New research article: ‘Radiomics for predicting response to neoadjuvant chemotherapy treatment in breast cancer’
Women who are diagnosed with breast cancer are referred to Neoadjuvant Chemotherapy Treatment (NACT) before surgery when treatment guidelines indicate that. Achieving complete response in this treatment is associated with improved overall survival compared with those experiencing a partial or no response at all.
In this paper conducted by researchers from IBM Research – Haifa, Institut Curie and VTT Technical Research Centre, the authors explore different clinical and medical imaging features to create effective prediction models in order to assess in advance pathologic complete response to NACT.
The study uses dataset that consists of a cohort from Institut Curie with 1383 patients; from which 528 patients have mammogram imaging. The data are analysed via image processing, machine learning and deep learning algorithms.
The research shows that for the study cohort, the overall model achieves sensitivity 0.954 while keeping good specificity of 0.222. This means that almost all patients that achieved pathologic complete response will also be correctly classified by the model. At the same time, for 22% of the patients, the model could correctly predict in advance that they won’t achieve pathologic complete response, enabling them to reassess in advance this treatment.
The paper ‘Radiomics for predicting response to neoadjuvant chemotherapy treatment in breast cancer‘ has been published in Proceedings of SPIE Medical Imaging Access. Access the study here.