Developing Virtual Colonoscopy for Cancer Screening

描述（由申请人提供）： 结直肠癌是美国第三大最常见的癌症，也是癌症死亡的第二大原因。它通常是在晚期被诊断出来的，在病人出现症状之后，这解释了它的高死亡率。由于大多数癌症是由息肉在5至15年的恶变期内引起的，因此提倡筛查直径小于1 cm的小息肉。不幸的是，大多数人都没有遵循这个建议。该项目的健康相关性是通过使用一种方便、几乎无风险的程序，大大增加愿意参加筛查计划的人数。 虚拟结肠镜检查（VC）是一种新的程序，其中计算机断层扫描（CT）图像的病人的腹部和计算机可视化系统是用来虚拟导航内构建的三维图像模型的结肠，模仿目前的黄金标准光学结肠镜检查（OC）。该项目的广泛的长期目标是将VC开发为一种准确，成本效益高，微创，压力最小的技术，以筛选大部分人群。 为了进一步推进这项技术，该项目更新的具体目标是：（1）研究用于VC的低剂量CT技术，以实现结肠息肉的大规模筛查;（2）扩展电子结肠清洗策略，通过基于混合的图像分割提取结肠粘膜层;（3）研究用于息肉建模的集成特征提取技术，以实现结肠息肉的计算机辅助检测（CAD）;以及（4）扩展我们当前的基于实时体绘制的导航算法，以包括CAD和交互式虚拟活检装置，用于分析疑似异常。 研究设计和方法将包括从低剂量CT图像中评估电子清洁结肠腔和提取粘膜层的能力，同时进行压力较小的肠道准备;通过记录整个结肠的CAD和交互式虚拟活检工具的VC速度和质量，将该技术带到一个容易获得的环境的可行性;以及通过使用试点研究比较同一患者的虚拟结肠镜和光学结肠镜息肉检测的准确性。

DESCRIPTION (provided by applicant): Colorectal carcinoma is the third most commonly diagnosed cancer and the second leading cause of death from cancer in the United States. Often it is diagnosed at an advanced stage, after the patient has developed symptoms, explaining its high mortality rate. Since most cancers arise from polyps over a 5 to 15 year period of malignant transformation, screening programs to detect small polyps less than 1 cm in diameter have been advocated. Unfortunately most people do not follow this recommendation. The health relatedness of this project is to dramatically increase the number of people willing to participate in screening programs by using a convenient, nearly risk-free procedure. Virtual colonoscopy (VC) is a new procedure in which computed tomographic (CT) images of the patient's abdomen are taken and a computer visualization system is used to virtually navigate within a constructed 3-D image model of the colon, mimicking the current gold-standard optical colonoscopy (OC). The broad, long-term objective of this project is to develop VC as an accurate, cost-effective, minimalinvasive, least-stressful technique to screen large segments of the population. To further advance this technology, the specific aims of this project renewal are: (1) to investigate low-dose CT techniques for VC towards massive screening of colonic polyps; (2) to extend electronic colon cleansing strategies to extract the colon mucosa layer by mixture-based image segmentation; (3) to investigate integrated feature-extraction techniques for polyp modeling towards computed aided detection (CAD) of colonic polyps; and (4) to extend our current real-time volume-rendering based navigation algorithms to include CAD and interactive virtual biopsy means for analysis of suspected abnormalities. The research design and methodology will include evaluating from low-dose CT images the ability to electronically clean the colon lumen and extract the mucosa layer with less-stressful bowel preparation; the feasibility of bringing the technology to a readily accessible environment by documenting VC speed and quality with CAD and interactive virtual biopsy tools through the entire colon; and the accuracy by comparing virtual and optical colonoscopy polyp detection in the same patient using a pilot study.