Clinical-Deep Neural Network and Clinical-Radiomics Nomograms for Predicting the Intraoperative Massive Blood Loss of Pelvic and Sacral Tumors.

ABSTRACT:

Background

Patients with pelvic and sacral tumors are prone to massive blood loss (MBL) during surgery, which may endanger their lives.

Purposes

This study aimed to determine the feasibility of using deep neural network (DNN) and radiomics nomogram (RN) based on 3D computed tomography (CT) features and clinical characteristics to predict the intraoperative MBL of pelvic and sacral tumors.

Materials and methods

This single-center retrospective analysis included 810 patients with pelvic and sacral tumors. 1316 CT and CT enhanced radiomics features were extracted. RN1 and RN2 were constructed by random grouping and time node grouping, respectively. The DNN models were constructed for comparison with RN. Clinical factors associated with the MBL were also evaluated. The ar

SUBMITTER: Yin P 

PROVIDER: S-EPMC8574215 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature