Evidence map›Paper›PMID 42163138›Full record

ArticleBMC medical imaging2026

Therapy-induced tumor regression heterogeneity for early prediction of response and prognosis in HER2-positive breast cancer.

Zewen Liu, Qin Li, Juntao Zhang, Xiaomei Jiang, Xiqing Wu, Haitong Yu, Shasha Wu, Chengsheng Li, Ying Chen, Peng Dong and 1 more

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In one paragraph

Article in BMC medical imaging, 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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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Zewen Liu *College of Medical Imaging, Shandong Second Medical University, Weifang, China.
Qin Li *Department of Medical Imaging Center, Weifang Hospital of Traditional Chinese Medicine, Weifang, China.
Juntao Zhang *Department of Medical Affairs, Pharmaceutical Diagnostics, GE Healthcare, Shanghai, China.
Xiaomei JiangNursing Department, Weifang Hospital of Traditional Chinese Medicine, Weifang, China.
Xiqing WuDepartment of Medical Imaging Center, Weifang Hospital of Traditional Chinese Medicine, Weifang, China.
Haitong YuDepartment of Medical Imaging Center, Weifang Hospital of Traditional Chinese Medicine, Weifang, China.
Shasha WuDepartment of Medical Imaging Center, Weifang Hospital of Traditional Chinese Medicine, Weifang, China.
Chengsheng LiCollege of Medical Imaging, Shandong Second Medical University, Weifang, China.
Ying ChenThe First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China.
Peng DongCollege of Medical Imaging, Shandong Second Medical University, Weifang, China. dongpeng@sdsmu.edu.cn.
Qingliang NiuDepartment of Medical Imaging Center, Weifang Hospital of Traditional Chinese Medicine, Weifang, China. qingliangniu@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly prediction of pathologic complete response (pCR) during neoadjuvant chemotherapy (NAC) in HER2-positive breast cancer remains challenging using conventional whole-tumor imaging approaches, particularly when substantial tumor shrinkage occurs on mid-NAC MRI (acquired after two cycles of NAC).

methodsThis retrospective study included 163 patients with HER2-positive breast cancer who underwent dynamic contrast-enhanced MRI at pre-NAC and mid-NAC. A therapy-induced tumor regression region (TRR) was defined as the regressed tumor volume between pre- and mid-NAC MRI. Tumor regression heterogeneity (TRH) was quantified within this region using a habitat-based radiomic approach. Logistic regression models were constructed and evaluated in training (n = 115) and validation (n = 48) cohorts.

resultspCR was achieved in 71 patients (43.6%). The TRH model demonstrated superior predictive performance compared with pre-NAC, mid-NAC, tumor regression region-based, and delta models, achieving an AUC of 0.83 (95% CI: 0.70-0.97) in the validation cohort. An integrated nomogram combining TRH with clinicopathologic factors further improved predictive performance.

conclusionsQuantification of spatial heterogeneity within therapy-induced tumor regression regions on mid-NAC MRI may enable improved prediction of treatment response during neoadjuvant therapy.

Indexed as

Breast NeoplasmsAdultAgedChemotherapy, AdjuvantDynamic Contrast Enhanced Magnetic Resonance ImagingErb-b2 Receptor Tyrosine KinasesFemaleHumansMagnetic Resonance ImagingMiddle AgedNeoadjuvant TherapyPathologic Complete ResponsePrognosisRadiomicsRetrospective StudiesTreatment Effect HeterogeneityERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesBreast cancerHuman epidermal growth factor receptor 2Magnetic resonance imagingNeoadjuvant therapyPathologic complete response

Identifiers

PMID42163138
PMCPMC13366909

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