18F-FET PET 在疑似脑胶质瘤的新诊断脑病变中的诊断性能。
Diagnostic performance of 18F-FET PET in newly diagnosed cerebral lesions suggestive of glioma.
机构信息
Department of Neurosurgery, Heinrich-Heine University, Düsseldorf, Germany.
出版信息
J Nucl Med. 2013 Feb;54(2):229-35. doi: 10.2967/jnumed.112.109603. Epub 2012 Dec 11.
UNLABELLED
The aim of this study was to assess the clinical value of O-(2-(18)F-fluoroethyl)-l-tyrosine ((18)F-FET) PET in the initial diagnosis of cerebral lesions suggestive of glioma.
METHODS
In a retrospective study, we analyzed the clinical, radiologic, and neuropathologic data of 174 patients (77 women and 97 men; mean age, 45 ± 15 y) who had been referred for neurosurgical assessment of unclear brain lesions and had undergone (18)F-FET PET. Initial histology (n = 168, confirmed after surgery or biopsy) and the clinical course and follow-up MR imaging in 2 patients revealed 66 high-grade gliomas (HGG), 77 low-grade gliomas (LGG), 2 lymphomas, and 25 nonneoplastic lesions (NNL). In a further 4 patients, initial histology was unspecific, but during the course of the disease all patients developed an HGG. The diagnostic value of maximum and mean tumor-to-brain ratios (TBR(max/)TBR(mean)) of (18)F-FET uptake was assessed using receiver-operating-characteristic (ROC) curve analyses to differentiate between neoplastic lesions and NNL, between HGG and LGG, and between high-grade tumor (HGG or lymphoma) and LGG or NNL.
RESULTS
Neoplastic lesions showed significantly higher (18)F-FET uptake than NNL (TBR(max), 3.0 ± 1.3 vs. 1.8 ± 0.5; P < 0.001). ROC analysis yielded an optimal cutoff of 2.5 for TBR(max) to differentiate between neoplastic lesions and NNLs (sensitivity, 57%; specificity, 92%; accuracy, 62%; area under the curve [AUC], 0.76; 95% confidence interval [CI], 0.68-0.84). The positive predictive value (PPV) was 98%, and the negative predictive value (NPV) was 27%. ROC analysis for differentiation between HGG and LGG (TBR(max), 3.6 ± 1.4 vs. 2.4 ± 1.0; P < 0.001) yielded an optimal cutoff of 2.5 for TBR(max) (sensitivity, 80%; specificity, 65%; accuracy, 72%; AUC, 0.77; PPV, 66%; NPV, 79%; 95% CI, 0.68-0.84). Best differentiation between high-grade tumors (HGG or lymphoma) and both NNL and LGG was achieved with a TBR(max) cutoff of 2.5 (sensitivity, 79%; specificity, 72%; accuracy, 75%; AUC, 0.79; PPV, 65%; NPV, 84%; 95% CI, 0.71-0.86). The results for TBR(mean) were similar with a cutoff of 1.9.
CONCLUSION
(18)F-FET uptake ratios provide valuable additional information for the differentiation of cerebral lesions and the grading of gliomas. TBR(max) of (18)F-FET uptake beyond the threshold of 2.5 has a high PPV for detection of a neoplastic lesion and supports the necessity of an invasive procedure, for example, biopsy or surgical resection. Low (18)F-FET uptake (TBR(max) < 2.5) excludes a high-grade tumor with high probability.
目的
本研究旨在评估 O-(2-(18)F-氟乙基)-L-酪氨酸（(18)F-FET）PET 在疑似脑胶质瘤的脑病变初始诊断中的临床价值。
方法
在一项回顾性研究中，我们分析了 174 例（77 名女性和 97 名男性；平均年龄 45 ± 15 岁）因不明原因脑病变而接受神经外科评估并接受(18)F-FET PET 的患者的临床、影像学和神经病理学数据。初始组织学（n=168，经手术或活检证实）和 2 例患者的临床过程和随访磁共振成像显示 66 例高级别胶质瘤（HGG）、77 例低级别胶质瘤（LGG）、2 例淋巴瘤和 25 例非肿瘤性病变（NNL）。在另外 4 例患者中，初始组织学不明确，但在疾病过程中所有患者均发展为 HGG。采用受试者工作特征（ROC）曲线分析评估最大和平均肿瘤与脑比值（TBR(max)/TBR(mean)）摄取的诊断价值，以区分肿瘤性病变和 NNL、HGG 和 LGG、高级别肿瘤（HGG 或淋巴瘤）和 LGG 或 NNL。
结果
肿瘤性病变的(18)F-FET 摄取明显高于 NNL（TBR(max)，3.0 ± 1.3 比 1.8 ± 0.5；P <0.001）。ROC 分析得出 TBR(max)的最佳截断值为 2.5，用于区分肿瘤性病变和 NNL（灵敏度 57%，特异性 92%，准确性 62%，曲线下面积[AUC]0.76；95%置信区间[CI]0.68-0.84）。阳性预测值（PPV）为 98%，阴性预测值（NPV）为 27%。用于区分 HGG 和 LGG（TBR(max)，3.6 ± 1.4 比 2.4 ± 1.0；P <0.001）的 TBR(max)ROC 分析得出 TBR(max)的最佳截断值为 2.5（灵敏度 80%，特异性 65%，准确性 72%，AUC 0.77；PPV 66%，NPV 79%，95%CI 0.68-0.84）。用 TBR(max)截断值 2.5 最佳区分高级别肿瘤（HGG 或淋巴瘤）和 NNL 和 LGG（灵敏度 79%，特异性 72%，准确性 75%，AUC 0.79；PPV 65%，NPV 84%，95%CI 0.71-0.86）。TBR(mean)的结果相似，截断值为 1.9。
结论
(18)F-FET 摄取比值为脑病变的鉴别和胶质瘤的分级提供了有价值的附加信息。(18)F-FET 摄取 TBR(max)超过阈值 2.5 时，对肿瘤性病变的检测具有较高的 PPV，并支持进行有创性操作的必要性，例如活检或手术切除。低摄取（TBR(max) < 2.5）极不可能为高级别肿瘤。
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