Share：
Share this content in WeChat
X
[Chinese][PDF]88787
• Review •
Research progress of functional magnetic resonance imaging techniques for evaluating the response to neoadjuvant chemotherapy in breast cancer
ZHANG Rong  LIU Yulin  LIU Daihong  LU Dongmei  YANG Xiaoping 

Cite this article as: Zhang R, Liu YL, Liu DH, et al. Research progress of functional magnetic resonance imaging techniques for evaluating the response to neoadjuvant chemotherapy in breast cancer. Chin J Magn Reson Imaging, 2019, 10(8): 620-624. DOI:10.12015/issn.1674-8034.2019.08.013.


[Abstract] Neoadjuvant chemotherapy (NAC) has been widely used as a standard preoperative treatment for locally advanced breast cancer, which can significantly reduce clinical staging and improve tumor prognosis. Functional magnetic resonance imaging (fMRI) can detect functional and metabolic changes of breast cancer before morphological changes after neoadjuvant chemotherapy, accurately predict pathological response, and help clinical effectively formulate and adjust further treatment programs. Techniques of functional MRI used commonly in clinic includ dynamic contrast enhanced MRI (DCE-MRI), diffusion weighted imaging (DWI), intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), etc. In this review, these common techniques used to evaluate the effect of neoadjuvant chemotherapy on breast cancer are summarized in terms of application and research progress.
[Keywords] functional magnetic resonance imaging；breast neoplasms；neoadjuvant chemotherapy；response evaluation

ZHANG Rong The Second Clinical Hospital of Lanzhou University, Lanzhou 730030, China

LIU Yulin The Second Clinical Hospital of Lanzhou University, Lanzhou 730030, China

LIU Daihong Department of Imaging Diagnostic Center, The 940th Hospital of Joint Logistics Support force of Chinese People’s Liberation Army, Lanzhou 730050, China

LU Dongmei The Second Clinical Hospital of Lanzhou University, Lanzhou 730030, China

YANG Xiaoping* Department of Imaging Diagnostic Center, The 940th Hospital of Joint Logistics Support force of Chinese People’s Liberation Army, Lanzhou 730050, China

*Corresponding to: Yang XP, E-mail: lwyxp_zxl@sohu.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part of Gansu Province Natural Sciences Foundation No.1606RJZA160
Received  2019-04-05
Accepted  2019-05-28
DOI: 10.12015/issn.1674-8034.2019.08.013
Cite this article as: Zhang R, Liu YL, Liu DH, et al. Research progress of functional magnetic resonance imaging techniques for evaluating the response to neoadjuvant chemotherapy in breast cancer. Chin J Magn Reson Imaging, 2019, 10(8): 620-624. DOI:10.12015/issn.1674-8034.2019.08.013.

[1]
Lee SC, Grant E, Sheth P, et al. Accuracy of contrast-enhanced ultrasound compared With magnetic resonance imaging in assessing the tumor response after neoadjuvant chemotherapy for breast cancer. J Ultrasound Med, 2017, 36(5): 901-911.
[2]
Man VC, Cheung PS. Neoadjuvant chemotherapy increases rates of breast-conserving surgery in early operable breast cancer. Hong Kong Med J, 2017, 23(3): 251-257.
[3]
Croshaw R, Shapiro-Wright H, Svensson E, et al. Accuracy of clinical examination, digital mammogram, ultrasound, and MRI in determining postneoadjuvant pathologic tumor response in operable breast cancer patients. Ann Surg Oncol, 2011, 18(11): 3160-3163.
[4]
Kim TH, Yoon J, Kang DK, et al. Value of volume-based metabolic parameters for predicting survival in breast cancer patients treated with neoadjuvant chemotherapy. Medicine, 2016, 95(41): e4605.
[5]
Kuhl CK, Mielcareck P, Klaschik S, et al. Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions?. Radiology, 1999, 211(1): 101-110.
[6]
Li H, Yao L, Jin P, et al. MRI and PET/CT for evaluation of the pathological response to neoadjuvant chemotherapy in breast cancer: A systematic review and meta-analysis. The Breast, 2018, 40(5): 106-115.
[7]
李鹍,郭晓敏，谢瑜，等. DCE-MRI在局部进展期乳腺癌新辅助化疗疗效评估中的应用价值．山东医药, 2013, 53(11): 8-11.
[8]
Sharma A, Sharma S, Sood S, et al. DCE-MRI and parametric imaging in monitoring response to neoadjuvant chemotherapy in breast carcinoma: a preliminary report. Pol J Radiol, 2018, 83: e220-e228.
[9]
李瑞敏，顾雅佳，彭卫军，等．定量动态增强磁共振评估乳腺癌新辅助化疗疗效的应用研究．中国癌症杂志, 2016, 26(7): 623-628.
[10]
Yu HJ, Chen JH, Mehta RS, et al. MRI measurements of tumor size and pharmacokinetic parameters as early predictors of response in breast cancer patients undergoing neoadjuvant anthracycline chemotherapy. J Magn Reson Imaging, 2007, 26(3): 615-623.
[11]
Tateishi U, Miyake M, Nagaoka T, et al. Neoadjuvant chemotherapy in breast cancer: prediction of pathologic response with PET/CT and dynamic contrast-enhanced MR imaging--prospective assessment. Radiology, 2012, 263(1): 53-63.
[12]
Lee J, Kim SH, Kang BJ. Pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: Perfusion metrics of dynamic contrast enhanced MRI. Sci Rep, 2018, 8(1): 9490.
[13]
Li SP, Makris A, Beresford MJ, et al. Use of dynamic contrast-enhanced MR imaging to predict survival in patients with primary breast cancer undergoing neoadjuvant chemotherapy. Radiology, 2011, 260(1): 68-78.
[14]
Zheng D, Yue Q, Ren W, et al. Early responses assessment of neoadjuvant chemotherapy in nasopharyngeal carcinoma by serial dynamic contrast-enhanced MR imaging. Magn Reson Med, 2017, 35(8): 125-131.
[15]
Minarikova L, Bogner W, Pinker K, et al. Investigating the prediction value of multiparametric magnetic resonance imaging at 3 T in response to neoadjuvant chemotherapy in breast cancer. Eur Radiol, 2017, 27(5): 1901-1911.
[16]
Hu XY, Li Y, Jin GQ, et al. Diffusion-weighted MR imaging in prediction of response to neoadjuvant chemotherapy in patients with breast cancer. Oncotarget, 2017, 8(45): 79642-79649.
[17]
Wilmes LJ, Li W, Shin HJ, et al. Diffusion tensor imaging for assessment of response to neoadjuvant chemotherapy in patients with breast cancer. Tomography, 2016, 2(4): 438-447.
[18]
Park SH, Moon WK, Cho N, et al. Diffusion-weighted MR imaging: pretreatment prediction of response to neoadjuvant chemotherapy in patients with breast cancer. Radiology, 2010, 257(1): 56-63.
[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. Medicine (Baltimore), 2016, 95(4): e2420.
[20]
Kim Y, Kim SH, Lee HW, et al. Intravoxel incoherent motion diffusion-weighted MRI for predicting response to neoadjuvant chemotherapy in breast cancer. Magn Reson Med, 2018, 48(11): 27-33.
[21]
Partridge SC, Ziadloo A, Murthy R, et al. Diffusion tensor MRI: preliminary anisotropy measures and mapping of breast tumors. J Magn Reson Imaging, 2010, 31(2): 339-347.
[22]
Furman HE, Nissan N, Ricart SV, et al. Quantitative evaluation of breast cancer response to neoadjuvant chemotherapy by diffusion tensor imaging: Initial results. J Magn Reson Imaging, 2018, 47(4): 1080-1090.
[23]
柯承露，车树楠，李静，等．扩散峰度成像鉴别诊断乳腺良恶性病变的价值及联合扩散加权成像的诊断效能．中华放射学杂志, 2018, 52(8): 593-597.
[24]
林艳，黄瑶，林伟洵，等．扩散峰度成像参数及其联合扩散加权成像与MR频谱参数鉴别乳腺良、恶性病变的价值．中华放射学杂志, 2017, 51(5): 350-354.
[25]
Kvistad KA, Bakken IJ, Gribbestad IS, et al. Characterization of neoplastic and normal human breast tissues with in vivo (1)H MR spectroscopy. J Magn Reson Imaging, 1999, 10(2): 159-164.
[26]
汪晓红，彭卫军，谭红娜，等．氢质子磁共振波谱监测乳腺癌新辅助化疗疗效的应用研究．中国医学计算机成像杂志, 2010, 16(1): 20-24.
[27]
Bolan PJ, Kim E, Herman BA, et al. MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial. J Magn Reson Imaging, 2017, 46(1): 290-302.

PREV Review of the application of CMR in post-operative follow-up of tetralogy of fallot
NEXT Quantitative assessment of MRI for treatment response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: A review
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn