中图分类号:
 
R737.9
R445.2 
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参考文献
[1]Forouzanfar MH, Foreman KJ, Delossantos AM, et al. Breast and cervical cancer in 187 countries between 1980 and 2010: a systematic analysis[J]. Lancet, 2011, 378(9801): 1461-1484.
[2]Hylton NM, Blume JD, Bernreuter WK, et al. Locally advanced breast cancer: MR imaging for prediction of response to neoadjuvant chemotherapy-results from ACRIN 6657/I-SPY TRIAL[J]. Radiology, 2012, 263(3): 663-672.
[3]Heldahl MG, Bathen TF, Rydland J, et al. Prognostic value of pretreatment dynamic contrast-enhanced MR imaging in breast cancer patients receiving neoadjuvant chemotherapy: overall survival predicted from combined time course and volume analysis[J]. Acta Radiologica, 2010, 51(6): 604-612.
[4]Fangberget A, Nilsen LB, Hole KH, et al. Neoadjuvant chemotherapy in breast cancer-response evaluation and prediction of response to treatment using dynamic contrast-enhanced and diffusion-weighted MR imaging[J]. Eur Radiol, 2011, 21(6): 1188-1199.
[5]Sharma U, Danishad KKA, Seenu V, et al. Longitudinal study of the assessment by MRI and diffusion-weighted imaging of tumor response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy[J]. NMR Biomed, 2009, 22(1): 104-113.
[6]Iwasa H, Kubota K, Hamada N, et al. Early prediction of response to neoadjuvant chemotherapy in patients with breast cancer using diffusion-weighted imaging and gray-scale ultrasonography[J]. Oncol Rep, 2014, 31(4): 1555-1560.
[7]顾雅佳,冯晓源,邱龙华,等. DWI对局部进展期乳腺癌新辅助化疗疗效评价的初步研究[J]. 放射学实践, 2008,22(12):1249-1255.
[8]Bufi E, Belli P, Costantini M, et al. Role of the apparent diffusion coefficient in the prediction of response to neoadjuvant chemotherapy in patients with locally advanced breast cancer[J]. Clin Breast Cancer, 2015, 15(5): 370-380.
[9]尹波,刘莉,邹丽萍,等. 乳腺癌新辅助化疗前后动态增强MRI半定量[J]. 中国医学计算机成像杂志,2011,17(3):226-229.
[10]石桥,王霄英,郭丽,等. MRI动态增强流出参数半定量分析对局部进展期乳腺癌新辅助化疗疗效评估的价值[J]. 中华放射学杂志,2013,47(8):699-703.
[11]Drisis S, Metens T, Ignatiadis M, et al. Quantitative DCE-MRI for prediction of pathological complete response following neoadjuvant treatment for locally advanced breast cancer: the impact of breast cancer subtypes on the diagnostic accuracy[J]. Eur Radiol, 2016, 26(5): 1474-1484.
[12]Le Bihan D, Breton E, Lallemand D, et al. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging[J]. Radiology, 1988, 168(2): 497-505.
[13]Bokacheva L, Kaplan JB, Giri DD, et al. Intravoxel incoherent motion diffusion-weighted MRI at 3.0 T differentiates malignant breast lesions from benign lesions and breast parenchyma[J]. J Mag Reson Imaging, 2014, 40(4): 813-823.
[14]Yoon JH, Lee JM, Yu MH, et al. Evaluation of hepatic focal lesions using diffusion-weighted MR imaging: Comparison of apparent diffusion coefficient and intravoxel incoherent motion-derived parameters[J]. J Mag Reson Imaging, 2014, 39(2): 276-285.
[15]Liu C, Liang C, Liu Z, et al. Intravoxel incoherent motion(IVIM) in evaluation of breast lesions: comparison with conventional DWI[J]. Eur J Radiol, 2013, 82(12): e782-e789.
[16]Lewin M, Fartoux L, Vignaud A, et al. The diffusion-weighted imaging perfusion fraction f is a potential marker of sorafenib treatment in advanced hepatocellular carcinoma: a pilot study[J]. Eur Radiol, 2011, 21(2): 281-290.
[17]Wang YC, Hu DY, Hu XM, et al. Assessing the Early Response of Advanced Cervical Cancer to Neoadjuvant Chemotherapy Using Intravoxel Incoherent Motion Diffusion-weighted Magnetic Resonance Imaging: A Pilot Study[J]. Chin Med J(Engl), 2016, 129(6): 665.
[18]Xiao Y, Pan J, Chen Y, et al. Intravoxel incoherent motion-magnetic resonance imaging as an early predictor of treatment response to neoadjuvant chemotherapy in locoregionally advanced nasopharyngeal carcinoma[J]. Medicine, 2015, 94(24): e973.
[19]Che S, Zhao X, Ou Y, et al. Role of the Intravoxel Incoherent Motion Diffusion Weighted Imaging in the Pre-treatment Prediction and Early Response Monitoring to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer[J]. Medicine, 2016, 95(4): e2420.
[20]汪晓红,李瑞敏,彭卫军. 磁共振功能成像在乳腺癌新辅助化疗早期疗效评价中的应用[J]. 磁共振成像,2011,2(3):172-176.
[21]Meisamy S, Bolan PJ, Baker EH, et al. Neoadjuvant chemotherapy of locally advanced breast cancer: predicting response with in vivo 1H MR spectroscopy-a pilot study at 4 T[J]. Radiology, 2004, 233(2): 424-431.
[22]Danishad KKA, Sharma U, Sah RG, et al. Assessment of therapeutic response of locally advanced breast cancer(LABC) patients undergoing neoadjuvant chemotherapy(NACT) monitored using sequential magnetic resonance spectroscopic imaging(MRSI)[J]. NMR Biomed, 2010, 23(3): 233-241.
[23]谢瑜,李卓琳,李鹍,等. 三维1H-MRS联合DWI评估乳腺癌新辅助化疗疗效的研究[J]. 实用放射学杂志,2015,31(10):1608-1612.
[24]Shin HJ, Baek HM, Ahn JH, et al. Prediction of pathologic response to neoadjuvant chemotherapy in patients with breast cancer using diffusion-weighted imaging and MRS[J]. NMR Biomed, 2012, 25(12): 1349-1359.
[25]Pickles MD, Gibbs P, Lowry M, et al. Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer[J]. Mag Res Imaging, 2006, 24(7): 843-847.
[26]Iacconi C, Giannelli M, Marini C, et al. The role of mean diffusivity(MD) as a predictive index of the response to chemotherapy in locally advanced breast cancer: a preliminary study[J]. Eur Radiol, 2010, 20(2): 303-308.
[27]Lobbes MB, Prevos R, Smidt M, et al. The role of magnetic resonance imaging in assessing residual disease and pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy: a systematic review[J]. Insights Imaging, 2013, 4(2): 163-175.