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目的探讨基于组织相似度图谱(TSM)MR灌注成像(PWI)评价脑胶质瘤血流灌注情况的可行性及在胶质瘤分级中的价值。方法搜集经手术病理证实的24例脑肿瘤(Ⅱ级9例,Ⅲ级8例,Ⅳ级7例)患者的MR常规及灌注成像资料。经TSM算法软件和MRI工作站PWI后处理软件将扫描数据进行处理,得到TSM图和脑血容量(CBV)图。分别测算肿瘤实质区和正常脑白质区(WM)的CBV_(PWI)值或CBV_(TSM)值,然后计算出脑胶质瘤的r CBV_(PWI)值、r CBV_(TSM)值,并分别对Ⅱ级、Ⅲ级、Ⅳ级胶质瘤r CBV_(PWI)值和r CBV_(TSM)值进行统计学分析。结果 (1)Ⅱ级、Ⅲ级和Ⅳ级胶质瘤的r CBV_(PWI)值和r CBV_(TSM)值之间差异均无统计学意义。(2)Ⅱ级胶质瘤的r CBV_(PWI)值(1.83±0.48)显著低于Ⅲ级(5.95±2.52)(P=0.002)和Ⅳ级(6.47±2.30)(P=0.001)。Ⅲ级和Ⅳ级之间差异无统计学意义(P=0.631)。同样,Ⅱ级胶质瘤的CBV_(TSM)值(2.18±0.38)显著低于Ⅲ级(6.06±2.81)(P=0.007)和Ⅳ级(6.27±2.76)(P=0.006)。Ⅲ级和Ⅳ级之间差异无统计学意义(P=0.87)。结论基于TSM的MR灌注成像可用于评价脑胶质瘤的血流动力学变化,并能于术前对胶质瘤进行分级诊断。
Objective To investigate the feasibility of assessing glioma perfusion based on tissue similarity map (TSM) MR perfusion imaging (PWI) and its value in glioma grading. Methods The routine MR imaging and perfusion imaging of 24 patients with brain tumor (9 in grade Ⅱ, 8 in grade Ⅲ and 7 in grade Ⅳ) were collected from 24 patients with brain tumor confirmed by surgery and pathology. TSM algorithm software and MRI workstation PWI post-processing software will be scanned data processing, TSM map and cerebral blood volume (CBV) map. CBV PWI value or CBV TSM value of tumor mass area and normal white matter area (WM) were calculated respectively, and r CBV PWI value and r CBV TSM value of glioma were calculated respectively The CBV PWI value and r CBV TSM value of Grade II, III and IV gliomas were statistically analyzed. Results (1) There was no significant difference in r CBV PWI value and r CBV TSM value between grade Ⅱ, grade Ⅲ and grade Ⅳ gliomas. (2) The level of r CBV PWI in group Ⅱ glioma was significantly lower than that in stage Ⅲ (5.95 ± 2.52) (P = 0.002) and stage Ⅳ (6.47 ± 2.30) (P = 0.001). There was no significant difference between grade Ⅲ and grade Ⅳ (P = 0.631). Similarly, the value of CBV TSM for grade II glioma was significantly lower than that of grade III 6.06 2.81 (P = 0.007) and grade IV (6.27 2.76) (P 0.006). There was no significant difference between grade Ⅲ and grade Ⅳ (P = 0.87). Conclusion MR perfusion imaging based on TSM can be used to evaluate the hemodynamic changes of gliomas and to classify gliomas preoperatively.