Prototype Lesion Tracking Clinical Workflow and Vendor Neutral Pre-Processing Platform for Medical Imaging

1960年以后出生的英国人口中有50%将在其一生中被诊断出患有某种形式的癌症。医学成像在60%的患者护理中用于诊断，在几乎所有癌症诊断、监测和治疗中发挥着至关重要的作用。在过去的十年里，成像在整个护理链中的应用，特别是在肿瘤学中，已经急剧增加。相关的医疗保健专业人员正被数据的数量和复杂性所淹没。此外，放射学成像数据库正在从图像存储和通信系统（PACS）转移到供应商中立存档（VNA）系统。由于平价医疗法案，报销模式在主要市场发生了巨大变化，例如美国。为了解决这些问题，布莱克福德将开发一种病变跟踪原型，将我们现有的最先进的配准和新的创新分割算法整合在一起。病变跟踪将成为供应商中立预处理平台（VNP 3）的工作流程，这将使布莱克福德的先进图像处理技术获得更广泛的市场渗透。它还将创建一个资源和时间效率高的机制，用于开发一套新的、以临床为重点的应用程序，并允许改善与寻求将研究商业化的学者的合作。病变跟踪将提高癌症诊断和监测的效率，这需要许多组件之间的相互作用，所有这些都是为了加速放射科医生的评估和提高临床医生的理解。它将解决目前系统中罕见和/或不完整的缺陷。虽然有些组件是数据管理驱动的，但有些组件需要更高水平的技术创新，即配准和半自动分割/测量。我们预测，这些组件的组合将推动病变跟踪效率提高50 -70%。

50% of the UK population born after 1960 will be diagnosed with some form of cancer duringtheir lifetime. Medical imaging is used for diagnosis in 60% of all patient care episodes andplays a vital role in almost all cancer diagnosis, monitoring and treatment. The use of imagingthroughout the care chain, specifically in oncology, has increased dramatically over the lastdecade. Healthcare professionals involved are being overwhelmed by the quantity andcomplexity of data. In addition, radiology imaging databases are moving from PictureArchiving and Communication System (PACS) to Vendor Neutral Archive (VNA) systems.Reimbursement models are shifting dramatically across major markets, e.g. the US due to theAffordable Care Act. To address these issues, Blackford will develop a Lesion Trackingprototype integrating both our existing state-of-the-art registration and new, innovativesegmentation algorithms. Lesion Tracking will be a workflow for a Vendor Neutral Pre-Processing Platform (VNP3) that will allow broader market penetration for Blackford’s highlyadvanced image processing technology. It will also create a resource- and time-efficientmechanism for developing a suite of new, clinically-focused applications and allow improvedcollaboration with academics seeking to commercialise research. Lesion Tracking willimprove the efficiency of cancer diagnosis and monitoring which requires interplay betweenmany components, all geared towards accelerating radiologist assessment and referringclinician understanding. It will address shortfalls in current systems that are rare and/orincomplete. While some components are data management driven, some require a higherlevel of technical innovation, namely registration and semi-automatedsegmentation/measurement. We predict that the combination of these components will drive a50-70% increase in lesion tracking productivity.