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Effect of Imaging Parameter Thresholds on MRI Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes

The purpose of this study is to evaluate the predictive performance of magnetic resonance imaging (MRI) markers in breast cancer patients by subtype. Sixty-four patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy were enrolled in this study. Each patient received a dynam...

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Detalles Bibliográficos
Autores principales: Lo, Wei-Ching, Li, Wen, Jones, Ella F., Newitt, David C., Kornak, John, Wilmes, Lisa J., Esserman, Laura J., Hylton, Nola M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4757528/
https://www.ncbi.nlm.nih.gov/pubmed/26886725
http://dx.doi.org/10.1371/journal.pone.0142047
Descripción
Sumario:The purpose of this study is to evaluate the predictive performance of magnetic resonance imaging (MRI) markers in breast cancer patients by subtype. Sixty-four patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy were enrolled in this study. Each patient received a dynamic contrast-enhanced (DCE-MRI) at baseline, after 1 cycle of chemotherapy and before surgery. Functional tumor volume (FTV), the imaging marker measured by DCE-MRI, was computed at various thresholds of percent enhancement (PE(t)) and signal-enhancement ratio (SER(t)). Final FTV before surgery and percent changes of FTVs at the early and final treatment time points were used to predict patients’ recurrence-free survival. The full cohort and each subtype defined by the status of hormone receptor and human epidermal growth factor receptor 2 (HR+/HER2-, HER2+, triple negative) were analyzed. Predictions were evaluated using the Cox proportional hazard model when PE(t) changed from 30% to 200% in steps of 10% and SER(t) changed from 0 to 2 in steps of 0.2. Predictions with high hazard ratios and low p-values were considered as strong. Different profiles of FTV as predictors for recurrence-free survival were observed in each breast cancer subtype and strong associations with survival were observed at different PE(t)/SER(t) combinations that resulted in different FTVs. Findings from this retrospective study suggest that the predictive performance of imaging markers based on FTV may be improved with enhancement thresholds being optimized separately for clinically-relevant subtypes defined by HR and HER2 receptor expression.