为了评估基于深度学习的肺腺癌浸润性分辨的结节内血管数量特征的作用。本回顾性研究包括来自474名患者的512个经过确认的地玻璃结节，其中包括241个前体腺样病变(PGL)、126个微小浸润性腺癌(MIA)和145个浸润性腺癌(IAC)。利用基于深度学习的区域分割和区域生长技术，对非对比增强计算机断层扫描图像进行肺血管重建。基于血管普遍性、血管类别和血管占结节体积比的自动计算，对结节内血管的存在进行评估。进一步通过Mantel-Haenszel χ2检验、χ2检验和方差分析比较不同浸润性组之间的差异。 PGL中结节内血管的检出率(33.2%)明显低于MIA(46.8%， P = 0.011)和IAC(55.2%， P < 0.001)，而血管类别相似 (全部P > 0.05)。IAC和MIA中血管变化比PGL更常见，主要表现为增加的血管占结节体积比(12.4 ± 19.0% 对 6.3 ± 13.1% 对 3.9 ± 9.4%，P < 0.001) 。IAC的平均结节内动脉和静脉体积百分比(7.5 ± 14.0% 和 5.0 ± 10.1%)高于PGL(2.1 ± 6.9% 和 1.7 ± 5.8%)和MIA(3.2 ± 9.1% 和 3.1 ± 8.7%)，具有统计学意义(全部 P < 0.05)。 对非对比增强计算机断层扫描图像上的结节内血管的定量分析表明，具有增加的内部血管普遍性和体积百分比的地玻璃结节存在更高的肿瘤浸润可能性。 © 2023 Wolters Kluwer Health, Inc. 保留所有权利。

To evaluate the role of quantitative features of intranodular vessels based on deep learning in distinguishing pulmonary adenocarcinoma invasiveness.This retrospective study included 512 confirmed ground-glass nodules from 474 patients with 241 precursor glandular lesions (PGL), 126 minimally invasive adenocarcinomas (MIA), and 145 invasive adenocarcinomas (IAC). The pulmonary blood vessels were reconstructed on noncontrast computed tomography images using deep learning-based region-segmentation and region-growing techniques. The presence of intranodular vessels was evaluated based on the automatic calculation of vessel prevalence, vascular categories, and vessel volume percentage. Further comparisons were made between different invasive groups by the Mantel-Haenszel χ2 test, χ2 test, and analysis of variance.The detection rate of intranodular vessels in PGL (33.2%) was significantly lower than that of MIA (46.8%, P = 0.011) and IAC (55.2%, P < 0.001), while the vascular categories were similar (all P > 0.05). Vascular changes were more common in IAC and MIA than in PGL, mainly in increased vessel volume percentage (12.4 ± 19.0% vs. 6.3 ± 13.1% vs. 3.9 ± 9.4%, P < 0.001). The average intranodular artery and vein volume percentage of IAC (7.5 ± 14.0% and 5.0 ± 10.1%) was higher than that of PGL (2.1 ± 6.9% and 1.7 ± 5.8%) and MIA (3.2 ± 9.1% and 3.1 ± 8.7%), with statistical significance (all P < 0.05).The quantitative analysis of intranodular vessels on noncontrast computed tomography images demonstrated that the ground-glass nodules with increased internal vessel prevalence and volume percentages had higher possibility of tumor invasiveness.Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.