Prediction of pathological response to neoadjuvant chemotherapy in breast cancer patients by imaging

被引:13
|
作者
Kaise, Hiroshi [1 ]
Shimizu, Fumika [2 ]
Akazawa, Kohei [2 ]
Hasegawa, Yoshie [3 ]
Horiguchi, Jun [4 ]
Miura, Daishu [5 ]
Kohno, Norio [6 ]
Ishikawa, Takashi [1 ]
机构
[1] Tokyo Med Univ Hosp, Dept Breast Oncol & Surg, Tokyo, Japan
[2] Niigata Univ Med & Dent Hosp, Dept Med Informat, Niigata, Japan
[3] Hirosaki Municipal Hosp, Dept Breast Surg, Aomori, Japan
[4] Gunma Univ Hosp, Dept Breast & Endocrine Surg, Gunma, Japan
[5] Toranomon Gen Hosp, Dept Breast & Endocrine Surg, Tokyo, Japan
[6] Kobe Kaisei Hosp, Dept Breast Surg, Kobe, Hyogo, Japan
关键词
Breast cancer; Neoadjuvant chemotherapy; Magnetic resonance imaging; Ultrasound; Pathological complete response; MRI; METAANALYSIS; ACCURACY;
D O I
10.1016/j.jss.2017.12.002
中图分类号
R61 [外科手术学];
学科分类号
摘要
Background: Diagnostic imaging is important for predicting the pathological response to chemotherapy during neoadjuvant chemotherapy (NAC) and for considering the surgical management with appropriate resection after NAC. This study was performed to examine the accuracy of the present radiological imaging for predicting the pathological complete response (pCR). Methods: From 188 patients in our previous JONIE1 Study, a randomized controlled trial comparing chemotherapy with and without zoledronic acid for patients with human epidermal growth factor receptor 2-negative breast cancer, we evaluated 122 patients whose tumor size was examined by magnetic resonance imaging or ultrasound at three points: before NAC; after administering fluorouracil, epirubicin, and cyclophosphamide; and after NAC. The maximum tumor diameter was evaluated by magnetic resonance imaging or ultrasound. Tumor reduction ratios were calculated at the same three points. The association between the radiological clinical response and the pCR was examined. Results: Among the 122 patients evaluated, there were 98 and 24 patients with luminal (Lum) and triple-negative (TN) subtypes, respectively. There were no patients who showed tumor progression after treatment. The radiological size of the tumors was finally reduced by an average of 58.4%. Clinical complete response and pCR were achieved in 22 (18.0%) and 15 (12.3%) patients, respectively. In the overall population (n = 122), the accuracy, sensitivity, and specificity for predicting pCR were 86.1%, 88.8%, and 66.7%, respectively. The negative predictive value and false-negative rate were 45.5% and 11.2%, respectively. According to subtypes, the accuracies were 83.7% and 95.8% in Lum and TN, respectively. Negative predictive value and false-negative rate were markedly different between the Lum (29.4% and 13.5%) and TN subtypes (100% and 0%), respectively. Conclusions: This randomized clinical trial demonstrated that NAC was safe for operable breast cancer patients with appropriate radiological monitoring. Radiological evaluation after NAC may be a reliable method for predicting pathological response in the TN subtype, but not in the Lum subtype. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:175 / 180
页数:6
相关论文
共 50 条
  • [31] Diffusion-weighted imaging in assessing pathological response of tumor in breast cancer subtype to neoadjuvant chemotherapy
    Liu, Shangang
    Ren, Ruimei
    Chen, Zhaoqiu
    Wang, Yongsheng
    Fan, Tingyong
    Li, Chengli
    Zhang, Pinliang
    JOURNAL OF MAGNETIC RESONANCE IMAGING, 2015, 42 (03) : 779 - 787
  • [32] Molecular Biomarkers Predict Pathological Complete Response of Neoadjuvant Chemotherapy in Breast Cancer Patients: Review
    Freitas, Ana Julia Aguiar de
    Causin, Rhafaela Lima
    Varuzza, Muriele Bertagna
    Hidalgo Filho, Cassio Murilo Trovo
    Silva, Vinicius Duval da
    Souza, Cristiano de Padua
    Marques, Marcia Maria Chiquitelli
    CANCERS, 2021, 13 (21)
  • [33] A Narrative Review of Ultrasound Technologies for the Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer
    Wang, Jing
    Chu, Yanhua
    Wang, Baohua
    Jiang, Tianan
    CANCER MANAGEMENT AND RESEARCH, 2021, 13 : 7885 - 7895
  • [34] Magnetic Resonance Imaging Evaluation of Pathological Response in Breast Cancer After Neoadjuvant Chemotherapy
    Gülçin Akkavak Palazalı
    Ravza Yılmaz
    Ozgkıour Palazalı
    Memduh Dursun
    Indian Journal of Surgery, 2023, 85 : 39 - 44
  • [35] Multimodality Imaging for Evaluating Response to Neoadjuvant Chemotherapy in Breast Cancer
    Rauch, Gaiane M.
    Adrada, Beatriz Elena
    Kuerer, Henry Mark
    van la Parra, Raquel F. D.
    Leung, Jessica W. T.
    Yang, Wei Tse
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2017, 208 (02) : 290 - 299
  • [36] Changes in quantitative ultrasound imaging as the predictor of response to neoadjuvant chemotherapy in patients with breast cancer
    Piotrzkowska-Wroblewska, Hanna
    Dobruch-Sobczak, Katarzyna
    Gumowska, Magdalena
    Litniewski, Jerzy
    2022 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IEEE IUS), 2022,
  • [37] Occult breast cancer with pathological complete response to neoadjuvant chemotherapy
    Ren, Ningning
    Liu, Shuo
    Shi, Peng
    Tian, Xingsong
    ASIAN JOURNAL OF SURGERY, 2024, 47 (11) : 4949 - 4951
  • [38] Computer-aided classification of MRI for pathological complete response to neoadjuvant chemotherapy in breast cancer
    Yan, Shaolei
    Peng, Haiyong
    Yu, Qiujie
    Chen, Xiaodan
    Liu, Yue
    Zhu, Ye
    Chen, Kaige
    Wang, Ping
    Li, Yujiao
    Zhang, Xiushi
    Meng, Wei
    FUTURE ONCOLOGY, 2022, 18 (08) : 991 - 1001
  • [39] Diagnosis of pathological complete response to neoadjuvant chemotherapy in breast cancer by minimal invasive biopsy techniques
    Heil, Joerg
    Kuemmel, Sherko
    Schaefgen, Benedikt
    Paepke, Stefan
    Thomssen, Christoph
    Rauch, Geraldine
    Ataseven, Beyhan
    Grosse, Regina
    Dreesmann, Volker
    Kuehn, Thorsten
    Loibl, Sibylle
    Blohmer, Jens-Uwe
    von Minckwitz, Gunter
    BRITISH JOURNAL OF CANCER, 2015, 113 (11) : 1565 - 1570
  • [40] Prediction of neoadjuvant chemotherapy pathological complete response for breast cancer based on radiomics nomogram of intratumoral and derived tissue
    Guangying Zheng
    Jie Hou
    Zhenyu Shu
    Jiaxuan Peng
    Lu Han
    Zhongyu Yuan
    Xiaodong He
    Xiangyang Gong
    BMC Medical Imaging, 24