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最小相对表观弥散系数值在低级别胶质瘤与反应性胶质增生鉴别诊断中的价值 被引量：3

Differentiation of Low-grade Glioma and Reactive Gliosis:Diagnostic Value of Minimum Relative Apparent Diffusion Coefficient
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摘要 目的:探讨低级别胶质瘤与反应性胶质增生中最小相对表观弥散系数值(rADCmin)的鉴别诊断价值。方法:病理证实的低级别胶质瘤(WHOⅡ级)58例与反应性胶质增生11例纳入研究,所有患者术前进行常规MRI和弥散加权成像(DWI),测量病变的rADCmin值并比较其在两种病理状态中的差异,计算用rADCmin诊断低级别胶质瘤的临界值、敏感性和特异性。结果:低级别胶质瘤的平均rADCmin(1.465±0.357)大于反应性胶质增生的1.062±0.120(P<0.05),ROC曲线分析显示当rADCmin=1.193时,敏感性为82.8%,特异性为100%。结论:rADCmin在低级别胶质瘤与反应性胶质增生的鉴别诊断中能够提供诊断价值。 Purpose： To evaluate the diagnostic value of minimum relative apparent diffusion coefficient （rADCmin） for the differentiation of lowgrade glioma and reactive gliosis. Methods：Fiftyeight cases of low - grade glioma and 11 cases of reactive gliosis were enrolled in this study. All patients had preoperatively undergone conventional MRI and diffusion weighed imaging （DWI）. The rADCmin values were measured and were evaluated regarding statistical differences between low - grade glioma and reactive gliosis. A receiver operating characteristic （ROC） analysis was used to determine the cutoff value for diagnosing low - grade glioma. Results： The mean rADCmin value of low - grade glioma （ 1,465 ＋ 0,357） was significantly higher than that of reactive gliosis（1. 062± 0. 120） （P 〈 0.05） . According to the ROC analysis, the cutoff value of 1. 193 for the rADCmin value generated the best combination of sensitivity （82.8 % ） and specificity （100 % ）. Conclusion： The rADCmin can provide valuable diagnostic information for the differentiation of low - grade glioma and reactive gliosis.
作者 胡步宏 贾中正 耿道颖
机构地区 复旦大学附属华山医院放射科
出处 《中国医学计算机成像杂志》 CSCD 北大核心 2011年第3期203-206,共4页 Chinese Computed Medical Imaging
关键词 表观弥散系数 弥散加权成像 胶质瘤 反应性胶质增生 Apparent diffusion coefficient Diffusion weighted imaging Glioma Reactive gliosis
分类号 R445.2 [医药卫生—影像医学与核医学]
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  • 1Nucifora PG, Verma R, Lee SK, et al. Diffusion-tensor MR imaging and tractography: exploring brain microstructure and connectivity. Radiology,2007,245 : 367 -384.
  • 2Mascalchi--M, Filippi M,Floris R, et al. Diffusion-weighted MR of the brain: methodology and clinical application. Radiol Med, 2005,109 : 155-197.
  • 3Hamon M, Coskun O, Courtheoux P,et al. Diffusion MR imaging of the central nervous system: clinical applications. J Radial, 2005,86:369-385.
  • 4Yamasaki F, Kurisu K, Satoh K, et al. Apparent diffusion coefficient of human brain tumors at MR imaging. Radiology, 2005,235:985-991.
  • 5Beppu T, Inoue T, Shibata Y, et al. Measurement of fractional anisotropy using diffusion tensor MRI in supratentorial astrocytic tumors. J Neurooncol,2003 ,63 :109-116,
  • 6Lu S, Ahn D, Johnson G, et al. Peritumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors. AJNR Am J Neuroradiol,2003 ,24 :937-941.
  • 7Price SJ, Burnet NG, Donovan T, et al. Diffusion tensor imaging of brain tumours at 3T: a potential tool for assessing white matter tract invasion? Clin Radiol,2003 ,58 :455-462.
  • 8Stadlbauer A, Ganslandt O, Buslei R, et al. Gliomas: histopathologic evaluation of changes in directionality and magnitude of water diffusion at diffusion-tensor MR imaging . Radiology , 2006,240:803-810.
  • 9Brat DJ, Castellano-Sanchez A, Kanr B, et al. Genetic and biologic progression in astrocytomas and their relation to angiogenic dysregulation. Adv Anat Pathol,2002 ,9 :24-36.
  • 10Smits M, Vernooij MW, Wielopolski PA, et al. Incorporating functional MR imaging into diffusion tensor tractography in the preoperative assessment of the corticospinal tract in patients with brain tumors. AJNR Am J Neuroradiol,2007 ,28 :1354-1361.

共引文献36

同被引文献21

  • 1Chawla S, Kim S, Loevner LA, et al. Prediction of disease-freesurvival in patients with squamous cell carcinomas of the head andneck using dynamic contrast-enhanced MR imaging. AJNR Am JNeuroradiol, 2011, 32(4) : 778-784.
  • 2Klerkx WM, Bax L, Veldhuis WB, et al. Detection of lymphnode metastases by gadolinium-enhanced magnetic resonance ima-ging .. Systematic review and meta-analysis. J Natl Cancer Inst,2010,102(4):244-253.
  • 3Herneth AM, Mayerhoefer M, Schernthaner R, et al. Diffusionweighted imaging : Lymph nodes. Eur J Radiol, 2010, 76(3) : 398-406.
  • 4Maeda M, Kato H, Sakuma H, et al. Usefulness of the apparentdiffusion coefficient in line scan diffusion-weighted imaging fordistinguishing between squamous cell carcinomas and malignantlymphomas of the head and neck. AJNR Am J Neuroradiol,2005,26(5):1186-1192.
  • 5Perrone A, Guerrisi P, Izzo L, et al. Diffusion-weighted MRI incervical lymph nodes : Differentiation between benign and malig-nant lesions. Eur J Radiol, 2011,77(2) :281-286.
  • 6Vandecaveye V, De Keyzer F, Dirix P, et al. Applications of dif-fusion-weighted magnetic resonance imaging in head and necksquamous cell carcinoma. Neuroradiology, 2010,52(9) :773-784.
  • 7Zhang F,Zhu L, Huang X,et al. Differentiation of reactive andtumor metastatic lymph nodes with diffusion-weighted and SPIO-enhanced MRI. Mol Imaging Biol, 2013,15(1) :40-47.
  • 8Kwee TC, Takahara T, Luijten PR, et al. ADC measurementsof lymph nodes : Inter- and intra-observer reproducibility studyand an overview of the literature. Eur J Radiol, 2010, 75(2):215-220.
  • 9Park SO, Kim JK, Kim KA, et al. Relative apparent diffusioncoefficient : Determination of reference site and validation of ben-efit for detecting metastatic lymph nodes in uterine cervical canc-er. J Magn Reson Imaging, 2009, 29(2) : 383-390.
  • 10Wilm BJ, Svensson J, Henning A, et ai. Reduced field-of-viewMRI using outer volume suppression for spinal cord diffusion im-aging. Magn Reson Med, 2007 , 57(3) : 625-630.

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中国医学计算机成像杂志
2011年 第3期

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