Pathologic response prediction to neoadjuvant chemotherapy utilizing pretreatment near-infrared imaging parameters and tumor pathologic criteria

Quing Zhu, Liqun Wang, Susan Tannenbaum, Andrew Ricci, Patricia DeFusco, Poornima Hegde

IntroductionThe purpose of this study is to develop a prediction model utilizing tumor hemoglobin parameters measured by ultrasound-guided near-infrared optical tomography (US-NIR), in conjunction with standard pathologic tumor characteristics to predict pathologic response before neoadjuvant chemotherapy (NAC) is given.MethodsThirty-four patients¿ data were retrospectively analyzed using a multiple logistic regression model to predict response. These patients were split into 30 groups of training (24 tumors) and testing (12 tumors) for cross validation. Tumor vascularity was assessed using US-NIR measurements of total hemoglobin (tHb), oxygenated and deoxygenated hemoglobin concentrations (oxyHb and deoxyHb) acquired before treatment. Tumor pathologic variables of tumor type, Nottingham score, mitotic index, the estrogen and progesterone receptors, and human epidermal growth factor receptor 2 acquired before NAC in biopsy specimens were also used in the prediction model. The patients¿ pathologic response was graded based on the Miller-Payne system. The overall performance of the prediction models was evaluated using Receiver Operating Characteristic (ROC) curves. The quantitative measures were sensitivity, specificity, positive and negative predictive values (PPV and NPV), and the area under the ROC curve (AUC).ResultsUtilizing tumor pathologic variables alone, an average sensitivity of 56.8%, specificity of 88.9%, PPV and NPV of 84.8% and 70.9%, and AUC of 84.0% were obtained from the testing data. Among the hemoglobin predictors with and without tumor pathological variables, the best predictor is tHb combined with tumor pathological variables followed by oxyHb with pathological variables. When tHb was included as an additional predictor to tumor pathological variables, the corresponding measures improved to 79%, 94%, 90%, 86%, and AUC 92.4%, respectively. When oxyHb was included as an additional predictor to tumor variables, these measures improved to 77%, 85%, 83%, 83%, and AUC 90.6%, respectively. The addition of tHb or oxyHb significantly improves the prediction sensitivity, NPV and AUC as compared with using tumor pathological variables alone.ConclusionsThese initial findings indicate that combining widely used tumor pathologic variables with hemoglobin parameters determined by US-NIR, may provide a powerful tool for predicting patient pathologic response to NAC before the initiation of the treatment.Trial registrationClincalTrials.gov, NCT00908609, registered 22 May 2009.