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Published on: April 18, 2015
Neoadjuvant chemotherapy in breast cancer: prediction of pathologic response with PET/CT and dynamic
Ukihide Tateishi1, Mototaka Miyake, Tomoaki Nagaoka
1Department of Radiology, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa 236-0004, Japan. utateish@yokohama-cu.ac.jp
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.
