摘要
目的:探讨质子磁共振波谱分析(1H-MRS)对颅内肿瘤对脑肿瘤诊断价值,同时利用弥散张量成像(DTI)观察皮质脊髓束的累及情况,评价颅内肿瘤预后中的价值。方法:选取40例颅内肿瘤患者,于手术前进行1H-MRS及DTI,并与术后病理结果进行对照,根据肿瘤内多种代谢产物水平对颅内肿瘤进行分型及胶质瘤恶性程度分级的能力,并行三维白质纤维重建,分析病灶侧白质纤维束的改变情况并观察手术前后肌力恢复情况。结果:星形细胞瘤25例,NAA减少到对侧正常组织的40%～70%,Cr明显下降与正常各半,比较Ⅰ～Ⅱ级与Ⅲ～Ⅳ级星形细胞瘤其肿瘤内代谢化合物NAA/Cr、NAA/Cho和Cho/Cr比值差异有统计学意义(P<0.05);转移瘤5例、脑膜瘤10例有NAA峰但明显低于星形细胞瘤,转移瘤及脑膜瘤NAA/Cho和NAA/Cr比值明显低于星形细胞瘤(P<0.05),转移瘤与脑膜瘤Cr低或缺乏,5例转移瘤都出现Lipid峰,3例出现Lac峰。星形细胞瘤、脑膜瘤、转移瘤Cho峰均显著增高,但脑膜瘤Cho显著升高更明显,其Cho/Cr显著升高。皮质脊髓束表现为无受压中断、受压无中断及中断、破坏,其受累侧肢体肌力术后表现无明显减退、治疗后肌力恢复、治疗后肌力无恢复。结论:颅内肿瘤采用1H-MRS的Cho/Cr、NAA/Cr、Lac/Cr、Lipid/Cr代谢物比值结合常规MRI对颅内肿瘤诊断及对胶质瘤进行无创性分级是可行的,DTI能够较直观地反映肿瘤对皮质脊髓束的影响情况,为判断手术后疗效提供重要预测依据。
Purpose：To evaluate the value of 1H-MRS in diagnosing and diffusion tensor imaging （DTI） technique in demonstrating of corticospinal tract in patients with brain tumors.Methods：Fourty patients with brain tumors underwent 1H-MRS and DTI before the operation. By using functool,N -acetylaspartate / Choline （NAA / Cho） ,NAA / creatine （Cr） and Cho / Cr ratios were calculated and white matter fiber tractography were observed. Results：Significant differences between low-grade （gradeⅠ～Ⅱ） and high-grade （gradeⅢ～Ⅳ） astrocytomas were found in NAA / Cho,NAA/Cr and Cho/ Cr ratios（P0.05）. NAA,NAA /Cho and NAA/Cr in meningioma and metastases were significantly lower （P 0. 05） than that in astrocytomas. Cho /Cr of meningioma was significantly higher than those of other tumors.Five cases of metastases showed Lipid,3 cases exhibited Lac. DTI demonstrated that the influences of corticospinal tract invasion by brain tumor could be divided into three types：compressed,compressed but not disrupted and disrupted.The myodnamia showed normal,recover to nomal or no recovering. Conclusion：1H-MRS may improve the accuracy of grade diagnosis of brain tumors. Evaluatingthe relationship between brain tumor and corticospinal tracts by DTI is helpful to design surgical approach,determine espectable scope and guide the specific procedure.
出处
《中国医学计算机成像杂志》
CSCD
北大核心
2010年第2期101-106,共6页
Chinese Computed Medical Imaging
基金
江苏省卫生厅重大科研课题(H200818)~~
