Shutter-Speed Model DCE-MRI for Assessment of Response to Cancer Therapy

描述(申请人提供)：在临床肿瘤学和药物开发中，确实需要灵敏和可重现的定量成像方法来早期预测治疗反应和准确评估治疗后残留癌症。这些方法有可能使无反应的患者免受无效和/或毒性治疗的影响，改善临床管理，并加快新疗法的疗效评估。动态对比增强(DOE)MRI可以很好地测量治疗引起的肿瘤血管改变。用于DCE-MRL药代动力学分析的标准模型(SM)错误地假设了有效的无限快平衡的房室间水交换动力学，结果往往低估了药代动力学参数KTrans和Ve。快门速度模型(SSM)考虑了有限的水交换动力学效应，并修正了成像生物标志物的低估。事实证明，它对血管变化比SM更敏感。此外，SSM DCE-MRL允许对新的成像生物标记物进行量化，例如？KTrans(=KTrans(SSM)-KTrans(SM)]-这是一种精确地测量水交换(快门速度)对KTrans估计的影响的指标。？Ktransis不仅是治疗反应的更敏感的生物标志物，而且也不容易出现在DCE-MRL定量中经常观察到的其他系统误差。在具体目标1中，快门速度模型将应用于两个疾病领域(乳腺癌和软组织肉瘤)的L/11期临床试验，SSMDCE-MRL将与SMDCE-MRL、扩散加权磁共振成像和肿瘤大小测量进行比较/结合，以评估治疗效果。在目标2中，将在治疗监测的范围内调查数据采集和处理方案对DCE-MRL生物标记物值的影响。在目标1和目标2中，病理结果将被用作与成像结果和统计分析相关联的终点。在目标3中，将开发符合caBIG的软件工具，利用单一和/或一组成像生物标记物来帮助临床研究。

DESCRIPTION (provided by applicant): In clinical oncology and drug development there is genuine need for sensitive and reproducible quantitative imaging methods for early prediction of therapy response and accurate assessment of post-therapy residual cancer. Such methods have the potential to spare non-responding patients from ineffective and/or toxic treatments, improve clinical management, and accelerate efficacy evaluation of novel therapies. Dynamic- Contrast-Enhanced (DOE) MRI can provide an excellent measure of therapy-induced tumor vascular changes. The Standard-Model (SM) for pharmacokinetic DCE-MRl analysis incorrectly assumes effectively infinitely fast equilibrium inter-compartmental water exchange kinetics and, as a result, often underestimates the pharmacokinetic parameters Ktrans and Ve. The Shutter-Speed Model (SSM) accounts for finite water exchange kinetics effects and corrects the imaging biomarker underestimations. It has proven more sensitive to vascular changes than the SM. In addition, SSM DCE-MRl allows quantification of novel imaging biomarkers, such as ?Ktrans(= Ktrans (SSM) - Ktrans (SM)] - a measure of precisely the water exchange (shutter-speed) effect on Ktrans estimation. ?Ktransis not only a more sensitive biomarker for therapeutic response, but also less prone to other systematic errors often observed in DCE-MRl quantification. In Specific Aim 1, the Shutter-Speed Model will be applied to phase l/ll clinical trials in two disease areas (breast cancer and soft tissue sarcoma), SSM DCE-MRl will be compared/combined with SM DCE-MRl, diffusion-weighted MRI and tumor size measurement for assessment of therapy response. In Aim 2, the effects of data acquisition and processing schemes on DCE-MRl biomarker values will be investigated within the context of therapeutic monitoring. In Aims 1 and 2, pathology results will be used as endpoints for correlation with imaging results and statistical analyses. In Aim 3, caBIG-compliant software tools will be developed that utilize a single and/or a set of imaging biomarkers to aid clinical research.