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首页> 外文会议>IEEE International Symposium on Computer-Based Medical Systems >Radiomics-Based Non-Invasive Lymph Node Metastases Prediction in Breast Cancer
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Radiomics-Based Non-Invasive Lymph Node Metastases Prediction in Breast Cancer

机译：乳腺癌中基于放射学的非侵入性淋巴结转移预测

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Breast cancer is the most common tumour in women and it is characterized by a huge variety of clinical and histological scenarios and imaging pattern. The axillary lymph node metastases presence or absence is one of the most important prognostic factors affecting the loco-regional recurrence and the overall survival. The lymph node status is usually determined by an histological exam, an invasive procedure that could result in complications. This work aims to provide a safer and non-invasive prognostic approach by introducing a radiomics-based method that predicts axillary lymph node metastasis. It combines primary tumor histological features and patients clinical data with quantitative measures extracted from the MR images. To compute these latter quantities we determine the convex hull of the ROIs and we introduce the Three Orthogonal Planes-Local Binary Pattern (TOP-LBP). On 99 samples the approach achieves a promising AUC equal to 85.6%.
机译：乳腺癌是女性中最常见的肿瘤，其特征是临床和组织学情况以及成像模式多种多样。腋窝淋巴结转移的存在与否是影响局部复发和整体生存的最重要的预后因素之一。淋巴结状态通常由组织学检查确定，这是可能导致并发症的侵入性检查。这项工作旨在通过引入基于放射学的预测腋窝淋巴结转移的方法，提供一种更安全，无创的预后方法。它结合了原发性肿瘤的组织学特征和患者的临床数据，并结合了从MR图像中提取的定量指标。为了计算后面的这些量，我们确定ROI的凸包，并引入三个正交平面-局部二值模式（TOP-LBP）。在99个样本上，该方法实现了有希望的AUC等于85.6％。

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