Coordination Funds

与优先计划的第一个资助期相比，我们希望专注于先进图像分析的临床实施和价值，以及这些技术的应用，以更深入地了解成像表型在大规模人群队列中的作用。毫无疑问，生物医学成像在现代医学中各种疾病的管理中发挥着越来越重要的作用。此外，影像学逐渐更多地被纳入研究环境，包括形成大规模的基于人群的队列，如德国国家队列（NAKO Gesundheitsstudie）。与此同时，随着强大的大规模计算能力设施的出现和现场专业知识的不断增长，先进的后处理方法，包括人工智能，深度学习或放射组学，用于从高分辨率成像数据中提取描述性，诊断或预后信息。因此，这些导出的参数（“成像表型”）补充了传统上可用和使用的图像信息，例如手动测量直径或仅仅存在疾病状态，并允许高容量、可再现和高质量的解释技能。然而，尽管有这些成功的努力，仍然只有早期的证据表明，这种先进的基于计算机的成像后处理提供了个性化医疗领域的增量诊断和预后信息，算法还没有完全进入临床竞技场。鉴于巨大的前景，PP旨在进一步发展和建立先进的图像解释方法在个性化医疗的不同临床场景中的作用，包括预防疾病的发展。SPP 2177第2阶段的目的包括：目的1确定人类成像数据的高级后处理方法在不同临床相关和/或基础研究环境中的诊断临床价值;目的2确定人类成像数据的高级后处理方法在临床相关环境和/或基础研究环境中的预后价值。该项目的总体目标是进一步保证有效的协调和管理，以进一步加强方案内具体研究项目之间的合作，并与学术界和工业界的国家和国际一级的外部利益攸关方合作。协调员及其工作队的活动包括组织务虚会、会议和讲习班、支助来访科学家、协调外联和公共关系活动、监测性别措施、控制方案资金以及建立通信和报告结构。协调还将确保项目的科学一致性。该项目将支持管理组织和协调方案伙伴关系内部活动所需的中央资金。

Compared to the first funding period of the Priority Programme we want to focus on the clinical implementation and value of advanced image analysis as well as the application of these techniques to gain deeper understanding of the role of imaging phenotypes in large-scale population cohorts. There is still not doubt that biomedical imaging plays an increasingly central role in the management of various disease settings in modern medicine. In addition, imaging is progressively more incorporated in research settings, including the formation of large-scale, population-based cohorts, such as the German National Cohort (NAKO Gesundheitsstudie). In parallel, with the advent of powerful, large scale computational power facilities and growing on-site expertise, advanced post-processing methods, including Artificial Intelligence, Deep-Learning, or Radiomics, are used to abstract descriptive, diagnostic, or prognostic information from high-resolution imaging data. As such, these derived parameters (“imaging phenotypes”) complement traditionally available and used image information, such as manual measurements of diameters or the mere presence of disease states and allow for high-volume, reproducible, and high-quality interpretation skills. However, despite these successful endeavours, there is still only early evidence that such advanced computer-based imaging post-processing provides incremental diagnostic and prognostic information in the field of personalised medicine, and algorithms have not fully entered the clinical arena yet. Given the great promise, the PP is designed to further develop and establish the role of advanced image interpretation approaches in different clinical scenarios in personalised medicine, including prevention of disease development. The aims of SPP2177 Phase 2 comprise: Aim 1 Determination of the diagnostic clinical value of advanced post-processing methods of human imaging data in different clinically relevant and/or in basic research settings; Aim 2 Determination of the prognostic value of advanced post-processing methods of human imaging data in clinically relevant settings and/or in basic research settings. The overall goal of the project is to further guarantee an efficient coordination and administration of the in order to further enhance the collaboration between the specific research projects within the programme, and with external stakeholders on national and international level in academia and industry. The activities of the coordinator and his team comprise the organization of retreats, conferences and workshops, support of visiting scientists, the coordination of outreach and public relation activities, the monitoring of gender measures, the control of programme finances and the establishment of communication and reporting structures. Coordination will also ensure scientific coherence of the projects. This project will support administration of central funds needed to organize and coordinate PP-internal activities.