Evidence map›Paper›PMID 40891579›Full record

ArticleCancer medicine2025

Prediction of HER2-Low Breast Cancer via Multimodal Ultrasound Imaging.

Feihang Dai, Baoliang Guo, Xin Ai, Dandan Liu, Longbin Dai, Chengzhi Zhang, Xiaoping Leng, Tong Wu

Abstract read
In one paragraph

Article in Cancer medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Feihang DaiDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.ORCID https://orcid.org/0009-0006-4398-7716
Baoliang GuoDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Xin AiDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Dandan LiuDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Longbin DaiDepartment of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China.
Chengzhi ZhangDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Xiaoping LengDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.
Tong WuDepartment of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, People's Republic of China.ORCID https://orcid.org/0009-0004-8839-8902

Funding

National Natural Science Foundation of China 81901761Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province LBH-Q20124
6 · The paper itself

Abstract

purposeHuman epidermal growth factor receptor 2 (HER2) is a key biomarker for clinical management and prognostic evaluation of breast cancer patients. This study was aimed at assisting the preoperative and non-invasive prediction of HER2-low breast cancer using multimodal ultrasound imaging and clinicopathological indicators, providing valuable imaging information for clinical precision diagnosis and personalized treatment strategies, especially in the application of antibody-drug conjugates such as T-DXd. MATERIALS AND

methodsThis retrospective study included 147 pathologically confirmed breast cancer patients from two institutions: 101 in the training set and 46 in the external validation set. All patients underwent multimodal ultrasound (grayscale, color Doppler, elastography, and contrast-enhanced imaging) and had complete clinicopathological data. Patients were categorized as HER2-negative, HER2-low, or HER2-positive based on immunohistochemistry. Logistic regression was used to construct predictive models.

resultsCompared with the HER2-negative group, low Ki-67, PR positivity, longer rise time (RT), and lower Emax values were independent predictors of HER2-low status (p < 0.05), yielding an AUC of 0.876, sensitivity 0.833, and specificity 0.781. Compared with HER2-positive cancers, HER2-low cases showed low Ki-67, ER/PR positivity, low Emax, and a DVPC pattern characterized by an initial increase followed by a subsequent decline as independent predictors (p < 0.05), with an AUC of 0.929, sensitivity 0.905, and specificity 0.856. External validation confirmed robust model performance (AUC = 0.925 and 0.918 for HER2-low vs. negative and positive, respectively).

conclusionA model integrating multimodal ultrasound and clinicopathological factors effectively predicts HER2-low breast cancer, offering valuable imaging-based support for clinical decision-making.

Indexed as

Breast NeoplasmsErb-b2 Receptor Tyrosine KinasesMultimodal ImagingUltrasonography, MammaryAdultAgedBiomarkers, TumorFemaleHumansMiddle AgedPrognosisRetrospective StudiesBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine Kinasesbreast cancercontrast‐enhanced ultrasoundHER‐2 low expressionmultimodal ultrasound

Identifiers

PMID40891579
PMCPMC12403018

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