Literature DB >> 22438441

Neoadjuvant chemotherapy in breast cancer: prediction of pathologic response with PET/CT and dynamic contrast-enhanced MR imaging--prospective assessment.

Ukihide Tateishi1, Mototaka Miyake, Tomoaki Nagaoka, Takashi Terauchi, Kazunori Kubota, Takayuki Kinoshita, Hiromitsu Daisaki, Homer A Macapinlac.   

Abstract

PURPOSE: To clarify whether fluorine 18 ((18)F) fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging performed after two cycles of neoadjuvant chemotherapy (NAC) can be used to predict pathologic response in breast cancer.
MATERIALS AND METHODS: Institutional human research committee approval and written informed consent were obtained. Accuracy after two cycles of NAC for predicting pathologic complete response (pCR) was examined in 142 women (mean age, 57 years: range, 43-72 years) with histologically proved breast cancer between December 2005 and February 2009. Quantitative PET/CT and DCE MR imaging were performed at baseline and after two cycles of NAC. Parameters of PET/CT and of blood flow and microvascular permeability at DCE MR were compared with pathologic response. Patients were also evaluated after NAC by using Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 based on DCE MR measurements and European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST) 1.0 based on PET/CT measurements. Multiple logistic regression analyses were performed to examine continuous variables at PET/CT and DCE MR to predict pCR, and diagnostic accuracies were compared with the McNemar test.
RESULTS: Significant decrease from baseline of all parameters at PET/CT and DCE MR was observed after NAC. Therapeutic response was obtained in 24 patients (17%) with pCR and 118 (83%) without pCR. Sensitivity, specificity, and accuracy to predict pCR were 45.5%, 85.5%, and 82.4%, respectively, with RECIST and 70.4%, 95.7%, and 90.8%, respectively, with EORTC and PERCIST. Multiple logistic regression revealed three significant independent predictors of pCR: percentage maximum standardized uptake value (%SUV(max)) (odds ratio [OR], 1.22; 95% confidence interval [CI]: 1.11, 1.34; P < .0001), percentage rate constant (%k(ep)) (OR, 1.07; CI: 1.03, 1.12; P = .002), and percentage area under the time-intensity curve over 90 seconds (%AUC(90)) (OR, 1.04; CI: 1.01, 1.07; P = .048). When diagnostic accuracies are compared, PET/CT is superior to DCE MR for the prediction of pCR (%SUV(max) [90.1%] vs %κ(ep) [83.8%] or %AUC(90) [76.8%]; P < .05).
CONCLUSION: The sensitivities of %SUV(max) (66.7%), %k(ep) (51.7%), and %AUC(90) (50.0%) at (18)F-FDG PET/CT and DCE MR after two cycles of NAC are not acceptable, but the specificities (96.4%, 92.0%, and 95.2%, respectively) are high for stratification of pCR cases in breast cancer. © RSNA, 2012.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 22438441     DOI: 10.1148/radiol.12111177

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  54 in total

Review 1.  Present and future role of FDG-PET/CT imaging in the management of breast cancer.

Authors:  Kazuhiro Kitajima; Yasuo Miyoshi
Journal:  Jpn J Radiol       Date:  2016-01-05       Impact factor: 2.374

Review 2.  The accuracy of 18F-FDG PET/CT in predicting the pathological response to neoadjuvant chemotherapy in patients with breast cancer: a meta-analysis and systematic review.

Authors:  Fangfang Tian; Guohua Shen; Yunfu Deng; Wei Diao; Zhiyun Jia
Journal:  Eur Radiol       Date:  2017-05-05       Impact factor: 5.315

3.  Multiparametric and Multimodality Functional Radiological Imaging for Breast Cancer Diagnosis and Early Treatment Response Assessment.

Authors:  Michael A Jacobs; Antonio C Wolff; Katarzyna J Macura; Vered Stearns; Ronald Ouwerkerk; Riham El Khouli; David A Bluemke; Richard Wahl
Journal:  J Natl Cancer Inst Monogr       Date:  2015-05

Review 4.  ¹⁸F-FDG PET/CT in the early prediction of pathological response in aggressive subtypes of breast cancer: review of the literature and recommendations for use in clinical trials.

Authors:  David Groheux; David Mankoff; Marc Espié; Elif Hindié
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-01-13       Impact factor: 9.236

5.  FDG-PET/CT and MRI for Evaluation of Pathologic Response to Neoadjuvant Chemotherapy in Patients With Breast Cancer: A Meta-Analysis of Diagnostic Accuracy Studies.

Authors:  Sara Sheikhbahaei; Tyler J Trahan; Jennifer Xiao; Mehdi Taghipour; Esther Mena; Roisin M Connolly; Rathan M Subramaniam
Journal:  Oncologist       Date:  2016-07-08

6.  MRI and ¹⁸F-FDG PET/CT in monitoring the response to neoadjuvant chemotherapy: is it necessary to appropriately select the patients?

Authors:  Laura Evangelista; Domenico Ruggieri; Luigi Pescarini; Giorgio Saladini
Journal:  Eur J Nucl Med Mol Imaging       Date:  2014-08       Impact factor: 9.236

7.  [Therapy monitoring of neoadjuvant therapy with MRI. RECIST and functional imaging].

Authors:  S Grandl; M Ingrisch; K Hellerhoff
Journal:  Radiologe       Date:  2014-03       Impact factor: 0.635

8.  Combined use of ¹⁸F-FDG PET/CT and MRI for response monitoring of breast cancer during neoadjuvant chemotherapy.

Authors:  Kenneth E Pengel; Bas B Koolen; Claudette E Loo; Wouter V Vogel; Jelle Wesseling; Esther H Lips; Emiel J Th Rutgers; Renato A Valdés Olmos; Marie Jeanne T F D Vrancken Peeters; Sjoerd Rodenhuis; Kenneth G A Gilhuijs
Journal:  Eur J Nucl Med Mol Imaging       Date:  2014-04-29       Impact factor: 9.236

9.  Response to neoadjuvant chemotherapy for breast cancer judged by PERCIST - multicenter study in Japan.

Authors:  Kazuhiro Kitajima; Koya Nakatani; Kazushige Yamaguchi; Masatoyo Nakajo; Atsushi Tani; Mana Ishibashi; Keiko Hosoya; Takahiro Morita; Takayuki Kinoshita; Hayato Kaida; Yasuo Miyoshi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-05-12       Impact factor: 9.236

10.  Current and emerging quantitative magnetic resonance imaging methods for assessing and predicting the response of breast cancer to neoadjuvant therapy.

Authors:  Richard G Abramson; Lori R Arlinghaus; Jared A Weis; Xia Li; Adrienne N Dula; Eduard Y Chekmenev; Seth A Smith; Michael I Miga; Vandana G Abramson; Thomas E Yankeelov
Journal:  Breast Cancer (Dove Med Press)       Date:  2012-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.