Human neural stem cells（h NSCs） derived from the ventral mesencephalon are powerful research tools and candidates for cell therapies in Parkinson＇s disease. However, their clinical translation has not been fully re...Human neural stem cells（h NSCs） derived from the ventral mesencephalon are powerful research tools and candidates for cell therapies in Parkinson＇s disease. However, their clinical translation has not been fully realized due, in part, to the limited ability to track stem cell regional localization and survival over long periods of time after in vivo transplantation. Magnetic resonance imaging provides an excellent non-invasive method to study the fate of transplanted cells in vivo. For magnetic resonance imaging cell tracking, cells need to be labeled with a contrast agent, such as magnetic nanoparticles, at a concentration high enough to be easily detected by magnetic resonance imaging. Grafting of human neural stem cells labeled with magnetic nanoparticles allows cell tracking by magnetic resonance imaging without impairment of cell survival, proliferation, self-renewal, and multipotency. However, the results reviewed here suggest that in long term grafting, activated microglia and macrophages could contribute to magnetic resonance imaging signal by engulfing dead labeled cells or iron nanoparticles dispersed freely in the brain parenchyma over time.展开更多
In this study, we established a Wistar rat model of right middle cerebral artery occlusion and observed pathological imaging changes （T2-weighted imaging [T2WI], T2FLAIR, and diffusion-weighted imaging [DWI]） follow...In this study, we established a Wistar rat model of right middle cerebral artery occlusion and observed pathological imaging changes （T2-weighted imaging [T2WI], T2FLAIR, and diffusion-weighted imaging [DWI]） following cerebral infarction. The pathological changes were divided into three phases： early cerebral infarction, middle cerebral infarction, and late cerebral infarction. In the early cerebral infarction phase （less than 2 hours post-infarction）, there was evidence of intracellular edema, which improved after reperfusion. This improvement was defined as the ischemic penumbra. In this phase, a high DWI signal and a low apparent diffusion coefficient were observed in the right basal ganglia region. By contrast, there were no abnormal T2WI and T2FLAIR signals. For the middle cerebral infarction phase （2-4 hours post-infarction）, a mixed edema was observed. After reperfusion, there was a mild improvement in cell edema, while the angioedema became more serious. A high DWI signal and a low apparent diffusion coefficient signal were observed, and some rats showed high T2WI and T2FLAIR signals. For the late cerebral infarction phase （4-6 hours post-infarction）, significant angioedema was visible in the infarction site. After reperfusion, there was a significant increase in angioedema, while there was evidence of hemorrhage and necrosis. A mixed signal was observed on DWI, while a high apparent diffusion coefficient signal, a high T2WI signal, and a high T2FLAIR signal were also observed. All 86 cerebral infarction patients were subjected to T2WI, T2FLAIR, and DWI. MRI results of clinic data similar to the early infarction phase of animal experiments were found in 51 patients, for which 10 patients （10/51） had an onset time greater than 6 hours. A total of 35 patients had MRI results similar to the middle and late infarction phase of animal experiments, of which eight patients （8/35） had an onset time less than 6 hours. These data suggest that defining the ＂therapeutic time window＂ as the time 6 hours after infarction may not be suitable for all patients. Integrated application of MRI sequences including T2WI, T2FLAIR, DW-MRI, and apparent diffusion coefficient mapping should be used to examine the ischemic penumbra, which may provide valuable information for identifying the ＂therapeutic time window＂.展开更多
Neuronal regeneration in the peripheral nervous system arises via a synergistic interplay of neurotrophic factors,integrins,cytoskeletal proteins,mechanical cues,cytokines,stem cells,glial cells and astrocytes.
The convolutional neural network(CNN)is one of the main algorithms that is applied to deep transfer learning for classifying two essential types of liver lesions;Hemangioma and hepatocellular carcinoma(HCC).Ultrasound...The convolutional neural network(CNN)is one of the main algorithms that is applied to deep transfer learning for classifying two essential types of liver lesions;Hemangioma and hepatocellular carcinoma(HCC).Ultrasound images,which are commonly available and have low cost and low risk compared to computerized tomography(CT)scan images,will be used as input for the model.A total of 350 ultrasound images belonging to 59 patients are used.The number of images with HCC is 202 and 148,respectively.These images were collected from ultrasound cases.info(28 Hemangiomas patients and 11 HCC patients),the department of radiology,the University of Washington(7 HCC patients),the Atlas of ultrasound Germany(3 HCC patients),and Radiopedia and others(10 HCC patients).The ultrasound images are divided into 225,52,and 73 for training,validation,and testing.A data augmentation technique is used to enhance the validation performance.We proposed an approach based on ensembles of the best-selected deep transfer models from the on-the-shelf models:VGG16,VGG19,DenseNet,Inception,InceptionResNet,ResNet,and EfficientNet.After tuning both the feature extraction and the classification layers,the best models are selected.Validation accuracy is used for model tuning and selection.The accuracy,sensitivity,specificity and AUROC are used to evaluate the performance.The experiments are concluded in five stages.The first stage aims to evaluate the base model performance by training the on-the-shelf models.The best accu-racy obtained in the first stage is 83.5%.In the second stage,we augmented the data and retrained the on-the-shelf models with the augmented data.The best accuracy we obtained in the second stage was 86.3%.In the third stage,we tuned the feature extraction layers of the on-the-shelf models.The best accuracy obtained in the third stage is 89%.In the fourth stage,we fine-tuned the classification layer and obtained an accuracy of 93%as the best accuracy.In the fifth stage,we applied the ensemble approach using the best three-performing models and obtained an accuracy,specificity,sensitivity,and AUROC of 94%,93.7%,95.1%,and 0.944,respectively.展开更多
Rotenone and 6-hydroxydopamine are two drugs commonly used to generate Parkinson＇s disease animal models.They not only achieve degenerative changes of dopaminergic neurons in the substantia nigra,but also satisfy the...Rotenone and 6-hydroxydopamine are two drugs commonly used to generate Parkinson＇s disease animal models.They not only achieve degenerative changes of dopaminergic neurons in the substantia nigra,but also satisfy the requirements for iron deposition.However,few studies have compared the characteristics of these two models by magnetic resonance imaging.In this study,rat models of Parkinson＇s disease were generated by injection of 3 μg rotenone or 10 μg 6-hydroxydopamine into the right substantia nigra.At 1,2,4,and 6 weeks after injection,coronal whole-brain T2-weighted imaging,transverse whole-brain T2-weighted imaging,and coronal diffusion tensor weighted imaging were conducted to measure fractional anisotropy and T2＊ values at the injury site.The fractional anisotropy value on the right side of the substantia nigra was remarkably lower at 6 weeks than at other time points in the rotenone group.In the 6-hydroxydopamine group,the fractional anisotropy value was decreased,but T2＊ values were increased on the right side of the substantia nigra at 1 week.Our findings confirm that the 6-hydroxydopamine-induced model is suitable for studying dopaminergic neurons over short periods,while the rotenone-induced model may be appropriate for studying the pathological and physiological processes of Parkinson＇s disease over long periods.展开更多
Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in bra...Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in brain activation induced by acupuncture. Thus, the time course of the therapeutic effects of acupuncture remains unclear. In this study, 32 patients with amnestic mild cognitive impairment were randomly divided into two groups, where they received either Tiaoshen Yizhi acupuncture or sham acupoint acupuncture. The needles were either twirled at Tiaoshen Yizhi acupoints, including Sishencong（EX-HN1）, Yintang（EX-HN3）, Neiguan（PC6）, Taixi（KI3）, Fenglong（ST40）, and Taichong（LR3）, or at related sham acupoints at a depth of approximately 15 mm, an angle of ± 60°, and a rate of approximately 120 times per minute. Acupuncture was conducted for 4 consecutive weeks, five times per week, on weekdays. Resting-state functional magnetic resonance imaging indicated that connections between cognition-related regions such as the insula, dorsolateral prefrontal cortex, hippocampus, thalamus, inferior parietal lobule, and anterior cingulate cortex increased after acupuncture at Tiaoshen Yizhi acupoints. The insula, dorsolateral prefrontal cortex, and hippocampus acted as central brain hubs. Patients in the Tiaoshen Yizhi group exhibited improved cognitive performance after acupuncture. In the sham acupoint acupuncture group, connections between brain regions were dispersed, and we found no differences in cognitive function following the treatment. These results indicate that acupuncture at Tiaoshen Yizhi acupoints can regulate brain networks by increasing connectivity between cognition-related regions, thereby improving cognitive function in patients with mild cognitive impairment.展开更多
Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only ＂see＂ pixelized...Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only ＂see＂ pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex（the implant area） is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine（LSVM） as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern.展开更多
Temporal lobe resection is an important treatment option for epilepsy that involves removal of potentially essential brain regions. Selective amygdalohippocampectomy is a widely performed temporal lobe surgery. We sug...Temporal lobe resection is an important treatment option for epilepsy that involves removal of potentially essential brain regions. Selective amygdalohippocampectomy is a widely performed temporal lobe surgery. We suggest starting the incision for selective amygdalohippocampectomy at the inferior temporal gyrus based on diffusion magnetic resonance imaging（MRI） tractography. Diffusion MRI data from 20 normal participants were obtained from Parkinson＇s Progression Markers Initiative（PPMI） database（www.ppmi-info.org）. A tractography algorithm was applied to extract neuronal fiber information for the temporal lobe, hippocampus, and amygdala. Fiber information was analyzed in terms of the number of fibers and betweenness centrality. Distances between starting incisions and surgical target regions were also considered to explore the length of the surgical path. Middle temporal and superior temporal gyrus regions have higher connectivity values than the inferior temporal gyrus and thus are not good candidates for starting the incision. The distances between inferior temporal gyrus and surgical target regions were shorter than those between middle temporal gyrus and target regions. Thus, the inferior temporal gyrus is a good candidate for starting the incision. Starting the incision from the inferior temporal gyrus would spare the important（in terms of betweenness centrality values） middle region and shorten the distance to the target regions of the hippocampus and amygdala.展开更多
A decision map contains complete and clear information about the image to be fused, which is crucial to various image fusion issues, especially multi-focus image fusion. However, in order to get a satisfactory image f...A decision map contains complete and clear information about the image to be fused, which is crucial to various image fusion issues, especially multi-focus image fusion. However, in order to get a satisfactory image fusion effect, getting a decision map is very necessary and usually difficult to finish. In this letter, we address this problem with convolutional neural network(CNN), aiming to get a state-of-the-art decision map. The main idea is that the max-pooling of CNN is replaced by a convolution layer, the residuals are propagated backwards by gradient descent, and the training parameters of the individual layers of the CNN are updated layer by layer. Based on this, we propose a new all CNN(ACNN)-based multi-focus image fusion method in spatial domain. We demonstrate that the decision map obtained from the ACNN is reliable and can lead to high-quality fusion results. Experimental results clearly validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.展开更多
基金To AMS:Instituto de Salud Carlos-III(RETICS Ter Cel RD12/0019/0013)Comunidad Autónoma de Madrid(S2010-BMD-2336)+3 种基金MINECO(SAF2010-17167)the institutional grant of the Fundación Ramón Areces to the CBMSOTo MRG:Reina Sofia FoundationComunidad Autónoma Madrid(S2010-BMD-2460)
文摘Human neural stem cells（h NSCs） derived from the ventral mesencephalon are powerful research tools and candidates for cell therapies in Parkinson＇s disease. However, their clinical translation has not been fully realized due, in part, to the limited ability to track stem cell regional localization and survival over long periods of time after in vivo transplantation. Magnetic resonance imaging provides an excellent non-invasive method to study the fate of transplanted cells in vivo. For magnetic resonance imaging cell tracking, cells need to be labeled with a contrast agent, such as magnetic nanoparticles, at a concentration high enough to be easily detected by magnetic resonance imaging. Grafting of human neural stem cells labeled with magnetic nanoparticles allows cell tracking by magnetic resonance imaging without impairment of cell survival, proliferation, self-renewal, and multipotency. However, the results reviewed here suggest that in long term grafting, activated microglia and macrophages could contribute to magnetic resonance imaging signal by engulfing dead labeled cells or iron nanoparticles dispersed freely in the brain parenchyma over time.
基金supported by the National Natural Science Foundation of China,No.30960399,and No.81160181
文摘In this study, we established a Wistar rat model of right middle cerebral artery occlusion and observed pathological imaging changes （T2-weighted imaging [T2WI], T2FLAIR, and diffusion-weighted imaging [DWI]） following cerebral infarction. The pathological changes were divided into three phases： early cerebral infarction, middle cerebral infarction, and late cerebral infarction. In the early cerebral infarction phase （less than 2 hours post-infarction）, there was evidence of intracellular edema, which improved after reperfusion. This improvement was defined as the ischemic penumbra. In this phase, a high DWI signal and a low apparent diffusion coefficient were observed in the right basal ganglia region. By contrast, there were no abnormal T2WI and T2FLAIR signals. For the middle cerebral infarction phase （2-4 hours post-infarction）, a mixed edema was observed. After reperfusion, there was a mild improvement in cell edema, while the angioedema became more serious. A high DWI signal and a low apparent diffusion coefficient signal were observed, and some rats showed high T2WI and T2FLAIR signals. For the late cerebral infarction phase （4-6 hours post-infarction）, significant angioedema was visible in the infarction site. After reperfusion, there was a significant increase in angioedema, while there was evidence of hemorrhage and necrosis. A mixed signal was observed on DWI, while a high apparent diffusion coefficient signal, a high T2WI signal, and a high T2FLAIR signal were also observed. All 86 cerebral infarction patients were subjected to T2WI, T2FLAIR, and DWI. MRI results of clinic data similar to the early infarction phase of animal experiments were found in 51 patients, for which 10 patients （10/51） had an onset time greater than 6 hours. A total of 35 patients had MRI results similar to the middle and late infarction phase of animal experiments, of which eight patients （8/35） had an onset time less than 6 hours. These data suggest that defining the ＂therapeutic time window＂ as the time 6 hours after infarction may not be suitable for all patients. Integrated application of MRI sequences including T2WI, T2FLAIR, DW-MRI, and apparent diffusion coefficient mapping should be used to examine the ischemic penumbra, which may provide valuable information for identifying the ＂therapeutic time window＂.
基金CSIRO, the ARC and the NHMRC for providing funding that supported this work
文摘Neuronal regeneration in the peripheral nervous system arises via a synergistic interplay of neurotrophic factors,integrins,cytoskeletal proteins,mechanical cues,cytokines,stem cells,glial cells and astrocytes.
基金funded by the Deanship of Scientific Research at Jouf University under Grant No.(DSR-2022-RG-0104).
文摘The convolutional neural network(CNN)is one of the main algorithms that is applied to deep transfer learning for classifying two essential types of liver lesions;Hemangioma and hepatocellular carcinoma(HCC).Ultrasound images,which are commonly available and have low cost and low risk compared to computerized tomography(CT)scan images,will be used as input for the model.A total of 350 ultrasound images belonging to 59 patients are used.The number of images with HCC is 202 and 148,respectively.These images were collected from ultrasound cases.info(28 Hemangiomas patients and 11 HCC patients),the department of radiology,the University of Washington(7 HCC patients),the Atlas of ultrasound Germany(3 HCC patients),and Radiopedia and others(10 HCC patients).The ultrasound images are divided into 225,52,and 73 for training,validation,and testing.A data augmentation technique is used to enhance the validation performance.We proposed an approach based on ensembles of the best-selected deep transfer models from the on-the-shelf models:VGG16,VGG19,DenseNet,Inception,InceptionResNet,ResNet,and EfficientNet.After tuning both the feature extraction and the classification layers,the best models are selected.Validation accuracy is used for model tuning and selection.The accuracy,sensitivity,specificity and AUROC are used to evaluate the performance.The experiments are concluded in five stages.The first stage aims to evaluate the base model performance by training the on-the-shelf models.The best accu-racy obtained in the first stage is 83.5%.In the second stage,we augmented the data and retrained the on-the-shelf models with the augmented data.The best accuracy we obtained in the second stage was 86.3%.In the third stage,we tuned the feature extraction layers of the on-the-shelf models.The best accuracy obtained in the third stage is 89%.In the fourth stage,we fine-tuned the classification layer and obtained an accuracy of 93%as the best accuracy.In the fifth stage,we applied the ensemble approach using the best three-performing models and obtained an accuracy,specificity,sensitivity,and AUROC of 94%,93.7%,95.1%,and 0.944,respectively.
基金supported by a grant from the Qinhuangdao Science-Technology Support Project of China,No.201402B036a grant from the Science and Technology Project of Hebei Province of China,No.1427777118D
文摘Rotenone and 6-hydroxydopamine are two drugs commonly used to generate Parkinson＇s disease animal models.They not only achieve degenerative changes of dopaminergic neurons in the substantia nigra,but also satisfy the requirements for iron deposition.However,few studies have compared the characteristics of these two models by magnetic resonance imaging.In this study,rat models of Parkinson＇s disease were generated by injection of 3 μg rotenone or 10 μg 6-hydroxydopamine into the right substantia nigra.At 1,2,4,and 6 weeks after injection,coronal whole-brain T2-weighted imaging,transverse whole-brain T2-weighted imaging,and coronal diffusion tensor weighted imaging were conducted to measure fractional anisotropy and T2＊ values at the injury site.The fractional anisotropy value on the right side of the substantia nigra was remarkably lower at 6 weeks than at other time points in the rotenone group.In the 6-hydroxydopamine group,the fractional anisotropy value was decreased,but T2＊ values were increased on the right side of the substantia nigra at 1 week.Our findings confirm that the 6-hydroxydopamine-induced model is suitable for studying dopaminergic neurons over short periods,while the rotenone-induced model may be appropriate for studying the pathological and physiological processes of Parkinson＇s disease over long periods.
基金supported by the National Natural Science Foundation of China,No.81173354a grant from the Science and Technology Plan Project of Guangdong Province of China,No.2013B021800099a grant from the Science and Technology Plan Project of Shenzhen City of China,No.JCYJ20150402152005642
文摘Functional magnetic resonance imaging has been widely used to investigate the effects of acupuncture on neural activity. However, most functional magnetic resonance imaging studies have focused on acute changes in brain activation induced by acupuncture. Thus, the time course of the therapeutic effects of acupuncture remains unclear. In this study, 32 patients with amnestic mild cognitive impairment were randomly divided into two groups, where they received either Tiaoshen Yizhi acupuncture or sham acupoint acupuncture. The needles were either twirled at Tiaoshen Yizhi acupoints, including Sishencong（EX-HN1）, Yintang（EX-HN3）, Neiguan（PC6）, Taixi（KI3）, Fenglong（ST40）, and Taichong（LR3）, or at related sham acupoints at a depth of approximately 15 mm, an angle of ± 60°, and a rate of approximately 120 times per minute. Acupuncture was conducted for 4 consecutive weeks, five times per week, on weekdays. Resting-state functional magnetic resonance imaging indicated that connections between cognition-related regions such as the insula, dorsolateral prefrontal cortex, hippocampus, thalamus, inferior parietal lobule, and anterior cingulate cortex increased after acupuncture at Tiaoshen Yizhi acupoints. The insula, dorsolateral prefrontal cortex, and hippocampus acted as central brain hubs. Patients in the Tiaoshen Yizhi group exhibited improved cognitive performance after acupuncture. In the sham acupoint acupuncture group, connections between brain regions were dispersed, and we found no differences in cognitive function following the treatment. These results indicate that acupuncture at Tiaoshen Yizhi acupoints can regulate brain networks by increasing connectivity between cognition-related regions, thereby improving cognitive function in patients with mild cognitive impairment.
基金supported by the National Natural Science Foundation of China,No.31070758,31271060the Natural Science Foundation of Chongqing in China,No.cstc2013jcyj A10085
文摘Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only ＂see＂ pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex（the implant area） is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine（LSVM） as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern.
基金supported by the National Research Foundation of Korea,No.20100023233
文摘Temporal lobe resection is an important treatment option for epilepsy that involves removal of potentially essential brain regions. Selective amygdalohippocampectomy is a widely performed temporal lobe surgery. We suggest starting the incision for selective amygdalohippocampectomy at the inferior temporal gyrus based on diffusion magnetic resonance imaging（MRI） tractography. Diffusion MRI data from 20 normal participants were obtained from Parkinson＇s Progression Markers Initiative（PPMI） database（www.ppmi-info.org）. A tractography algorithm was applied to extract neuronal fiber information for the temporal lobe, hippocampus, and amygdala. Fiber information was analyzed in terms of the number of fibers and betweenness centrality. Distances between starting incisions and surgical target regions were also considered to explore the length of the surgical path. Middle temporal and superior temporal gyrus regions have higher connectivity values than the inferior temporal gyrus and thus are not good candidates for starting the incision. The distances between inferior temporal gyrus and surgical target regions were shorter than those between middle temporal gyrus and target regions. Thus, the inferior temporal gyrus is a good candidate for starting the incision. Starting the incision from the inferior temporal gyrus would spare the important（in terms of betweenness centrality values） middle region and shorten the distance to the target regions of the hippocampus and amygdala.
基金supported by the National Natural Science Foundation of China(No.61174193)
文摘A decision map contains complete and clear information about the image to be fused, which is crucial to various image fusion issues, especially multi-focus image fusion. However, in order to get a satisfactory image fusion effect, getting a decision map is very necessary and usually difficult to finish. In this letter, we address this problem with convolutional neural network(CNN), aiming to get a state-of-the-art decision map. The main idea is that the max-pooling of CNN is replaced by a convolution layer, the residuals are propagated backwards by gradient descent, and the training parameters of the individual layers of the CNN are updated layer by layer. Based on this, we propose a new all CNN(ACNN)-based multi-focus image fusion method in spatial domain. We demonstrate that the decision map obtained from the ACNN is reliable and can lead to high-quality fusion results. Experimental results clearly validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.
