Studying measurement variability in tumor volume and volume change on MDCT

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通过连续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联系起来，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广泛用于反应评估，但当代CT数据分析及其指导临床试验解释的作用既没有得到验证，也没有得到优化。随着临床试验开始将体积CT （VCT）纳入新疗法的评估，以及越来越多的计算机算法已经或正在开发用于辅助测量肿瘤体积，现在进行这样严格的评估是至关重要的。我们的第一个目标是系统地探索在图像采集和肿瘤大小测量过程中引入的体积和体积变化测量的来源和可变性，这些测量使用具有已知基础真相（体积）的FDA胸部假体和在同一天重复CT扫描中获得的体内肺癌肿瘤（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、串行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随后的反应评估。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的准确性、一致性和反应评估至关重要。即使在准确性和可重复性方面有所提高，如果没有显示VCT与临床结果的强大相关性，单独增强的图像量化也不会被肿瘤学界接受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）中这样做，该试验正在评估一种新的新辅助方案（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，我们期望我们的发现将广泛用于药物发现和临床护理。

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. PUBLIC HEALTH RELEVANCE: Confirmation of the ability of VCT to detect earlier response or progression would lower the cost and accelerate the timelines of future clinical trials. The outcome of this study will be of great value in helping establish standards of imaging protocols and response criteria for the use of VCT in clinical trials and clinical care where treatment benefit is measured by the changes in tumor size assessed by CT.