Stephen F Sener1,2, Rachel E Sargent1,2, Connie Lee1,2, Tejas Manchandia1,3, Vivian Le-Tran1,2, Yuliya Olimpiadi1,2, Nicole Zaremba1,2, Andrew Alabd2, Maria Nelson1,2, Julie E Lang1,2. 1. Los Angeles County+University of Southern California (LAC+USC) Medical Center, Los Angeles, California. 2. Department of Surgery and Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California. 3. Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California.
Abstract
BACKGROUND: This study assessed whether magnetic resonance imaging (MRI) could accurately predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) for patients receiving standardized treatment, pre- and post-NAC MRI on the same instrumentation using a consistent imaging protocol, interpreted by a single breast fellowship-trained radiologist. METHODS: A single-institution retrospective analysis was performed including clinical, radiographic, and pathologic parameters for all patients with breast cancer treated with NAC from 2015 to 2018. Radiographic complete response (rCR) was defined as absence of suspicious MRI findings in the ipsilateral breast or lymph nodes. pCR was defined as the absence of invasive cancer or ductal carcinoma in-situ in breast or lymph nodes after operation (ypT0N0M0). RESULTS: Data for 102 consecutive patients demonstrated that 44 (43.1%) had rCR and 41 (40.1%) had pCR. pCR occurred in 12 (25.0%) of 48 estrogen receptor positive (ER+) patients, 29 (53.7%) of 54 ER- patients, and 25 (52.1%) of 48 human epidermal growth factor receptor 2 positive patients. The positive predictive value for MRI after NAC was 84.5% and the negative predictive value was 72.7%. The accuracy rate for MRI was 78.6%. Of the 44 patients with rCR, 12 (27.3%) had residual cancer on the pathologic specimen after surgical excision. CONCLUSION: rCR is not accurate enough to serve as a surrogate marker for pCR on MRI after NAC.
BACKGROUND: This study assessed whether magnetic resonance imaging (MRI) could accurately predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) for patients receiving standardized treatment, pre- and post-NAC MRI on the same instrumentation using a consistent imaging protocol, interpreted by a single breast fellowship-trained radiologist. METHODS: A single-institution retrospective analysis was performed including clinical, radiographic, and pathologic parameters for all patients with breast cancer treated with NAC from 2015 to 2018. Radiographic complete response (rCR) was defined as absence of suspicious MRI findings in the ipsilateral breast or lymph nodes. pCR was defined as the absence of invasive cancer or ductal carcinoma in-situ in breast or lymph nodes after operation (ypT0N0M0). RESULTS: Data for 102 consecutive patients demonstrated that 44 (43.1%) had rCR and 41 (40.1%) had pCR. pCR occurred in 12 (25.0%) of 48 estrogen receptor positive (ER+) patients, 29 (53.7%) of 54 ER- patients, and 25 (52.1%) of 48 humanepidermal growth factor receptor 2 positive patients. The positive predictive value for MRI after NAC was 84.5% and the negative predictive value was 72.7%. The accuracy rate for MRI was 78.6%. Of the 44 patients with rCR, 12 (27.3%) had residual cancer on the pathologic specimen after surgical excision. CONCLUSION:rCR is not accurate enough to serve as a surrogate marker for pCR on MRI after NAC.
Authors: Nola M Hylton; Jeffrey D Blume; Wanda K Bernreuter; Etta D Pisano; Mark A Rosen; Elizabeth A Morris; Paul T Weatherall; Constance D Lehman; Gillian M Newstead; Sandra Polin; Helga S Marques; Laura J Esserman; Mitchell D Schnall Journal: Radiology Date: 2012-06 Impact factor: 11.105
Authors: Gunter von Minckwitz; Andreas Schneeweiss; Sibylle Loibl; Christoph Salat; Carsten Denkert; Mahdi Rezai; Jens U Blohmer; Christian Jackisch; Stefan Paepke; Bernd Gerber; Dirk M Zahm; Sherko Kümmel; Holger Eidtmann; Peter Klare; Jens Huober; Serban Costa; Hans Tesch; Claus Hanusch; Jörn Hilfrich; Fariba Khandan; Peter A Fasching; Bruno V Sinn; Knut Engels; Keyur Mehta; Valentina Nekljudova; Michael Untch Journal: Lancet Oncol Date: 2014-04-30 Impact factor: 41.316
Authors: Mette S van Ramshorst; Claudette E Loo; Emilie J Groen; Gonneke H Winter-Warnars; Jelle Wesseling; Frederieke van Duijnhoven; Marie-Jeanne T Vrancken Peeters; Gabe S Sonke Journal: Breast Cancer Res Treat Date: 2017-04-21 Impact factor: 4.872
Authors: Shadfar Bahri; Jeon-Hor Chen; Rita S Mehta; Philip M Carpenter; Ke Nie; Soon-Young Kwon; Hon J Yu; Orhan Nalcioglu; Min-Ying Su Journal: Ann Surg Oncol Date: 2009-03-31 Impact factor: 5.344
Authors: Savannah C Partridge; Zheng Zhang; David C Newitt; Jessica E Gibbs; Thomas L Chenevert; Mark A Rosen; Patrick J Bolan; Helga S Marques; Justin Romanoff; Lisa Cimino; Bonnie N Joe; Heidi R Umphrey; Haydee Ojeda-Fournier; Basak Dogan; Karen Oh; Hiroyuki Abe; Jennifer S Drukteinis; Laura J Esserman; Nola M Hylton Journal: Radiology Date: 2018-09-04 Impact factor: 29.146
Authors: Briete Goorts; Kelly M A Dreuning; Janneke B Houwers; Loes F S Kooreman; Evert-Jan G Boerma; Ritse M Mann; Marc B I Lobbes; Marjolein L Smidt Journal: Breast Cancer Res Date: 2018-04-18 Impact factor: 6.466
Authors: Michael L Marinovich; Petra Macaskill; Les Irwig; Francesco Sardanelli; Eleftherios Mamounas; Gunter von Minckwitz; Valentina Guarneri; Savannah C Partridge; Frances C Wright; Jae Hyuck Choi; Madhumita Bhattacharyya; Laura Martincich; Eren Yeh; Viviana Londero; Nehmat Houssami Journal: BMC Cancer Date: 2015-10-08 Impact factor: 4.430
Authors: Bruna M Thompson; Luciano F Chala; Carlos Shimizu; Max S Mano; José R Filassi; Felipe C Geyer; Ulysses S Torres; Giselle Guedes Netto de Mello; Cláudia da Costa Leite Journal: Eur Radiol Date: 2021-10-30 Impact factor: 7.034