Predicting breast cancer response to neoadjuvant chemotherapy using pretreatment diffuse optical spectroscopic texture analysis.
作者信息
Tran William T, Gangeh Mehrdad J, Sannachi Lakshmanan, Chin Lee, Watkins Elyse, Bruni Silvio G, Rastegar Rashin Fallah, Curpen Belinda, Trudeau Maureen, Gandhi Sonal, Yaffe Martin, Slodkowska Elzbieta, Childs Charmaine, Sadeghi-Naini Ali, Czarnota Gregory J
机构信息
Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada.
Centre for Health and Social Care Research, Sheffield Hallam University, 32 Collegiate Crescent, Sheffield S10 2BP, UK.
出版信息
Br J Cancer. 2017 May 9;116(10):1329-1339. doi: 10.1038/bjc.2017.97. Epub 2017 Apr 18.
BACKGROUND
Diffuse optical spectroscopy (DOS) has been demonstrated capable of monitoring response to neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC) patients. In this study, we evaluate texture features of pretreatment DOS functional maps for predicting LABC response to NAC.
METHODS
Locally advanced breast cancer patients (n=37) underwent DOS breast imaging before starting NAC. Breast tissue parametric maps were constructed and texture analyses were performed based on grey-level co-occurrence matrices for feature extraction. Ground truth labels as responders (R) or non-responders (NR) were assigned to patients based on Miller-Payne pathological response criteria. The capability of DOS textural features computed on volumetric tumour data before the start of treatment (i.e., 'pretreatment') to predict patient responses to NAC was evaluated using a leave-one-out validation scheme at subject level. Data were analysed using a logistic regression, naive Bayes, and k-nearest neighbour classifiers.
RESULTS
Data indicated that textural characteristics of pretreatment DOS parametric maps can differentiate between treatment response outcomes. The HbO homogeneity resulted in the highest accuracy among univariate parameters in predicting response to chemotherapy: sensitivity (%Sn) and specificity (%Sp) were 86.5% and 89.0%, respectively, and accuracy was 87.8%. The highest predictors using multivariate (binary) combination features were the Hb-contrast+HbO-homogeneity, which resulted in a %Sn/%Sp=78.0/81.0% and an accuracy of 79.5%.
CONCLUSIONS
This study demonstrated that the pretreatment DOS texture features can predict breast cancer response to NAC and potentially guide treatments.
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