Perfusion imaging of brain tumors using arterial spin-labeling: Correlation with histopathologic vascular density
Perfusion imaging of brain tumors using arterial spin-labeling: Correlation with histopathologic vascular density
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DOI：
10.3174/ajnr.a0903
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发表时间：
2008-04-01
影响因子：
3.5
通讯作者：
Honda, H.
中科院分区：
文献类型：
--
作者：
Noguchi, T.;Yoshiura, T.;Honda, H.
背景和目的：我们探讨了肿瘤血流测量的基础上灌注成像动脉自旋标记（ASL-PI）和脑tumors.MATERIALS和方法的病理结果之间的关系：我们使用ASL-PI检查35例脑肿瘤，包括11例胶质瘤，9例脑膜瘤，9例神经鞘瘤，1例弥漫性大B细胞淋巴瘤，4例血管母细胞瘤，1例脑转移瘤。作为肿瘤灌注的指标，每个肿瘤的相对信号强度（SI）（%信号强度）被确定为肿瘤内的最大SI/ASL-PI上正常脑灰质内的平均SI的百分比。相对血管衰减（%血管）确定为CD-34免疫染色组织病理学标本上每整个组织面积的总微血管面积。计算胶质瘤的MIB 1指数。比较不同病理类型及高、低级别胶质瘤的%信号强度差异。此外，%信号强度和%血管或MIB 1指数之间的相关性进行了评估在glioma.Results：%信号强度之间的统计学显着差异，观察血管母细胞瘤与胶质瘤（P < .005），脑膜瘤（P < .05），和神经鞘瘤（P < .005）。在胶质瘤中，高级别肿瘤的%信号强度显著高于低级别肿瘤（P <0.05）。相关性分析显示，35例患者的%信号强度与%血管之间存在显著正相关，包括所有6种组织病理学类型（rs = 0.782，P <0.00005）和胶质瘤（rs = 0.773，P <0.05）。此外，胶质瘤中%信号强度与MIB 1指数呈显著正相关（rs = 0.700，P <0.05）。结论：ASL-PI可预测脑肿瘤的组织病理学血管密度，并可用于区分高、低级别胶质瘤及血管母细胞瘤与其他脑肿瘤。
BACKGROUND AND PURPOSE: We investigated the relationship between tumor blood-flow measurement based on perfusion imaging by arterial spin-labeling (ASL-PI) and histopathologic findings in brain tumors.MATERIALS AND METHODS: We used ASL-PI to examine 35 patients with brain tumors, including 11 gliomas, 9 meningiomas, 9 schwannomas, 1 diffuse large B-cell lymphoma, 4 hemangioblastomas, and 1 metastatic brain tumor. As an index of tumor perfusion, the relative signal intensity (SI) of each tumor (%Signal intensity) was determined as a percentage of the maximal SI within the tumor per averaged SI within normal cerebral gray matter on ASL-PI. Relative vascular attenuation (%Vessel) was determined as the total microvessel area per the entire tissue area on CD-34-immunostained histopathologic specimens. MIB1 indices of gliomas were also calculated. The differences in %Signal intensity among different histopathologic types and between high- and low-grade gliomas were compared. In addition, the correlations between %Signal intensity and %Vessel or MIB1 index were evaluated in gliomas.RESULTS: Statistically significant differences in %Signal intensity were observed between hemangioblastomas versus gliomas (P < .005), meningionnas (P < .05), and schwannomas (P < .005). Among gliomas, %Signal intensity was significantly higher for high-grade than for low-grade tumors (P < .05). Correlation analyses revealed significant positive correlations between %Signal intensity and %Vessel in 35 patients, including all 6 histopathologic types (rs = 0.782, P < .00005) and in gliomas (rs = 0.773, P < .05). In addition, in gliomas, %Signal intensity and MIB1 index were significantly positively correlated (rs = 0.700, P < .05).CONCLUSION: ASL-PI may predict histopathologic vascular densities of brain tumors and may be useful in distinguishing between high- and low-grade gliomas and in differentiating hemangioblastomas from other brain tumors.