A priori prediction of breast tumour response to chemotherapy using quantitative ultrasound imaging and artificial neural networks.

ABSTRACT: We demonstrate the clinical utility of combining quantitative ultrasound (QUS) imaging of the breast with an artificial neural network (ANN) classifier to predict the response of breast cancer patients to neoadjuvant chemotherapy (NAC) administration prior to the start of treatment. Using a 6 MHz ultrasound system, radiofrequency (RF) ultrasound data were acquired from 100 patients with biopsy-confirmed locally advanced breast cancer prior to the start of NAC. Quantitative ultrasound mean parameter intensity and texture features were computed from the tumour core and margin, and were compared to the clinical/pathological response and 5-year recurrence-free survival (RFS) of patients. A multi-parametric QUS model in conjunction with an ANN classifier predicted patient response with 96 ± 6%

SUBMITTER: Tadayyon H 

PROVIDER: S-EPMC6570472 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature