doi:10.16150/j.1671-2870.2016.05.020

[1] Woodhams R, Matsunaga K, Iwabuchi K, et al.Diffusion-weighted imaging of malignant breast tumors: the usefulness of apparent diffusion coefficient(ADC) value and ADC map for the detection of malignant breast tumors and evaluation of cancer extension[J]. J Comput Assist Tomogr,2005,29(5):644-649.
[2] Bammer R.Basic principles of diffusion-weighted ima-ging[J]. Eur J Radiol,2003,45(3):169-184.
[3] 张静, 安宁豫, 程流泉, 等. 1.5TMR乳腺扩散加权成像b值的优化[J]. 中华放射学杂志,2011,45(10):937-941.
[4] Pereira FP, Martins G, Figueiredo E, et al.Assessment of breast lesions with diffusion-weighted MRI: comparing the use of different b values[J]. Am J Roentgenol,2009, 193(4):1030-1035.
[5] Dorrius MD, Dijkstra H, Oudkerk M, et al.Effect of b value and pre-admission of contrast on diagnostic accuracy of 1.5-T breast DWI: a systematic review and meta-analysis[J]. Eur Radiol,2014,24(11):2835-2847.
[6] Chen X, Li WL, Zhang YL, et al.Meta-analysis of quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesions[J]. BMC Cancer,2010,10:693.
[7] 刘敏, 刘万花, 王瑞, 等. 3.0T MR扩散加权成像不同b值条件下乳腺病灶信噪比及信号强度比的变化[J]. 中华放射学杂志,2014,48(3):189-192.
[8] Park MJ, Cha ES, Kang BJ, et al.The role of diffusion-weighted imaging and the apparent diffusion coefficient (ADC) values for breast tumors[J]. Korean J Radiol,2007, 8(5):390-396.
[9] Cipolla V, Santucci D, Guerrieri D, et al.Correlation between 3T apparent diffusion coefficient values and gra-ding of invasive breast carcinoma[J]. Eur J Radiol,2014, 83(12):2144-2150.
[10] 邓丹琼, 涂蓉, 尤小光. 磁共振扩散加权成像ADC值与乳腺癌病理组织分级的相关性研究[J]. 临床放射学杂志,2013,32(10):1428-1431.
[11] Park 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]. J Magn Reson Imaging,2015,41(1):175-182.
[12] Jeh SK, Kim SH, Kim HS, et al.Correlation of the apparent diffusion coefficient value and dynamic magnetic resonance imaging findings with prognostic factors in invasive ductal carcinoma[J]. J Magn Reson Imaging,2011, 33(1):102-109.
[13] Wu LM, Hu JN, Gu HY, et al.Can diffusion-weighted MR imaging and contrast-enhanced MR imaging precisely evaluate and predict pathological response to neoadjuvant chemotherapy in patients with breast cancer?[J]. Breast Cancer Res Treat,2012,135(1):17-28.
[14] Chen JH, Su MY.Clinical application of magnetic resonance imaging in management of breast cancer patients receiving neoadjuvant chemotherapy[J]. Biomed Res Int,2013,2013:348167.
[15] Park SH, Moon WK, Cho N, et al.Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer[J]. Radiology,2010,257(1):56-63.
[16] Prevos R, Smidt ML, Tjan-Heijnen VC, et al.Pre-treatment differences and early response monitoring of neoadjuvant chemotherapy in breast cancer patients using magnetic resonance imaging: a systematic review[J]. Eur Radiol,2012,22(12):2607-2616.
[17] 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.
[18] Ichikawa S, Motosugi U, Ichikawa T, et al.Intravoxel incoherent motion imaging of focal hepatic lesions[J]. J Magn Reson Imaging,2013,37(6):1371-1376.
[19] Liu C, Wang K, Chan Q, et al. Intravoxel incoherent motion MR imaging for breast lesions: comparison and correlation with pharmacokinetic evaluation from dyna-mic contrast-enhanced MR imaging[J/OL]. Eur Radiol,2016-02-10[2016-07-14].https://www.ncbi.nlm.nih.gov/pubmed/26863896.
[20] 王庆军, 李小娟, 张静, 等. 磁共振体素内不相干运动对于肿块样乳腺良恶性病变的诊断价值[J]. 中华临床医师杂志,2014, 8(19):3238-3443.
[21] 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.
[22] Cho GY, Moy L, Kim SG, et al.Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors[J]. Eur Radiol,2016,26(8):2547-2558.
[23] Kim Y, Ko K, Kim D, et al.Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer: association with histopathological features and subtypes[J]. Br J Radiol,2016,89(1063):20160140.
[24] 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 (Baltimore),2016,95(4):e2420.
[25] Jensen JH, Helpern JA, Ramani A, et al.Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging[J]. Magn Reson Med,2005,53(6):1432-1440.
[26] Nogueira L, Brandão S, Matos E, et al Application of the diffusion kurtosis model for the study of breast lesions[J]. Eur Radiol,2014,24(6):1197-1203.
[27] Wu D, Li G, Zhang J, et al.Characterization of breast tumors using diffusion kurtosis imaging (DKI)[J]. PLoS One,2014,9(11):e113240.
[28] Sun K, Chen X, Chai W, et al.Breast Cancer: Diffusion Kurtosis MR Imaging-Diagnostic Accuracy and Correlation with Clinical-Pathologic Factors[J]. Radiology,2015, 277(1):46-55.
[29] Chen Y, Ren W, Zheng D, et al.Diffusion kurtosis ima-ging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients[J]. J Magn Reson Imaging,2015,42(5):1354-1361.
[30] Bogner W, Pinker-Domenig K, Bickel H, et al.Readout-segmented echo-planar imaging improves the diagnostic performance of diffusion-weighted MR breast examinations at 3.0 T[J]. Radiology,2012,263(1):64-76.

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