Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indice...Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.展开更多
AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished...AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished by differences in dynamic amplitude of low-frequency fluctuations(dALFF)in specific brain regions.METHODS:The resting-state functional magnetic resonance imaging(rs-fMRI)data were collected from 15 myopic patients who underwent LASIK and 15 matched healthy controls.This method was selected to calculate the corresponding dALFF values of each participant,to compare dALFF between the groups and to determine whether dALFF distinguishes reliably between myopic patients after LASIK and HCs using the linear support vector machine(SVM)permutation test(5000 repetitions).RESULTS:dALFF was lower in POL than in HCs at the right precentral gyrus and right insula.Classification accuracy of the SVM was 89.1%(P<0.001).CONCLUSION:The activity of spontaneous neurons in the right precentral gyrus and right insula of myopic patients change significantly after LASIK.SVM can correctly classify POL patients and HCs based on dALFF differences.展开更多
Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson’s disease(PD)with mild cognitive impairment(MCI)is a focus in resting-state functional MRI(rs-fMRI)studies.This study aimed to i...Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson’s disease(PD)with mild cognitive impairment(MCI)is a focus in resting-state functional MRI(rs-fMRI)studies.This study aimed to investigate the alteration of brain functional connectivity in PD with MCI in a systematical way at two levels:functional connectivity analysis within resting state networks(RSNs)and functional network connectivity(FNC)analysis.Using group independent component analysis(ICA)on rs-fMRI data acquired from 30 participants(14 healthy controls and 16 PD patients with MCI),16 RSNs were identified,and functional connectivity analysis within the RSNs and FNC analysis were carried out between groups.Compared to controls,patients with PD showed decreased functional connectivity within putamen network,thalamus network,cerebellar network,attention network,and self-referential network,and increased functional connectivity within execution network.Globally disturbed,mostly increased functional connectivity of FNC was observed in PD group,and insular network and execution network were the dominant network with extensively increased functional connectivity with other RSNs.Cerebellar network showed decreased functional connectivity with caudate network,insular network,and self-referential network.In general,decreased functional connectivity within RSNs and globally disturbed,mostly increased functional connectivity of FNC may be characteristics of PD.Increased functional connectivity within execution network may be an early marker of PD.The multi-perspective study based on RSNs may be a valuable means to assess functional changes corresponding to specific RSN,contributing to the understanding of the neural mechanism of PD.展开更多
Epilepsy is a disease characterized by abnormal spontaneous activity in the brain.Resting-state functional magnetic resonance imaging（RS-fMRI） is a powerful technique for exploring this activity.With good spatial an...Epilepsy is a disease characterized by abnormal spontaneous activity in the brain.Resting-state functional magnetic resonance imaging（RS-fMRI） is a powerful technique for exploring this activity.With good spatial and temporal resolution,RS-fMRI is a promising approach for accurate localization of the focus of seizure activity.Although simultaneous electroencephalogram-fMRI has been performed with patients in the resting state,most studies focused on activation.This mini-review focuses on RS-fMRI alone,including its computational methods and its application to epilepsy.展开更多
Tension-type headache（TTH） is the most prevalent type of primary headache. Many studies have shown that the pathogenesis of primary headache is associated with fine structural or functional changes. However, these s...Tension-type headache（TTH） is the most prevalent type of primary headache. Many studies have shown that the pathogenesis of primary headache is associated with fine structural or functional changes. However, these studies were mainly based on migraine. The present study aimed to investigate whether TTH patients show functional disturbances compared with healthy subjects. We used restingstate functional magnetic resonance imaging（f MRI） and regional homogeneity（Re Ho） analysis to identify changes in the local synchronization of spontaneous activity in patients with TTH. Ten patients with TTH and 10 age-, gender-, and education-matched healthy controls participated in the study. After demographic and clinical characteristics were acquired, a 3.0-T MRI system was used to obtain restingstate f MRIs. Compared with healthy controls, the TTH group exhibited significantly lower Re Ho values in the bilateral caudate nucleus, the precuneus, the putamen, the left middle frontal gyrus, and the superior frontal gyrus. There was no correlation between mean Re Ho values in TTH patients and duration of TTH, number of attacks, duration of daily attacks, Visual Analogue Scale score, or Headache Impact Test-6 score. These results suggest that TTHpatients exhibit reduced synchronization of neuronal activity in multiple regions involved in the integration and processing of pain signals.展开更多
Attention deficit and hyperactivity disorder（ADHD） is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influen...Attention deficit and hyperactivity disorder（ADHD） is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influenced by the complex interaction of brain networks which were under explored.We explored age-related brain network differences between ADHD patients and typically developing（TD） subjects using resting state f MRI（rs-f MRI） for three age groups of children,adolescents,and adults.We collected rs-f MRI data from 184 individuals（27 ADHD children and 31 TD children;32 ADHD adolescents and 32 TD adolescents;and 31 ADHD adults and 31 TD adults）.The Brainnetome Atlas was used to define nodes in the network analysis.We compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality,a well-known measure of nodal centrality.The left middle temporal gyrus showed significant interaction effects between disease status（i.e.,ADHD or TD） and age（i.e.,child,adolescent,or adult）（P 0.001）.Additional regions were identified at a relaxed threshold（P 0.05）.Many of the identified regions（the left inferior frontal gyrus,the left middle temporal gyrus,and the left insular gyrus） were related to cognitive function.The results of our study suggest that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients.These findings contribute to better understand how brain function influences the symptoms of ADHD.展开更多
基金supported by the National Natural Science Foundation of China,No.82071909(to GF)the Natural Science Foundation of Liaoning Province,No.2023-MS-07(to HL)。
文摘Freezing of gait is a significant and debilitating motor symptom often observed in individuals with Parkinson's disease.Resting-state functional magnetic resonance imaging,along with its multi-level feature indices,has provided a fresh perspective and valuable insight into the study of freezing of gait in Parkinson's disease.It has been revealed that Parkinson's disease is accompanied by widespread irregularities in inherent brain network activity.However,the effective integration of the multi-level indices of resting-state functional magnetic resonance imaging into clinical settings for the diagnosis of freezing of gait in Parkinson's disease remains a challenge.Although previous studies have demonstrated that radiomics can extract optimal features as biomarkers to identify or predict diseases,a knowledge gap still exists in the field of freezing of gait in Parkinson's disease.This cross-sectional study aimed to evaluate the ability of radiomics features based on multi-level indices of resting-state functional magnetic resonance imaging,along with clinical features,to distinguish between Parkinson's disease patients with and without freezing of gait.We recruited 28 patients with Parkinson's disease who had freezing of gait(15 men and 13 women,average age 63 years)and 30 patients with Parkinson's disease who had no freezing of gait(16 men and 14 women,average age 64 years).Magnetic resonance imaging scans were obtained using a 3.0T scanner to extract the mean amplitude of low-frequency fluctuations,mean regional homogeneity,and degree centrality.Neurological and clinical characteristics were also evaluated.We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators.We then performed predictive analysis of three distinct groups based on resting-state functional magnetic resonance imaging indicators indicators combined with clinical features.Subsequently,we conducted 100 additional five-fold cross-validations to determine the most effective model for each classification task and evaluated the performance of the model using the area under the receiver operating characteristic curve.The results showed that when differentiating patients with Parkinson's disease who had freezing of gait from those who did not have freezing of gait,or from healthy controls,the models using only the mean regional homogeneity values achieved the highest area under the receiver operating characteristic curve values of 0.750(with an accuracy of 70.9%)and 0.759(with an accuracy of 65.3%),respectively.When classifying patients with Parkinson's disease who had freezing of gait from those who had no freezing of gait,the model using the mean amplitude of low-frequency fluctuation values combined with two clinical features achieved the highest area under the receiver operating characteristic curve of 0.847(with an accuracy of 74.3%).The most significant features for patients with Parkinson's disease who had freezing of gait were amplitude of low-frequency fluctuation alterations in the left parahippocampal gyrus and two clinical characteristics:Montreal Cognitive Assessment and Hamilton Depression Scale scores.Our findings suggest that radiomics features derived from resting-state functional magnetic resonance imaging indices and clinical information can serve as valuable indices for the identification of freezing of gait in Parkinson's disease.
基金Supported by National Natural Science Foundation of China(No.82160195No.82460203)Key R&D Program of Jiangxi Province(No.20223BBH80014).
文摘AIM:To investigate changes in local brain activity after laser assisted in situ keratomileusis(LASIK)in myopia patients,and further explore whether post-LASIK(POL)patients and healthy controls(HCs)can be distinguished by differences in dynamic amplitude of low-frequency fluctuations(dALFF)in specific brain regions.METHODS:The resting-state functional magnetic resonance imaging(rs-fMRI)data were collected from 15 myopic patients who underwent LASIK and 15 matched healthy controls.This method was selected to calculate the corresponding dALFF values of each participant,to compare dALFF between the groups and to determine whether dALFF distinguishes reliably between myopic patients after LASIK and HCs using the linear support vector machine(SVM)permutation test(5000 repetitions).RESULTS:dALFF was lower in POL than in HCs at the right precentral gyrus and right insula.Classification accuracy of the SVM was 89.1%(P<0.001).CONCLUSION:The activity of spontaneous neurons in the right precentral gyrus and right insula of myopic patients change significantly after LASIK.SVM can correctly classify POL patients and HCs based on dALFF differences.
基金This project was supported by grants from National Natural Science Foundation of China(No.81701655 and No.81600317)Platform Research Foundation of Union Hospital,Tongji Medical College,Huazhong university of Science and Technology(No.02.03.2017-14).
文摘Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson’s disease(PD)with mild cognitive impairment(MCI)is a focus in resting-state functional MRI(rs-fMRI)studies.This study aimed to investigate the alteration of brain functional connectivity in PD with MCI in a systematical way at two levels:functional connectivity analysis within resting state networks(RSNs)and functional network connectivity(FNC)analysis.Using group independent component analysis(ICA)on rs-fMRI data acquired from 30 participants(14 healthy controls and 16 PD patients with MCI),16 RSNs were identified,and functional connectivity analysis within the RSNs and FNC analysis were carried out between groups.Compared to controls,patients with PD showed decreased functional connectivity within putamen network,thalamus network,cerebellar network,attention network,and self-referential network,and increased functional connectivity within execution network.Globally disturbed,mostly increased functional connectivity of FNC was observed in PD group,and insular network and execution network were the dominant network with extensively increased functional connectivity with other RSNs.Cerebellar network showed decreased functional connectivity with caudate network,insular network,and self-referential network.In general,decreased functional connectivity within RSNs and globally disturbed,mostly increased functional connectivity of FNC may be characteristics of PD.Increased functional connectivity within execution network may be an early marker of PD.The multi-perspective study based on RSNs may be a valuable means to assess functional changes corresponding to specific RSN,contributing to the understanding of the neural mechanism of PD.
基金supported by National Natural Science Foundation of Inner Mongolia Autonomous Region(2009MS1163)National Natural Science Foundation of China(81020108022,30770594)
文摘Epilepsy is a disease characterized by abnormal spontaneous activity in the brain.Resting-state functional magnetic resonance imaging（RS-fMRI） is a powerful technique for exploring this activity.With good spatial and temporal resolution,RS-fMRI is a promising approach for accurate localization of the focus of seizure activity.Although simultaneous electroencephalogram-fMRI has been performed with patients in the resting state,most studies focused on activation.This mini-review focuses on RS-fMRI alone,including its computational methods and its application to epilepsy.
基金supported by the National Natural Science Foundation of China (81071140)
文摘Tension-type headache（TTH） is the most prevalent type of primary headache. Many studies have shown that the pathogenesis of primary headache is associated with fine structural or functional changes. However, these studies were mainly based on migraine. The present study aimed to investigate whether TTH patients show functional disturbances compared with healthy subjects. We used restingstate functional magnetic resonance imaging（f MRI） and regional homogeneity（Re Ho） analysis to identify changes in the local synchronization of spontaneous activity in patients with TTH. Ten patients with TTH and 10 age-, gender-, and education-matched healthy controls participated in the study. After demographic and clinical characteristics were acquired, a 3.0-T MRI system was used to obtain restingstate f MRIs. Compared with healthy controls, the TTH group exhibited significantly lower Re Ho values in the bilateral caudate nucleus, the precuneus, the putamen, the left middle frontal gyrus, and the superior frontal gyrus. There was no correlation between mean Re Ho values in TTH patients and duration of TTH, number of attacks, duration of daily attacks, Visual Analogue Scale score, or Headache Impact Test-6 score. These results suggest that TTHpatients exhibit reduced synchronization of neuronal activity in multiple regions involved in the integration and processing of pain signals.
基金supported by the Institute for Basic Science[grant No.IBS-R015-D1]the National Research Foundation of Korea(grant No.NRF-2016R1A2B4008545)
文摘Attention deficit and hyperactivity disorder（ADHD） is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influenced by the complex interaction of brain networks which were under explored.We explored age-related brain network differences between ADHD patients and typically developing（TD） subjects using resting state f MRI（rs-f MRI） for three age groups of children,adolescents,and adults.We collected rs-f MRI data from 184 individuals（27 ADHD children and 31 TD children;32 ADHD adolescents and 32 TD adolescents;and 31 ADHD adults and 31 TD adults）.The Brainnetome Atlas was used to define nodes in the network analysis.We compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality,a well-known measure of nodal centrality.The left middle temporal gyrus showed significant interaction effects between disease status（i.e.,ADHD or TD） and age（i.e.,child,adolescent,or adult）（P 0.001）.Additional regions were identified at a relaxed threshold（P 0.05）.Many of the identified regions（the left inferior frontal gyrus,the left middle temporal gyrus,and the left insular gyrus） were related to cognitive function.The results of our study suggest that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients.These findings contribute to better understand how brain function influences the symptoms of ADHD.
