Evidence map›Paper›PMID 42682338›Full record

ArticleInternational journal of surgery (London, England)2026

Noninvasive stratification of HER2 status in breast cancer using multiparametric DECT: a prospective cohort study.

Huifang Chen, Yao Huang, Xiangfei Zeng, Ying Cao, Xueqin Gong, Sun Tang, Lu Wang, Lan Li, Tao Yu, Yue Cheng and 2 more

Abstract read
In one paragraph

Article in International journal of surgery (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Huifang ChenDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Yao HuangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Xiangfei ZengDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Ying CaoDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Xueqin GongDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Sun TangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Lu WangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Lan LiDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Tao YuDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Yue ChengDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Xiaoxia WangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.
Jiuquan ZhangDepartment of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing, China.ORCID https://orcid.org/0000-0003-0239-6988

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: HER2 heterogeneity in breast cancer requires precise stratification for treatment guidance. Differences in dual-energy computed tomography (DECT)-derived parameters among HER2-zero, HER2-low, and HER2-positive breast cancers remain unknown. We aimed to evaluate the performance of DECT-based quantitative parameters to distinguish HER2-zero, HER2-low, and HER2-positive expression status in breast cancer, and to compare the efficacy between DECT-predicted HER2 status and pathological HER2 status in predicting pathologic complete response (pCR). Methods: A total of 469 breast cancer patients who underwent chest DECT for staging (November 2020-May 2023) were prospectively recruited. DECT quantitative parameters, such as the normalized iodine concentration (NIC), the normalized effective atomic number (nZeff), the slope of the spectral Hounsfield unit curve (λHu), and polyenergetic images (PEI), were obtained from reconstructed images. Decision tree models were constructed to classify the HER2-zero, HER2-low, and HER2-positive status based on six DECT parameters. These models were tested for performance using the area under the receiver operating characteristic curve (AUC) in training ( Results: Statistical analysis revealed significant differences in arterial and venous phase NIC, ΔNIC, venous phase λHu, ΔλHu, and venous phase PEI (HU) among HER2 subtypes (all Conclusions: DECT-based quantitative parameters enable noninvasive stratification of HER2-zero, HER2-low, and HER2-positive breast cancers. Additionally, HER2 predicted by DECT outperformed conventional pathological HER2 status in predicting pCR in patients undergoing neoadjuvant chemotherapy.

Indexed as

breast imagingHER2-lowmultiparametric dual-energy computed tomographyneoadjuvant chemotherapypathologic complete responseprospective cohort study

Identifiers

PMID42682338
PMCPMC13249338

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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.