Chuthip Pornthida, Sitthinamsuwan Bunpot, Witthiwej Theerapol, Tansirisithikul Chottiwat, Khumpalikit Inthira, Nunta-Aree Sarun
Division of Neurosurgery, Department of Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Department of Surgery, Pattani Hospital, Pattani, Thailand.
Asian J Neurosurg. 2024 Jun 6;19(2):186-201. doi: 10.1055/s-0044-1787051. eCollection 2024 Jun.
Differentiation between glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and metastasis is important in decision-making before surgery. However, these malignant brain tumors have overlapping features. This study aimed to identify predictors differentiating between GBM, PCNSL, and metastasis. Patients with a solitary intracranial enhancing tumor and a histopathological diagnosis of GBM, PCNSL, or metastasis were investigated. All patients with intracranial lymphoma had PCNSL without extracranial involvement. Demographic, clinical, and radiographic data were analyzed to determine their associations with the tumor types. The predictors associated with GBM were functional impairment ( = 0.001), large tumor size ( < 0.001), irregular tumor margin ( < 0.001), heterogeneous contrast enhancement ( < 0.001), central necrosis ( < 0.001), intratumoral hemorrhage ( = 0.018), abnormal flow void ( < 0.001), and hypodensity component on noncontrast cranial computed tomography (CT) scan ( < 0.001). The predictors associated with PCNSL comprised functional impairment ( = 0.005), deep-seated tumor location ( = 0.006), homogeneous contrast enhancement ( < 0.001), absence of cystic appearance ( = 0.008), presence of hypointensity component on precontrast cranial T1-weighted magnetic resonance imaging (MRI; = 0.027), and presence of isodensity component on noncontrast cranial CT ( < 0.008). Finally, the predictors for metastasis were an infratentorial ( < 0.001) or extra-axial tumor location ( = 0.035), smooth tumor margin ( < 0.001), and presence of isointensity component on cranial fluid-attenuated inversion recovery MRI ( = 0.047). These predictors may be used to differentiate between GBM, PCNSL, and metastasis, and they are useful in clinical management.
在手术前的决策过程中,区分胶质母细胞瘤(GBM)、原发性中枢神经系统淋巴瘤(PCNSL)和脑转移瘤非常重要。然而,这些恶性脑肿瘤具有一些重叠的特征。本研究旨在确定区分GBM、PCNSL和脑转移瘤的预测因素。
对患有孤立性颅内强化肿瘤且组织病理学诊断为GBM、PCNSL或脑转移瘤的患者进行了调查。所有颅内淋巴瘤患者均为无颅外受累的PCNSL。分析了人口统计学、临床和影像学数据,以确定它们与肿瘤类型的关联。
与GBM相关的预测因素包括功能障碍(P = 0.001)、肿瘤体积大(P < 0.001)、肿瘤边缘不规则(P < 0.001)、不均匀对比增强(P < 0.001)、中央坏死(P < 0.001)、瘤内出血(P = 0.018)、异常血流空洞(P < 0.001)以及非增强头颅计算机断层扫描(CT)上的低密度成分(P < 0.001)。与PCNSL相关的预测因素包括功能障碍(P = 0.005)、肿瘤位于深部(P = 0.006)、均匀对比增强(P < 0.001)、无囊状表现(P = 0.008)、在头颅T1加权磁共振成像(MRI)平扫前存在低信号成分(P = 0.027)以及在非增强头颅CT上存在等密度成分(P < 0.008)。最后,脑转移瘤的预测因素为幕下(P < 0.001)或轴外肿瘤位置(P = 0.035)、肿瘤边缘光滑(P < 0.001)以及在头颅液体衰减反转恢复序列MRI上存在等信号成分(P = 0.047)。
这些预测因素可用于区分GBM、PCNSL和脑转移瘤,对临床管理具有重要意义。