Evidence map›Paper›PMID 40597006›Full record

ArticleBMC medical imaging2025

Predict status of axillary lymph node after neoadjuvant chemotherapy with dual-energy CT in breast cancer.

Zhen Wang, Zhao-Qing Fan, Li-Ze Wang, Kun Cao, Rong Long, Yao Luo, Xiao-Ting Li, Liang You, Qing-Yang Li, Ying-Shi Sun

Abstract read
In one paragraph

Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

10 authors.

Zhen Wang *Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Zhao-Qing Fan *Breast Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Li-Ze Wang *Breast Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Kun CaoDepartment of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Rong LongDepartment of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Yao LuoDepartment of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Xiao-Ting LiDepartment of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Liang YouDepartment of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Qing-Yang LiDepartment of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China.
Ying-Shi SunDepartment of Radiology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital and Institute, No. 52 Fu Cheng Rd, Hai Dian District, Beijing, 100142, China. sys27@163.com.

Funding

National Key R&D Program of China 2023YFC3402805the Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of Inner Mongolia Academy of Medical Sciences 2023GLLH0122
6 · The paper itself

Abstract

backgroundA proportion of breast patients achieve axillary pathological complete response (pCR) following NAC. However, few studies have investigated the potential of quantitative parameters derived from dual-energy CT (DECT) for predicting axillary lymph node (ALN) downstaging after NAC.

methodsThis study included a prospective training and retrospective validation cohort from December 2019 to June 2022. Both groups enrolled invasive breast cancer with biopsy-proved metastatic ALNs who underwent contrast-enhanced DECT and NAC followed by surgery. A metastatic ALN, named target lymph node (TLN), was marked with metal clip at baseline. Quantitative DECT parameters and size of TLN, and clinical information were compared between pCR and non-pCR node group referring to postoperative pathology. Three predictive models, clinical, quantitative CT, and combinational models, were built by logistic regression and nomogram was drawn accordingly. The performance was evaluated by the receiver operator characteristic curve and clinical usefulness was assessed by decision curve analysis.

resultsA total of 75 and 53 patients were included in training and validation cohort respectively. Of them, 34 (45.3%) and 22 (41.5%) patients achieved nodal pCR in the two sets. Multivariable analyses revealed that negative estrogen receptor expression, parenchyma thickness and the iodine concentration of TLN at post-NAC CT were independently predictive factors for pCR. The combinational model showed discriminatory power than the single clinical model (AUC, 0.724; p = 0.003) and quantitative CT model (AUC, 0.728; p = 0.030) with AUC of 0.847 and 0.828 in training and validation cohort. It provided enhanced net benefits within a wide range of threshold probabilities.

conclusionQuantitative DECT parameters can be used to evaluate axillary nodal status after NAC and guide personalized treatment strategies.

Indexed as

Breast NeoplasmsLymphatic MetastasisLymph NodesNeoadjuvant TherapyTomography, X-Ray ComputedAdultAgedAxillaFemaleHumansMiddle AgedNomogramsProspective StudiesRadiography, Dual-Energy Scanned ProjectionRetrospective StudiesAxillary lymph nodeBreast cancerDual-energy CTNeoadjuvant chemotherapy

Identifiers

PMID40597006
PMCPMC12220156

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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.