基于MRI放射学预测乳腺癌隐匿前哨淋巴结转移和D2-40表达。

IF 2.8 4区 医学 Q3 ONCOLOGY
Technology in Cancer Research & Treatment Pub Date : 2025-01-01 Epub Date: 2025-10-15 DOI:10.1177/15330338251386676
Mingming Chen, Chen Wang, Qiyue Zhang, Zhongyuan Li, Peiji Song, Aimei Ouyang
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引用次数: 0

摘要

摘要磁共振成像(MRI)腋窝淋巴结(ALN)阴性的乳腺癌患者仍可能存在隐匿前哨淋巴结(SLN)转移,这可能影响临床治疗策略。本研究旨在建立一种基于mri的放射组学模型,用于预测隐匿性SLN转移和D2-40表达,并探讨D2-40表达、SLN状态和相关放射组学特征之间的内在联系。方法回顾性研究纳入141例mri诊断为aln阴性的乳腺癌患者,随机分为训练组(n = 98)和验证组(n = 43),比例为7:3。从中心1 + 2建立独立的外部验证队列(n = 40)进行模型验证。建立了三个逻辑回归模型:(1)临床模型,(2)放射组学模型,(3)临床-放射组学nomogram预测SLN转移(模型1)和D2-40表达(模型2)。此外,本研究采用卡方检验分析D2-40表达与SLN状态的相关性。并分别采用Spearman和Pearson相关分析评估SLN放射组学模型与D2-40放射组学模型的特征相关性以及D2-40与模型1特征的关联强度。结果模型1 (AUC: 0.821验证/0.746外部)和模型2 (AUC: 0.810验证/0.645外部)的nomogram均优于其他模型。D2-40与SLN状态相关(P
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MRI Radiomics-Based Prediction of Occult Sentinel Lymph Node Metastasis and D2-40 Expression in Breast Cancer.

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 (P < .001). There were feature correlations between Model 1 and Model 2 features (Spearman) and between D2-40 and Model 1 features (Pearson).ConclusionsMRI-based radiomics features were effective in predicting occult SLN metastasis and D2-40 expression status in MRI ALN-negative breast cancers. An association was identified between D2-40 expression and SLN status, along with the corresponding radiomics features.

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来源期刊
CiteScore
4.40
自引率
0.00%
发文量
202
审稿时长
2 months
期刊介绍: Technology in Cancer Research & Treatment (TCRT) is a JCR-ranked, broad-spectrum, open access, peer-reviewed publication whose aim is to provide researchers and clinicians with a platform to share and discuss developments in the prevention, diagnosis, treatment, and monitoring of cancer.
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