Habitat imaging with intratumoral radiomics for prediction of axillary response after neoadjuvant chemotherapy in breast cancer patients.

IF 3.9 3区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Frontiers in Molecular Biosciences Pub Date : 2025-10-01 eCollection Date: 2025-01-01 DOI:10.3389/fmolb.2025.1684809
Xiaomeng Ji, Bingxin Zhao, Yan Mao, Meng Lv, Yongmei Wang, Xiaohui Su, Zaixian Zhang, Jie Wu, Qi Wang
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引用次数: 0

Abstract

Rationale and objectives: Breast cancer remains a leading cause of cancer-related morbidity and mortality globally. This study aimed to develop and validate predictive models for ALN pCR following NAC in breast cancer patients.

Materials and methods: We conducted a retrospective analysis involving 189 patients who were diagnosed with primary breast cancer at the Affiliated Hospital of Qingdao University. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was utilized to assess the characteristics of the tumors. Tumor segmentation was performed using itk-SNAP software, followed by voxel clustering to identify distinct habitat-derived regions. Logistic regression (LR) and multilayer perceptron (MLP) models were constructed using these features.

Results: The classification model incorporating with habitat-based radiomic features demonstrating superior predictive performance (AUC of 0.88 in training and 0.81 in test for LR). A clinicopathologic signature that includes factors such as age, hormone receptor status, the Ki-67 index, and clinical stage was established, achieving in an AUC of 0.81. To construct a nomogram, we integrated habitat-derived radiomic signature with clinicopathologic signature. This nomogram attained an AUC of 0.92 for the training cohort and 0.89 for the test cohort. Furthermore, calibration and decision curve analyses confirmed the nomogram's reliability and practical applicability in clinical settings.

Conclusion: In summary, our results indicate that radiomic features extracted from pre-NAC DCE-MRI can improve the predictive accuracy for ALN pCR following NAC in individuals diagnosed with breast cancer. This finding highlights the promise of personalized treatment strategies for individual patients.

肿瘤内放射组学用于预测乳腺癌患者新辅助化疗后腋窝反应的栖息地成像。
理由和目的:乳腺癌仍然是全球癌症相关发病率和死亡率的主要原因。本研究旨在建立和验证乳腺癌患者NAC后ALN pCR的预测模型。材料与方法:我们对青岛大学附属医院189例确诊为原发性乳腺癌的患者进行回顾性分析。采用动态对比增强磁共振成像(DCE-MRI)评估肿瘤特征。使用itk-SNAP软件进行肿瘤分割,然后进行体素聚类以识别不同的生境衍生区域。利用这些特征构建了逻辑回归(LR)和多层感知器(MLP)模型。结果:结合栖息地放射学特征的分类模型具有较好的预测性能(训练AUC为0.88,LR测试AUC为0.81)。建立了包括年龄、激素受体状态、Ki-67指数和临床分期等因素在内的临床病理特征,AUC为0.81。为了构建nomogram,我们将居住地放射学特征与临床病理特征结合起来。训练组和测试组的nomogram AUC分别为0.92和0.89。此外,校正和决策曲线分析证实了nomogram在临床环境中的可靠性和实用性。结论:总之,我们的研究结果表明,从NAC前的DCE-MRI中提取的放射学特征可以提高诊断为乳腺癌的个体NAC后ALN pCR的预测准确性。这一发现强调了针对个别患者的个性化治疗策略的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Molecular Biosciences
Frontiers in Molecular Biosciences Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
7.20
自引率
4.00%
发文量
1361
审稿时长
14 weeks
期刊介绍: Much of contemporary investigation in the life sciences is devoted to the molecular-scale understanding of the relationships between genes and the environment — in particular, dynamic alterations in the levels, modifications, and interactions of cellular effectors, including proteins. Frontiers in Molecular Biosciences offers an international publication platform for basic as well as applied research; we encourage contributions spanning both established and emerging areas of biology. To this end, the journal draws from empirical disciplines such as structural biology, enzymology, biochemistry, and biophysics, capitalizing as well on the technological advancements that have enabled metabolomics and proteomics measurements in massively parallel throughput, and the development of robust and innovative computational biology strategies. We also recognize influences from medicine and technology, welcoming studies in molecular genetics, molecular diagnostics and therapeutics, and nanotechnology. Our ultimate objective is the comprehensive illustration of the molecular mechanisms regulating proteins, nucleic acids, carbohydrates, lipids, and small metabolites in organisms across all branches of life. In addition to interesting new findings, techniques, and applications, Frontiers in Molecular Biosciences will consider new testable hypotheses to inspire different perspectives and stimulate scientific dialogue. The integration of in silico, in vitro, and in vivo approaches will benefit endeavors across all domains of the life sciences.
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