| 1 | Radiological biomarkers of idiopathic normal pressure hydrocephalus:new approaches for detecting concomitant Alzheimer’s disease and predicting prognosis显示文摘Idiopathic normal pressure hydrocephalus(iNPH)is a clinical syndrome characterized by cognitive decline,gait disturbance,and urinary incontinence.As iNPH often occurs in elderly individuals prone tomany types of comorbidity,a differential diagnosis with other neurodegenerative diseases is crucial,especially Alzheimer’s disease(AD).A growing body of published work provides evidence of radiological methods,including multimodal magnetic resonance imaging and positron emission tomography,which may help noninvasively differentiate iNPH from AD or reveal concurrent AD pathology in vivo.Imaging methods detecting morphological changes,white matter microstructural changes,cerebrospinal fluid circulation,and molecular imaging have been widely applied in iNPH patients.Here,we review radiological biomarkers using different methods in evaluating iNPH pathophysiology and differentiating or detecting concomitant AD,to noninvasively predict the possible outcome postshunt and select candidates for shunt surgery. | Hanlin Cai Yinxi Zou Hui Gao Keru Huang Yu Liu Yuting Cheng Yi Liu Liangxue Zhou Dong Zhou Qin Chen | 2022 | Psychoradiology2022，2，4： | 0 |
| 2 | Advancing diagnostic performance and clinical applicability of deep learning-driven generative adversarial networks for Alzheimer’s disease显示文摘Alzheimer’s disease(AD)is a neurodegenerative disease that severely affects the activities of daily living in aged individuals,which typically needs to be diagnosed at an early stage.Generative adversarial networks(GANs)provide a new deep learning method that show good performance in image processing,while it remains to be verified whether a GAN brings benefit in AD diagnosis.The purpose of this research is to systematically review psychoradiological studies on the application of a GAN in the diagnosis of AD from the aspects of classification of AD state and AD-related image processing compared with other methods.In addition,we evaluated the research methodology and provided suggestions from the perspective of clinical application.Compared with othermethods,a GAN has higher accuracy in the classification of AD state and better performance in AD-related image processing(e.g.image denoising and segmentation).Most studies used data from public databases but lacked clinical validation,and the process of quantitative assessment and comparison in these studies lacked clinicians’participation,which may have an impact on the improvement of generation effect and generalization ability of the GAN model.The application value of GANs in the classification of AD state and AD-related image processing has been confirmed in reviewed studies.Improvement methods toward better GAN architecture were also discussed in this paper.In sum,the present study demonstrated advancing diagnostic performance and clinical applicability of GAN for AD,and suggested that the future researchers should consider recruiting clinicians to compare the algorithm with clinician manual methods and evaluate the clinical effect of the algorithm. | Changxing Qu Yinxi Zou Qingyi Dai Yingqiao Ma Jinbo He Qihong Liu Weihong Kuang Zhiyun Jia Taolin Chen Qiyong Gong | 2021 | Psychoradiology2021，1，4： | 0 |
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