Evidence map›Paper›PMID 41988124›Full record

ArticleFrontiers in oncology2026

Multiparametric MRI-based radiomics of whole-tumor and habitat regions for predicting HER2 status in young breast cancer: a two-center study.

Xiaobin Jiang, Darong Zhu, Xumeng Luo, Siqing Fang, Nianshi Song, Qian Yu, Sicong Huang, Shiwei Wang

Abstract read
In one paragraph

Article in Frontiers in oncology, 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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1 · What the graph read from it

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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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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Xiaobin Jiang *Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, Zhejiang, China.
Darong Zhu *Department of Radiology, Hangzhou First People's Hospital, Hangzhou, Zhejiang, China.
Xumeng LuoThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Siqing FangThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Nianshi SongDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, Zhejiang, China.
Qian YuDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, Zhejiang, China.
Sicong HuangClinical Science, Philips Healthcare, Beijing, China.
Shiwei WangDepartment of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Habitat imaging can quantify intratumoral heterogeneity in young breast cancer patients, providing support for the prediction of HER2 expression levels. Therefore, this study aimed to compare the predictive ability of habitat models and conventional whole-tumor models for HER2 expression status in young breast cancer patients using multiparametric MRI. Methods: A retrospective cohort consisting of 375 young breast cancer patients (age < 40 years) who underwent preoperative MRI scanning at two medical centers was included in this study. Two binary classification tasks were designed: Task 1 (HER2 negative expression vs. HER2 positive expression) and Task 2 (HER2 zero expression vs. HER2 low expression). The training cohort (n=206) comprised patients from Center 1, with the external validation cohort (n=169) recruited from Center 2. Clinicopathological and MRI characteristics were collected. Radiomics features based on whole-tumor and habitat regions were extracted from DCE-MRI and DWI images, respectively. Clinical models, conventional whole-tumor models, habitat models, and combined models were constructed. Subsequently, model performance was evaluated by the AUC, sensitivity, and specificity. Results: In Task 1, the AUC of the clinical model, conventional whole-tumor model, habitat model, and combined model in the training cohort were 0.683, 0.731, 0.761, and 0.768 respectively. In Task 2, no clinicopathological features were determined as independent risk factors, thus no clinical model was developed. The AUC for the whole-tumor model, habitat model, and combined model in the training cohort were 0.673, 0.649, and 0.758 respectively. Conclusion: The habitat model exhibited better discriminatory effectiveness in identifying HER2 positive expression in young breast cancer patients, in comparison to the whole-tumor radiomics model. The integration of conventional whole-tumor radiomics features with habitat features and clinicopathological characteristics can enhance model performance.

Indexed as

breast cancerhabitatHER2multiparametric magnetic resonance imagingradiomicsyoung

Identifiers

PMID41988124
PMCPMC13076129

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