Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast cancer.

ABSTRACT:

Background

To investigate quantitative ultrasound (QUS) based higher-order texture derivatives in predicting the response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC).

Materials and methods

100 Patients with LABC were scanned before starting NAC. Five QUS parametric image-types were generated from radio-frequency data over the tumor volume. From each QUS parametric-image, 4 grey level co-occurrence matrix-based texture images were derived (20 QUS-Tex¹), which were further processed to create texture derivatives (80 QUS-Tex¹-Tex²). Patients were classified into responders and non-responders based on clinical/pathological responses to treatment. Three machine learning algorithms based on linear discri

SUBMITTER: Dasgupta A 

PROVIDER: S-EPMC7584238 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature