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，可以早期检测治疗反应，以指导治疗。定量FDG-PET成像已被广泛应用于达纳-法伯癌症研究所（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）扫描之间新型癌症疗法的反应。标准的分析方法，包括手动描述感兴趣的区域，是健壮的，但在范围、时间和主观方面是有限的。在神经影像学的背景下，我们建议发展更客观的方法，可以显示大脑任何地方的变化，并纠正正常脑代谢的整体和区域变化引起的混淆。这是通过预处理和后处理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，对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一个

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.