Prediction model of axillary lymph node status using an automated breast volume ultrasound radiomics nomogram in early breast cancer with negative axillary ultrasound.

ABSTRACT:

Background

Construction and validation of an automated breast volume ultrasound (ABVS)-based nomogram for assessing axillary lymph node (ALNs) metastasis in axillary ultrasound (AUS)-negative early breast cancer.

Methods

A retrospective study of 174 patients with AUS-negative early-stage breast cancer was divided into a training and test with a ratio of 7:3. Radiomics features were extracted by combining images of intra-tumor and peri-tumor ABVS. Select the best classifier from 3 machine learning techniques to build Model 1and radiomics-score (RS). Differences in ER, PR, Her-2, Ki-67 expression were analyzed for intra-tumoral and peri-tumoral habitat radiomics features. Model 2 (based on sonogram features) and Model 3 (based on RS and sonogram features) were constructed by m

SUBMITTER: Ma Q 

PROVIDER: S-EPMC11937125 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature