SBIR Phase I: An Integrated Search, Analytics, and Imaging (SAI) Platform for Clinical Decision Support and Mobile Health

该小型企业创新研究（SBIR）第一阶段项目旨在为医疗保健企业开发和提供下一代成像、分析和搜索解决方案，不仅满足当前多企业医疗图像查看的需求，还满足与临床决策支持和移动的健康相关的新兴需求。该项目解决了一个？大数据？医疗成像的问题，即在医疗保健企业内的任何地方提供对大型研究、高级成像工具和跨从强大的个人计算机到移动的设备的一系列设备的基于图像的分析的访问。该项目更广泛的影响/商业潜力是将使用定量成像生物标志物的新研究转化为实际的临床实践。医学成像通常用于癌症筛查，治疗计划和监测，但来自这些图像的纯粹定性解释的结果并不总是确定的。最近的进展表明，高通量提取和分析先进的定量成像功能，从医学图像（？放射学？）在某些情况下，可用于提高癌症筛查的准确性和可信度。该项目的目标是将这些分析纳入商业可用的系统，用于医学图像显示和分发，这对于广泛的临床应用是必要的。这些进步将使医疗保健提供者能够降低与不必要的随访检查相关的成本，并通过识别更可能对治疗产生抗性的肿瘤来改善患者的预后，并使用医学成像更有效和准确地监测对治疗的反应。

This Small Business Innovation Research (SBIR) Phase I Project proposes to develop and deliver to health care enterprises a next generation imaging, analytics, and search solution that meets not only the current needs of multi-enterprise medical image viewing, but satisfies emerging demands related to clinical decision support and mobile health. The project addresses one of the ?Big Data? problems of medical imaging, i.e. providing access anywhere within the healthcare enterprise to large studies, advanced imaging tools, and image-based analytics across a spectrum of devices from powerful personal computers to mobile devices. The broader impact/commercial potential of this project is to translate novel research using quantitative imaging biomarkers into actual clinical practice. Medical imaging is commonly used for cancer screening, treatment planning, and monitoring but the results that come from purely qualitative interpretations of these images are not always definitive. Recent progress has shown that high-throughput extraction and analysis of advanced quantitative imaging features from medical images (?radiomics?) can be used to increase the accuracy and confidence of cancer screening in certain cases. The goals of this project are to incorporate these analytics into a commercially available system for medical image display and distribution which is necessary for widespread clinical adoption. These advances will enable health care providers to lower costs associated with unnecessary follow up exams as well as to improve patient outcomes through identification of tumors that are more likely to be resistant to treatment and to more efficiently and accurately monitor the response to treatment using medical imaging.