Magnetic resonance imaging(MRI) has allowed a comprehensive evaluation of articular disease, increasing the detection of early cartilage involvement, bone erosions, and edema in soft tissue and bone marrow compared to...Magnetic resonance imaging(MRI) has allowed a comprehensive evaluation of articular disease, increasing the detection of early cartilage involvement, bone erosions, and edema in soft tissue and bone marrow compared to other imaging techniques. In the era of functional imaging, new advanced MRI sequences are being successfully applied for articular evaluation in cases of inflammatory, infectious, and degenerative arthropathies. Diffusion weighted imaging, new fat suppression techniques such as DIXON, dynamic contrast enhanced-MRI, and specific T2 mapping cartilage sequences allow a better understanding of the physiopathological processes that underlie these different arthropathies. They provide valuable quantitative information that aids in their differentiation and can be used as potential biomarkers of articular disease course and treatment response.展开更多
The use of artificial intelligence-based tools is regarded as a promising approach to increase clinical efficiency in diagnostic imaging,improve the interpretability of results,and support decision-making for the dete...The use of artificial intelligence-based tools is regarded as a promising approach to increase clinical efficiency in diagnostic imaging,improve the interpretability of results,and support decision-making for the detection and prevention of diseases.Radiology,endoscopy and pathology images are suitable for deep-learning analysis,potentially changing the way care is delivered in gastroenterology.The aim of this review is to examine the key aspects of different neural network architectures used for the evaluation of gastrointestinal conditions,by discussing how different models behave in critical tasks,such as lesion detection or characterization(i.e.the distinction between benign and malignant lesions of the esophagus,the stomach and the colon).To this end,we provide an overview on recent achievements and future prospects in deep learning methods applied to the analysis of radiology,endoscopy and histologic whole-slide images of the gastrointestinal tract.展开更多
Objective: To identify clinical factors contributing to the lateralization of mesiotemporal memory functions in epilepsy by using memory- activated fMRI. Methods: Sixty patients aged 16 to 63 years with mesial tempora...Objective: To identify clinical factors contributing to the lateralization of mesiotemporal memory functions in epilepsy by using memory- activated fMRI. Methods: Sixty patients aged 16 to 63 years with mesial temporal lobe epilepsy (MTLE)and 20 patients aged 16 to 60 years with extratemporal epilepsy (ETE) due to circumscribed epileptogenic lesions who cnsecutively underwent presurgical evaluation including continuous video- EEG monitoring and structural MRI examinations were examined. During memory fMRI, the activation condition consisted of retrieval from long- term memory induced by selfpaced performance of an imaginative walk through the patient’ s hometown. On the basis of a previous study, memory lateralization was defined as typical if larger fMRI activation was in the mesiotemporal structures contralateral to the epileptic focus. Results: There were 45 patients with MTLE who had typical memory lateralization (75% ), whereas only 9 patients (45% ) with ETE exhibited typical memory lateralization (p = 0.013). In MTLE patients, bilateral independent epileptiform discharges occurred more often in the atypical group than in patients with typical memory lateralization (p = 0.015). Conclusions: The fMRI lateralization of mesiotemporal visuospatial memory functions in patients with mesiotemporal lobe epilepsy (MTLE) is asymmetric: The larger activation usually appears contralateral to the side of the epileptogenic region. These findings occur more often in MTLE; in patients with extratemporal epilepsy, such type of asymmetry is not characteristic. In MTLE patients with bilateral independent epileptiform discharges, this type of asymmetry is also less frequent.展开更多
Objective: To test pathophysiologic hypotheses regarding the occurrence of a splenial lesion in patients with epilepsy. Methods: The authors studied 16 patients with a splenial lesion and 32 control patients, all of w...Objective: To test pathophysiologic hypotheses regarding the occurrence of a splenial lesion in patients with epilepsy. Methods: The authors studied 16 patients with a splenial lesion and 32 control patients, all of whom had MRI examination immediately after presurgical EEG long-term monitoring (LTM). The authors compared the number of generalized tonic-clonic and partial seizures during LTM, antiepileptic drug (AED) withdrawal, and laboratory results, Results: All of the patients with a splenial lesion had their AEDs stopped completely,vs 47%of the controls (p = 0.001). Patients with SCC lesion had a longer duration of complete withdrawal (median 3.5vs 2 days, p = 0.03). There was no correlation with seiz ure frequency or the introduction of new AEDs. Conclusion: Alesion of the splenium of the corpus callosum in patients with epilepsy is not associated with toxic drug effects or high seizure frequency, but might be induced by a rapid and relatively long-lasting reduction of antiepileptic drugs. Its frequency might be underestimated as MRI after long-term monitoring is rarely done.展开更多
Brain-computer interface (BCI) is a communication system that can help lock-in patients to interact with the outside environment by translating brain signals into machine commands.The present work provides a design fo...Brain-computer interface (BCI) is a communication system that can help lock-in patients to interact with the outside environment by translating brain signals into machine commands.The present work provides a design for a virtual reality (VR) based BCI system that allows human participants to control a virtual hand to make gestures by P300 signals,with a positive peak of potential about 300 ms posterior to the onset of target stimulus.In this virtual environment,the participants can obtain a more immersed experience with the BCI system,such as controlling a virtual hand or walking around in the virtual world.Methods of modeling the virtual hand and analyzing the P300 signals are also described in detail.Template matching and support vector machine were used as the P300 classifier and the experiment results showed that both algorithms perform well in the system.After a short time of practice,most participants could learn to control the virtual hand during the online experiment with greater than 70% accuracy.展开更多
文摘Magnetic resonance imaging(MRI) has allowed a comprehensive evaluation of articular disease, increasing the detection of early cartilage involvement, bone erosions, and edema in soft tissue and bone marrow compared to other imaging techniques. In the era of functional imaging, new advanced MRI sequences are being successfully applied for articular evaluation in cases of inflammatory, infectious, and degenerative arthropathies. Diffusion weighted imaging, new fat suppression techniques such as DIXON, dynamic contrast enhanced-MRI, and specific T2 mapping cartilage sequences allow a better understanding of the physiopathological processes that underlie these different arthropathies. They provide valuable quantitative information that aids in their differentiation and can be used as potential biomarkers of articular disease course and treatment response.
文摘The use of artificial intelligence-based tools is regarded as a promising approach to increase clinical efficiency in diagnostic imaging,improve the interpretability of results,and support decision-making for the detection and prevention of diseases.Radiology,endoscopy and pathology images are suitable for deep-learning analysis,potentially changing the way care is delivered in gastroenterology.The aim of this review is to examine the key aspects of different neural network architectures used for the evaluation of gastrointestinal conditions,by discussing how different models behave in critical tasks,such as lesion detection or characterization(i.e.the distinction between benign and malignant lesions of the esophagus,the stomach and the colon).To this end,we provide an overview on recent achievements and future prospects in deep learning methods applied to the analysis of radiology,endoscopy and histologic whole-slide images of the gastrointestinal tract.
文摘Objective: To identify clinical factors contributing to the lateralization of mesiotemporal memory functions in epilepsy by using memory- activated fMRI. Methods: Sixty patients aged 16 to 63 years with mesial temporal lobe epilepsy (MTLE)and 20 patients aged 16 to 60 years with extratemporal epilepsy (ETE) due to circumscribed epileptogenic lesions who cnsecutively underwent presurgical evaluation including continuous video- EEG monitoring and structural MRI examinations were examined. During memory fMRI, the activation condition consisted of retrieval from long- term memory induced by selfpaced performance of an imaginative walk through the patient’ s hometown. On the basis of a previous study, memory lateralization was defined as typical if larger fMRI activation was in the mesiotemporal structures contralateral to the epileptic focus. Results: There were 45 patients with MTLE who had typical memory lateralization (75% ), whereas only 9 patients (45% ) with ETE exhibited typical memory lateralization (p = 0.013). In MTLE patients, bilateral independent epileptiform discharges occurred more often in the atypical group than in patients with typical memory lateralization (p = 0.015). Conclusions: The fMRI lateralization of mesiotemporal visuospatial memory functions in patients with mesiotemporal lobe epilepsy (MTLE) is asymmetric: The larger activation usually appears contralateral to the side of the epileptogenic region. These findings occur more often in MTLE; in patients with extratemporal epilepsy, such type of asymmetry is not characteristic. In MTLE patients with bilateral independent epileptiform discharges, this type of asymmetry is also less frequent.
文摘Objective: To test pathophysiologic hypotheses regarding the occurrence of a splenial lesion in patients with epilepsy. Methods: The authors studied 16 patients with a splenial lesion and 32 control patients, all of whom had MRI examination immediately after presurgical EEG long-term monitoring (LTM). The authors compared the number of generalized tonic-clonic and partial seizures during LTM, antiepileptic drug (AED) withdrawal, and laboratory results, Results: All of the patients with a splenial lesion had their AEDs stopped completely,vs 47%of the controls (p = 0.001). Patients with SCC lesion had a longer duration of complete withdrawal (median 3.5vs 2 days, p = 0.03). There was no correlation with seiz ure frequency or the introduction of new AEDs. Conclusion: Alesion of the splenium of the corpus callosum in patients with epilepsy is not associated with toxic drug effects or high seizure frequency, but might be induced by a rapid and relatively long-lasting reduction of antiepileptic drugs. Its frequency might be underestimated as MRI after long-term monitoring is rarely done.
基金Project supported by the Natural Science Foundation of Zhejiang Province, China （No. LZ12F02004）, the Program of Xinmiao Talent of Zhejiang Province, China （No. ZX13005002064）, and the National Natural Science Foundation of China （No. 81471734）
基金Project supported by the National Natural Science Foundation of China (No.60873125)the National Institute of Biomedical Imaging and Bioengineering (No.1R03EB008235-01A1)+1 种基金the Shanghai Commission of Science and Technology (No.10440710200)the Fundamental Research Funds for the Central Universities
文摘Brain-computer interface (BCI) is a communication system that can help lock-in patients to interact with the outside environment by translating brain signals into machine commands.The present work provides a design for a virtual reality (VR) based BCI system that allows human participants to control a virtual hand to make gestures by P300 signals,with a positive peak of potential about 300 ms posterior to the onset of target stimulus.In this virtual environment,the participants can obtain a more immersed experience with the BCI system,such as controlling a virtual hand or walking around in the virtual world.Methods of modeling the virtual hand and analyzing the P300 signals are also described in detail.Template matching and support vector machine were used as the P300 classifier and the experiment results showed that both algorithms perform well in the system.After a short time of practice,most participants could learn to control the virtual hand during the online experiment with greater than 70% accuracy.
