Screening Lung Cancer by Ultra Low-Dose Computed Tomography

通过超低剂量计算机断层扫描筛查肺癌

• 批准号: 8517444
• 负责人: JEROME Z LIANG
• 金额: $ 29.52万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2015-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8517444
• 关键词: American Cancer Society; Back; Biopsy; Breast; Cancer Etiology; Cessation of life; Clinic; Clinical; Clinical Trials; Clinical assessments; Colon; Complex; Computer software; Data; Data Analyses; Data Correlations; Detection; Devices; Diagnosis; Discipline of Nuclear Medicine; Dose; Evaluation; Goals; Gold; Heart; High Resolution Computed Tomography; Image; Journals; Lead; Least-Squares Analysis; Lung; Lung nodule; Malignant Neoplasms; Malignant neoplasm of lung; Manufacturer Name; Measures; Medicine; Modality; Modeling; Modification; Morphologic artifacts; New England; Nodule; Noise; Normal Statistical Distribution; Organ; Patients; Performance; Pilot Projects; Population; Positron-Emission Tomography; Principal Investigator; Probability; Procedures; Process; Property; Protocols documentation; Radiation; Radiology Specialty; Reading; Receiver Operating Characteristics; Recruitment Activity; Reporting; Research; Resolution; Risk; Roentgen Rays; Sampling; Scanning; Signal Transduction; Slice; Solutions; Source; Speed; Staging; Survival Rate; System; Testing; Time; Tomography, Computed, Scanners; Tube; United States; Variant; Weight; X-Ray Computed Tomography; abstracting; base; clinical practice; cost; cost effective; data modeling; digital; distraction; experience; follow-up; image reconstruction; image visualization; improved; lung cancer screening; new technology; novel; prevent; programs; reconstruction; research study; restoration; screening; simulation; single photon emission computed tomography; statistics; treatment strategy; volunteer

Principal Investigators/Program Directors (Last, First, Middle): Liang, Jerome Z. Project Summary/Abstract According to American Cancer Society statistics, lung cancer is the leading cause of cancer-related death in the United States, 212,380 of new cases diagnosed and 160,390 deaths in 2007. Early detection of lung cancers (less than 3 cm) can achieve a 90% ten-year survival rate. Early sign of the cancer is small lung nodules. Current screening of the lung nodules is performed by high-resolution computed tomography (CT), which carries a significant radiation and could increase the risk of getting cancer by as high as 2% according to a recent report in The New England Journal of Medicine. In addition to the screening, more CT scans are performed for follow-up and/or biopsy procedures. Reducing the radiation risk has been attempted by CT manufacturers by both hardware optimization and software enhancement. We have been exploring adaptive noise-treatment strategies to reconstruct similar image quality at significantly low mAs level for ultra low-dose CT applications on currently available hardware configuration. Iterative image reconstruction under a statistical cost function is one of the strategies which needs powerful computing engine (costs more than a half million dollars). Analytical image reconstruction after data restoration by a statistical cost function is another strategy which generates similar results as the iterative means with a dramatic reduction of computing burden. Our pilot studies by both phantom and volunteer experiments have demonstrated great potential of the latter restoration strategy for radiation reduction while retaining the image quality and reconstruction speed on currently available CT scanners. The proposed specific aims to further explore the potential for screening lung nodules are: (SA-1). To further investigate the adaptive noise-treatment strategies toward as low mAs as achievable for lung screening: Because the first and second moments of low-mAs CT data contain the essential statistical information about the noise (higher order moments have less impact on noise reduction), we will study the properties of sample mean and variance of the data as mAs level goes down as low as achievable. In addition, data correlations in the three-dimensional spatial domain associated with tomographic imaging will be investigated. Both the noise properties and data correlation will be incorporated into a statistical cost function, i.e., Kharhunen-Lo¿ve domain penalized weighted least-squares, which can be efficiently minimized for data restoration by an analytical fashion at the highest speed. Image reconstruction from the restored data will also be analytical at the highest speed. For comparison purpose, iterative image reconstruction under a similar statistical cost function will be refined. (SA-2). To evaluate the investigated adaptive strategies by the detection of small lung nodules: The presented strategies will be first evaluated by repeated experiments on anthropomorphic phantoms with variable low mAs protocols using noise-resolution tradeoff measure and receiver operating characteristics (ROC) and channelized Hotelling trace (CHT) observer studies. Then the evaluation will be on patient lung nodule detection with comparison to currently-used mAs level by a same CT scanner, where quantitative measures will be made using performance equivalence tests and ROC studies. The successfully evaluated strategies may lead to a large clinical trial for ultra low-dose CT screening of the lung nodules, and could be extended to screening of other vital organs, such as the colon, heart, and breasts. PHS 398 (Rev. 04/06) Page __1___ Continuation Format Page

首席研究员/项目总监（最后、第一、中间）：Liang, Jerome Z. 项目概要/摘要 根据美国癌症协会的统计，肺癌是癌症相关死亡的主要原因 美国 2007 年新诊断病例 212,380 例，死亡 160,390 例。早期发现肺结核 癌症（小于3厘米）的十年生存率可达90% 癌症的早期迹象是小肺。 目前肺结节的筛查是通过高分辨率计算机断层扫描（CT）进行的， 据研究，它带有大量辐射，可能会增加患癌症的风险高达 2% 《新英格兰医学杂志》最近的一篇报道除了筛查之外，还进行了更多的 CT 扫描。 已尝试通过 CT 进行随访和/或活检程序以降低辐射风险。 厂商通过硬件优化和软件增强两方面都在探索自适应。 噪声处理策略，可在超低剂量的极低 mAs 水平下重建相似的图像质量 CT应用在当前可用的硬件配置下进行迭代图像重建。 统计成本函数是需要强大计算引擎的策略之一（成本超过一半 百万美元）是另一个通过统计成本函数恢复数据后的分析图像重建。 该策略产生与迭代方法类似的结果，并且大大减少了计算负担。 我们通过模型实验和志愿者实验进行的初步研究证明了后者的巨大潜力 减少辐射的恢复策略，同时保持图像质量和重建速度 目前可用的 CT 扫描仪的具体目的是进一步探索肺部筛查的潜力。 结节是： (SA-1) 进一步研究自适应噪声处理策略，以实现尽可能低的 mAs。 用于肺部筛查： 因为低mAs CT 数据的一阶矩和二阶矩包含了重要的统计信息 关于噪声（高阶矩对降噪影响较小），我们将研究 当 mAs 水平降至尽可能低时，数据的样本均值和方差此外，数据。 将研究与断层扫描成像相关的三维空间域中的相关性。 噪声属性和数据相关性都将被纳入统计成本函数中，即 哈胡宁-洛科ve 域惩罚加权最小二乘法，可以有效地最小化数据 还可以通过分析方式以最快的速度从恢复的数据中重建图像。 为了比较的目的，在类似的情况下迭代图像重建。 统计成本函数将得到细化。 (SA-2)。通过检测小肺结节来评估所研究的适应性策略： 所提出的策略将首先通过对拟人化模型的重复实验进行评估 具有可变低 mAs 协议，使用噪声分辨率权衡措施和接收器工作特性 （ROC）和通道化霍特林追踪（CHT）观察者研究然后对患者肺部进行评估。 通过同一 CT 扫描仪与当前使用的 mAs 水平进行比较，进行结节检测，其中定量 将使用性能等效测试和 ROC 研究来制定措施，并进行成功评估。 策略可能会导致对肺结节进行超低剂量 CT 筛查的大型临床试验，并且可能会 扩展到其他重要器官的筛查，如结肠、心脏和乳房。 PHS 398（修订版 04/06）第 __1___ 继续格式页