Glioblastoma Recurrence Versus Radiotherapy Injury Combined Model of Diffusion Kurtosis Imaging and 11C-MET Using PET/MRI May Increase Accuracy of Differentiation
Glioblastoma Recurrence Versus Radiotherapy Injury Combined Model of Diffusion Kurtosis Imaging and 11C-MET Using PET/MRI May Increase Accuracy of Differentiation
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DOI：
10.1097/rlu.0000000000004167
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发表时间：
2022-06-01
影响因子：
10.6
通讯作者：
Xu, Baixuan
中科院分区：
文献类型：
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作者：
Dang, Haodan;Zhang, Jinming;Xu, Baixuan
目的评价扩散峰度成像（DKI）和C-11-蛋氨酸（C-11-MET）PET决策树模型在胶质母细胞瘤放疗损伤与复发鉴别诊断中的应用价值。方法回顾性分析86例胶质母细胞瘤放疗后可疑病灶的临床资料。根据组织病理学或随访，48例患者被诊断为局部胶质母细胞瘤复发，38例患者在2014年4月至2019年12月期间发生RT损伤。所有患者均行PET/MRI检查。根据肿瘤与正常对照（TNR）的比值，计算多个参数，包括SUVmax和SUVmean，DKI的峰度和扩散系数（MK，MD）的平均值，以及直方图参数。采用决策树方法建立诊断模型。应用受试者工作特征分析评价各独立参数及各诊断模型的诊断准确性。结果DKI、PET和纹理参数的簇间相关性较弱，而簇内相关性较强。与单独的DKI模型（灵敏度= 1.00，特异性= 0.70，曲线下面积[AUC]= 0.85）和单独的PET模型（灵敏度= 0.83，特异性= 0.90，AUC = 0.89）相比，联合模型显示出最佳的诊断准确性（灵敏度= 1.00，特异性= 0.90，AUC = 0.95）。结论扩散峰度成像、C-11-MET PET和直方图参数提供了有关组织的补充信息。结合这些参数的决策树模型有可能进一步提高诊断准确性，以区分RT损伤和胶质母细胞瘤复发，超过神经肿瘤学标准中的标准反应评估。因此，C-11-MET PET/MRI可能有助于RT后疑似病变的胶质母细胞瘤患者的管理。
Purpose To evaluate the diagnostic potential of decision-tree model of diffusion kurtosis imaging (DKI) and C-11-methionine (C-11-MET) PET, for the differentiation of radiotherapy (RT) injury from glioblastoma recurrence. Methods Eighty-six glioblastoma cases with suspected lesions after RT were retrospectively enrolled. Based on histopathology or follow-up, 48 patients were diagnosed with local glioblastoma recurrence, and 38 patients had RT injury between April 2014 and December 2019. All the patients underwent PET/MRI examinations. Multiple parameters were derived based on the ratio of tumor to normal control (TNR), including SUVmax and SUVmean, mean value of kurtosis and diffusivity (MK, MD) from DKI, and histogram parameters. The diagnostic models were established by decision trees. Receiver operating characteristic analysis was used for evaluating the diagnostic accuracy of each independent parameter and all the diagnostic models. Results The intercluster correlations of DKI, PET, and texture parameters were relatively weak, whereas the intracluster correlations were strong. Compared with models of DKI alone (sensitivity =1.00, specificity = 0.70, area under the curve [AUC] = 0.85) and PET alone (sensitivity = 0.83, specificity = 0.90, AUC = 0.89), the combined model demonstrated the best diagnostic accuracy (sensitivity = 1.00, specificity = 0.90, AUC = 0.95). Conclusions Diffusion kurtosis imaging, C-11-MET PET, and histogram parameters provide complementary information about tissue. The decision-tree model combined with these parameters has the potential to further increase diagnostic accuracy for the discrimination between RT injury and glioblastoma recurrence over the standard Response Assessment in Neuro-Oncology criteria. C-11-MET PET/MRI may thus contribute to the management of glioblastoma patients with suspected lesions after RT.