PT - JOURNAL ARTICLE AU - Qingfeng Li AU - Lijuan Jiang AU - Kaini Qiao AU - Yang Hu AU - Bing Chen AU - Xiaochen Zhang AU - Yue Ding AU - Zhi Yang AU - Chunbo Li TI - INCloud: integrated neuroimaging cloud for data collection, management, analysis and clinical translations AID - 10.1136/gpsych-2021-100651 DP - 2021 Dec 01 TA - General Psychiatry PG - e100651 VI - 34 IP - 6 4099 - http://gpsych.bmj.com/content/34/6/e100651.short 4100 - http://gpsych.bmj.com/content/34/6/e100651.full SO - Gen Psych2021 Dec 01; 34 AB - Background Neuroimaging techniques provide rich and accurate measures of brain structure and function, and have become one of the most popular methods in mental health and neuroscience research. Rapidly growing neuroimaging research generates massive amounts of data, bringing new challenges in data collection, large-scale data management, efficient computing requirements and data mining and analyses.Aims To tackle the challenges and promote the application of neuroimaging technology in clinical practice, we developed an integrated neuroimaging cloud (INCloud). INCloud provides a full-stack solution for the entire process of large-scale neuroimaging data collection, management, analysis and clinical applications.Methods INCloud consists of data acquisition systems, a data warehouse, automatic multimodal image quality check and processing systems, a brain feature library, a high-performance computing cluster and computer-aided diagnosis systems (CADS) for mental disorders. A unique design of INCloud is the brain feature library that converts the unit of data management from image to image features such as hippocampal volume. Connecting the CADS to the scientific database, INCloud allows the accumulation of scientific data to continuously improve the accuracy of objective diagnosis of mental disorders.Results Users can manage and analyze neuroimaging data on INCloud, without the need to download them to the local device. INCloud users can query, manage, analyze and share image features based on customized criteria. Several examples of 'mega-analyses' based on the brain feature library are shown.Conclusions Compared with traditional neuroimaging acquisition and analysis workflow, INCloud features safe and convenient data management and sharing, reduced technical requirements for researchers, high-efficiency computing and data mining, and straightforward translations to clinical service. The design and implementation of the system are also applicable to imaging research platforms in other fields.Data may be obtained from a third party and are not publicly available.