有利于最小化损伤并保留更多的功能性肺组织，所以有限的手术被认为依赖于淋巴结（LN）侵犯的情况。然而，有限的手术可能会忽略超声淋巴结转移 (OLM) 病变，成为手术切除后局部复发的风险因素。本研究的目的是评估基于计算机断层扫描增强图像的 OLAM 风险因素，并在临床肺腺癌 (ADC) 患者中进行评估。从2016年1月至2022年7月，707例临床IIA期ADC受试者进行了肺叶切除和系统性 LN 清除，并根据不同机构划分为训练组和验证组。进行单变量分析，随后进行多变量逻辑回归以估计不同的 OLM 风险因素。采用视觉量表建立了预测模型，并进行外部验证，并根据准确性、灵敏度、特异度和受试者工作特征曲线下面积（AUC）进行评估。 有59例患者被诊断出患有 OLM（11.9%），并且确定了四个 LN 参与的独立预测因子：更大的病变直径（OR，2.35，95%置信区间[CI]：1.06，5.22，p = 0.013）、支气管血管束增厚（OR，1.99，95% CI：1.00，3.95，p = 0.049）、分叶（OR，2.92，95% CI：1.22，6.99，p = 0.016）和阻塞性变化（OR，1.69，95% CI：1.17，6.16，p = 0.020）。该模型具有良好的校准性 （Hosmer-Lemeshow 拟合度，p = 0.816），AUC 为 0.821 （95% CI：0.775，0.853）。对于验证组，AUC 是 0.788（95% CI：0.732，0.806）。 我们的预测模型可以在临床 IIA 期 ADC 患者中非侵入性地评估 OLM 的风险，让外科医生在术前进行个性化的预测，并协助临床决策程序。Copyright © 2023 The Association of University Radiologists。Elsevier Inc. 发布。版权所有。

With the advantage of minimizing damage and preserving more functional lung tissue, limited surgery is considered depend on the lymph node (LN) involvement situation. However, occult lymph node metastasis (OLM) may be ignored by limited surgery and become a risk factor for local recurrence after surgical resection. The aim of this study was to assess the risk factors for OLM based on computed tomography enhanced image in patients with clinical lung adenocarcinoma (ADC).From January 2016 to July 2022, 707 patients with clinical stage IA-IIA ADC underwent lobectomy with systematic LN dissection and were divided into training and validation group based on different institution. Univariate analysis followed by multivariable logistic regression were performed to estimate different risk factors of OLM. A predictive model was established with visual nomogram and external validation, and evaluated in terms of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Fifty-nine patients were diagnosed with OLM (11.9%), and four independent predictors of LN involvement were identified: larger consolidation diameter (odds ratio [OR], 2.35, 95% confidence interval [CI]: 1.06, 5.22, p = 0.013), bronchovascular bundle thickening (OR, 1.99, 95% CI: 1.00, 3.95, p = 0.049), lobulation (OR, 2.92, 95% CI: 1.22, 6.99, p = 0.016) and obstructive change (OR, 1.69, 95% CI: 1.17, 6.16, p = 0.020). The model showed good calibration (Hosmer-Lemeshow goodness-of-fit, p = 0.816) with an AUC of 0.821 (95% CI: 0.775, 0.853). For the validation group, the AUC was 0.788 (95% CI: 0.732, 0.806).Our predictive model can non-invasively assess the risk of OLM in patients with clinical stage IA-IIA ADC, enable surgeons perform an individualized prediction preoperatively, and assist the clinical decision-making procedure.Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.