Evidence map›Paper›PMID 40137571›Full record

ArticleTomography (Ann Arbor, Mich.)2025

Distinguishing Low Expression Levels of Human Epidermal Growth Factor Receptor 2 in Breast Cancer: Insights from Qualitative and Quantitative Magnetic Resonance Imaging Analysis.

Yiyuan Shen, Xu Zhang, Jinlong Zheng, Simin Wang, Jie Ding, Shiyun Sun, Qianming Bai, Caixia Fu, Junlong Wang, Jing Gong and 2 more

Abstract read
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 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

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

1 citing paper in PubMed.

  1. Review
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

12 authors.

Yiyuan ShenDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.
Xu ZhangDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.
Jinlong ZhengDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.
Simin WangDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.
Jie DingDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.
Shiyun SunDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.
Qianming BaiDepartment of Oncology, Shanghai Medical College, Fudan University, 270 Dongan Road, Shanghai 200032, China.
Caixia FuMR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen 518057, China.
Junlong WangDepartment of Nuclear Medicine, Insel Hospital, University of Bern, 3010 Bern, Switzerland.
Jing GongDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.
Chao YouDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.
Yajia GuDepartment of Radiology, Fudan University Shanghai Cancer Center, 270 Dongan Road, Shanghai 200032, China.

Funding

National Natural Science Foundation of China NO. 82071878 and NO. 82271957
6 · The paper itself

Abstract

backgroundThe discovery of novel antibody-drug conjugates for low-expression human epidermal growth factor receptor 2 (HER2-low) breast cancer highlights the inadequacy of the conventional binary classification of HER2 status as either negative or positive. Identification of HER2-low breast cancer is crucial for selecting patients who may benefit from targeted therapies. This study aims to determine whether qualitative and quantitative magnetic resonance imaging (MRI) features can effectively reflect low-HER2-expression breast cancer.

methodsPre-treatment breast MRI images from 232 patients with pathologically confirmed breast cancer were retrospectively analyzed. Both clinicopathologic and MRI features were recorded. Qualitative MRI features included Breast Imaging Reporting and Data System (BI-RADS) descriptors from dynamic contrast-enhanced MRI (DCE-MRI), as well as intratumoral T2 hyperintensity and peritumoral edema observed in T2-weighted imaging (T2WI). Quantitative features were derived from diffusion kurtosis imaging (DKI) using multiple b-values and included statistics such as mean, median, 5th and 95th percentiles, skewness, kurtosis, and entropy from apparent diffusion coefficient (ADC), D

resultsHER2 status was categorized as HER2-zero (n = 60), HER2-low (n = 91), and HER2-overexpressed (n = 81). Clinically, estrogen receptor (ER), progesterone receptor (PR), hormone receptor (HR), and Ki-67 levels significantly differed between the HER2-low group and others (all

conclusionsQualitative and quantitative MRI features offer valuable insights into low-HER2-expression breast cancer. While qualitative features are more effective for mass lesions, quantitative features are more suitable for NME lesions. These findings provide a more accessible and cost-effective approach to noninvasively identifying patients who may benefit from targeted therapy.

Indexed as

Breast NeoplasmsErb-b2 Receptor Tyrosine KinasesMagnetic Resonance ImagingAdultAgedAged, 80 and overBiomarkers, TumorBreastContrast MediaFemaleHumansMiddle AgedRetrospective StudiesBiomarkers, TumorContrast MediaERBB2 protein, humanErb-b2 Receptor Tyrosine Kinasesbreast cancerhuman epidermal growth factor receptor 2low HER2 expressionmagnetic resonance imaging

Identifiers

PMID40137571
PMCPMC11945706

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Registered trials

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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.