Literature DB >> 23255899

Analysis of complete response by MRI following neoadjuvant chemotherapy predicts pathological tumor responses differently for molecular subtypes of breast cancer.

Yuji Hayashi1, Hiroyuki Takei, Satoshi Nozu, Yoshihiro Tochigi, Akihiro Ichikawa, Naoki Kobayashi, Masafumi Kurosumi, Kenichi Inoue, Takashi Yoshida, Shigenori E Nagai, Hanako Oba, Toshio Tabei, Jun Horiguchi, Izumi Takeyoshi.   

Abstract

In the present study, clinical tumor response following neoadjuvant chemotherapy (NAC) was diagnosed by magnetic resonance imaging (MRI) and clinicopathological factors, including molecular subtypes at baseline, were analyzed for correlations with pathological tumor responses. In addition, clinicopathological factors were analyzed for a correlation with the MRI capacity to predict pathological complete response (pCR). Clinical tumor response evaluated by MRI following NAC was determined as a clinical CR (cCR) or a residual tumor. cCR was confirmed if no gadolinium enhancement or an enhancement equal to or less than that of glandular tissue was observed in any phase of the MRI. Pathological tumor responses following NAC were classified into grades 0 (no change) to 3 (no residual invasive cancer) according to criteria of the Japanese Breast Cancer Society. pCR was defined as grade 3 in the present study. Of 264 cases of invasive breast cancer in 260 patients (4 synchronous bilateral breast cancer cases), 59 (22%) were diagnosed by MRI following NAC as cCR and 98 (37%) were pathologically diagnosed as pCR. In terms of predicting pCR by MRI, the sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) were 44, 90, 73, 73 and 73%, respectively. Tumor size, hormone receptor status, human epidermal growth factor receptor 2 (HER2) status, molecular subtype and histological type were significantly correlated with pathological tumor responses. pCR rates increased in the following order: luminal/HER2-negative (14%), luminal/HER2-positive (32%), triple-negative (46%) and non-luminal/HER2-positive (73%) tumors. Sensitivity and specificity were the highest (60 and 100%, respectively) in triple-negative tumors. PPV decreased in the following order: triple-negative (100%), non-luminal/HER2-positive (92%), luminal/HER2-positive (46%) and luminal/HER2-negative (33%) tumors. In conclusion, MRI evaluation is useful for predicting pCR following NAC, particularly for triple-negative tumors.

Entities:  

Year:  2012        PMID: 23255899      PMCID: PMC3525359          DOI: 10.3892/ol.2012.1004

Source DB:  PubMed          Journal:  Oncol Lett        ISSN: 1792-1074            Impact factor:   2.967


  16 in total

1.  Accuracy of breast magnetic resonance imaging in predicting pathologic response in patients treated with neoadjuvant chemotherapy.

Authors:  Jennifer De Los Santos; Wanda Bernreuter; Kimberly Keene; Helen Krontiras; John Carpenter; Kirby Bland; Alan Cantor; Andres Forero
Journal:  Clin Breast Cancer       Date:  2011-08-10       Impact factor: 3.225

Review 2.  MR imaging for assessment of breast cancer response to neoadjuvant chemotherapy.

Authors:  Nola Hylton
Journal:  Magn Reson Imaging Clin N Am       Date:  2006-08       Impact factor: 2.266

3.  Neoadjuvant therapy with paclitaxel followed by 5-fluorouracil, epirubicin, and cyclophosphamide chemotherapy and concurrent trastuzumab in human epidermal growth factor receptor 2-positive operable breast cancer: an update of the initial randomized study population and data of additional patients treated with the same regimen.

Authors:  Aman U Buzdar; Vicente Valero; Nuhad K Ibrahim; Deborah Francis; Kristine R Broglio; Richard L Theriault; Lajos Pusztai; Marjorie C Green; Sonja E Singletary; Kelly K Hunt; Aysegul A Sahin; Francisco Esteva; William F Symmans; Michael S Ewer; Thomas A Buchholz; Gabriel N Hortobagyi
Journal:  Clin Cancer Res       Date:  2007-01-01       Impact factor: 12.531

4.  Histopathological criteria for assessment of therapeutic response in breast cancer (2007 version).

Authors:  Masafumi Kurosumi; Sadako Akashi-Tanaka; Futoshi Akiyama; Yoshifumi Komoike; Hirofumi Mukai; Seigo Nakamura; Hitoshi Tsuda
Journal:  Breast Cancer       Date:  2008       Impact factor: 4.239

5.  Diagnostic performance of magnetic resonance imaging for assessing tumor response in patients with HER2-negative breast cancer receiving neoadjuvant chemotherapy is associated with molecular biomarker profile.

Authors:  Aida Kuzucan; Jeon-Hor Chen; Shadfar Bahri; Rita S Mehta; Philip M Carpenter; Peter T Fwu; Hon J Yu; David J B Hsiang; Karen T Lane; John A Butler; Stephen A Feig; Min-Ying Su
Journal:  Clin Breast Cancer       Date:  2012-04       Impact factor: 3.225

6.  MRI staging after neoadjuvant chemotherapy for breast cancer: does tumor biology affect accuracy?

Authors:  Kandace P McGuire; Jorge Toro-Burguete; Hang Dang; Jessica Young; Atilla Soran; Margarita Zuley; Rohit Bhargava; Marguerite Bonaventura; Ronald Johnson; Gretchen Ahrendt
Journal:  Ann Surg Oncol       Date:  2011-09-27       Impact factor: 5.344

7.  Neoadjuvant chemotherapy in breast cancer: significantly enhanced response with docetaxel.

Authors:  Ian C Smith; Steven D Heys; Andrew W Hutcheon; Iain D Miller; Simon Payne; Fiona J Gilbert; Antoinne K Ah-See; Oleg Eremin; Leslie G Walker; Tarun K Sarkar; S Peter Eggleton; Keith N Ogston
Journal:  J Clin Oncol       Date:  2002-03-15       Impact factor: 44.544

8.  Effect of preoperative chemotherapy on the outcome of women with operable breast cancer.

Authors:  B Fisher; J Bryant; N Wolmark; E Mamounas; A Brown; E R Fisher; D L Wickerham; M Begovic; A DeCillis; A Robidoux; R G Margolese; A B Cruz; J L Hoehn; A W Lees; N V Dimitrov; H D Bear
Journal:  J Clin Oncol       Date:  1998-08       Impact factor: 44.544

9.  MRI evaluation of pathologically complete response and residual tumors in breast cancer after neoadjuvant chemotherapy.

Authors:  Jeon Hor Chen; Byron Feig; Byon Feig; Garima Agrawal; Hon Yu; Philip M Carpenter; Rita S Mehta; Orhan Nalcioglu; Min Ying Su
Journal:  Cancer       Date:  2008-01-01       Impact factor: 6.860

10.  Measurement of residual breast cancer burden to predict survival after neoadjuvant chemotherapy.

Authors:  W Fraser Symmans; Florentia Peintinger; Christos Hatzis; Radhika Rajan; Henry Kuerer; Vicente Valero; Lina Assad; Anna Poniecka; Bryan Hennessy; Marjorie Green; Aman U Buzdar; S Eva Singletary; Gabriel N Hortobagyi; Lajos Pusztai
Journal:  J Clin Oncol       Date:  2007-09-04       Impact factor: 44.544

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  15 in total

1.  Neoadjuvant chemotherapy for different molecular breast cancer subtypes: a retrospective study in Russian population.

Authors:  Nataliya Babyshkina; Elena Malinovskaya; Stanislav Patalyak; Olga Bragina; Natalia Tarabanovskaya; Artem Doroshenko; Elena Slonimskaya; Vladimir Perelmuter; Nadejda Cherdyntseva
Journal:  Med Oncol       Date:  2014-08-20       Impact factor: 3.064

2.  Monitoring Serum VEGF in Neoadjuvant Chemotherapy for Patients with Triple-Negative Breast Cancer: A New Strategy for Early Prediction of Treatment Response and Patient Survival.

Authors:  Ruo-Xi Wang; Sheng Chen; Liang Huang; Ying Zhou; Zhi-Ming Shao
Journal:  Oncologist       Date:  2018-08-20

3.  Identification of tumor biomarkers for pathological complete response to neoadjuvant treatment in locally advanced breast cancer.

Authors:  Prarthana Gopinath; Sridevi Veluswami; Gopal Gopisetty; Shirley Sundersingh; Swaminathan Rajaraman; Rajkumar Thangarajan
Journal:  Breast Cancer Res Treat       Date:  2022-05-21       Impact factor: 4.872

4.  Prediction of pathologic complete response on MRI in patients with breast cancer receiving neoadjuvant chemotherapy according to molecular subtypes.

Authors:  Jieun Kim; Boo-Kyung Han; Eun Young Ko; Eun Sook Ko; Ji Soo Choi; Ko Woon Park
Journal:  Eur Radiol       Date:  2022-01-06       Impact factor: 5.315

Review 5.  Imaging for Response Assessment in Cancer Clinical Trials.

Authors:  Anna G Sorace; Asser A Elkassem; Samuel J Galgano; Suzanne E Lapi; Benjamin M Larimer; Savannah C Partridge; C Chad Quarles; Kirsten Reeves; Tiara S Napier; Patrick N Song; Thomas E Yankeelov; Stefanie Woodard; Andrew D Smith
Journal:  Semin Nucl Med       Date:  2020-06-10       Impact factor: 4.446

6.  Impact of factors affecting the residual tumor size diagnosed by MRI following neoadjuvant chemotherapy in comparison to pathology.

Authors:  Jeon-Hor Chen; Shadfar Bahri; Rita S Mehta; Philip M Carpenter; Christine E McLaren; Wen-Pin Chen; Peter T Fwu; David J B Hsiang; Karen T Lane; John A Butler; Min-Ying Su
Journal:  J Surg Oncol       Date:  2013-10-28       Impact factor: 3.454

7.  The diagnostic performance of CESM and CE-MRI in evaluating the pathological response to neoadjuvant therapy in breast cancer: a systematic review and meta-analysis.

Authors:  Sudan Tang; Chunhong Xiang; Quan Yang
Journal:  Br J Radiol       Date:  2020-07-02       Impact factor: 3.039

8.  Kinetic information from dynamic contrast-enhanced MRI enables prediction of residual cancer burden and prognosis in triple-negative breast cancer: a retrospective study.

Authors:  Ayane Yamaguchi; Maya Honda; Hiroshi Ishiguro; Masako Kataoka; Tatsuki R Kataoka; Hanako Shimizu; Masae Torii; Yukiko Mori; Nobuko Kawaguchi-Sakita; Kentaro Ueno; Masahiro Kawashima; Masahiro Takada; Eiji Suzuki; Yuji Nakamoto; Kosuke Kawaguchi; Masakazu Toi
Journal:  Sci Rep       Date:  2021-05-12       Impact factor: 4.379

9.  The diagnostic accuracy of magnetic resonance imaging in predicting pathologic complete response after neoadjuvant chemotherapy in patients with different molecular subtypes of breast cancer.

Authors:  Xinfeng Zhang; Dandan Wang; Zhuangkai Liu; Zheng Wang; Qiang Li; Hong Xu; Bin Zhang; Ting Liu; Feng Jin
Journal:  Quant Imaging Med Surg       Date:  2020-01

10.  Accuracy of magnetic resonance imaging for predicting pathological complete response of breast cancer after neoadjuvant chemotherapy: association with breast cancer subtype.

Authors:  Takayo Fukuda; Rie Horii; Naoya Gomi; Yumi Miyagi; Shunji Takahashi; Yoshinori Ito; Futoshi Akiyama; Shinji Ohno; Takuji Iwase
Journal:  Springerplus       Date:  2016-02-24
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