期刊文献+

乳腺癌MRI非形态学特征与C-erbB-2表达的相关性研究 被引量:10

Correlation on MRI non-morphological features and C-erbB-2 expression of breast cancer
下载PDF
导出
摘要 目的探讨乳腺癌MRI非形态学特征(血流动力学、功能学)与C-erbB-2表达的相关性。材料与方法对77例手术证实的乳腺癌患者的MRI非形态学特征与C-erbB-2表达情况进行分析,统计病变时间-信号强度曲线、早期强化率及ADC值,应用t检验、χ2检验及Spearman秩相关分析其与C-erbB-2表达的相关性。结果乳腺癌时间-信号强度曲线、早期强化率与C-erbB-2表达无相关,ADC值与C-erbB-2表达呈负相关,C-erbB-2表达组间ADC值差异有统计学意义,应用ROC曲线分析,得到判断C-erbB-2表达的最佳ADC值诊断界值为0.988×10-3mm2/s。结论乳腺癌C-erbB-2表达与MRI血流动力学指标无相关性,与ADC值呈负相关。 Objective:To explore the correlations of MRI non-morphological features (hemodynamic performance and function characteristics) and C-erbB-2 of breast cancer. Materials and Methods:Seventy-seven patients diagnosed as breast cancers by pathologic examination were reviewed, analysis the MRI non- morphological features and the C-erbB-2 expression, to explore pathological changes of time-signal intensity curve, early intensive rate and ADC values, using t-test and chi-square test and Spearman rank correlation analysis with the correlation of C-erbB-2 expression. Results: The time-signal intensity curve of breast cancer, early intensive rate had no correlation with C-erbB-2 expression, ADC values had negative correlation with C-erbB-2 expression, ADC values differences between the groups of C-erbB-2 expression was statistically signiifcant, the best threshold of ADC value to judgment C-erbB-2 expression was 0.988×10-3mm2/s by ROC curve. Conclusions: C-erbB-2 expression had no correlation with MRI hemodynamic performance indicators, had negative correlation with ADC values.
出处 《磁共振成像》 CAS CSCD 2014年第4期269-273,共5页 Chinese Journal of Magnetic Resonance Imaging
关键词 乳腺肿瘤 磁共振成像 Breast neoplasms Magnetic resonance imaging
  • 相关文献

参考文献12

二级参考文献94

共引文献406

同被引文献73

  • 1陈蓉,龚水根,张伟国,陈金华,何双梧,刘宝华,李增鹏.乳腺癌MRI形态学表现与病理、分子生物学相关性研究[J].中华放射学杂志,2004,38(6):620-625. 被引量:55
  • 2刘书政,黄韬.磁共振成像动态增强对乳腺癌血管生成的研究[J].中国肿瘤临床,2005,32(9):516-519. 被引量:34
  • 3Caivano R, Villonio A, D' Antuono F, et al. Diffusion weighted imaging and apparent diffusion coefficient in 3 tesla magnetic resonance imaging of breast lesions. Cancer Invest, 2015, 33 (5): 159-64.
  • 4Choi SY, Chang YW, Park HJ, et al. Correlation of the apparent diffusion coefficiency values on diffusion-weighted imaging with prognostic factors for breast cancer. Br J Radiol, 2012, 85 (1016): e474-479.
  • 5Belli P, Costantini M, Buff E, et al. Diffusion magnetic resonance imaging in breast cancer characterisation: correlations between the apparent diffusion coefficient and major prognostic factors. Radiol Med, 2015, 120 (3): 268-76.
  • 6Tsushima Y, Takahashi-Taketomi A, Endo K. Magnetic resonance (MR) differential diagnosis of breast tumors using apparent diffusion coefficient (ADC) on 1.5-T. J Magn Reson Imaging, 2009, 30(2): 249-255.
  • 7Kuroki-Stmuki S, Kuroki Y, Nasu K, et al. Detecting breast cancer with non-contrast MR imaging: combining diffusion-weighted and STIR imaging. Magn Reson Med Sci, 2007, 6(l): 21-27.
  • 8Park SH, Choi HY, Hahn SY. Correlations between apparent diffusion coefficient values of invasive ductal carcinoma and pathologic factors on diffusion-weighted MRI at 3.0 Tesla. J Magn Reson Imaging, 2015, 41 (1): 175-82.
  • 9Razek AA, Gaballa G, Denewer A, et al. Invasive ductal carcinoma: correlation of apparent diffusion coefficient value with pathological prognostic factors. NMR Biomed, 2010, 23(6): 619-23.
  • 10Kamitani T, Matsuo Y, Yabuuchi H, et al. Correlations between apparent diffusion coefficient values and prognostic factors of breast cancer. Magn Reson Med Sci, 2013, 12 (3): 193-199.

引证文献10

二级引证文献89

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部