Deep Learning and Radiomics predict complete response after neo-adjuvant chemoradiation for locally advanced rectal cancer.

ABSTRACT: Treatment of locally advanced rectal cancer involves chemoradiation, followed by total mesorectum excision. Complete response after chemoradiation is an accurate surrogate for long-term local control. Predicting complete response from pre-treatment features could represent a major step towards conservative treatment. Patients with a T2-4 N0-1 rectal adenocarcinoma treated between June 2010 and October 2016 with neo-adjuvant chemoradiation from three academic institutions were included. All clinical and treatment data was integrated in our clinical data warehouse, from which we extracted the features. Radiomics features were extracted from the tumor volume from the treatment planning CT Scan. A Deep Neural Network (DNN) was created to predict complete response, as a methodological proof-of-

SUBMITTER: Bibault JE 

PROVIDER: S-EPMC6105676 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature