Smith Ethan A, Carlos Ruth C, Junck Larry R, Tsien Christina I, Elias Augusto, Sundgren Pia C
Department of Radiology, University of Michigan Health System, Ann Arbor, MI 48109-5030, USA.
AJR Am J Roentgenol. 2009 Feb;192(2):W45-52. doi: 10.2214/AJR.07.3934.
Differentiation between recurrent neoplasm and postradiation change in patients previously treated for primary brain tumors is often difficult based on imaging features alone. The purpose of this study was to develop a method using alterations in the ratios of standard brain metabolites-choline (Cho), creatine (Cr), and N-acetylaspartate (NAA)-to predict the probability of tumor recurrence in patients previously treated for brain tumors with new contrast-enhancing lesions.
Thirty-three patients who had undergone treatment for primary brain tumors in whom routine MRI showed new contrast-enhancing lesions were retrospectively studied. The final diagnosis was assigned using histopathology (n = 13) or imaging follow-up (n = 20; range, 2-27 months). Ratios of three metabolites (Cho, Cr, and NAA) were calculated, and the results were correlated with the final diagnosis using a Wilcoxon's rank sum analysis. A logistic regression model was then used to create a prediction model based on the most statistically significant ratio.
Elevations of the metabolic ratios Cho/Cr (p < 0.001) and Cho/NAA (p < 0.001) and a decrease in the ratio NAA/Cr (p = 0.018) were found in patients with recurrent tumor (n = 20) versus those with postradiation change (n = 13). A prediction model using the Cho/NAA ratio yielded a sensitivity of 85%, a specificity of 69.2%, and an area under the receiver operating characteristic curve of 0.92.
An elevated Cho/NAA ratio correlated with evidence of tumor recurrence and allowed creation of a prediction rule to aid in lesion classification. The results suggest that MR spectroscopy is a useful tool in assigning patients with nonspecific enhancing lesions to either invasive biopsy or conservative management.
对于曾接受原发性脑肿瘤治疗的患者,仅依据影像学特征往往难以区分肿瘤复发与放疗后改变。本研究的目的是开发一种利用标准脑代谢物——胆碱(Cho)、肌酸(Cr)和N - 乙酰天门冬氨酸(NAA)——比值变化来预测曾接受脑肿瘤治疗且出现新的对比增强病变患者肿瘤复发概率的方法。
对33例曾接受原发性脑肿瘤治疗且常规MRI显示有新的对比增强病变的患者进行回顾性研究。最终诊断通过组织病理学(n = 13)或影像学随访(n = 20;范围为2 - 27个月)确定。计算三种代谢物(Cho、Cr和NAA)的比值,并使用Wilcoxon秩和分析将结果与最终诊断相关联。然后使用逻辑回归模型基于统计学上最显著的比值创建预测模型。
与放疗后改变患者(n = 13)相比,复发肿瘤患者(n = 20)的代谢比值Cho/Cr(p < 0.001)和Cho/NAA(p < 0.001)升高,而NAA/Cr比值降低(p = 0.018)。使用Cho/NAA比值的预测模型敏感性为85%,特异性为69.2%,受试者操作特征曲线下面积为0.92。
Cho/NAA比值升高与肿瘤复发证据相关,并有助于创建用于病变分类的预测规则。结果表明磁共振波谱是一种有用的工具,可帮助将具有非特异性增强病变的患者分配至侵入性活检或保守治疗。