Restriction Spectrum Imaging for Evaluating Glioma Treatment Response

用于评估神经胶质瘤治疗反应的限制谱成像

• 批准号: 1430082
• 负责人: Nathan White
• 金额: $ 29.66万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1430082&HistoricalAwards=false
• 关键词: Restriction; Spectrum; Imaging; Evaluating; Glioma; Restriction; Spectrum; Imaging; Evaluating; Glioma

This EAGER project "Restriction Spectrum Imaging for evaluating glioma treatment response" will create a unique data set that can be used by theoretical scientists to understand how these hard to treat tumors respond and evade treatment. This high-precision data is needed for scientists to be able to distinguish between different models of cancer growth that currently exist. Understanding tumor growth during treatment will help with the regiment of medicines used for glioma treatment and will reveal how some cells die and others evade current therapies, which is essential for the development of better strategies to treat this lethal disease. The proposed technique is based on the different physics of normal and cancerous tissue and fits well within the Physics of Living Systems (PoLS) program at NSF as a high-risk, but high-return project.The need for a human tumor growth data set that is well characterized and with low noise, which can be used by the theoretical physics community to test novel theories of tumor kinetics was recognized at: "The Physical Principles of Human Cancer Imaging Workshop" held on November 4-5, 2013 in Boston. This bold project, from a young scientist, reflects this need and the objective of this research is to evaluate the utility of a novel, non-invasive Magnetic Resonance Imaging technique, Restriction Spectrum Imaging (RSI), to detect and quantify tumor response to treatment in glioma patients. The specific objectives are to 1) procure and organize existing (and ongoing) MRI data sets (including RSI) collected across time on glioma patients at UCSD Moores Cancer Center who receive standard of care therapy which may include radiation, chemo, and anti-VEGF treatments. 2) With the help of a board certified neuro-radiologist, the second objective would be to evaluate glioma treatment response in these patients using standard published radiographic response criteria (RANO/McDonald/RECIST). 3) The final objective would be to analyze and quantify tumor cell populations directly using RSI (including the spatial extent (3D volume) and density (intensity-weighted volume)) and compare these quantitative RSI measures with the standard response criteria. RSI is a technique developed by the PI that has recently been shown to be resistant to pseudo-response and pseudo-progression, both of which plague standard radiographic response criteria and pose severe limitations to researchers involved in mathematical and physical modeling of tumor spread and resistance. RSI quantitative measures of tumor cell populations that are insensitive to pseudo-response and pseudo-progression will allow researchers and clinicians to further understand the temporal and treatment dynamics of cancer cells, to develop more targeted cancer treatments and to advance mathematical and physical models of the disease. RSI mapping of tumor cell populations may ultimately transform clinical practice and change clinical care for cancer patients. By providing an objective and quantitative measure of tumor cell volume and density directly on imaging non-invasively, patients who undergo cancer treatment may be evaluated and monitored over time with RSI to see if and where the cancer spreads to or alternatively if the particular cancer treatment is working.

这个急切的项目“用于评估神经胶质瘤治疗反应的限制频谱成像”将创建一个独特的数据集，理论科学家可以使用该集合，以了解这些难以治疗肿瘤的反应和逃避治疗。需要这种高精度数据才能使科学家能够区分目前存在的癌症生长模型。了解治疗过程中的肿瘤生长将有助于用于用于神经胶质瘤治疗的药物团，并将揭示一些细胞如何死亡，而另一些细胞逃避当前的疗法，这对于制定更好治疗这种致命疾病的策略至关重要。 The proposed technique is based on the different physics of normal and cancerous tissue and fits well within the Physics of Living Systems (PoLS) program at NSF as a high-risk, but high-return project.The need for a human tumor growth data set that is well characterized and with low noise, which can be used by the theoretical physics community to test novel theories of tumor kinetics was recognized at: "The Physical Principles of Human Cancer Imaging Workshop" held on 2013年11月4日至5日在波士顿。这个大胆的项目来自一位年轻的科学家，反映了这一需求，这项研究的目的是评估一种新型的，非侵入性的磁共振成像技术，限制频谱成像（RSI）的实用性，以检测和量化对胶质瘤患者治疗的肿瘤反应。具体目标是1）在UCSD Moores癌症中心收集的胶质瘤患者收集的现有（及其正在进行的）MRI数据集（包括RSI），他们接受了护理疗法，其中可能包括辐射，化学疗法和抗VEGF治疗。 2）借助董事会认证的神经放射科医生，第二个目标是使用标准发表的放射学反应标准（Rano/McDonald/Recist）评估这些患者的神经胶质瘤治疗反应。 3）最终目标是使用RSI（包括空间范围（3D体积）和密度（强度加权体积））直接分析和量化肿瘤细胞种群，并将这些定量RSI测量与标准响应标准进行比较。 RSI是PI开发的一种技术，最近已证明对伪反应和伪产生具有抵抗力，这两者都会损害标准的X射线照相响应标准，并对参与肿瘤扩散和耐药性数学和物理建模的研究人员产生了严重的限制。对伪反应和伪产生不敏感的肿瘤细胞群体的RSI定量测量将使研究人员和临床医生能够进一步了解癌细胞的时间和治疗动态，以开发更具靶向的癌症治疗并推动疾病的数学和物理模型。肿瘤细胞种群的RSI图可能最终改变临床实践并改变癌症患者的临床护理。通过直接在非侵入性上提供对肿瘤细胞体积和密度的客观和定量度量，可以随时间对接受癌症治疗的患者进行评估和监测，以查看癌症是否以及在特定癌症治疗起作用的癌症是否扩散到或替代癌症。