Wang Yun, Lyu Deng, Fan Li, Liu Shiyuan
Department of Radiology, Second Affiliated Hospital of Navy Medical University, Shanghai, China.
Transl Cancer Res. 2023 Mar 31;12(3):624-630. doi: 10.21037/tcr-22-2593. Epub 2023 Mar 1.
In 2015, the World Health Organization (WHO) officially defined spread through air spaces (STAS) as the fourth type of lung adenocarcinoma (ADC) invasion. STAS is recognized to have effects on the survival rate and the prognosis of patients who have received lung cancer surgery. Given that postoperative pathological diagnosis is the gold standard for STAS diagnosis, but the pathological findings cannot guide the selection of preoperative surgical plan, it is essential to accurately predict STAS before surgery to achieve optimal outcomes.
A comprehensive, non-systematic review of the latest literature was carried out in order to define the advancement of imaging in predicting STAS. PubMed database was being examined and the last run was on 27 June 2022.
In this review, the definition and the clinical significance of predicting STAS for lung cancer patients were being discussed. By summarizing the STAS prediction efficacy from imaging-related research, the results suggest that computed tomography (CT), 18-fluorine-fluorodeoxyglucose positron emission tomography/CT (F-FDG PET/CT), radiomics and deep learning (DL) are of great value in predicting STAS.
STAS is an important invasion type of lung cancer, affecting the survival prognosis of patients. Preoperative CT and F-FDG PET/CT have certain value in predicting the status of STAS, assisting clinicians in selecting an optimal surgical approach and postsurgical treatment. The prediction of STAS based on radiomics and DL can represent a future research direction.
2015年，世界卫生组织（WHO）正式将气腔播散（STAS）定义为肺腺癌（ADC）的第四种侵袭类型。STAS被认为会影响接受肺癌手术患者的生存率和预后。鉴于术后病理诊断是STAS诊断的金标准，但病理结果无法指导术前手术方案的选择，因此在手术前准确预测STAS以实现最佳治疗效果至关重要。
为了明确影像学在预测STAS方面的进展，对最新文献进行了全面的非系统性综述。检索了PubMed数据库，最后一次检索时间为2022年6月27日。
在本综述中，讨论了肺癌患者预测STAS的定义及临床意义。通过总结影像学相关研究的STAS预测效能，结果表明计算机断层扫描（CT）、18氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描（F-FDG PET/CT）、影像组学和深度学习（DL）在预测STAS方面具有重要价值。
STAS是肺癌的一种重要侵袭类型，影响患者的生存预后。术前CT和F-FDG PET/CT在预测STAS状态方面具有一定价值，可协助临床医生选择最佳手术方式和术后治疗方案。基于影像组学和DL的STAS预测可能代表未来的研究方向。
