Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma.

ABSTRACT:

Objective

To build and validate a CT radiomic model for pre-operatively predicting lymph node metastasis in early cervical carcinoma.

Methods and materials

A data set of 150 patients with Stage IB1 to IIA2 cervical carcinoma was retrospectively collected from the Nanfang hospital and separated into a training cohort (n = 104) and test cohort (n = 46). A total of 348 radiomic features were extracted from the delay phase of CT images. Mann-Whitney U test, recursive feature elimination, and backward elimination were used to select key radiomic features. Ridge logistics regression was used to build a radiomic model for prediction of lymph node metastasis (LNM) status by combining radiomic and clinical features. The area under the receiver operating character

SUBMITTER: Chen J 

PROVIDER: S-EPMC7362918 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature