Developing Virtual Colonoscopy for Cancer Screening

开发用于癌症筛查的虚拟结肠镜检查

基本信息

批准号：
7985504
负责人：
JEROME Z LIANG
金额：
$ 31.39万
依托单位：
STATE UNIVERSITY NEW YORK STONY BROOK
依托单位国家：
美国
项目类别：
财政年份：
2001
资助国家：
美国
起止时间：
2001-04-01 至 2014-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7985504
关键词：
Abdomen Achievement Address Advocate Algorithms Anatomy Angiography Area Barium Biopsy Bladder Blood Vessels Cathartics Cause of Death Clinical Clinical Trials Colon Colon Carcinoma Colonic Polyps Colonoscopy Computed Tomographic Colonography Computer Assisted Cystography Data Data Correlations Derivation procedure Detection Development Diagnosis Diet Documentation Dose Early Diagnosis Electronics Ensure Environment Generations Genus Cola Gold Growth Health Heterogeneity Image Intervention Intestines Iodine Laboratories Large Intestine Carcinoma Lead Learning Least-Squares Analysis Licensing Malignant - descriptor Malignant Neoplasms Manufacturer Name Marketing Measures Medicare Methods Modality Modeling Morphologic artifacts Mucous Membrane Nature Noise Optics Oral Output Patients Performance Play Poisson Distribution Polyps Population Positron-Emission Tomography Preparation Procedures Property Protocols documentation Publications Radiation Reader Recommendation Retinal Cone Risk Roentgen Rays Role Scanning Scheme Screening for cancer Screening procedure Second Primary Cancers Slice Solutions Staging Statistical Models Stress Surface Symptoms System Techniques Technology Texture Thick Time Tissues Training Tube United States Variant Virtual Endoscopy Weight Work X-Ray Computed Tomography base cancer diagnosis cost cost effectiveness data acquisition density expectation experience image reconstruction imaging Segmentation improved innovation interest laxative mortality prevent programs prospective prototype public health relevance quantum radiologist reconstruction restoration single photon emission computed tomography statistics tool virtual virtual reality

项目摘要

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 colon cancers arise from polyps over a 5 to 15 year period of malignant transformation, screening programs to detect small polyps 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 developing a convenient, nearly risk-free method of detecting small polyps. Computed tomography colonography (CTC) or CT-based virtual colonoscopy (VC) has shown a comparable performance to the gold-standard optical colonoscopy (OC) for detecting polyps of 8mm and larger by a less invasive manner. To be a screening tool, current CTC has to be advanced for acceptance by a larger population with higher detection capability on smaller polyps. These needs are documented by the recent refusal of CTC being accepted by Medicare coverage, such as reducing CT radiation, detecting smaller polyps, relieving bowel preparation (BP) stress, minimizing reader variation, improving efficiency, etc. We have made good progress in technical advancement toward the broad, long-term objective of this project, i.e., developing CTC as a safe, accurate, cost-effective, minimal-invasive, least-stressful screening modality. To advance CTC toward the long-term objective, the specific aims of this project renewal are: (1) To develop and evaluate an adaptive statistical reconstruction algorithm to obtain the current abdominal CT image quality at as low mAs level as achievable to minimize the risk of X-ray exposure. The algorithm will consider not only the X-ray quanta statistics and energy spectrum, but also the system background noise because this noise plays a noticeable role at low mAs level. (2) To develop and evaluate a partial-volume (PV) statistical segmentation algorithm with correction of fecal tagging inhomogeneity to improve electronic colon cleansing (ECC). The improvement will lead to the detection of smaller polyps, reduction of CT radiation by a half, and relief of patient stress on BP by approaching toward cathartic-free CTC. (3) To develop and evaluate an ECC-adaptive, texture-based, feature-extraction algorithm to improve computer-aided polyp detection (CADpolyp) toward enhancement of CTC cost-effectiveness. It is hoped that an improved performance with higher detection capability on smaller polyps and more acceptable by a large population (via less radiation and stress) would advance CTC toward a screening modality with acceptance by Medicare coverage. The low-mAs statistical reconstruction would be helpful to other CT applications. The PV image segmentation with correction of inhomogeneity would be beneficial to other virtual endoscopy applications, such as extracting blood vessel wall for plaque analysis in virtual angiography and bladder wall for early detection of growth in virtual cystography. PUBLIC HEALTH RELEVANCE: This proposal aims to develop computed tomography colonography (CTC) or CT-based virtual colonoscopy (VC) toward a screening modality by using (1) as low as achievable low-dose CT scan, (2) less-stressful bowel preparation (BP), e.g., minimal laxative and/or cathartic-free BP, and (3) integration of computer-aided detection (CAD) and three-dimensional (3D) endoscopic views for polyp detection.

描述（由申请人提供）：结直肠癌是美国第三大最常诊断的癌症，也是第二大癌症死亡原因。通常在患者出现症状后才被诊断为晚期，这也解释了其高死亡率的原因。由于大多数结肠癌是由经过 5 至 15 年恶变的息肉引起的，因此提倡采用筛查计划来检测小息肉。不幸的是大多数人不遵循这个建议。该项目与健康的相关性在于，通过开发一种方便、几乎无风险的小息肉检测方法，大幅增加愿意参与筛查项目的人数。计算机断层扫描结肠镜 (CTC) 或基于 CT 的虚拟结肠镜检查 (VC) 已显示出与金标准光学结肠镜检查 (OC) 相当的性能，可通过侵入性较小的方式检测 8 毫米及更大的息肉。为了成为一种筛查工具，当前的 CTC 必须经过改进才能被更多人群接受，并且对较小的息肉具有更高的检测能力。这些需求从最近拒绝接受 Medicare 覆盖的 CTC 就可以看出，例如减少 CT 辐射、检测较小的息肉、缓解肠道准备 (BP) 压力、最大限度地减少读者变异、提高效率等。我们在技术方面取得了良好进展。朝着该项目的广泛、长期目标迈进，即将 CTC 开发为一种安全、准确、具有成本效益、微创、压力最小的筛查方式。为了推动CTC实现长期目标，本项目更新的具体目标是：（1）开发和评估自适应统计重建算法，以尽可能低的mAs水平获得当前腹部CT图像质量，以最大程度地降低风险X 射线暴露。该算法不仅会考虑 X 射线量子统计和能谱，还会考虑系统背景噪声，因为这种噪声在低 mAs 水平下起着显着的作用。 (2) 开发和评估部分体积（PV）统计分割算法，纠正粪便标记不均匀性，以改进电子结肠清洁（ECC）。这一改进将导致更小的息肉的检测、CT 辐射减少一半，并通过接近无泻药的 CTC 来减轻患者对血压的压力。 (3) 开发和评估 ECC 自适应、基于纹理的特征提取算法，以改进计算机辅助息肉检测 (CADpolyp)，从而提高 CTC 成本效益。希望改进的性能、对较小息肉的更高检测能力以及更容易被大量人群接受（通过更少的辐射和压力）将推动 CTC 迈向被医疗保险覆盖范围接受的筛查模式。低mAs统计重建将有助于其他CT应用。具有不均匀性校正的 PV 图像分割将有利于其他虚拟内窥镜检查应用，例如提取血管壁以在虚拟血管造影中进行斑块分析，以及提取膀胱壁以在虚拟膀胱造影中早期检测生长。公共健康相关性：该提案旨在开发计算机断层扫描结肠成像 (CTC) 或基于 CT 的虚拟结肠镜检查 (VC)，通过使用 (1) 尽可能低的低剂量 CT 扫描，(2) 肠道压力较小准备（BP），例如最小限度的泻药和/或无泻药血压，以及（3）计算机辅助检测（CAD）和三维（3D）内窥镜的集成息肉检测视图。