Advanced MRI methods for detecting pseudo-progression of glioblastomas

描述(申请人提供)：配合替莫唑胺的新辅助化疗和放射治疗已成为治疗胶质瘤的标准疗法，因为这种方案可提高新诊断的胶质母细胞瘤患者的存活率。然而，在大约三分之一的患者中，MRI上的进行性和强化病变在化疗结束后六个月内发生，无需进一步干预即可消失。这些病变被称为假性进展(PSP)，因为它们在标准的临床MRI上模仿肿瘤的外观。PSP患者的生存期较长，表明进展性病变是由于治疗效果而不是真正的肿瘤进展(TP)所致。准确识别PSP对于患者管理至关重要，因为PSP患者可以避免不必要的重复手术并继续有效的化疗，同时可以为TP提供包括切除或免疫治疗在内的替代治疗。功能磁共振成像工具，如扩散张量成像(DTI)、灌注成像和磁共振波谱(MRS)、水流动性、血流和组织代谢的探头变化，在发现变化方面比标准MRI观察到的解剖变化更敏感。此外，在临床环境中，单一的成像参数或方式不太可能满足PSP的准确检测。因此，我们假设，结合全脑MRS、灌注成像和DTI可以提供更准确的PSP检测。为了验证这一假设，我们将开发一种新的决策支持系统，它以完全无偏见的方式使用所有成像模式的重要特征。具体地说，我们将实现以下目标：SA1：评估3D EPSI在区分PSP患者和TP患者中的应用。SA2：探讨动态磁化率加权对比成像在PSP与TP鉴别诊断中的作用。SA3：评价平均弥散系数(MD)、分数各向异性(FA)和张量形状测量(包括线性各向异性系数(CL)、平面各向异性系数(CP)和球面各向异性系数(CS))在PSP鉴别诊断中的准确性。SA4：确定准确诊断PSP的最佳成像参数组合。这些参数的有效性将在首次临床表现(基线)时进行测试，并在一个月的随访扫描中测试这些参数的变化。基于贝叶斯网络的决策支持系统将用于检测PSP，其中将包括高级成像参数，以及这些参数自基线以来的变化。这种方法的新奇之处在于，它将提供脑肿瘤的多维分析，这将有助于PSP的准确诊断，并避免这些患者不必要的二次手术。

DESCRIPTION (provided by applicant): Neo-adjuvant chemotherapy with temozolomide, along with radiation therapy has become the standard of care for the treatment of gliomas as this regimen improves survival of newly diagnosed glioblastoma patients. However, in about a third of the patients, progressive and enhancing lesions on MRI occur within six months after end of chemo-radiation therapy, which resolve without further interventions. These lesions are termed as pseudo-progression (PsP) as they mimic the appearance of a tumor on standard clinical MRI. Patients with PsP have a longer survival indicating that the progressive lesions were due to treatment effect rather than due to true tumor progression (TP). Accurate identification of PsP is critical for patient management as PsP patients can avoid unnecessary repeat surgery and continue effective chemotherapy, while alternative treatments, including resection or immunotherapy can be offered for TP. Functional MRI tools, such as, diffusion tensor imaging (DTI), perfusion imaging and magnetic resonance spectroscopy (MRS), probe changes in water mobility, blood flow and tissue metabolism, which are more sensitive in detecting changes than anatomical changes observed by standard MRI. Furthermore, in a clinical setting, it is unlikely that a single imaging parameter or modality will suffice in accurae detection of PsP. We thus hypothesize that the combination of whole brain MRS, perfusion imaging and DTI can provide a more accurate detection of PsP. In order to test this hypothesis, we will develop a novel decision support system that uses important features from all the imaging modalities in a completely non-biased way. Specifically, we will achieve the following aims: SA1: To assess the utility of 3D EPSI in differentiation of PsP patients from TP. SA2: To determine the role of dynamic susceptibility weighted contrast imaging in differentiation of PsP from TP. SA3: To evaluate the accuracy of DTI parameters, such as mean diffusivity (MD), fractional anisotropy (FA) and tensor shape measures including linear anisotropy coefficient (CL), planar anisotropy coefficient (CP) and spherical anisotropy coefficient (CS) in the identification of PsP. SA4: To determine the best combination of imaging parameters for accurate diagnosis of PsP. The utility of these parameters will be tested both at first clinical presentation (baseline) as well as change in these parameters on one-month follow up scan. A Bayesian network based decision support system will be used to detect PsP which will include advanced imaging parameters, as well as change in these parameters from baseline. The novelty of this approach is that it will provide a multi-dimensional analysis of brain tumors, whic will facilitate an accurate diagnosis of PsP and avoid unnecessary second-look surgery in these patients.