Evidence map›Paper›PMID 41091808›Full record

ArticleTechnology in cancer research & treatment

MRI Radiomics-Based Prediction of Occult Sentinel Lymph Node Metastasis and D2-40 Expression in Breast Cancer.

Mingming Chen, Chen Wang, Qiyue Zhang, Zhongyuan Li, Peiji Song, Aimei Ouyang

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Article in Technology in cancer research & treatment. 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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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

6 authors.

Mingming ChenSchool of Medical Imaging, Shandong Second Medical University, Weifang, Shandong, P.R.China.ORCID 0009-0001-0808-6182
Chen WangDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R.China.ORCID 0009-0006-7482-4987
Qiyue ZhangShandong First Medical University, Jinan, Shandong, P.R.China.ORCID 0009-0007-7240-9373
Zhongyuan LiSchool of Medical Imaging, Shandong Second Medical University, Weifang, Shandong, P.R.China.ORCID 0000-0001-5470-7149
Peiji SongDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R.China.ORCID 0000-0001-8384-0264
Aimei OuyangDepartment of Radiology, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R.China.ORCID 0000-0002-2318-8654

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionPatients with Magnetic Resonance Imaging (MRI) axillary lymph node (ALN) negative in breast cancer may still have occult sentinel lymph node (SLN) metastases, which can influence clinical treatment strategies. This study aimed to develop an MRI-based radiomics model for predicting occult SLN metastases and D2-40 expression, and to investigate the intrinsic associations between D2-40 expression, SLN status, and related radiomics features.MethodsThis retrospective study included 141 MRI-diagnosed ALN-negative breast cancer patients from Center 1, randomly divided into training (n = 98) and validation (n = 43) sets (7:3 ratio). An independent external validation cohort (n = 40) from Centers 1 + 2 was established for model validation. Three logistic regression models were developed: (1) a clinical model, (2) a radiomics model, and (3) a clinic-radiomics nomogram, which predict SLN metastasis (Model 1) and D2-40 expression (Model 2). In addition, the correlation between D2-40 expression and SLN status was analyzed in this study using chi-square test. And the feature correlation between SLN radiomics model and D2-40 radiomics model and the strength of association between D2-40 and Model 1 features were assessed by Spearman and Pearson correlation analysis, respectively.ResultsThe nomogram outperformed the other models in both Model 1 (AUC: 0.821 validation/0.746 external) and Model 2 (AUC: 0.810 validation/0.645 external). D2-40 correlated with SLN status (

Indexed as

Breast NeoplasmsMagnetic Resonance ImagingSentinel Lymph NodeAdultAgedAntibodies, Monoclonal, Murine-DerivedFemaleHumansLymphatic MetastasisMiddle AgedNomogramsRadiomicsRetrospective StudiesROC CurveSentinel Lymph Node BiopsyAntibodies, Monoclonal, Murine-Derivedmonoclonal antibody D2-40breast cancerD2-40DCE-MRIradiomicssentinel lymph node

Identifiers

PMID41091808
PMCPMC12536181

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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.