MRI radiomics and biological correlations for predicting axillary lymph node burden in early-stage breast cancer

The MRI radiomics model effectively predicted the ALN burden and prognosis of early-stage breast cancer. Moreover, radiogenomic analysis revealed key cellular and immune patterns associated with the radscore.

Authors

Institutions

Publication Details

Journal
Journal of Translational Medicine
Published
2024-09-06
DOI
https://doi.org/10.1186/s12967-024-05619-4
Citations
18
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
7.28

Funders

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

MRI radiomics and biological correlations for predicting axillary lymph node burden in early-stage breast cancer

Maosheng Xu, Zhong‐Hua Chen, Minping Hong, Sijia Fan et al.
18 citations
Journal of Translational Medicine
Radiomics and Machine Learning in Medical Imaging
7.28
article

MRI radiomics and biological correlations for predicting axillary lymph node burden in early-stage breast cancer

Maosheng Xu, Zhong‐Hua Chen, Minping Hong, Sijia Fan, Jie Hou, Xiaobo Chen, Junyan Wang, Changyu Zhou, Yanqi Huang, Chaokang Han, Zeyan Xu, Yanting Liang, Zhen Fang, Keng Ling, P H Lai
article en
18 citations

Abstract

The MRI radiomics model effectively predicted the ALN burden and prognosis of early-stage breast cancer. Moreover, radiogenomic analysis revealed key cellular and immune patterns associated with the radscore.

Journal of Translational MedicineVol. 22(1)
Zhejiang Chinese Medical University (CN), Kunming Medical University (CN), Jiaxing University (CN), Zhejiang Provincial People's Hospital (CN), First Hospital of Jiaxing (CN), Guangdong Academy of Medical Sciences (CN), First People's Hospital of Nanning (CN), Guangdong Provincial People's Hospital (CN), First Affiliated Hospital Zhejiang University (CN), Southern Medical University (CN)
Natural Science Foundation of Guangdong Province, Science and Technology Bureau of Jiaxing City, Zhejiang Traditional Chinese Medicine Administration, Natural Science Foundation of Guangdong Province for Distinguished Young Scholars, Medical Science and Technology Project of Zhejiang Province, Science and Technology Program of Zhejiang Province, Zhejiang Provincial Outstanding Youth Science Foundation
Good health and well-being
Openalex Percentile: Top 2%
Radiomics and Machine Learning in Medical Imaging
7.28
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.