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Breast MRI
Comparison of DWI IVIM model and mono-exponential model in evaluating the response of neoadjuvant chemotherapy for breast cancer
GENG Xiao-chuan  ZHANG Qing  HUA Jia  CHAI Wei-ming  SUO Shi-teng  CHENG Fang  ZHANG Ke-bei  CHEN Jie 

DOI:10.12015/issn.1674-8034.2017.03.004.


[Abstract] Objective: To analyze the value of intravoxel incoherent motion (IVIM) model and DWI mono-exponential model in evaluating the response of neoadjuvant chemotherapy (NAC) for breast cancer by comparing the parameters of two models.Materials and Methods: Thirty patients confirmed breast cancer by needle biopsy who received NAC were enrolled in the study. The patients were divided into responders (n=19) and nonresponders (n=11) according to the pathological classification of Miller & Payne. ADC, Ds, Df, f and MR imaging data of patients before, after 2 and 4 cycles of NAC were analyzed retrospectively. Two independent samples t test were used to compare the parameters between the responder and nonresponders. The diagnostic efficacy of different parameters was analyzed by receiver operating characteristics (ROC) curves. The paired samples t test was used to compare the parameters after 2, 4 cycles of NAC to parameters before NAC respectively.Results: ADC and Ds before NAC were significantly higher in responders than those in the nonresponders; the sensitivity and specificity of ADC and Ds were about the same. ADC after 2 cycles of NAC was significantly higher than that before NAC Ds after 2 and 4 cycles of NAC was significantly lower than that before NAC. f after 4 cycles of NAC was significantly lower than that before NAC.Conclusions: ADC value and Ds value are helpful to predict the response to NAC before treatment, and ADC value and Ds value are equivalent in predicting the response of NAC. During the NAC course, ADC, Ds and f values play a certain role in predicting the response of NAC. Mono-exponential model is a better method to evaluate the response of NAC in breast cancer.
[Keywords] Diffusion magnetic resonance imaging;Breast neoplasms;Neoadjuvant chemotherapy

GENG Xiao-chuan Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China

ZHANG Qing Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China

HUA Jia Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China

CHAI Wei-ming Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China

SUO Shi-teng Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China

CHENG Fang Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China

ZHANG Ke-bei Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China

CHEN Jie* Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China

*Correspondence to: Chen J, E-mail: cjpure@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This study was funded by the Multidisciplinary Cross-program Development Fund Project No. YG2014ZD05
Received  2016-12-16
Accepted  2017-01-09
DOI: 10.12015/issn.1674-8034.2017.03.004
DOI:10.12015/issn.1674-8034.2017.03.004.

[1]
Feldman LD, Hortobagyi GN, Buzdar AU, et al. Pathological assessment of response to induction chemotherapy in breast cancer. Cancer Res, 1986, 46(5): 2578-2581.
[2]
Heys SD, Eremin JM, Sarkar TK, et al. Role of multimodality therapy in the management of locally advanced carcinoma of the breast. J Am Coll Surg, 1994, 179(4): 493-504.
[3]
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. Oncol Rep, 2014, 31(4): 1555-1560.
[4]
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.
[5]
中华医学会放射学分会乳腺学组.乳腺MRI检查共识.中华放射学杂志, 2014, 48(9): 723-725.
[6]
Le Bihan D. Intravoxel incoherent motion imaging using steady-state free precession. Magn Reson Med, 1988, 7(3): 346-351.
[7]
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.
[8]
Ogston KN, Miller ID, Payne S, et al. A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival. Breast, 2003, 12(5): 320-327.
[9]
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. Clin Breast Cancer, 2015, 15(5): 370-380.
[10]
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. Medicine (Baltimore), 2015, 94(24): e973.
[11]
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. Chin Med J (Engl), 2016, 129(6): 665-671.
[12]
Song XL, Kang HK, Jeong GW, et al. Intravoxel incoherent motion diffusion-weighted imaging for monitoring chemotherapeutic efficacy in gastric cancer. World J Gastroenterol, 2016, 22(24): 5520-5531.
[13]
Herneth AM, Guccione S, Bednarski M. Apparent diffusion coefficient: a quantitative parameter for in vivo tumor characterization. Eur J Radiol, 2003, 45(3): 208-213.
[14]
Ah-See ML, Makris A, Taylor NJ, et al. Early changes in functional dynamic magnetic resonance imaging predict for pathologic response to neoadjuvant chemotherapy in primary breast cancer. Clin Cancer Res, 2008, 14(20): 6580-6589.
[15]
Joo I, Lee JM, Han JK, et al. Intravoxel incoherent motion diffusion-weighted MR imaging for monitoring the therapeutic efficacy of the vascular disrupting agent CKD-516 in rabbit VX2 liver tumors. Radiology, 2014, 272(2): 417-426.
[16]
Liu S, Ren R, Chen Z, et al. Diffusion-weighted imaging in assessing pathological response of tumor in breast cancer subtype to neoadjuvant chemotherapy. J Magn Reson Imaging, 2015, 42(3): 779-787.

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