Evidence map›Paper›PMID 42866467›Full record

ArticleGland surgery2026

Habitat-based ultrasound radiomics for preoperative prediction of axillary lymph node metastasis in breast cancer: a two-center study.

Zimeng Fang, Xiaoyu Yan, Yunyun Zhan, Yu Bi, Xiabi Wu, Mingdi Fang, Yufan Zhang, Jiajia Wang, Mei Peng

Abstract read
In one paragraph

Article in Gland surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Zimeng FangDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Xiaoyu YanDepartment of Ultrasound Medicine, Taihe County People's Hospital, Fuyang, China.
Yunyun ZhanDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Yu BiDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Xiabi WuDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Mingdi FangDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Yufan ZhangDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Jiajia WangDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Mei PengDepartment of Ultrasound Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accurate preoperative prediction of axillary lymph node metastasis (ALNM) remains challenging. This study investigates whether habitat-based ultrasound radiomics of suspicious axillary lymph nodes can predict preoperative ALNM in patients with breast cancer. Methods: This retrospective two-center study included 416 breast cancer patients with suspicious axillary lymph nodes and pathologically confirmed nodal status. Patients from the Second Affiliated Hospital of Anhui Medical University were randomly assigned to the training and internal validation cohorts at a ratio of 7:3, whereas patients from Taihe County People's Hospital constituted the external test cohort. Suspicious lymph nodes were manually segmented. Pixel-level features were clustered using the K-means algorithm to divide each node into four habitat subregions. Radiomics features were extracted from the intranodal region of interest and each habitat subregion to construct the intranodal radiomics, individual habitat, and habitat radiomics models. A combined nomogram integrating the optimal radiomics signature with independent clinical predictors was developed. Results: Cortical thickness and lymph node vascular pattern were independent predictors of ALNM. The habitat radiomics model outperformed the intranodal radiomics and individual habitat models, with areas under the receiver operating characteristic curve (AUCs) of 0.859, 0.809, and 0.791 in the training, internal validation, and external test cohorts, respectively. The combined nomogram achieved the highest AUCs of 0.866, 0.819, and 0.806 in the corresponding cohorts, and its clinical utility was confirmed by decision curve analysis. Conclusions: Habitat-based ultrasound radiomics improved ALNM prediction by capturing intranodal heterogeneity. The nomogram may provide a practical noninvasive tool for individualized preoperative assessment of suspicious axillary lymph nodes.

Indexed as

axillary lymph node metastasis (ALNM)Breast cancerhabitat analysisnomogramultrasound radiomics

Identifiers

PMID42866467
PMCPMC13657774

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.