Wolmark N, Wang J, Mamounas E, Bryant J, Fisher B. Preoperative chemotherapy in patients with operable breast cancer: nine-year results from National Surgical Adjuvant Breast and Bowel Project B-18. J Natl Cancer Inst Monogr. 2001;30:96–102.

Article  Google Scholar 

Bear HD, Anderson S, Brown A, Smith R, Mamounas EP, Fisher B, et al. The effect on tumor response of adding sequential preoperative docetaxel to preoperative doxorubicin and cyclophosphamide: preliminary results from National Surgical Adjuvant Breast and Bowel Project Protocol B-27. J Clin Oncol. 2003;21:4165–74.

Article  CAS  PubMed  Google Scholar 

Pilewskie M, Morrow M. Axillary nodal management following neoadjuvant chemotherapy: a review. JAMA Oncol. 2017;3:549–55.

Article  PubMed  PubMed Central  Google Scholar 

Boughey JC, Suman VJ, Mittendorf EA, Ahrendt GM, Wilke LG, Taback B, et al. Factors affecting sentinel lymph node identification rate after neoadjuvant chemotherapy for breast cancer patients enrolled in ACOSOG Z1071 (Alliance). Ann Surg. 2015;261:547–52.

Article  PubMed  Google Scholar 

Kuehn T, Bauerfeind I, Fehm T, Fleige B, Hausschild M, Helms G, et al. Sentinel-lymph-node biopsy in patients with breast cancer before and after neoadjuvant chemotherapy (SENTINA): a prospective, multicentre cohort study. Lancet Oncol. 2013;14:609–18.

Article  PubMed  Google Scholar 

Boileau JF, Poirier B, Basik M, Holloway CM, Gaboury L, Sideris L, et al. Sentinel node biopsy after neoadjuvant chemotherapy in biopsy-proven node-positive breast cancer: the SN FNAC study. J Clin Oncol. 2015;33:258–64.

Article  PubMed  Google Scholar 

Caudle AS, Yang WT, Krishnamurthy S, Mittendorf EA, Black DM, Gilcrease MZ, et al. Improved Axillary Evaluation Following Neoadjuvant Therapy for Patients With Node-Positive Breast Cancer Using Selective Evaluation of Clipped Nodes: Implementation of Targeted Axillary Dissection. J Clin Oncol. 2016;34:1072–8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kuemmel S, Heil J, Rueland A, Seiberling C, Harrach H, Schindowski D, et al. A Prospective, Multicenter Registry Study to Evaluate the Clinical Feasibility of Targeted Axillary Dissection (TAD) in Node-positive Breast Cancer Patients. Ann Surg. 2022;276:e553–e62.

Article  PubMed  Google Scholar 

Swarnkar PK, Tayeh S, Michell MJ, Mokbel K. The evolving role of marked lymph node biopsy (MLNB) and targeted axillary dissection (TAD) after neoadjuvant chemotherapy (NACT) for node-positive breast cancer: systematic review and pooled analysis. Cancers. 2021;13:1539.

Vila J, Mittendorf EA, Farante G, Bassett RL, Veronesi P, Galimberti V, et al. Nomograms for Predicting Axillary Response to Neoadjuvant Chemotherapy in Clinically Node-Positive Patients with Breast Cancer. Ann Surg Oncol. 2016;23:3501–9.

Article  PubMed  Google Scholar 

Murphy BL, Hoskin TL, Heins CDN, Habermann EB, Boughey JC. Preoperative Prediction of Node-Negative Disease After Neoadjuvant Chemotherapy in Patients Presenting with Node-Negative or Node-Positive Breast Cancer. Ann Surg Oncol. 2017;24:2518–25.

Article  PubMed  Google Scholar 

Schipper RJ, Moossdorff M, Nelemans PJ, Nieuwenhuijzen GA, de Vries B, Strobbe LJ, et al. A model to predict pathologic complete response of axillary lymph nodes to neoadjuvant chemo(immuno)therapy in patients with clinically node-positive breast cancer. Clin Breast Cancer. 2014;14:315–22.

Article  CAS  PubMed  Google Scholar 

Skarping I, Förnvik D, Zackrisson S, Borgquist S, Rydén L. Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer. Breast Cancer Res Treat. 2021;189:131–44.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Al-Hattali S, Vinnicombe SJ, Gowdh NM, Evans A, Armstrong S, Adamson D, et al. Breast MRI and tumour biology predict axillary lymph node response to neoadjuvant chemotherapy for breast cancer. Cancer Imaging. 2019;19:91.

Article  PubMed  PubMed Central  Google Scholar 

Kim R, Chang JM, Lee HB, Lee SH, Kim SY, Kim ES, et al. Predicting Axillary Response to Neoadjuvant Chemotherapy: Breast MRI and US in Patients with Node-Positive Breast Cancer. Radiology. 2019;293:49–57.

Article  PubMed  Google Scholar 

Huang X, Shi Z, Mai J, Liu C, Liu C, Chen S. An MRI-based scoring system for preoperative prediction of axillary response to neoadjuvant chemotherapy in node-positive breast cancer: a multicenter retrospective study. Acad Radiol. 2022:1257–1269.

Zhu T, Lin X, Zhang T, Li W, Gao H, Yang C, et al. A model incorporating axillary tail position on mammography for preoperative prediction of non-sentinel lymph node metastasis in patients with initial cn+ breast cancer after neoadjuvant chemotherapy. Acad Radiol. 2022;29:e271–e8.

Article  PubMed  Google Scholar 

Slanetz PJ, Moy L, Baron P, diFlorio RM, Green ED, Heller SL, et al. ACR Appropriateness Criteria(®) monitoring response to neoadjuvant systemic therapy for breast cancer. J Am Coll Radiology: JACR. 2017;14:S462–s75.

Article  PubMed  Google Scholar 

You S, Kang DK, Jung YS, An YS, Jeon GS, Kim TH. Evaluation of lymph node status after neoadjuvant chemotherapy in breast cancer patients: comparison of diagnostic performance of ultrasound, MRI and 18F-FDG PET/CT. Br J Radiol. 2015;88:20150143.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Javid S, Segara D, Lotfi P, Raza S, Golshan M. Can breast MRI predict axillary lymph node metastasis in women undergoing neoadjuvant chemotherapy. Ann Surg Oncol. 2010;17:1841–6.

Article  PubMed  Google Scholar 

Hieken TJ, Boughey JC, Jones KN, Shah SS, Glazebrook KN. Imaging response and residual metastatic axillary lymph node disease after neoadjuvant chemotherapy for primary breast cancer. Ann Surg Oncol. 2013;20:3199–204.

Article  PubMed  Google Scholar 

Bitencourt AGV, Gibbs P, Rossi Saccarelli C, Daimiel I, Lo Gullo R, Fox MJ, et al. MRI-based machine learning radiomics can predict HER2 expression level and pathologic response after neoadjuvant therapy in HER2 overexpressing breast cancer. EBioMedicine. 2020;61:103042.

Article  PubMed  PubMed Central  Google Scholar 

Yu Y, He Z, Ouyang J, Tan Y, Chen Y, Gu Y, et al. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: a machine learning, multicenter study. EBioMedicine. 2021;69:103460.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Drukker K, Edwards A, Doyle C, Papaioannou J, Kulkarni K, Giger ML. Breast MRI radiomics for the pretreatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients. J Med imaging. 2019;6:034502.

Article  Google Scholar 

Minarikova L, Bogner W, Pinker K, Valkovič L, Zaric O, Bago-Horvath Z, 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;27:1901–11.

Article  PubMed  Google Scholar 

Pereira NP, Curi C, Osório C, Marques EF, Makdissi FB, Pinker K, et al. Diffusion-weighted magnetic resonance imaging of patients with breast cancer following neoadjuvant chemotherapy provides early prediction of pathological response - a prospective study. Sci Rep. 2019;9:16372.

Article  PubMed  PubMed Central  Google Scholar 

Eun NL, Kang D, Son EJ, Park JS, Youk JH, Kim JA, et al. Texture analysis with 3.0-T MRI for association of response to neoadjuvant chemotherapy in breast cancer. Radiology. 2020;294:31–41.

Article  PubMed  Google Scholar 

Nadrljanski MM, Milosevic ZC. Tumor texture parameters of invasive ductal breast carcinoma in neoadjuvant chemotherapy: early identification of non-responders on breast MRI. Clin imaging. 2020;65:119–23.

Article  PubMed  Google Scholar 

Tudorica A, Oh KY, Chui SY, Roy N, Troxell ML, Naik A, et al. Early prediction and evaluation of breast cancer response to neoadjuvant chemotherapy using quantitative DCE-MRI. Transl Oncol. 2016;9:8–17.

Article  PubMed  PubMed Central  Google Scholar 

Dogan BE, Yuan Q, Bassett R, Guvenc I, Jackson EF, Cristofanilli M, et al. Comparing the performances of magnetic resonance imaging size vs pharmacokinetic parameters to predict response to neoadjuvant chemotherapy and survival in patients with breast cancer. Curr Probl Diagn Radiol. 2019;48:235–40.

Article  PubMed  Google Scholar 

Liu Z, Li Z, Qu J, Zhang R, Zhou X, Li L. et al. Radiomics of multiparametric MRI for pretreatment prediction of pathologic complete response to neoadjuvant chemotherapy in breast cancer: a multicenter study.Clin Cancer Res. 2019;25:3538–47.

Article  CAS  PubMed  Google Scholar 

Han L, Zhu Y, Liu Z, Yu T, He C, Jiang W, et al. Radiomic nomogram for prediction of axillary lymph node metastasis in breast cancer. Eur Radiol. 2019;29:3820–9.

Article  PubMed  Google Scholar