Can proton MR spectroscopic and perfusion imaging differentiate between neoplastic and nonneoplastic brain lesions in adults?
Can proton MR spectroscopic and perfusion imaging differentiate between neoplastic and nonneoplastic brain lesions in adults?
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DOI：
10.3174/ajnr.a0810
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发表时间：
2008-02-01
影响因子：
3.5
通讯作者：
Horska, A.
中科院分区：
文献类型：
--
作者：
Hourani, R.;Brant, L. J.;Horska, A.
背景和目的：脑病变的无创性诊断对于正确选择治疗方法非常重要。我们的目的是调查是否1）质子磁共振波谱成像MR灌注成像可提高脑内病变的分类。材料和方法：我们回顾性检查了69例未经治疗的成人原发性脑病变（脑肿瘤，n = 36;良性病变，n = 10;中风，n = 4;脱髓鞘，n = 10;和病理检查未证实的稳定病变，n = 9）。活检或治疗前在1.5T下进行MR成像和1H-MRSI。N-乙酰天冬氨酸（NAA），肌酸（Cr）和胆碱（Cho）在病变的浓度表示为代谢物的比例，并归一化到对侧半球。在一组患者（n = 32）中进行动态磁敏感对比增强灌注MR成像;评价相对脑血容量（rCBV）。判别函数分析被用来确定变量，可以预测纳入肿瘤或非肿瘤病变组。采用受试者工作特征（ROC）分析方法比较H-1-MRSI与MR灌注成像的判别能力。结果：判别函数分析对原始分组病例的正确分类率为84.2%（P
BACKGROUND AND PURPOSE: Noninvasive diagnosis of brain lesions is important for the correct choice of treatment. Our aims were to investigate whether 1) proton MR spectroscopic imaging (H-1-MRSI) can aid in differentiating between tumors and nonneoplastic brain lesions, and 2) perfusion MR imaging can improve the classification.MATERIALS AND METHODS: We retrospectively examined 69 adults with untreated primary brain lesions (brain tumors, n = 36; benign lesions, n = 10; stroke, n = 4; demyelination, n = 10; and stable lesions not confirmed on pathologic examination, n = 9). MR imaging and 1H-MRSI were performed at 1.5T before biopsy or treatment. Concentrations of N-acetylaspartate (NAA), creatine (Cr), and choline (Cho) in the lesion were expressed as metabolite ratios and were normalized to the contralateral hemisphere. Dynamic susceptibility contrast-enhanced perfusion MR imaging was performed in a subset of patients (n = 32); relative cerebral blood volume (rCBV) was evaluated. Discriminant function analysis was used to identify variables that can predict inclusion in the neoplastic or nonneoplastic lesion groups. Receiver operator characteristic (ROC) analysis was used to compare the discriminatory capability of H-1-MRSI and perfusion MR imaging.RESULTS: The discriminant function analysis correctly classified 84.2% of original grouped cases (P