Diffusion MRI of Treatment Response for De-escalation of Radiation Therapy

弥散 MRI 评估放射治疗降级的治疗反应

• 批准号: 10328699
• 负责人: Sungheon Gene Kim
• 金额: $ 32.17万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10328699
• 关键词: Diffusion; MRI; Treatment; Response; De

PROJECT SUMMARY Chemo-radiation therapy is a standard treatment regimen for locally advanced head and neck squamous cell carcinoma (HNSCC). The treatment regimen, however, is difficult for patients as they experience high rates of grade 3 or higher toxicities including leukopenia (42%) and the need for feeding tube (52%). Recent studies showed that a subgroup of HNSCC patients with human-papilloma virus (HPV)-positive oropharyngeal (OP) SCC have significantly better prognosis. These clinical data lead to important considerations to de-intensify treatment for this low-risk, younger population in order to reduce acute and chronic toxicity without compromising disease control. It has been suggested that the adaptive de-escalation of treatment can be tailored for individual patients based on the early tumor volume change. However, volumetric assessment is often inadequate because the treatment response of a tumor can be heterogeneous in terms of (i) cell viability, (ii) cellular metabolism, and (iii) perfusion that are relevant to the success of any chemoradiation therapy. These complex changes may not be adequately represented by tumor volume change at the early stage. The proposed study is based on a combination of the quantitative diffusion MRI (dMRI) methods with their own technical innovations that can also be applied to other clinical studies. dMRI is a unique in vivo imaging technique sensitive to cellular microstructures at the scale of water diffusion length on the order of a few microns. However, quantitative dMRI remains challenging as dMRI data represent different biophysical properties of tissue depending on diffusion weighting strength (q) and diffusion time (t) used for the measurement. The scientific premise of the proposal is that this study will establish a quantitative way to utilize both q- and t-dependent dMRI data as a tailored approach to quantify cell viability, cellular metabolism and perfusion from this non-contrast MRI method. We demonstrated that both diffusion coefficient D and diffusional kurtosis coefficient K are promising imaging markers for cell viability. Cellular metabolism can be evaluated in terms of the water exchange τex, measured by the diffusion time-dependent K, that is regulated by the ATP- dependent trans-membrane ion channels co-transporting water molecules. Intravoxel incoherent motion MRI metrics (pseudo diffusivity, Dp; perfusion fraction, fp) can provide information about perfusion flow. Ultimately, these dMRI measures will better identify patients who have the potential to benefit from adaptive de-escalation or escalation of therapy. In this proposal, we will further optimize and establish a set of quantitative non-contrast imaging markers of cell viability (D and K), cellular metabolism (τex), and perfusion (fp⋅Dp) as a clinical tool for assessment of treatment response and validate it in a clinical trial. The data acquisition and analysis software tools to be developed in this study will enable comprehensive and quantitative assessment of cancer treatment response to tailor chemoradiation therapies for individual patients.

项目总结