OBJECTIVES The sensitivity for tumor spread through air space (STAS), an independent risk factor for locoregional recurrence after sublobar resection for lung cancer, has been relatively low in frozen sections. We aimed to determine predictors with high negative predictive value for the presence of STAS and to provide the flowchart in combination with these predictors for the decision-making for sublobar resection. MATERIALS AND METHODS Between July 2015 and December 2017, 387 patients who underwent surgery for non-small cell lung cancer (NSCLC) with pathologic findings of the total masses measuring ≤ 2 cm were enrolled. The lesions were divided into two groups according to presence of STAS. We compared the preoperative characteristics, operative data, and developed a flowchart for STAS prediction using receiver operator characteristic curve analysis and multivariable logistic regression. RESULTS The STAS-positive group (N = 111) had a significantly higher preoperative tumor size (1.70 [1.5] vs 1.50 [0.69], p < 0.001) and standardized uptake value tumor-to-liver (SUV T/L) ratio (1.40 [1.60] vs 0.60 [1.10], p < 0.001) and a significantly lower two-dimensional ground-glass opacity (GGO) percentage (35.86 [61.00] vs 78.14 [39.00], p < 0.001). Meanwhile, the STAS-negative group (N = 286) had higher lepidic predominance (41.6% vs. 1.8%, p < 0.001). We developed a flowchart for predicting STAS in combination with two-dimensional GGO percentage on computed tomography (CT), SUV T/L ratio on positron-emission CT, and lepidic predominant pattern. The sensitivity, specificity, and negative predictive value for STAS positivity were 79.3%, 68.5%, and 89.5%, respectively. CONCLUSIONS The stepwise flowchart using two-dimensional GGO percentage on CT, maximum SUV, and lepidic predominance might be helpful in selecting patients with early NSCLC for sublobar resection.

中文翻译：

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通过评估早期肺癌中通过气隙的扩散来决定大叶下切除的分步流程图1。

目的肺癌在肺叶切除后局部区域复发的独立危险因素中，肿瘤通过气隙扩散（STAS）的敏感性在冰冻切片中相对较低。我们旨在确定对于STAS的存在具有较高负预测价值的预测因素，并提供与这些预测因素相结合的流程图，以进行肺叶下切除的决策。材料与方法在2015年7月至2017年12月之间，共入选了387例接受非小细胞肺癌（NSCLC）手术治疗且总病理量≤2 cm的病理结果的患者。根据STAS的存在将病变分为两组。我们比较了术前特征，手术数据，并开发了使用接收器操作员特征曲线分析和多变量Logistic回归进行STAS预测的流程图。结果STAS阳性组（N = 111）的术前肿瘤大小明显更高（1.70 [1.5]比1.50 [0.69]，p <0.001），并且标准化的摄取值肿瘤与肝脏（SUV T / L）比（ 1.40 [1.60]和0.60 [1.10]，p <0.001）和更低的二维毛玻璃不透明度（GGO）百分比（35.86 [61.00] vs 78.14 [39.00]，p <0.001）。同时，STAS阴性组（N = 286）的癫痫发病率较高（41.6％对1.8％，p <0.001）。我们开发了一种流程图，用于结合计算机断层扫描（CT）上的二维GGO百分比，正电子发射CT上的SUV T / L比以及癫痫样优势模式来预测STAS。敏感性，特异性，STAS阳性的阴性预测值和阴性预测值分别为79.3％，68.5％和89.5％。结论使用二维GGO百分比的CT，最大SUV和癫痫优势的逐步流程图可能有助于选择早期NSCLC患者进行叶下切除。