 0.05). The rsFC within contra-lesioned M1 that innervates the normal side was weakened compared with that of normal controls (p < 0.05). Stronger rsFC of motor components in left hemisphere was confirmed by rs-fNIRS as the "secret of dominance" for the first time, while post-stroke hemiplegia broke this cortical asymmetry. Meanwhile, a statistically strengthened rsFC between left S1 and M1 only in right-hemiplegia group may act as a compensation for the impairment of the dominant side. This research has implications for brain-computer interfaces synchronizing sensory feedback with motor performance and transcranial magnetic regulation for cortical excitability to induce cortical plasticity.
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11
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Rojas Albert A, Backhaus W, Graterol Pérez JA, Braaβ H, Schön G, Choe CU, Feldheim J, Bönstrup M, Cheng B, Thomalla G, Gerloff C, Schulz R. Cortical thickness of contralesional cortices positively relates to future outcome after severe stroke. Cereb Cortex 2022; 32:5622-5627. [PMID: 35169830 DOI: 10.1093/cercor/bhac040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 01/21/2022] [Accepted: 01/22/2022] [Indexed: 01/25/2023] Open
Abstract
Imaging studies have evidenced that contralesional cortices are involved in recovery after motor stroke. Cortical thickness (CT) analysis has proven its potential to capture the changes of cortical anatomy, which have been related to recovery and treatment gains under therapy. An open question is whether CT obtained in the acute phase after stroke might inform correlational models to explain outcome variability. Data of 38 severely impaired (median NIH Stroke Scale 9, interquartile range: 6-13) acute stroke patients of 2 independent cohorts were reanalyzed. Structural imaging data were processed via the FreeSurfer pipeline to quantify regional CT of the contralesional hemisphere. Ordinal logistic regression models were fit to relate CT to modified Rankin Scale as an established measure of global disability after 3-6 months, adjusted for the initial deficit, lesion volume, and age. The data show that CT of contralesional cortices, such as the precentral gyrus, the superior frontal sulcus, and temporal and cingulate cortices, positively relates to the outcome after stroke. This work shows that the baseline cortical anatomy of selected contralesional cortices can explain the outcome variability after severe stroke, which further contributes to the concept of structural brain reserve with respect to contralesional cortices to promote recovery.
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Affiliation(s)
- Alina Rojas Albert
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Winifried Backhaus
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - José A Graterol Pérez
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Hanna Braaβ
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Gerhard Schön
- Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Chi-Un Choe
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Jan Feldheim
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Marlene Bönstrup
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany.,Department of Neurology, University Medical Center, Leipzig 04103, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
| | - Robert Schulz
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg 20246, Germany
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12
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Liu J, Wang C, Qin W, Ding H, Peng Y, Guo J, Han T, Cheng J, Yu C. Cortical structural changes after subcortical stroke: Patterns and correlates. Hum Brain Mapp 2022; 44:727-743. [PMID: 36189822 PMCID: PMC9842916 DOI: 10.1002/hbm.26095] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 09/11/2022] [Accepted: 09/14/2022] [Indexed: 01/25/2023] Open
Abstract
Subcortical ischemic stroke can lead to persistent structural changes in the cerebral cortex. The evolution of cortical structural changes after subcortical stroke is largely unknown, as are their relations with motor recovery, lesion location, and early impairment of specific subsets of fibers in the corticospinal tract (CST). In this observational study, cortical structural changes were compared between 181 chronic patients with subcortical stroke involving the motor pathway and 113 healthy controls. The impacts of acute lesion location and early impairments of specific CSTs on cortical structural changes were investigated in the patients by combining voxel-based correlation analysis with an association study that compared CST damage and cortical structural changes. Longitudinal patterns of cortical structural change were explored in a group of 81 patients with subcortical stroke using a linear mixed-effects model. In the cross-sectional analyses, patients with partial recovery showed more significant reductions in cortical thickness, surface area, or gray matter volume in the sensorimotor cortex, cingulate gyrus, and gyrus rectus than did patients with complete recovery; however, patients with complete recovery demonstrated more significant increases in the cortical structural measures in frontal, temporal, and occipital regions than did patients with partial recovery. Voxel-based correlation analysis in these patients showed that acute stroke lesions involving the CST fibers originating from the primary motor cortex were associated with cortical thickness reductions in the ipsilesional motor cortex in the chronic stage. Acute stroke lesions in the putamen were correlated with increased surface area in the temporal pole in the chronic stage. The early impairment of the CST fibers originating from the primary sensory area was associated with increased cortical thickness in the occipital cortex. In the longitudinal analyses, patients with partial recovery showed gradually reduced cortical thickness, surface area, and gray matter volume in brain regions with significant structural damage in the chronic stage. Patients with complete recovery demonstrated gradually increasing cortical thickness, surface area, and gray-matter volume in the frontal, temporal, and occipital regions. The directions of slow structural changes in the frontal, occipital, and cingulate cortices were completely different between patients with partial and complete recovery. Complex cortical structural changes and their dynamic evolution patterns were different, even contrasting, in patients with partial and complete recovery, and were associated with lesion location and with impairment of specific CST fiber subsets.
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Affiliation(s)
- Jingchun Liu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Caihong Wang
- Department of MRIThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenanChina
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina
| | - Hao Ding
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina,School of Medical ImagingTianjin Medical UniversityTianjinChina
| | - Yanmin Peng
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina,School of Medical ImagingTianjin Medical UniversityTianjinChina
| | - Jun Guo
- Department of RadiologyTianjin Huanhu HospitalTianjinChina
| | - Tong Han
- Department of RadiologyTianjin Huanhu HospitalTianjinChina
| | - Jingliang Cheng
- Department of MRIThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenanChina
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional ImagingTianjin Medical University General HospitalTianjinChina,CAS Center for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghaiChina
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13
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Sagnier S, Catheline G, Dilharreguy B, Linck PA, Coupé P, Munsch F, Bigourdan A, Poli M, Debruxelles S, Renou P, Olindo S, Rouanet F, Dousset V, Tourdias T, Sibon I. Normal-Appearing White Matter Deteriorates over the Year After an Ischemic Stroke and Is Associated with Global Cognition. Transl Stroke Res 2022; 13:716-724. [PMID: 35106712 DOI: 10.1007/s12975-022-00988-8] [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: 10/02/2021] [Revised: 11/19/2021] [Accepted: 01/17/2022] [Indexed: 10/19/2022]
Abstract
Normal-appearing white matter (NAWM) is a hub of plasticity, but data relating to its influence on post-ischemic stroke (IS) outcome remain scarce. The aim of this study was to evaluate the relationship between NAWM integrity and cognitive outcome after an IS. A longitudinal study was conducted including supra-tentorial IS patients. A 3-Tesla brain MRI was performed at baseline and 1 year, allowing the analyses of mean fractional anisotropy (FA) and mean diffusivity (MD) in NAWM masks, along with the volume of white matter hyperintensities (WMH) and IS. A Montreal Cognitive Assessment (MoCA), an Isaacs set test, and a Zazzo's cancellation task were performed at baseline, 3 months and 1 year. Mixed models were built, followed by Tract-based Spatial Statistics (TBSS) analyses. Ninety-five patients were included in the analyses (38% women, median age 69 ± 20). FA significantly decreased, and MD significantly increased between baseline and 1 year, while cognitive scores improved. Patients who decreased their NAWM FA more over the year had a slower cognitive improvement on MoCA (β = - 0.11, p = 0.05). The TBSS analyses showed that patients who presented the highest decrease of FA in various tracts of white matter less improved their MoCA performances, regardless of WMH and IS volumes, demographic confounders, and clinical severity. NAWM integrity deteriorates over the year after an IS, and is associated with a cognitive recovery slowdown. The diffusion changes recorded here in patients starting with an early preserved white matter structure could have long term impact on cognition.
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Affiliation(s)
- Sharmila Sagnier
- UMR-5287, CNRS, Université de Bordeaux, EPHE PSL Research University, Bordeaux, France.
- CHU de Bordeaux, Unité Neuro-Vasculaire, Bordeaux, France.
- INCIA Université Bordeaux 2, 146 rue Léo Saignat Zone Nord, Bâtiment 2A, 2e étage, 33076, Bordeaux, France.
| | - Gwenaëlle Catheline
- UMR-5287, CNRS, Université de Bordeaux, EPHE PSL Research University, Bordeaux, France
| | - Bixente Dilharreguy
- UMR-5287, CNRS, Université de Bordeaux, EPHE PSL Research University, Bordeaux, France
| | | | - Pierrick Coupé
- UMR-5800, CNRS, Université de Bordeaux, LaBRI, Talence, France
| | - Fanny Munsch
- Beth Israel Deaconess Medical Center, Harvard University, Boston, USA
| | | | - Mathilde Poli
- CHU de Bordeaux, Unité Neuro-Vasculaire, Bordeaux, France
| | | | - Pauline Renou
- CHU de Bordeaux, Unité Neuro-Vasculaire, Bordeaux, France
| | | | | | - Vincent Dousset
- CHU de Bordeaux, Neuroradiologie, Bordeaux, France
- INSERM-U1215, Neurocentre Magendie, Bordeaux, France
| | - Thomas Tourdias
- CHU de Bordeaux, Neuroradiologie, Bordeaux, France
- INSERM-U1215, Neurocentre Magendie, Bordeaux, France
| | - Igor Sibon
- UMR-5287, CNRS, Université de Bordeaux, EPHE PSL Research University, Bordeaux, France
- CHU de Bordeaux, Unité Neuro-Vasculaire, Bordeaux, France
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14
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Firwana YMS, Zolkefley MKI, Mohamed Hatta HZ, Rowbin C, Che Mohd Nassir CMN, Hanafi MH, Abdullah MS, Keserci B, Lannin NA, Mustapha M. Regional cerebral blood perfusion changes in chronic stroke survivors as potential brain correlates of the functional outcome following gamified home-based rehabilitation (IntelliRehab)-a pilot study. J Neuroeng Rehabil 2022; 19:94. [PMID: 36002827 PMCID: PMC9404656 DOI: 10.1186/s12984-022-01072-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 08/18/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Hospital-based stroke rehabilitation for stroke survivors in developing countries may be limited by staffing ratios and length of stay that could hamper recovery potential. Thus, a home-based, gamified rehabilitation system (i.e., IntelliRehab) was tested for its ability to increase cerebral blood flow (CBF), and the secondary impact of changes on the upper limb motor function and functional outcomes. OBJECTIVE To explore the effect of IntelliRehab on CBF in chronic stroke patients and its correlation with the upper limb motor function. METHODS Two-dimensional pulsed Arterial Spin Labelling (2D-pASL) was used to obtain CBF images of stable, chronic stroke subjects (n = 8) over 3-months intervention period. CBF alterations were mapped, and the detected differences were marked as regions of interest. Motor functions represented by Fugl-Meyer Upper Extremity Assessment (FMA) and Stroke Impact Scale (SIS) were used to assess the primary and secondary outcomes, respectively. RESULTS Regional CBF were significantly increased in right inferior temporal gyrus and left superior temporal white matter after 1-month (p = 0.044) and 3-months (p = 0.01) of rehabilitation, respectively. However, regional CBF in left middle fronto-orbital gyrus significantly declined after 1-month of rehabilitation (p = 0.012). Moreover, SIS-Q7 and FMA scores significantly increased after 1-month and 3-months of rehabilitation. There were no significant correlations, however, between CBF changes and upper limb motor function. CONCLUSIONS Participants demonstrated improved motor functions, supporting the benefit of using IntelliRehab as a tool for home-based rehabilitation. However, within-participant improvements may have limited potential that suggests the need for a timely administration of IntelliRehab to get the maximum capacity of improvement.
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Affiliation(s)
- Younis M S Firwana
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Mohd Khairul Izamil Zolkefley
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia.,Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Kuantan, Malaysia
| | - Hasnetty Zuria Mohamed Hatta
- Rehabilitation Unit, Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Christina Rowbin
- Rehabilitation Unit, Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Che Mohd Nasril Che Mohd Nassir
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia.,Kulliyyah of Islamic Revealed Knowledge and Human Sciences, International Islamic University Malaysia, Kuala Lumpur, Malaysia
| | - Muhammad Hafiz Hanafi
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia.,Rehabilitation Unit, Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Mohd Shafie Abdullah
- Department of Radiology, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Bilgin Keserci
- Department of Radiology, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Natasha A Lannin
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Muzaimi Mustapha
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia.
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15
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Graterol Pérez JA, Guder S, Choe CU, Gerloff C, Schulz R. Relationship Between Cortical Excitability Changes and Cortical Thickness in Subcortical Chronic Stroke. Front Neurol 2022; 13:802113. [PMID: 35345406 PMCID: PMC8957093 DOI: 10.3389/fneur.2022.802113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 01/31/2022] [Indexed: 11/21/2022] Open
Abstract
Ischemic stroke leads to excitability changes of the motor network as probed by means of transcranial magnetic stimulation (TMS). There is still limited data that shows to what extent structural alterations of the motor network might be linked to excitability changes. Previous results argue that the microstructural state of specific corticofugal motor tracts such as the corticospinal tract associate with cortical excitability in chronic stroke patients. The relationship between changes of cortical anatomy after stroke, as operationalized by means of decreases or increases in local cortical thickness (CT), has scarcely been addressed. In the present study, we re-analyzed TMS data and recruitment curve properties of motor evoked potentials and CT data in a group of 14 well-recovered chronic stroke patients with isolated supratentorial subcortical lesions. CT data of the stroke patients were compared to CT data of 17 healthy controls. Whole-brain and region-of-interest based analyses were conducted to relate CT data to measures of motor cortical excitability and clinical data. We found that stroke patients exhibited significantly reduced CT not only in the ipsilesional primary motor cortex but also in numerous secondary motor and non-motor brain regions, particularly in the ipsilesional hemisphere including areas along the central sulcus, the inferior frontal sulcus, the intraparietal sulcus, and cingulate cortices. We could not detect any significant relationship between the extent of CT reduction and stroke-related excitability changes of the motor network or clinical scores.
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Affiliation(s)
- José A Graterol Pérez
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stephanie Guder
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Chi-Un Choe
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Robert Schulz
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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16
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Wei Y, Wang C, Liu J, Miao P, Wu L, Wang Y, Wang K, Cheng J. Longitudinal gray matter atrophy and accompanied functional connectivity alterations in patients with pontine infarction. Neurol Res 2021; 44:667-676. [PMID: 34937529 DOI: 10.1080/01616412.2021.2018122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVES To investigate the longitudinal changes in gray matter volume (GMV) and functional connectivity (FC) in patients with pontine infarction (PI) during a 6-month follow-up period. METHODS Twenty-two patients underwent MRI scans and behavioral assessments at 1 week, 1 month, 3 months, and 6 months after PI. Twenty-two normal controls (NC) were administered once with a similar examination. Voxel-wise GMV analysis was used to investigate the difference between the 1 week of PI and NC groups. Longitudinal changes in GMV were assessed and then used as seed regions to explore the accompanying FC changes during the 6-month follow-up. Correlations of the behavioral scores with the imaging indices of clusters with altered GMV and FC were also investigated. RESULTS The LPI group exhibited GMV atrophy in the left cerebellar Crus II, right cerebellar lobule VI, right Vermis VI, while the RPI group showed GMV atrophy in the left cerebellar Crus II. The significant decrease of GMV firstly appeared at 1 month and gradually decreased over time. When using brain regions with GMV atrophy as seeds, longitudinal analysis of FC showed a significant decrease between the left cerebellar Crus II and left middle frontal gyrus at 6 months in the LPI group. Furthermore, the longitudinally altered FC values were negatively correlated with motor scores over time. CONCLUSION These findings provide evidence for progressive GMV atrophy in the cerebellum and impaired relative FC in patients with PI, which could provide vital information for investigating neural bases of behavioral recovery in PI.
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Affiliation(s)
- Ying Wei
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Caihong Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingchun Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Peifang Miao
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Luobing Wu
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yingying Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- Department of MR research, GE Healthcare, Beijing, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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17
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Chen Y, Jiang Y, Kong X, Zhao C, Zhong S, Yang L, Feng T, Peng S, Bi Y, Corbetta M, Gong G. Common and unique structural plasticity after left and right hemisphere stroke. J Cereb Blood Flow Metab 2021; 41:3350-3364. [PMID: 34415210 PMCID: PMC8669287 DOI: 10.1177/0271678x211036606] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Strokes to the left and right hemisphere lead to distinctive behavioral profiles. Are left and right hemisphere strokes (LHS and RHS) associated with distinct or common poststroke neuroplasticity patterns? Understanding this issue would reveal hemispheric neuroplasticity mechanisms in response to brain damage. To this end, we investigated poststroke structural changes (2 weeks to 3 months post-onset) using longitudinal MRI data from 69 LHS and 55 RHS patients and 31 demographic-matched healthy control participants. Both LHS and RHS groups showed statistically common plasticity independent of the lesioned hemisphere, including 1) gray matter (GM) expansion in the ipsilesional and contralesional precuneus, and contralesional superior frontal gyrus; 2) GM shrinkage in the ipsilesional medial orbital frontal gyrus and middle cingulate cortex. On the other hand, only RHS patients had significant GM expansion in the ipsilesional medial superior and orbital frontal cortex. Importantly, these common and unique GM changes post-stroke largely overlapped with highly-connected cortical hub regions in healthy individuals. Moreover, they correlated with behavioral recovery, indicating that post-stroke GM volumetric changes in cortical hubs reflect compensatory rather than maladaptive mechanisms. These results highlight the importance of structural neuroplasticity in hub regions of the cortex, along with the hemispheric specificity, for stroke recovery.
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Affiliation(s)
- Yijun Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yaya Jiang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Xiangyu Kong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chenxi Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Suyu Zhong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Liyuan Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tao Feng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.,Department of Rehabilitation, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
| | - Shaoling Peng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yanchao Bi
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Maurizio Corbetta
- Department of Neuroscience, Neurology Clinic, University of Padua, Padua, Italy.,Padova Neuroscience Center, University of Padua, Padua, Italy.,Venetian Institute of Molecular Medicine, Padova, Italy.,Department of Neurology, Radiology, and Neuroscience, Washington University in St. Louis, St. Louis, USA
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
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18
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Cai H, Zhao Z, Ni L, Han G, Hu X, Wu D, Ding X, Wang J. Structural and Functional Deficits in Patients with Poststroke Dementia: A Multimodal MRI Study. Neural Plast 2021; 2021:3536234. [PMID: 34777496 PMCID: PMC8580696 DOI: 10.1155/2021/3536234] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/25/2021] [Accepted: 10/12/2021] [Indexed: 11/30/2022] Open
Abstract
Although many neuroimaging studies have reported structural and functional abnormalities in the brains of patients with cognitive impairments following stroke, little is known about the pattern of such brain reorganization in poststroke dementia (PSD). The present study was aimed at investigating alterations in spontaneous brain activity and gray matter volume (GMV) in PSD patients. We collected T1-weighted and resting-state functional magnetic resonance imaging data from 20 PSD patients, 24 poststroke nondementia (PSND) patients, and 21 well-matched normal controls (NCs). We compared the differences among the groups in GMV and the fractional amplitude of low-frequency fluctuations (fALFF). Then, we evaluated the relationship between these brain measures and cognitive assessments and explored the possible distinguisher for PSD by receiver operating characteristic (ROC) curve analysis. PSD patients showed smaller GMV in the right superior temporal gyrus and lower fALFF values in the right inferior frontal gyrus than both PSND patients and NCs, but such differences were not observed between PSND patients and NCs. Moreover, GMV in the left medial prefrontal cortex showed a significant positive correlation with the Mini-Cog assessment in PSD patients, and GMV in the left CPL displayed the highest area under the ROC curve among all the features for classifying PSD versus PSND patients. Our findings suggest that PSD patients show dementia-specific structural and functional alteration patterns, which may help elucidate the pathophysiological mechanisms underlying PSD.
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Affiliation(s)
- Huaying Cai
- Department of Neurology, Neuroscience Center, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Linhui Ni
- Department of Neurology, Neuroscience Center, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
| | - Guocan Han
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
| | - Xingyue Hu
- Department of Neurology, Neuroscience Center, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Xianjun Ding
- Department of Orthopaedic Surgery, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
| | - Jin Wang
- Department of Neurology, Neuroscience Center, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
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Zhao Y, Zhang C, Yang H, Liu C, Yu T, Lu J, Chen N, Li K. Recovery of cortical atrophy in patients with temporal lobe epilepsy after successful anterior temporal lobectomy. Epilepsy Behav 2021; 123:108272. [PMID: 34500432 DOI: 10.1016/j.yebeh.2021.108272] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/09/2021] [Accepted: 08/14/2021] [Indexed: 11/30/2022]
Abstract
The aims of this study were to investigate whether the cortical atrophy caused by temporal lobe epilepsy (TLE) was reversible after successful anterior temporal lobectomy (ATL) and to further observe whether possible changes are related to age at surgery and cognitive changes. Twelve patients with unilateral mesial TLE who received ATL and remained seizure free in one year follow-up were included. They underwent two MRI scans few days before and oneyear after surgery. Thirty age- and sex-matched healthy participants were recruited as controls. Group comparisons were used to test the differences in cortical thickness (CTh) between the pre-/postsurgical patients and controls. Longitudinal test was used to directly show postsurgical changes of the patients. Besides, the correlations between regional cortical volume (CVo) changes and age at surgery or cognitive changes were also tested. Compared with controls, the patients with TLE showed dispersed cortical thinning especially in the bilateral frontal lobes before surgery and no significant cortical thinning except for cortices near the resected areas after surgery. The longitudinal analysis showed CTh increment in the ipsilateral precentral and postcentral gyrus, cuneus and widespread in the contralateral cortex. In the volumetric analysis, the CVo changes in the contralateral hemisphere were negatively correlated with age at surgery and positively correlated with MoCA score changes. This study suggests that the cortical atrophy caused by TLE could recover after successful ATL. The recovery ability is greater in younger subjects and is positively related to cognitive recovery. These findings could serve as new clues that patients with TLE can benefit from timely and successful ATL.
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Affiliation(s)
- Yongxiang Zhao
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing 100053, PR China
| | - Chao Zhang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing 100053, PR China; Department of Radiology, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu Province 221006, PR China
| | - Hongyu Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing 100053, PR China; Department of Radiology, Luhe Hospital, Capital Medical University, Beijing 101100, PR China
| | - Chang Liu
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China
| | - Tao Yu
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing 100053, PR China
| | - Nan Chen
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing 100053, PR China.
| | - Kuncheng Li
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing 100053, PR China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing 100053, PR China.
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20
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Wu L, Wang C, Liu J, Guo J, Wei Y, Wang K, Miao P, Wang Y, Cheng J. Voxel-Mirrored Homotopic Connectivity Associated With Change of Cognitive Function in Chronic Pontine Stroke. Front Aging Neurosci 2021; 13:621767. [PMID: 33679376 PMCID: PMC7929989 DOI: 10.3389/fnagi.2021.621767] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 01/18/2021] [Indexed: 12/14/2022] Open
Abstract
Recent neuroimaging studies have shown the possibility of cognitive impairment after pontine stroke. In this study, we aimed to use voxel-mirrored homotopic connectivity (VMHC) to investigate changes in the cognitive function in chronic pontine stroke. Functional MRI (fMRI) and behavioral assessments of cognitive function were obtained from 56 patients with chronic pontine ischemic stroke [28 patients with left-sided pontine stroke (LP) and 28 patients with right-sided pontine stroke (RP)] and 35 matched healthy controls (HC). The one-way ANOVA test was performed for the three groups after the VMHC analysis. Results showed that there were significant decreases in the bilateral lingual gyrus (Lingual_L and Lingual_R) and the left precuneus (Precuneus_L) in patients with chronic pontine ischemic stroke compared to HCs. However, in a post-hoc multiple comparison test, this difference remained only between the HC and RP groups. Moreover, we explored the relationship between the decreased z-values in VMHC and the behavior-task scores using a Pearson's correlation test and found that both scores of short-term memory and long-term memory in the Rey Auditory Verbal Learning Test were positively correlated with z-values of the left lingual gyrus (Lingual_L), the right lingual gyrus (Lingual_R), and the left precuneus (Precuneus_L) in VMHC. Besides that, the z-values of Precuneus_L in VMHC were also negatively correlated with the reaction time for correct responses in the Flanker task and the spatial memory task. In conclusion, first, the lingual gyrus played an important role in verbal memory. Second, the precuneus influenced the working memory, both auditory-verbal memory and visual memory. Third, the right-sided stroke played a greater role in the results of this study. This study provides a basis for further elucidation of the characteristics and mechanisms of cognitive impairment after pontine stroke.
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Affiliation(s)
- Luobing Wu
- Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Caihong Wang
- Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingchun Liu
- Tianjin Key Laboratory of Functional Imaging, Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Jun Guo
- Department of Radiology, Tianjin Huanhu Hospital, Tianjin, China
| | - Ying Wei
- Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- GE Healthcare MR Research, Beijing, China
| | - Peifang Miao
- Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yingying Wang
- Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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21
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Peng Y, Zhang X, Li Y, Su Q, Wang S, Liu F, Yu C, Liang M. MVPANI: A Toolkit With Friendly Graphical User Interface for Multivariate Pattern Analysis of Neuroimaging Data. Front Neurosci 2020; 14:545. [PMID: 32742251 PMCID: PMC7364177 DOI: 10.3389/fnins.2020.00545] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 05/04/2020] [Indexed: 12/03/2022] Open
Abstract
With the rapid development of machine learning techniques, multivariate pattern analysis (MVPA) is becoming increasingly popular in the field of neuroimaging data analysis. Several software packages have been developed to facilitate its application in neuroimaging studies. As most of these software packages are based on command lines, researchers are required to learn how to program, which has greatly limited the use of MVPA for researchers without programming skills. Moreover, lacking a graphical user interface (GUI) also hinders the standardization of the application of MVPA in neuroimaging studies and, consequently, the replication of previous studies or comparisons of results between different studies. Therefore, we developed a GUI-based toolkit for MVPA of neuroimaging data: MVPANI (MVPA for Neuroimaging). Compared with other existing software packages, MVPANI has several advantages. First, MVPANI has a GUI and is, thus, more friendly for non-programmers. Second, MVPANI offers a variety of machine learning algorithms with the flexibility of parameter modification so that researchers can test different algorithms and tune parameters to identify the most suitable algorithms and parameters for their own data. Third, MVPANI also offers the function of data fusion at two levels (feature level or decision level) to utilize complementary information contained in different measures obtained from multimodal neuroimaging techniques. In this paper, we introduce this toolkit and provide four examples to demonstrate its usage, including (1) classification between patients and controls, (2) identification of brain areas containing discriminating information, (3) prediction of clinical scores, and (4) multimodal data fusion.
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Affiliation(s)
- Yanmin Peng
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Xi Zhang
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Yifan Li
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Qian Su
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Sijia Wang
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
| | - Feng Liu
- Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.,Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Chunshui Yu
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.,Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Meng Liang
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.,Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China
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22
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Liu H, Peng X, Dahmani L, Wang H, Zhang M, Shan Y, Rong D, Guo Y, Li J, Li N, Wang L, Lin Y, Pan R, Lu J, Wang D. Patterns of motor recovery and structural neuroplasticity after basal ganglia infarcts. Neurology 2020; 95:e1174-e1187. [PMID: 32586896 DOI: 10.1212/wnl.0000000000010149] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 03/02/2020] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE To elucidate the timeframe and spatial patterns of cortical reorganization after different stroke-induced basal ganglia lesions, we measured cortical thickness at 5 time points over a 6-month period. We hypothesized that cortical reorganization would occur very early and that, along with motor recovery, it would vary based on the stroke lesion site. METHODS Thirty-three patients with unilateral basal ganglia stroke and 23 healthy control participants underwent MRI scanning and behavioral testing. To further decrease heterogeneity, we split patients into 2 groups according to whether or not the lesions mainly affect the striatal motor network as defined by resting-state functional connectivity. A priori measures included cortical thickness and motor outcome, as assessed with the Fugl-Meyer scale. RESULTS Within 14 days poststroke, cortical thickness already increased in widespread brain areas (p = 0.001), mostly in the frontal and temporal cortices rather than in the motor cortex. Critically, the 2 groups differed in the severity of motor symptoms (p = 0.03) as well as in the cerebral reorganization they exhibited over a period of 6 months (Dice overlap index = 0.16). Specifically, the frontal and temporal regions demonstrating cortical thickening showed minimal overlap between these 2 groups, indicating different patterns of reorganization. CONCLUSIONS Our findings underline the importance of assessing patients early and of considering individual differences, as patterns of cortical reorganization differ substantially depending on the precise location of damage and occur very soon after stroke. A better understanding of the macrostructural brain changes following stroke and their relationship with recovery may inform individualized treatment strategies.
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Affiliation(s)
- Hesheng Liu
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Xiaolong Peng
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Louisa Dahmani
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Hongfeng Wang
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Miao Zhang
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Yi Shan
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Dongdong Rong
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Yanjun Guo
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Junchao Li
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Nianlin Li
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Long Wang
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Yuanxiang Lin
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Ruiqi Pan
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
| | - Jie Lu
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China.
| | - Danhong Wang
- From the Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology (H.L., X.P., L.D., H.W., J. Li, N.L., R.P., D.W.), Massachusetts General Hospital, Harvard Medical School, Charlestown; Beijing Institute for Brain Disorders (H.L.), Departments of Radiology (M.Z., Y.S., D.R., J. Lu) and Nuclear Medicine (J. Lu), Xuanwu Hospital, and Department of Neurology, Beijing Friendship Hospital (Y.G.), Capital Medical University; Liaoyuan Hospital of Traditional Chinese Medicine (L.W.); Department of Neurosurgery (Y.L.), First Affiliated Hospital, Fujian Medical University, Fuzhou, China; Department of Neuroscience (H.L., X.P.), Medical University of South Carolina, Charleston; Department of Radiology (X.P.), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan; Changchun University of Chinese Medicine (H.W.); and Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics (M.Z., Y.S., D.R., J. Lu), China
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23
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Liu J, Wang C, Qin W, Ding H, Guo J, Han T, Cheng J, Yu C. Corticospinal Fibers With Different Origins Impact Motor Outcome and Brain After Subcortical Stroke. Stroke 2020; 51:2170-2178. [PMID: 32568657 DOI: 10.1161/strokeaha.120.029508] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Motor deficit is the most common disability after stroke, and early prediction of motor outcome is critical for early interventions. Here, we constructed a fine map of the corticospinal tract (CST) for early prediction of motor outcome and for understanding the secondary brain changes after subcortical stroke. METHODS Diffusion spectrum imaging data from 50 healthy adults were used to reconstruct fine maps of CST with different origins, including primary motor area (M1), primary sensory area (S1), premotor cortex, and supplementary motor area (SMA). Their diffusion properties correlated with motor functions in healthy adults. The impacts of the impairments of different CST on motor outcomes and on structural and functional changes of brain were investigated in 136 patients with subcortical stroke by combining CST damage-symptom association study and voxel-based lesion-symptom mapping. RESULTS In healthy adults, the isotropy of M1 fiber correlated with walking endurance and that of SMA fiber with motor dexterity. In chronic stroke patients, the integrity of M1 and SMA fibers showed the most significant correlation with motor deficits. The percentage of early damage of M1 and SMA fibers correlated with that of chronic motor deficits. Voxel-based lesion-symptom mapping revealed that acute stroke lesions in the bilateral M1 and right SMA fibers were associated with chronic motor deficits. The early damage of M1 fiber negatively correlated with the integrity of M1-M1 fiber, and the early damage of SMA fiber negatively correlated with gray matter volume of the contralateral cerebellum in the chronic stage. CONCLUSIONS The CST that originated from the M1 and SMA are closely associated with motor outcomes and brain structural changes, and the fine maps of CST from these 2 cortical areas are useful in assessing and predicting long-term motor outcome in patients with subcortical stroke.
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Affiliation(s)
- Jingchun Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, China (J.L., W.Q., H.D., C.Y.)
| | - Caihong Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Henan, China (C.W., J.C.)
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, China (J.L., W.Q., H.D., C.Y.)
| | - Hao Ding
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, China (J.L., W.Q., H.D., C.Y.)
| | - Jun Guo
- Department of Medical Imaging, Tianjin Medical University, China (H.D.). Department of Radiology, Tianjin Huanhu Hospital, China (J.G., T.H.)
| | - Tong Han
- Department of Medical Imaging, Tianjin Medical University, China (H.D.). Department of Radiology, Tianjin Huanhu Hospital, China (J.G., T.H.)
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Henan, China (C.W., J.C.)
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, China (J.L., W.Q., H.D., C.Y.)
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24
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Diao Q, Liu J, Zhang X. Enhanced positive functional connectivity strength in left-sided chronic subcortical stroke. Brain Res 2020; 1733:146727. [PMID: 32061738 DOI: 10.1016/j.brainres.2020.146727] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 02/08/2020] [Accepted: 02/13/2020] [Indexed: 01/20/2023]
Abstract
Patients with stroke often exhibit evidence of abnormal functional connectivity (FC). However, whether and how anatomical distance affects FC at rest remains unclear in patients with chronic subcortical stroke. Eighty-six patients with chronic (more than six months post-onset) subcortical stroke (44 left-sided patients and 42 right-sided patients) with different degrees of functional recovery, and 75 matched healthy controls underwent resting-state functional magnetic resonance imaging scanning. Positive functional connectivity strength (FCS) was computed for each voxel in the brain using a data-driven whole-brain resting state FCS method, which was further divided into short- and long-range FCS. Compared with healthy controls, patients with left-sided infarctions exhibited stronger global- and long-range FCS in the left sensorimotor cortex (SMC), and no significant intergroup difference was found for short-range FCS. No significant differences were found between the patients with right-sided infarctions and healthy controls for global, long- and short-range FCS. These findings suggested that the positive FCS alteration was connection-distance dependent within patients with left-sided chronic subcortical stroke. Also, a positive correlation was found between the FCS in the left SMC and the accuracy of the Flanker test, reflecting a compensatory FCS alteration for altered attention and executive function abilities exhibited by those with left-sided stroke.
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Affiliation(s)
- Qingqing Diao
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, China
| | - Jingchun Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xuejun Zhang
- School of Medical Imaging, Tianjin Medical University, Tianjin, China.
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25
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Wang C, Miao P, Liu J, Wei S, Guo Y, Li Z, Zheng D, Cheng J. Cerebral blood flow features in chronic subcortical stroke: Lesion location-dependent study. Brain Res 2019; 1706:177-183. [DOI: 10.1016/j.brainres.2018.11.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Revised: 11/07/2018] [Accepted: 11/08/2018] [Indexed: 02/07/2023]
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26
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Wang C, Zhao L, Luo Y, Liu J, Miao P, Wei S, Shi L, Cheng J. Structural covariance in subcortical stroke patients measured by automated MRI-based volumetry. NEUROIMAGE-CLINICAL 2019; 22:101682. [PMID: 30710874 PMCID: PMC6357849 DOI: 10.1016/j.nicl.2019.101682] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 12/27/2018] [Accepted: 01/20/2019] [Indexed: 12/03/2022]
Abstract
A network-level investigation of the volumetric changes of subcortical stroke patients is still lacking. Here, we explored the alterations of structural covariance caused by subcortical stroke with automated brain volumetry. T1-weighed brain MRI scans were obtained from 63 normal controls (NC), 46 stroke patients with infarct in left internal capsule (CI_L), 33 stroke patients with infarct in right internal capsule (CI_R). We performed automatic anatomical segmentation of the T1-weighted brain images with AccuBrain. Volumetric structural covariance analyses were first performed within the basal ganglia structures that were both identified by voxel-based morphometry with AAL atlas and AccuBrain. Subsequently, we additionally included the infratentorial regions that were particularly quantified by AccuBrain for the structural covariance analyses and investigated the alterations of anatomical connections within these subcortical regions in CI_L and CI_R compared with NC. The association between the regional brain volumetry and motor function was also evaluated in stroke groups. There were significant and extensive volumetric differences in stroke patients. These significant regions were generally symmetric for CI_L and CI_R group depending on the side of stroke, involving both regions close to lesions and remote regions. The structural covariance analyses revealed the synergy volume alteration in subcortical regions both in CI_L and CI_R group. In addition, the alterations of volumetric structural covariance were more extensive in CI_L group than CI_R group. Moreover, we found that the subcortical regions with atrophy contributed to the deficits of motor function in CI_R group but not CI_L group, indicating a lesion-side effect of brain volumetric changes after stroke. These findings indicated that the chronic subcortical stroke patients have extensive disordered anatomical connections involving the whole-brain level network, and the connections patterns depend on the lesion-side. Chronic subcortical stroke patients show extensive brain volumetric atrophy. Subcortical stroke patients show disordered structural covariance network pattern. Brain volumetric and connections patterns change depend on the lesion-side.
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Affiliation(s)
- Caihong Wang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lei Zhao
- BrainNow Research Institute, Shenzhen, Guangdong Province, China
| | - Yishan Luo
- BrainNow Research Institute, Shenzhen, Guangdong Province, China
| | - Jingchun Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Peifang Miao
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Sen Wei
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lin Shi
- BrainNow Research Institute, Shenzhen, Guangdong Province, China; Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, Hong Kong.
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
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27
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Wang P, Jia X, Zhang M, Cao Y, Zhao Z, Shan Y, Ma Q, Qian T, Wang J, Lu J, Li K. Correlation of Longitudinal Gray Matter Volume Changes and Motor Recovery in Patients After Pontine Infarction. Front Neurol 2018; 9:312. [PMID: 29910762 PMCID: PMC5992285 DOI: 10.3389/fneur.2018.00312] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 04/19/2018] [Indexed: 11/18/2022] Open
Abstract
The mechanisms of motor functional recovery after pontine infarction (PI) remain unclear. Here, we assessed longitudinal changes in gray matter volume (GMV) and examined the relationship between GMV and clinical outcome. Fifteen patients with unilateral PI underwent magnetic resonance imaging and neurological exams five times during a period of 6 months. Another 15 healthy participants were enrolled as the normal control (NC) group and were examined with the same protocol. The MR exam included routine protocol and a 3D T1-weighted magnetization-prepared rapid acquisition gradient echo scan. Changes in GMV were assessed using voxel-based morphometry. Furthermore, the correlations between GMV changes in regions of interest and clinical scores were assessed. Compared with NCs, the decreased GMVs in the contralateral uvula of cerebellum and the ipsilateral tuber of cerebellum were detected at third month after stroke onset. At the sixth month after stroke onset, the decreased GMVs were detected in the contralateral culmen of cerebellum, putamen, as well as in the ipsilateral tuber/tonsil of cerebellum. Compared with NC, the PI group exhibited significant increases in GMV at each follow-up time point relative to stroke onset. Specifically, the significant GMV increase was found in the ipsilateral middle frontal gyrus and ventral anterior nucleus of thalamus at second week after stroke onset. At first month after stroke onset, the increased GMVs in the ipsilateral middle temporal gyrus were detected. The significant GMV increase in the ipsilateral mediodorsal thalamus was noted at third month after stroke onset. At the end of sixth month after stroke onset, the GMV increase was found in the ipsilateral mediodorsal thalamus, superior frontal gyrus, and the contralateral precuneus. Across five times during a period of 6-month, a negative correlation was observed between mean GMV in the contralateral uvula, culmen, putamen, and ipsilateral tuber/tonsil and mean Fugl-Meyer (FM) score. However, mean GMV in the ipsilateral mediodorsal thalamus was positively correlated with mean FM score. Our findings suggest that structural reorganization of the ipsilateral mediodorsal thalamus might contribute to motor functional recovery after PI.
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Affiliation(s)
- Peipei Wang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Xiuqin Jia
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Radiology, Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Miao Zhang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yanxiang Cao
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Zhilian Zhao
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Yi Shan
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Qingfeng Ma
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tianyi Qian
- Collaborations NE Asia, Siemens Healthcare, Beijing, China
| | - Jingjuan Wang
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China.,Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
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