Quantitative Imaging Core

项目摘要 定量成像核心 定量成像核心（QIC）（前身为图像响应评估团队）的总体目标 （IRAT），是提供一站式专业知识，在标准化的医学成像和可再生的图像生物标志物 从临床和临床前收集的放射学和数字病理学图像的分析发展而来 问题研究QIC为放射学肿瘤缓解评估测量和报告提供专业知识和工具， 成像数据管理、研究协调以及标准和高级图像处理操作， 包括多光谱分析、放射组学和病理组学。QIC还提供定制定量 成像算法开发和临床研究放射成像协议设计。跨越多个 QIC提供活细胞显微镜获取的图像数据的定量分析， 数字病理学、小动物成像和临床成像。从图像中提取的数据提供给 适合下游生物信息学、生物统计学和机器学习分析的格式的成员。QIC 为实现其目标而开展的活动是按照沿着三个具体目标组织的： 目的1：为标准放射学肿瘤缓解评估提供高可靠性和快速周转时间 指标. 目的2：通过提供交钥匙成像生物标志物，改善Moffitt的临床和临床前研究 定量成像、放射组学和病理组学分析服务。 目的3：教育科学家和临床医生关于可重复性所需的实验设计元素 临床和临床前研究中QI数据的采集和分析。 QIC开发的可定制算法允许成员追求独特的假设， 量化癌症进展、演变和对治疗的反应。QIC服务使调查人员能够解锁 在临床、转化和临床前收集的放射学和数字病理学图像中包含的信息 问题研究自2016年以来，QIC的使用量增加了29%，并为87篇出版物做出了贡献（25篇具有高影响力）， 和600个临床方案，代表4，668名独特的患者。QIC自2016年以来增加了人员配置，目前 使用率为68%。在2020财年，QIC在所有五个计划中为60名成员提供了支持（CBE 14%，CE 5%，MM 66%，HOB 1%，IO 14%），其中64%的成员持有同行评审资金。这代表 占所有QIC使用量的81% QIC未来的重点是利用Moffitt的企业级云分析 平台，并实施新开发的数字病理学和多重免疫组织化学图像 处理模块以支持肿瘤切片的分析。使用商业图像处理工具，QIC将 并加强对会员、学员和工作人员的培训。

PROJECT SUMMARY QUANTITATIVE IMAGING CORE The overarching goal of the Quantitative Imaging Core (QIC), formerly the Image Response Assessment Team (IRAT), is to provide one-stop expertise in standardized medical imaging and reproducible image biomarker development from the analysis of radiologic and digital pathology images collected in clinical and preclinical studies. QIC provides expertise and tools for radiologic tumor response assessment measurement and reporting, imaging data management, study coordination, and standard and advanced image processing operations, including multispectral analysis, radiomics and pathomics. QIC also provides expertise in custom quantitative image algorithm development and in design of radiologic imaging protocols for clinical studies. Spanning multiple imaging scales and modalities, QIC offers quantitative analysis of image data acquired by live-cell microscopy, digital pathology, small animal imaging, and clinical imaging. Data extracted from images are provided to Members in formats suitable for downstream bioinformatics, biostatistics, and machine learning analyses. QIC activities towards its goals are organized along three Specific Aims: Aim 1: To provide high reliability and fast turnaround times for standard radiologic tumor response assessment metrics. Aim 2: To improve clinical and preclinical research studies at Moffitt, by providing turnkey imaging biomarker services from quantitative imaging, radiomics and pathomics analyses. Aim 3: To educate scientists and clinicians on experimental design elements required for the reproducible acquisition and analysis of QI data in clinical and preclinical studies. Customizable algorithms developed by QIC allow Members to pursue unique hypotheses characterizing and quantifying cancer progression, evolution and response to therapy. QIC services enable investigators to unlock information contained in radiologic and digital pathology images collected in clinical, translational and pre-clinical studies. Since 2016, QIC usage has increased by 29% and has contributed to 87 publications (25 high impact), and 600 clinical protocols, representing 4,668 unique patients. QIC increased staffing since 2016 and currently operates at 68% usage capacity. In FY20, QIC supported 60 Members across all five Programs (CBE 14%, CE 5%, MM 66%, HOB 1%, IO 14%), with 64% of those Members holding peer review funding. This represented 81% of all QIC usage. Future priorities of the QIC are to leverage Moffitt’s enterprise-scale, cloud-based analytics platforms and to implement newly developed digital pathology and multiplex immunohistochemistry image processing modules to support analyses of tumor sections. Using commercial image processing tools, QIC will also enhance training for Members, trainees, and staff.