Radiomics in predicting recurrence for patients with locally advanced breast cancer using quantitative ultrasound.

ABSTRACT:

Background

The purpose of the study was to investigate the role of pre-treatment quantitative ultrasound (QUS)-radiomics in predicting recurrence for patients with locally advanced breast cancer (LABC).

Materials and methods

A prospective study was conducted in patients with LABC (n = 83). Primary tumours were scanned using a clinical ultrasound device before starting treatment. Ninety-five imaging features were extracted-spectral features, texture, and texture-derivatives. Patients were determined to have recurrence or no recurrence based on clinical outcomes. Machine learning classifiers with k-nearest neighbour (KNN) and support vector machine (SVM) were evaluated for model development using a maximum of 3 features and leave-one-out cross-validation.

Results

SUBMITTER: Dasgupta A 

PROVIDER: S-EPMC8664392 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature