SBIR Phase II: A Minable, Quantitative Imaging Platform for Evidence-Based Medicine within Oncology

这个小型企业创新研究（SBIR）第二阶段项目的更广泛的影响/商业潜力是通过为他们的护理提供者提供临床数据和图像分析的集成平台，以更好地做出临床决策，从而显着改善癌症患者的护理。临床数据与放射学图像的紧密结合将使循证方法能够被肿瘤学的护理提供者使用。该项目正在开发的工具将使全面的数据驱动的癌症研究加速过渡到临床实践，以做出与癌症诊断和治疗相关的决策。最近的趋势，如电子医疗记录和放射图像的广泛采用以及以合理价格提供强大的计算能力，使得有可能提高数据的预后和诊断能力，特别是医疗保健中的成像数据分析。 正在开发的综合分析平台将通过成像简化治疗监测并减少诊断错误，从而提高癌症护理质量。拟议项目旨在开发一个综合的、可挖掘的、临床和成像数据分析平台。该平台将数据挖掘、上下文搜索、图像分割和变形配准方面的最新进展结合到部署在护理点的成像系统中。通过将当前病例的病变特征与来自具有已知诊断的其他研究的大量病变库进行比较的能力，将增强临床和图像数据的诊断潜力。所提出的搜索工具将生成具有给定的一组诊断和治疗条件的患者队列，并将相关图像呈现给诊断医生。其他技术将定位和跟踪肿瘤，并提供详细的特征，如大小，形状，位置和纹理与详细的分析。一个大型的，可挖掘的数据库分割肿瘤和详细的指标将推进研究，以确定？成像生物标志物？嵌入式成像平台将允许临床医生在从功能强大的个人电脑到平板电脑和其他移动的设备的广泛范围内访问这些决策支持工具。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to significantly improve the care of cancer patients by providing an integrated platform for clinical data and image analytics to their care providers for better clinical decision making. Tight integration of clinical data with radiology images will enable evidence-based approaches to be used by care providers in oncology. The tools being developed in this project will enable accelerated transition of comprehensive data-driven cancer research into clinical practice for decision making related to diagnosis and treatment of cancer. Recent trends, such as wide adoption of electronic medical records and radiological images and availability of powerful computing at reasonable prices have made it possible to improve the prognostic and diagnostic power of data, in particular imaging data analysis in healthcare. The integrated analytics platform being developed will streamline treatment monitoring by imaging and reduce diagnostic errors; hence increasing the quality to cancer care.The proposed project aims to develop an integrated, minable, clinical and imaging data analytics platform for oncology. The platform combines recent advances in data mining, context search, image segmentation and deformable registration into an imaging system deployed at the point of care. The diagnostic potential of clinical and image data will be enhanced by the ability to compare lesion characteristics of the current case to a large repository of lesions from other studies with known diagnosis. The proposed search tool will generate patient cohorts with a given set of diagnosis and treatment conditions and present the related images to the diagnostician. Additional technology will locate and track tumors and provide detailed characterization such as size, shape, location and texture with detailed analytics. A large, minable database of segmented tumors and detailed metrics will advance research into identifying ?imaging biomarkers?. The embedded imaging platform will allow clinicians to access these decision support tools across a wide spectrum of devices from powerful personal computers to tablets and other mobile devices.