Voxelwise analysis of imaging response to therapy in neuro-oncology

描述(申请人提供)：脑癌的侵袭性需要量化评估工具，可以及早检测治疗反应，以指导治疗。在Dana-Farber癌症研究所(DFCI)和其他地方的临床试验中，定量FDG-PET成像已被广泛使用，以评估新癌症疗法在基线(治疗前)和后续(治疗后)扫描之间的反应。标准的分析方法，包括手工描绘感兴趣的区域，是稳健的，但范围有限，耗时和主观。在神经成像的背景下，我们建议开发更客观的方法，可以指示大脑中任何位置的变化，并纠正由正常大脑代谢的全局和局部变化引起的混淆。这是通过在处理前和处理后的3D扫描之间进行体素比较来实现的，在此之前是空间配准、分割和背景调整，然后是显著性阈值。在临床试验中，生成的体素变化图的汇总测量被评估为生存的预测因子。本提案中的方法将提供 更好的放射学评估患者进展或反应的工具，以及在临床试验中评估治疗的更好标准。利用互补的专业知识和兴趣 在图像分析方面，DFCI成像和生物统计学部门之间的这种独特的合作有望开发出基本的方法，这些方法可以立即进行评估，并在以前和未来的临床试验中使用。 公共卫生相关性：本提案中的方法将为脑癌患者进展或治疗反应的放射学评估提供更好的工具，并为临床试验中的治疗评估提供更好的标准。

DESCRIPTION (provided by applicant): The aggressiveness of brain cancer requires quantitative evaluation tools that can detect response to therapy early in order to guide treatment. Quantitative FDG-PET imaging has been used extensively, both within clinical trials at the Dana-Farber Cancer Institute (DFCI) and elsewhere, to evaluate the response of novel cancer therapies between a baseline (pre-treatment) and a follow-up (post-treatment) scan. The standard analysis approach, involving manual delineation of regions of interest, is robust but limited in scope, time-consuming, and subjective. In the context of neuroimaging, we propose to develop more objective methods that can indicate changes anywhere in the brain and correct for the confounding induced by global and regional changes in normal brain metabolism. This is achieved by a voxelwise comparison between the pre-treatment and post-treatment 3D scans, preceded by spatial registration, segmentation and background adjustment, and followed by significance thresholding. Summary measures of the generated voxelwise change maps are evaluated as predictors of survival in clinical trials. The methods in this proposal will provide a better tool for radiological assessment of patient progression or response and a better standard for evaluation of therapy in clinical trials. Capitalizing on complimentary expertise and interests in image analysis, this unique collaboration between the departments of Imaging and Biostatistics at DFCI holds the promise of developing fundamental methodologies that can immediately be evaluated and utilized in previous and future clinical trials. PUBLIC HEALTH RELEVANCE: The methods in this proposal will provide a better tool for radiological assessment of patient progression or response to treatment in brain cancer and a better standard for evaluation of therapy in clinical trials.