Acute ischemic stroke is recognized as a common cerebral vascular disease in aging people. Accurate diagnosis and timely treatment can effectively improve the blood supply of the ischemic area and reduce the risk of disability or even death. Understanding the location and size of infarcts plays a critical role in the diagnosis decision. However, manual localization and quantification of stroke lesions are laborious and time-consuming. In this paper, we propose a novel automatic method to segment acute ischemic stroke from diffusion weighted images (DWIs) using deep 3-D convolutional neural networks (CNNs). Our method can efficiently utilize 3-D contextual information and automatically learn very discriminative features in an end-to-end and data-driven way. To relieve the difficulty of training very deep 3-D CNN, we equip our network with dense connectivity to enable the unimpeded propagation of information and gradients throughout the network. We train our model with Dice objective function to combat the severe class imbalance problem in data. A DWI data set containing 242 subjects (90 for training, 62 for validation, and 90 for testing) with various types of acute ischemic stroke was constructed to evaluate our method. Our model achieved high performance on various metrics (Dice similarity coefficient: 79.13%, lesionwise precision: 92.67%, and lesionwise F1 score: 89.25%), outperforming the other state-of-the-art CNN methods by a large margin. We also evaluated the model on ISLES2015-SSIS data set and achieved very competitive performance, which further demonstrated its generalization capacity. The proposed method is fast and accurate, demonstrating a good potential in clinical routines.

To investigate (1) the effects of indoor incense burning upon cognition over 3 years; (2) the associations between indoor incense burning with the brain's structure and functional connectivity of the default mode network (DMN); and (3) the interactions between indoor incense burning and vascular disease markers upon cognitive functions. Community older adults without stroke or dementia were recruited (n = 515). Indoor incense use was self-reported as having burnt incense at home ≥ weekly basis over the past 5 years. Detailed neuropsychological battery was administered at baseline (n = 227) and the Montreal Cognitive Assessment at baseline and year 3 (n = 515). MRI structural measures and functional connectivity of the DMN were recorded at baseline. Demographic and vascular risk factors and levels of outdoor pollutants were treated as covariates. Indoor incense burning was associated with reduced performance across multiple cognitive domains at baseline and year 3 as well as decreased connectivity in the DMN. It interacted with diabetes mellitus, hyperlipidemia and white matter hyperintensities to predict poorer cognitive performance. Indoor incense burning is (1) associated with poorer cognitive performance over 3 years; (2) related to decreased brain connectivity; and (3) it interacts with vascular disease to predispose poor cognitive performance. Incense burning is a religious ritual commonly practised in many cultures and is popular among older adults. Incense comes in many forms, with 'joss sticks' being the commonest choice for home use (Fig. 1). Incense is made up of a mixture of fragrance materials and herbal, wood and adhesive powder 1. When incense is burnt, pollutants including particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO 2), sulfur dioxide (SO 2), nitrogen dioxide (NO 2), volatile organic compounds, aldehydes and polycyclic aromatic hydrocarbons (PAHs) are released into the air 1,2. Incense burning is considered a major source of indoor air pollution; the amount of PM generated by incense can be up to 4.5 times of that by cigarettes 2. Incense smoke is associated with carcinogenicity, increased cardiovascular mortality and respiratory conditions 1,3-5. Although there is currently a lack of published data showing a direct link between incense burning with cognitive and brain health, air pollution research suggests that pollutants emitted from incense smoke are associated with accelerated cognitive aging, intellectual decline and an increased risk for Alzheimer's Disease (AD) and vascular dementia 6-11. Moreover, long term exposure to air pollution is associated with smaller total brain volume and volume in prefrontal cortex, white matter and associations areas in frontal, temporal regions and corpus callosum. It is also related to the development of

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Recent studies have demonstrated the working memory impairment in patients with amnestic mild cognitive impairment (aMCI). However, the neurophysiological basis of the working memory deficit in aMCI is poorly understood. The aim of this study was to explore the abnormal activity during encoding and recognition procedures, as well as the reorganization of the background network maintaining the working memory state in aMCI. Using event-related fMRI during a visuospatial working memory task with three recognition difficulty levels, the task-related activations and network efficiency of the background network in 17 aMCI patients and 19 matched controls were investigated. Compared with cognitively healthy controls, patients with aMCI showed significantly decreased activity in the frontal and visual cortices during the encoding phase, while during the recognition phase, decreased activity was detected in the frontal, parietal, and visual regions. In addition, increased local efficiency was also observed in the background network of patients with aMCI. The results suggest patients with aMCI showed impaired encoding and recognition functions during the visuospatial working memory task, and may pay more effort to maintain the cognitive state. This study extends our understanding of the impaired working memory function in aMCI and provides a new perspective to investigate the compensatory mechanism in aMCI.