Voxelwise analysis of imaging response to therapy in neuro-oncology

描述（由申请人提供）：脑癌的侵袭性需要定量评估工具，这些工具可以早期检测对治疗的反应，以指导治疗。定量FDG-PET成像已被广泛用于Dana-Farber癌症研究所（DFCI）和其他地方的临床试验中，以评估基线（治疗前）和随访（治疗后）扫描之间的新型癌症治疗的反应。标准的分析方法，涉及手动划定的兴趣区，是强大的，但范围有限，耗时，主观。在神经影像学的背景下，我们建议开发更客观的方法，可以指示大脑中任何地方的变化，并纠正正常大脑代谢的全球和区域变化引起的混淆。这是通过治疗前和治疗后3D扫描之间的体素比较来实现的，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，将生成的体素变化图的汇总测量值作为生存预测因子进行评价。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，以及更好的临床试验治疗评价标准。利用互补的专业知识和兴趣 在图像分析方面，DFCI成像和生物统计部门之间的这种独特合作有望开发出可立即在以前和未来的临床试验中进行评估和使用的基本方法。 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.