Evidence map›Paper›PMID 42098848›Full record

ArticleBreast cancer research : BCR2026

Multimodal radiomics incorporating intratumoral heterogeneity for prognostic assessment of metastatic outcomes in invasive breast cancer.

Liwei Sun, Zhengtong Wang, Weizhi Zhang, Yunfei Yang, Pei Nie, Wenjian Xu

Abstract readValidation Study
In one paragraph

Article in Breast cancer research : BCR, 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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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Liwei SunDepartment of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266001, China.
Zhengtong WangDepartment of Radiology, The Affiliated Hospital of Jining Medical University, Jining, 272000, China.
Weizhi ZhangDepartment of Hepatic Surgery, Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
Yunfei YangDepartment of Radiology, The First Affiliated Hospital of Shandong First Medical University, Jinan, 250000, China.
Pei Nie *Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266001, China. niepei@qdu.edu.cn.
Wenjian Xu *Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, 266001, China. wjxu2021@qdu.edu.cn.

Funding

Taishan Scholar Foundation of Shandong Province tsqn202408392the National Natural Science Foundation of China 81671658the Natural Science Foundation of Qingdao City 25-1-1-238-zyyd-jch
6 · The paper itself

Abstract

objectiveThis study aimed to develop prognostic models of distant metastasis (DM) and bone metastasis (BM) in invasive breast cancer (IBC) incorporating whole-tumor radiomics, intratumoral heterogeneity (ITH) metrics.

methodsA total of 1097 patients with IBC from three centers were included and divided into a training cohort (n = 610), a validation cohort (n = 153), and two independent testing cohorts (n = 170 and n = 164). Whole-tumor radiomic features were extracted from two-dimensional regions of interest (ROIs) on mammography and three-dimensional ROIs on the second post-contrast phase of dynamic contrast-enhanced MRI, while ITH metrics were derived from enhancement-based subregions. Predictive performance was assessed for each model, and the resulting risk scores were further used for risk stratification analyses. SHapley Additive exPlanations (SHAP) were used to assess the importance of individual ITH metrics and to quantify the contributions of each component within the combined model.

resultsThe combined model achieved the highest concordance index and robust risk stratification performance for both DM and BM. SHAP analysis indicated that the radiomics-based risk score ranked as the most influential predictor across both endpoints, while the ITH score consistently showed higher relative importance for BM than for DM. Distance-, shape-, and topology-related ITH metrics were among the most influential contributors across both endpoints.

conclusionThe combined model demonstrated robust prognostic performance, and the differential contribution of the ITH score between DM and BM indicates a more prominent role of imaging-derived heterogeneity in BM.

Indexed as

Bone NeoplasmsBreast NeoplasmsRadiomicsAdultDynamic Contrast Enhanced Magnetic Resonance ImagingFemaleFollow-Up StudiesHumansImage Processing, Computer-AssistedMammographyMiddle AgedNeoplasm InvasivenessPrognosisRetrospective StudiesRisk AssessmentBone metastasisDistant metastasisInvasive breast cancerITHMultimodalRadiomics

Identifiers

PMID42098848
PMCPMC13330097

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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.