Supratentorial low-grade glioma resectability: Statistical predictive analysis based on anatomic MR features and tumor characteristics
Supratentorial low-grade glioma resectability: Statistical predictive analysis based on anatomic MR features and tumor characteristics
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DOI：
10.1148/radiol.2392050661
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发表时间：
2006-05-01
期刊：
影响因子：
19.7
通讯作者：
Jolesz, FA
中科院分区：
文献类型：
--
作者：
Talos, IF;Zou, KH;Jolesz, FA
目的：回顾性评价影响磁共振成像完全切除幕上低级别胶质瘤的主要因素。材料和方法：这项符合hipaa的回顾性研究获得了机构审查委员会的批准，并放弃了知情同意的要求。我们分析了101例（男61例，女40例，平均年龄39岁，年龄范围18-72岁）的幕上非强化肿块病变，经组织病理学诊断为低级别（世界卫生组织II级）胶质瘤，并在术中MR成像指导下连续接受手术的患者的数据。低级别星形细胞瘤21例，少突胶质细胞瘤64例，混合型少突星形细胞瘤16例。在术中t2加权MR图像和三维破坏梯度回声MR图像上测量初始和残余肿瘤体积。根据术前磁共振成像结果，分析肿瘤与皮层和/或皮层下区域之间的解剖关系以及这些关系对切除范围的影响。进行汇总测量、单变量Fisher精确检验和t检验以及多变量logistic回归分析。结果：肿瘤体积范围为2.7 ~ 231.0 mL。单因素分析显示以下肿瘤特征是肿瘤不完全切除的重要预测变量：t2加权MR图像上弥漫的肿瘤边缘、少突胶质细胞瘤或少突星形细胞瘤的组织病理学类型、肿瘤体积大（均P < 0.05）。肿瘤累及以下结构与不完全切除相关：胼胝体、皮质脊髓束、岛叶、大脑中动脉、运动皮质、视辐射、视觉皮质和基底神经节（所有P < 0.05）。多因素分析显示，肿瘤切除不完全是由于肿瘤累及皮质脊髓束（P < 0.01）、肿瘤体积大（P < 0.01）和少突胶质细胞瘤的组织病理类型（P < 0.02）。结论：应用统计学预测分析方法，确定了101例肿瘤不完全切除的主要影响因素。(c) RSNA， 2006年。
Purpose: To retrospectively assess the main variables that affect the complete magnetic resonance (MR) imaging-guided resection of supratentorial low-grade gliomas.Materials and Methods: Institutional review board approval was obtained for this retrospective HIPAA-compliant study, with the requirement for informed consent waived. Data from 101 patients (61 men, 40 women; mean age, 39 years; age range, 18-72 years) who had nonenhancing supratentorial mass lesions that were histopathologically diagnosed as low-grade (World Health Organization grade II) gliomas and consecutively underwent surgery with intraoperative MR imaging guidance were analyzed. There were 21 low-grade astrocytomas, 64 oligodendrogliomas, and 16 mixed oligoastrocytomas. Initial and residual tumor volumes were measured on intraoperative T2-weighted MR images and three-dimensional spoiled gradient- echo MR images. The anatomic relationships between the tumor and eloquent cortical and/or subcortical regions and the influence of these relationships on the extent of resection were analyzed on the basis of preoperative MR imaging findings. Summary measures, univariate Fisher exact test and t test, and multivariate logistic regression analyses were performed.Results: Tumor volume ranged from 2.7-231.0 mL. Univariate analyses revealed the following tumor characteristics to be significant predictive variables of incomplete tumor resection: diffuse tumor margin on T2-weighted MR images, oligodendroglioma or oligoastrocytoma histopathologic type, and large tumor volume (P < .05 for all). Tumor involvement of the following structures was associated with incomplete resection: corpus callosum, corticospinal tract, insular lobe, middle cerebral artery, motor cortex, optic radiation, visual cortex, and basal ganglia (P < .05 for all). Multivariate analyses revealed that incomplete tumor resection was due to tumor involvement of the corticospinal tract (P < .01), large tumor volume (P < .01), and oligodendroglioma histopathologic type (P < .02).Conclusion: The main variables associated with incomplete tumor resection in 101 patients were identified by using statistical predictive analyses. (c) RSNA, 2006.