Studying measurement variability in tumor volume and volume change on MDCT

研究 MDCT 上肿瘤体积和体积变化的测量变异性

• 批准号: 8449712
• 负责人: Binsheng Zhao
• 金额: $ 32.11万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8449712
• 关键词: Address; Affect; Algorithms; Biological Markers; Caliber; Cancer Patient; Cancer and Leukemia Group B; Chest; Clinical; Clinical Data; Clinical Trials; Clinical Trials Design; Communities; Community Clinical Oncology Program; Computational algorithm; Computers; Convolution Kernel; Data; Data Set; Databases; Devices; Disease-Free Survival; Epidermal Growth Factor Receptor; Evaluation; Future; Gefitinib; Goals; Home environment; Hospitals; Image; Image Analysis; Imaging technology; Individual; Malignant neoplasm of lung; Measurement; Measures; Methods; Modeling; Molecular; Monitor; Multicenter Trials; Mutation; Neoadjuvant Therapy; Non-Small-Cell Lung Carcinoma; Operative Surgical Procedures; Outcome; Outcome Study; Pathologic; Patient Care; Patients; Phase; Picture Archiving and Communication System; Protocols documentation; Regimen; Reproducibility; Research; Role; Running; Scanning; Scientist; Series; Slice; Solid Neoplasm; Source; Specimen; Standardization; Technology; Thick; Time; TimeLine; Tumor Volume; Variant; Vendor; X-Ray Computed Tomography; anticancer research; base; chemotherapy; clinical care; clinical practice; cost; design; drug discovery; follow-up; imaging Segmentation; imaging modality; improved; in vivo; insight; lung imaging; novel; oncology; prospective; public health relevance; response; success; tool; tumor

DESCRIPTION (provided by applicant): For 30 years, the standard way to assess a patient's response to treatment has been to monitor changes in tumor diameter using serial CT exams. However, studies began to show the inadequacy of conventional methods in assessing tumor responses to novel targeted therapies. Indeed, our recent study correlating early radiographic response induced by a targeted therapy, gefitinib, with the presence of epidermal growth factor receptor mutations suggests that tumor volume change is better for detecting biologic activity of the target in non-small cell lung cancer. Despite the widespread use of CT in response assessment, contemporary analysis of CT data and its role in guiding clinical trial interpretation has neither been validated nor optimized. It is now critical that such a rigorous evaluation be undertaken as clinical trials begin incorporating volumetric CT (VCT) into the assessment of new therapies and as more computer algorithms haven been/are being developed for assisting in measuring tumor volumes. Our first goal is to systematically explore sources and variability in volume and volume change measurements that are introduced during image acquisition and tumor size measurement using both an FDA chest phantom with known ground truth (volume) and in vivo lung cancer tumors taken on same-day repeat CT scans (Aims 1 and 2). Achieving this goal will allow us to gain key insights into how and to what extent different CT vendor platforms and scanning parameters, serial CT scans, and image segmentation algorithms affect tumor volume measurement and subsequent response assessment. Such information will be essential for helping establish standards for CT imaging protocols and select appropriate algorithms to improve accuracy, consistency of volume measurements and response assessments in multicenter clinical trials. Even with improvements in accuracy and reproducibility, enhanced image quantification alone will not be accepted by the oncology community as an improved biomarker for novel therapies without showing a robust correlation of VCT with clinical outcomes. Our second goal, therefore, is to validate VCT as an early and more accurate biomarker for predicting pathologic response and disease free survival. We will do this in a prospective multicenter lung cancer trial (CALGB 30803) that is evaluating a novel neoadjuvant regimen (Aim 3). Because CT imaging technology is globally available, our algorithm can be widely distributed, run on standard computers and be integrated with picture archiving and communication systems, we expect that our findings will be broadly useful for both drug discovery and clinical care.

描述（由申请人提供）：30年来，评估患者对治疗反应的标准方法是使用连续CT检查监测肿瘤直径的变化。然而，研究开始显示传统方法在评估肿瘤对新型靶向治疗的反应方面的不足。事实上，我们最近的研究将靶向治疗吉非替尼诱导的早期放射学反应与表皮生长因子受体突变的存在相关联，表明肿瘤体积变化更适合检测非小细胞肺癌靶点的生物活性。尽管CT广泛用于缓解评估，但CT数据的当代分析及其在指导临床试验解释中的作用尚未得到验证或优化。随着临床试验开始将容积CT（VCT）纳入新疗法的评估中，以及随着更多的计算机算法已经/正在开发用于辅助测量肿瘤体积，进行如此严格的评估至关重要。 我们的第一个目标是系统地探索体积和体积变化测量的来源和变异性，这些测量是在图像采集和肿瘤尺寸测量过程中引入的，使用具有已知基础事实（体积）的FDA胸部体模和在同一天重复CT扫描中拍摄的体内肺癌肿瘤（目标1和2）。实现这一目标将使我们能够深入了解不同的CT供应商平台和扫描参数、连续CT扫描和图像分割算法如何以及在多大程度上影响肿瘤体积测量和后续反应评估。这些信息对于帮助建立CT成像方案的标准和选择适当的算法以提高多中心临床试验中体积测量和反应评估的准确性、一致性至关重要。即使在准确性和可重复性方面有所改进，在没有显示VCT与临床结局的稳健相关性的情况下，肿瘤学界也不会接受单独的增强图像定量作为新疗法的改进生物标志物。因此，我们的第二个目标是验证VCT作为预测病理反应和无病生存率的早期和更准确的生物标志物。我们将在一项前瞻性多中心肺癌试验（CALGB 30803）中评估一种新的新辅助治疗方案（Aim 3）。由于CT成像技术是全球可用的，我们的算法可以广泛分布，在标准计算机上运行，并与图像存档和通信系统集成，我们希望我们的研究结果将广泛用于药物发现和临床护理。