Vertebral artery orifice stenting may improve blood supply of the posterior circulation of the brain to regions such as the cerebellum and brainstem. However, previous studies have mainly focused on recovery of cerebr...Vertebral artery orifice stenting may improve blood supply of the posterior circulation of the brain to regions such as the cerebellum and brainstem. However, previous studies have mainly focused on recovery of cerebral blood flow and perfusion in the posterior circulation after interventional therapy. This study examined the effects of functional recovery of local brain tissue on cerebellar function remodeling using blood oxygen level-dependent functional magnetic reso- nance imaging before and after interventional therapy. A total of 40 Chinese patients with severe unilateral vertebral artery orifice stenosis were enrolled in this study. Patients were equally and randomly assigned to intervention and control groups. The control group received drug treat- ment only. The intervention group received vertebral artery orifice angioplasty and stenting ＋ identical drug treatment to the control group. At 13 days after treatment, the Dizziness Handicap Inventory score was compared between the intervention and control groups. Cerebellar function remodeling was observed between the two groups using blood oxygen level-dependent functional magnetic resonance imaging. The improvement in dizziness handicap and cerebellar function was more obvious in the intervention group than in the control group. Interventional therapy for severe vertebral artery orifice stenosis may effectively promote cerebellar function remodeling and exert neuroprotective effects.展开更多
Alzheimer’s disease (AD) is a dementing disorder and one of the major public health problems in countries with greater longevity. The cerebral cortical thickness and cerebral blood flow (CBF), which are considered as...Alzheimer’s disease (AD) is a dementing disorder and one of the major public health problems in countries with greater longevity. The cerebral cortical thickness and cerebral blood flow (CBF), which are considered as morphological and functional image features, respectively, could be decreased in specific cerebral regions of patients with dementia of Alzheimer type. Therefore, the aim of this study was to develop a computer-aided classification system for AD patients based on machine learning with the morphological and functional image features derived from a magnetic resonance (MR) imaging system. The cortical thicknesses in ten cerebral regions were derived as morphological features by using gradient vector trajectories in fuzzy membership images. Functional CBF maps were measured with an arterial spin labeling technique, and ten regional CBF values were obtained by registration between the CBF map and Talairach atlas using an affine transformation and a free form deformation. We applied two systems based on an arterial neural network (ANN) and a support vector machine (SVM), which were trained with 4 morphological and 6 functional image features, to 15 AD patients and 15 clinically normal (CN) subjects for classification of AD. The area under the receiver operating characteristic curve (AUC) values for the two systems based on the ANN and SVM with both image?features were 0.901 and 0.915, respectively. The AUC values for the ANN-and SVM-based systems with the morphological features were 0.710 and 0.660, respectively, and those with the functional features were 0.878 and 0.903, respectively. Our preliminary results suggest that the proposed method may have potential for assisting radiologists in the differential diagnosis of AD patients by using morphological and functional image features.展开更多
Background： About 50% of the cerebral ischemia events are induced by intracranial and extracranial atheroscterosis. This study aimed to evaluate the feasibility and accuracy for displaying atherosclerotic plaques in ...Background： About 50% of the cerebral ischemia events are induced by intracranial and extracranial atheroscterosis. This study aimed to evaluate the feasibility and accuracy for displaying atherosclerotic plaques in carotid arteries and analyzing their ingredients by using high-resolution new magnetic resonance imaging （MRI） techniques. Methods： Totally, 49 patients suspected ofextracranial carotid artery stenosis were subjected to cranial MRI scan and magnetic resonance angiography （MRA） examination on carotid arteries, and high-resolution bright-blood and black-blood MRI analysis was carried out within 1 week. Digital subtraction angiography （DSA） examination was carried out for 16 patients within I month. Results： Totally, 103 plaques were detected in the 49 patients, which were characterized by localized or diffusive thickening of the vessel wall, with the intrusion of crescent-shaped abnormal signal into lumens. Fibrous cap was displayed as isointensity in T I -weighted image （T I WI） and hyperintensities in proton density weighted image （PDWI） and T2-weighted image （T2WI）, lipid core was displayed as isointensity or slight hyperintensities in T1WI, isointensity, hyperintensities or hypointensity in PDWI, and hypointensity in T2WI. Calcification in plaques was detected in 11 patients. Eight patients were detected with irregular plaque surface or ulcerative plaques, which were characterized by irregular intravascular space surface in the black-blood sequences, black hypointensity band was not detected in three-dimensional time-of-flight, or the hypointensity band was not continuous, and intrusion of hyperintensities into plaques can be detected. Bright-blood and black-blood techniques were highly correlated with the diagnosis of contrast-enhanced MRA in angiostenosis degree, Rs 0.97, P 〈 0.001. In comparison to DSA, the sensitivity, specificity, and accuracy of MRI diagnosis of stenosis for ≥50% were 88.9%. 100%, and 97.9%, respectively. Conclusions： High-resolution bright-blood and black-blood sequential MRI analysis can accurately analyze ingredients in atherosclerotic plaques, Determined by DSA, MRI diagnosis of stenosis can correctly evaluate the serious degree of arteriostenosis.展开更多
BACKGROUND Automated,accurate,objective,and quantitative medical image segmentation has remained a challenging goal in computer science since its inception.This study applies the technique of convolutional neural netw...BACKGROUND Automated,accurate,objective,and quantitative medical image segmentation has remained a challenging goal in computer science since its inception.This study applies the technique of convolutional neural networks(CNNs)to the task of segmenting carotid arteries to aid in the assessment of pathology.AIM To investigate CNN’s utility as an ancillary tool for researchers who require accurate segmentation of carotid vessels.METHODS An expert reader delineated vessel wall boundaries on 4422 axial T2-weighted magnetic resonance images of bilateral carotid arteries from 189 subjects with clinically evident atherosclerotic disease.A portion of this dataset was used to train two CNNs(one to segment the vessel lumen and the other to segment the vessel wall)with the remaining portion used to test the algorithm’s efficacy by comparing CNN segmented images with those of an expert reader.Overall quantitative assessment between automated and manual segmentations was determined by computing the DICE coefficient for each pair of segmented images in the test dataset for each CNN applied.The average DICE coefficient for the test dataset(CNN segmentations compared to expert’s segmentations)was 0.96 for the lumen and 0.87 for the vessel wall.Pearson correlation values and the intra-class correlation coefficient(ICC)were computed for the lumen(Pearson=0.98,ICC=0.98)and vessel wall(Pearson=0.88,ICC=0.86)segmentations.Bland-Altman plots of area measurements for the CNN and expert readers indicate good agreement with a mean bias of 1%-8%.CONCLUSION Although the technique produces reasonable results that are on par with expert human assessments,our application requires human supervision and monitoring to ensure consistent results.We intend to deploy this algorithm as part of a software platform to lessen researchers’workload to more quickly obtain reliable results.展开更多
Background:The effect of arteriosclerotic intracranial arterial vessel wall enhancement(IAVWE)on downstream collateral flow found in vessel wall imaging(VWI)is not clear.Regardless of the mechanism underlying IAVWE on...Background:The effect of arteriosclerotic intracranial arterial vessel wall enhancement(IAVWE)on downstream collateral flow found in vessel wall imaging(VWI)is not clear.Regardless of the mechanism underlying IAVWE on VWI,damage to the patient’s nervous system caused by IAVWE is likely achieved by affecting downstream cerebral blood flow.The present study aimed to investigate the effect of arteriosclerotic IAVWE on downstream collateral flow.Methods:The present study recruited 63 consecutive patients at the Second Hospital of Hebei Medical University from January 2021 to November 2021 with underlying atherosclerotic diseases and unilateral middle cerebral artery(MCA)M1-segment stenosis who underwent an magnetic resonance scan within 3 days of symptom onset.The patients were divided into 4 groups according to IAVWE and the stenosis ratio(Group 1,n=17;Group 2,n=19;Group 3,n=13;Group 4,n=14),and downstream collateral flow was analyzed using three-dimensional pseudocontinuous arterial spin labeling(3D-pCASL)and RAPID software.The National Institutes of Health Stroke Scale(NIHSS)scores of the patients were also recorded.Two-factor multivariate analysis of variance using Pillai’s trace was used as the main statistical method.Results:No statistically significant difference was found in baseline demographic characteristics among the groups.IAVWE,but not the stenosis ratio,had a statistically significant significance on the late-arriving retrograde flow proportion(LARFP),hypoperfusion intensity ratio(HIR),and NIHSS scores(F=20.941,P<0.001,Pillai’s trace statistic=0.567).The between-subject effects test showed that IAVWE had a significant effect on the three dependent variables:LARFP(R^(2)=0.088,F=10.899,P=0.002),HIR(R^(2)=0.234,F=29.354,P<0.001),and NIHSS(R^(2)=114.339,F=33.338,P<0.001).Conclusions:Arteriosclerotic IAVWE significantly reduced downstream collateral flow and affected relevant neurological deficits.It was an independent factor affecting downstream collateral flow and NIHSS scores,which should be a focus of future studies.Trial Registration:ChiCTR.org.cn,ChiCTR2100053661.展开更多
基金supported by the Natural Science Foundation of Yongchuan District of Chongqing in China,No.Ycstc,2013nc8031the Foundation of Chongqing Municipal Health Bureau in China,No.2010-2-250+1 种基金the Foundation of Chongqing Health and Family Planning Commission in China,No.20143001the Soft Science Foundation of Yongchuan District of Chongqing in China,No.Ycstc,2011BE5004
文摘Vertebral artery orifice stenting may improve blood supply of the posterior circulation of the brain to regions such as the cerebellum and brainstem. However, previous studies have mainly focused on recovery of cerebral blood flow and perfusion in the posterior circulation after interventional therapy. This study examined the effects of functional recovery of local brain tissue on cerebellar function remodeling using blood oxygen level-dependent functional magnetic reso- nance imaging before and after interventional therapy. A total of 40 Chinese patients with severe unilateral vertebral artery orifice stenosis were enrolled in this study. Patients were equally and randomly assigned to intervention and control groups. The control group received drug treat- ment only. The intervention group received vertebral artery orifice angioplasty and stenting ＋ identical drug treatment to the control group. At 13 days after treatment, the Dizziness Handicap Inventory score was compared between the intervention and control groups. Cerebellar function remodeling was observed between the two groups using blood oxygen level-dependent functional magnetic resonance imaging. The improvement in dizziness handicap and cerebellar function was more obvious in the intervention group than in the control group. Interventional therapy for severe vertebral artery orifice stenosis may effectively promote cerebellar function remodeling and exert neuroprotective effects.
文摘Alzheimer’s disease (AD) is a dementing disorder and one of the major public health problems in countries with greater longevity. The cerebral cortical thickness and cerebral blood flow (CBF), which are considered as morphological and functional image features, respectively, could be decreased in specific cerebral regions of patients with dementia of Alzheimer type. Therefore, the aim of this study was to develop a computer-aided classification system for AD patients based on machine learning with the morphological and functional image features derived from a magnetic resonance (MR) imaging system. The cortical thicknesses in ten cerebral regions were derived as morphological features by using gradient vector trajectories in fuzzy membership images. Functional CBF maps were measured with an arterial spin labeling technique, and ten regional CBF values were obtained by registration between the CBF map and Talairach atlas using an affine transformation and a free form deformation. We applied two systems based on an arterial neural network (ANN) and a support vector machine (SVM), which were trained with 4 morphological and 6 functional image features, to 15 AD patients and 15 clinically normal (CN) subjects for classification of AD. The area under the receiver operating characteristic curve (AUC) values for the two systems based on the ANN and SVM with both image?features were 0.901 and 0.915, respectively. The AUC values for the ANN-and SVM-based systems with the morphological features were 0.710 and 0.660, respectively, and those with the functional features were 0.878 and 0.903, respectively. Our preliminary results suggest that the proposed method may have potential for assisting radiologists in the differential diagnosis of AD patients by using morphological and functional image features.
文摘Background： About 50% of the cerebral ischemia events are induced by intracranial and extracranial atheroscterosis. This study aimed to evaluate the feasibility and accuracy for displaying atherosclerotic plaques in carotid arteries and analyzing their ingredients by using high-resolution new magnetic resonance imaging （MRI） techniques. Methods： Totally, 49 patients suspected ofextracranial carotid artery stenosis were subjected to cranial MRI scan and magnetic resonance angiography （MRA） examination on carotid arteries, and high-resolution bright-blood and black-blood MRI analysis was carried out within 1 week. Digital subtraction angiography （DSA） examination was carried out for 16 patients within I month. Results： Totally, 103 plaques were detected in the 49 patients, which were characterized by localized or diffusive thickening of the vessel wall, with the intrusion of crescent-shaped abnormal signal into lumens. Fibrous cap was displayed as isointensity in T I -weighted image （T I WI） and hyperintensities in proton density weighted image （PDWI） and T2-weighted image （T2WI）, lipid core was displayed as isointensity or slight hyperintensities in T1WI, isointensity, hyperintensities or hypointensity in PDWI, and hypointensity in T2WI. Calcification in plaques was detected in 11 patients. Eight patients were detected with irregular plaque surface or ulcerative plaques, which were characterized by irregular intravascular space surface in the black-blood sequences, black hypointensity band was not detected in three-dimensional time-of-flight, or the hypointensity band was not continuous, and intrusion of hyperintensities into plaques can be detected. Bright-blood and black-blood techniques were highly correlated with the diagnosis of contrast-enhanced MRA in angiostenosis degree, Rs 0.97, P 〈 0.001. In comparison to DSA, the sensitivity, specificity, and accuracy of MRI diagnosis of stenosis for ≥50% were 88.9%. 100%, and 97.9%, respectively. Conclusions： High-resolution bright-blood and black-blood sequential MRI analysis can accurately analyze ingredients in atherosclerotic plaques, Determined by DSA, MRI diagnosis of stenosis can correctly evaluate the serious degree of arteriostenosis.
基金Supported by American Heart Association Grant in Aid Founders Affiliate No.17GRNT33420119(Mani V)NIH NHLBI 2R01HL070121(Fayad ZA)and NIH NHLBI 1R01HL135878(Fayad ZA)
文摘BACKGROUND Automated,accurate,objective,and quantitative medical image segmentation has remained a challenging goal in computer science since its inception.This study applies the technique of convolutional neural networks(CNNs)to the task of segmenting carotid arteries to aid in the assessment of pathology.AIM To investigate CNN’s utility as an ancillary tool for researchers who require accurate segmentation of carotid vessels.METHODS An expert reader delineated vessel wall boundaries on 4422 axial T2-weighted magnetic resonance images of bilateral carotid arteries from 189 subjects with clinically evident atherosclerotic disease.A portion of this dataset was used to train two CNNs(one to segment the vessel lumen and the other to segment the vessel wall)with the remaining portion used to test the algorithm’s efficacy by comparing CNN segmented images with those of an expert reader.Overall quantitative assessment between automated and manual segmentations was determined by computing the DICE coefficient for each pair of segmented images in the test dataset for each CNN applied.The average DICE coefficient for the test dataset(CNN segmentations compared to expert’s segmentations)was 0.96 for the lumen and 0.87 for the vessel wall.Pearson correlation values and the intra-class correlation coefficient(ICC)were computed for the lumen(Pearson=0.98,ICC=0.98)and vessel wall(Pearson=0.88,ICC=0.86)segmentations.Bland-Altman plots of area measurements for the CNN and expert readers indicate good agreement with a mean bias of 1%-8%.CONCLUSION Although the technique produces reasonable results that are on par with expert human assessments,our application requires human supervision and monitoring to ensure consistent results.We intend to deploy this algorithm as part of a software platform to lessen researchers’workload to more quickly obtain reliable results.
基金Beijing Scholar 2015(No.2015-160)Health Commission of Hebei Province(No.20200919)Scientific Research Fund Project of the Second Hospital of Hebei Medical University(No.2HC202056)
文摘Background:The effect of arteriosclerotic intracranial arterial vessel wall enhancement(IAVWE)on downstream collateral flow found in vessel wall imaging(VWI)is not clear.Regardless of the mechanism underlying IAVWE on VWI,damage to the patient’s nervous system caused by IAVWE is likely achieved by affecting downstream cerebral blood flow.The present study aimed to investigate the effect of arteriosclerotic IAVWE on downstream collateral flow.Methods:The present study recruited 63 consecutive patients at the Second Hospital of Hebei Medical University from January 2021 to November 2021 with underlying atherosclerotic diseases and unilateral middle cerebral artery(MCA)M1-segment stenosis who underwent an magnetic resonance scan within 3 days of symptom onset.The patients were divided into 4 groups according to IAVWE and the stenosis ratio(Group 1,n=17;Group 2,n=19;Group 3,n=13;Group 4,n=14),and downstream collateral flow was analyzed using three-dimensional pseudocontinuous arterial spin labeling(3D-pCASL)and RAPID software.The National Institutes of Health Stroke Scale(NIHSS)scores of the patients were also recorded.Two-factor multivariate analysis of variance using Pillai’s trace was used as the main statistical method.Results:No statistically significant difference was found in baseline demographic characteristics among the groups.IAVWE,but not the stenosis ratio,had a statistically significant significance on the late-arriving retrograde flow proportion(LARFP),hypoperfusion intensity ratio(HIR),and NIHSS scores(F=20.941,P<0.001,Pillai’s trace statistic=0.567).The between-subject effects test showed that IAVWE had a significant effect on the three dependent variables:LARFP(R^(2)=0.088,F=10.899,P=0.002),HIR(R^(2)=0.234,F=29.354,P<0.001),and NIHSS(R^(2)=114.339,F=33.338,P<0.001).Conclusions:Arteriosclerotic IAVWE significantly reduced downstream collateral flow and affected relevant neurological deficits.It was an independent factor affecting downstream collateral flow and NIHSS scores,which should be a focus of future studies.Trial Registration:ChiCTR.org.cn,ChiCTR2100053661.
