Quantifying vascular invasion in pancreatic cancer-a contrast CT based method for surgical resectability evaluation.
Quantifying vascular invasion in pancreatic cancer-a contrast CT based method for surgical resectability evaluation.
复制标题
量化胰腺癌的血管侵犯——一种基于对比 CT 的手术可切除性评估方法。
DOI：
10.1088/1361-6560/ab8106
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发表时间：
2020
影响因子：
3.5
通讯作者：
Tuli,Richard
中科院分区：
文献类型：
--
作者：
Lao,Yi;David,John;Fan,Zhaoyang;Bian,Shelly;Shiu,Almon;Chang,EricL;Sheng,Ke;Yang,Wensha;Tuli,Richard
胰腺癌（Pancreatic cancer，PC）是世界上最致命的恶性肿瘤之一，其局部耐药率高，5年生存率低。迄今为止，手术切除仍然是唯一的治疗选择提供潜在的治愈。不幸的是，在诊断时，大多数患者表现出不同程度的血管浸润，这可能禁忌手术切除。不适合立即切除的患者进一步分为局部晚期（LA）和边缘可切除（BR），治疗目标和治疗设计不同。因此，可切除性的准确定义对于PC患者至关重要，然而现有的确定可切除性的方法依赖于对周围血管的描述性邻接，而不是定量几何特征。在这里，我们的目的是引入一种新的对象内的对象空间支持向量机（OsSVM）的方法来定量表征血管参与的程度-决定PC可切除性的主要因素。在107例对比CT扫描（56例LA、BR和26例可切除（RE）PC病例）中应用受试者内OsSVM，以优化肿瘤-血管分离。计算来自OsSVM边缘的九个度量作为总体血管浸润的指标。由弹性网络选择的组合矩阵集在LA和BR（AUC= 0.95）以及BR和RE（AUC= 0.98）之间产生高分类能力。所提出的OsSVM方法可以提供改进的定量成像指南，以完善PC可切除性分级系统。
Pancreatic cancer (PC) is one of the most lethal cancers, with frequent local therapy resistance and dismal 5-year survival rate. To date, surgical resection remains to be the only treatment option offering potential cure. Unfortunately, at diagnosis, the majority of patients demonstrate varying levels of vascular infiltration, which can contraindicate surgical resection. Patients unsuitable for immediate resection are further divided into locally advanced (LA) and borderline resectable (BR), with different treatment goals and therapeutic designs. Accurate definition of resectability is thus critical for PC patients, yet the existing methods to determine resectability rely on descriptive abutment to surrounding vessels rather than quantitative geometric characterization. Here, we aim to introduce a novel intra-subject object-space support-vector-machine (OsSVM) method to quantitatively characterize the degree of vascular involvement—the main factor determining the PC resectability. Intra-subject OsSVMs were applied on 107 contrast CT scans (56 LA, BR and 26 resectable (RE) PC cases) for optimized tumor-vessel separations. Nine metrics derived from OsSVM margins were calculated as indicators of the overall vascular infiltration. The combined sets of matrics selected by the elastic net yielded high classification capability between LA and BR (AUC= 0.95), as well as BR and RE (AUC= 0.98). The proposed OsSVM method may provide an improved quantitative imaging guideline to refine the PC resectability grading system.