Diagnosis of non-polypoid neoplasia of the colon with CT colonography

描述(由申请人提供)： 结肠癌是美国男性和女性癌症死亡的第二大原因，如果检测到并切除前驱结肠癌病变，就可以预防结肠癌。拟议项目的长期目标是开发一种基于图像的诊断方法，以促进结肠癌的早期检测。计算机体层摄影术(CTC)，或虚拟结肠镜检查，是一种新兴的结肠癌筛查工具，适用于中等风险患者。基于最近的大规模多中心临床试验(包括国家CT结肠造影术试验)所证明的每个患者在检测具有临床意义的息肉方面的高敏感度和特异度，CTC现在被美国癌症协会、美国多社会任务组和美国放射学会联合指南列为结直肠癌的可行筛查选项。在Sotikno等人最近报道的一系列美国人中，很明显，亚洲和西方人群都可能患上非息肉样结直肠肿瘤，这种肿瘤占所有早期结直肠癌的54%，并倾向于与原位或粘膜下浸润性癌相关。这一发现表明，形态扁平的病变有很高的严重病理发生率，这表明有效的筛查方法将需要准确地识别这些病变。目前CTC作为筛查工具的问题是，它在检测扁平病变方面的表现在不同研究中有所不同，因此仍不确定。拟议项目的短期目标是开发和评估计算机辅助扁平病变检测(CAFD)方案，该方案可以在高分辨率CTC图像中自动检测扁平病变，并开发和评估帮助放射科医生快速准确地检测扁平病变的扁平病变解释系统。我们假设CAFD方案将为扁平病变产生临床可接受的高检测性能，并且扁平病变解释系统将提高放射科医生在CTC图像中检测扁平病变的性能。所提出的扁平病变解释系统的成功开发将大大推进基于CT的结肠癌筛查的临床实施，提高筛查率，促进结肠癌的早期诊断，并最终降低结肠癌的死亡率。

DESCRIPTION (provided by applicant): Colon cancer, the second leading cause of cancer deaths for men and women in the United States, can be prevented if precursor colonic lesions are detected and removed. The long-term goal of the proposed project is to develop an image-based diagnostic method that advances the early detection of colon cancer. Computed tomographic colonography (CTC), or virtual colonoscopy, is an emerging alternative screening tool for colon cancer in average risk patients. Based on the high per-patient sensitivity and specificity in the detection of clinically significant polyps that were demonstrated by the recent large-scale, multi-center clinical trials, including the National CT Colonography Trial, CTC is now listed as a viable screening option for colorectal cancer in the joint guideline from the American Cancer Society, the U.S. Multi-Society Task Force, and the American College of Radiology. In a recent U.S. series reported by Soetikno et al., it became clear that both Asian and Western populations may develop non-polypoidal colorectal neoplasia, which contribute to 54% of all early colorectal cancers and tend to be associated with in situ or submucosal invasive carcinomas. The finding that morphologically flat lesions have high rates of serious pathology suggests that effective screening methods will need to accurately identify these lesions. Current problem with CTC as a screening tool is that its performance for the detection of flat lesions varies across studies and thus remains undetermined. The short-term goal of the proposed project is to develop and evaluate a computer-aided flat-lesion detection (CAfD) scheme that automatically detects flat lesions in high-resolution CTC images, and to develop and evaluate a flat-lesion interpretation system that assists radiologists in detecting flat lesions quickly and accurately. We hypothesize that the CAfD scheme will yield clinically acceptable high detection performance for flat lesions, and that the flat-lesion interpretation system will improve radiologists' performance in the detection of flat lesions in CTC images. Successful development of the proposed flat-lesion interpretation system will substantially advance the clinical implementation of CT-based colon cancer screening in large populations, lead to an increased screening rate, promote the early diagnosis of colon cancer, and ultimately reduce the mortality due to colon cancer.