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首页> 外文会议>International workshop on breast imaging >Predicting Triple-Negative Breast Cancer and Axillary Lymph Node Metastasis Using Diagnostic MRI
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Predicting Triple-Negative Breast Cancer and Axillary Lymph Node Metastasis Using Diagnostic MRI

机译：使用诊断性MRI预测三阴性乳腺癌和腋窝淋巴结转移

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Early classification of breast cancers by molecular subtype allows for expeditious characterization of the disease and selection of appropriate treatment options. This ability is especially a concern for "triple-negative" cancers, which lack expression of the three cell surface receptors that most breast cancer hormonal therapies target, tend to be the most aggressive/metastatic compared to other subtypes, have lymph node involvement at diagnoses, and have relatively poor prognoses. In this study, we aim to develop predictive models using Dynamic Contrast-Enhanced (DCE) MRI-extracted features to identify triple-negative cancers and axillary lymph node metastasis at the time of diagnostic imaging. Using only morphological, pharmacokinetic, densitometric, statistical, textural, and textural kinetic features obtained from DCE-MRI, we were able to classify 91.3% of 69 lesions correctly for triple-negative status with a sensitivity of 55.6%, a specificity of 96.7, and an AUC of 0.889; 71.6% of lesions correctly for lymph node metastasis with a sensitivity of 50.0%, a specificity of 82.2%, and an AUC of 0.677.
机译：通过分子亚型对乳腺癌进行早期分类，可以对疾病进行快速表征，并选择适当的治疗方案。对于“三阴性”癌症，该功能尤为令人关注，该癌症缺乏大多数乳腺癌激素疗法靶向的三种细胞表面受体的表达，与其他亚型相比，往往是最具侵袭性/转移性的，在诊断中涉及淋巴结转移，并且预后相对较差。在这项研究中，我们旨在利用动态对比度增强（DCE）MRI提取的特征开发预测模型，以在诊断成像时识别三阴性癌症和腋窝淋巴结转移。仅使用从DCE-MRI获得的形态学，药代动力学，光密度，统计学，组织和组织动力学特征，我们就能够正确地将69个病变中的91.3％归为三阴性状态，灵敏度为55.6％，特异性为96.7， AUC为0.889;淋巴结转移正确的病变占71.6％，敏感性为50.0％，特异性为82.2％，AUC为0.677。

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