Impact of contrast-enhanced ultrasound optimized breast imaging reporting and data system category on the biopsy decision for non-mass breast lesions

The CEUS-optimized BI-RADS category prediction model could provide valuable guidance for biopsy decision-making in NMLs.

Authors

Institutions

Publication Details

Journal
Frontiers in Oncology
Published
2026-02-23
DOI
https://doi.org/10.3389/fonc.2026.1731762
Primary Topic
Breast Lesions and Carcinomas
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of contrast-enhanced ultrasound optimized breast imaging reporting and data system category on the biopsy decision for non-mass breast lesions

Xuexue Chen, Mengyuan Fang, Bing Ling, Lei Li et al.
Frontiers in Oncology
Breast Lesions and Carcinomas
article

Impact of contrast-enhanced ultrasound optimized breast imaging reporting and data system category on the biopsy decision for non-mass breast lesions

Xuexue Chen, Mengyuan Fang, Bing Ling, Lei Li, Huajie Pei, Yingying He, Liu Wei, Qiao Hu, Haimei Lun, Bing Zhang
article en

Abstract

The CEUS-optimized BI-RADS category prediction model could provide valuable guidance for biopsy decision-making in NMLs.

Frontiers in OncologyVol. 16
The People's Hospital of Guangxi Zhuang Autonomous Region (CN), Changsha Hospital for Maternal and Child Health Care (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province, Guangxi Key Research and Development Program
Peace, Justice and strong institutions
Openalex Percentile: Top 48%
Breast Lesions and Carcinomas
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.