Cloud-computer-aided diagnostic imaging decision support system

描述(申请人提供)：高性能云计算(HPCC)将高性能计算(HPC)与云计算相结合，为处理和移动显示高质量的多维诊断图像提供所需的超级计算信息学基础设施。这样的基础设施将促进高通量癌症筛查，如虚拟结肠镜(VC)，也称为计算机断层扫描结肠镜(CTC)。该建议的短期目标是开发和验证新型移动式下一代HPCC-VC决策支持系统(HPCC-VC2)的临床益处，该系统集成了(1)用于重建超低剂量(ULD)超分辨率(SR)多能量无泻剂CTC(ME-lfCTC)图像的高性能迭代重建技术(HpIRT)；(2)用于清除残留粪便的高效计算机辅助肠道准备(HpCABP)方案和高性能计算机辅助检测(HpCADe)方案以及ME-lfCTC中息肉和扁平非息肉状病变的检测。具体地说，我们假设HPCC-VC2系统将(1)在ULD为1 MSY或更低的情况下提供ME-lfCTC检查，(2)实现对大肠病变的高检测性能，(3)在5分钟内准备CTC检查，以及(4)提高阅读器从移动显示设备上显示的lfCTC图像检测大肠病变的性能。具体目标是：(1)开发用于将原始CTC数据快速上传到HPCC的动态压缩方案；(2)为ULD SR ME-CTC开发并行hpIRT方法；(3)为HPCC-VC2开发并行hpCABP和hpCADe方案；以及(4)评估HPCC-VC2系统的临床效益。HPCC-VC2系统的成功开发将展示该平台在改善诊断成像和促进患者高度接受的准确、高通量结肠癌筛查方面的临床好处。从长远来看，HPCC-VC2系统的广泛采用和使用将有助于早期和准确的诊断，从而降低结肠癌的死亡率，结肠癌目前是美国癌症死亡的第三大原因。

DESCRIPTION (provided by applicant): High-performance cloud computing (HPCC) integrates high-performance computing (HPC) with cloud computing to provide the supercomputing informatics infrastructure needed for the processing and mobile display of high quality, multi-dimensional diagnostic images. Such infrastructure would advance high-throughput cancer screening like virtual colonoscopy (VC), also known as computed tomography colonography (CTC). The short-term goals of this proposal are to develop and validate the clinical benefits of a novel mobile next-generation HPCC-VC decision support system (HPCC-VC2) that integrates (1) a high-performance iterative reconstruction techniques (hpIRT) for reconstructing ultra-low-dose (ULD) super-resolution (SR) multi-energy laxative-free CTC (ME-lfCTC) images, (2) a high-performance computer-assisted bowel preparation (hpCABP) scheme for removal of residual fecal materials and a high-performance computer-aided detection (hpCADe) scheme and detection of polypoid and flat non-polypoid lesions in ME-lfCTC. Specifically, we hypothesize that the HPCC-VC2 system will (1) provide an ME-lfCTC examination at an ULD of 1 mSy or less, (2) achieve high detection performance for colorectal lesions, (3) prepare a CTC examination within 5 minutes, and (4) improve readers' performance in the detection of colorectal lesions from lfCTC images shown on mobile display devices. The specific aims are: (1) develop dynamic compression scheme for rapid uploading of raw CTC data to the HPCC; (2) develop parallel hpIRT method for ULD SR ME-CTC; (3) develop parallel hpCABP and hpCADe schemes for the HPCC-VC2; and (4) evaluate the clinical benefit of the HPCC-VC2 system. Successful development of the HPCC-VC2 system will demonstrate the clinical benefit of the platform for improved diagnostic imaging and facilitation of accurate, high-throughput colon cancer screening that is highly acceptable to patients. In the longer term, broad adoption and use of the HPCC-VC2 system will facilitate early and accurate diagnoses, and thus will reduce mortality from colon cancer that is currently the third leading cause of cancer deaths in the United States.