Baolian Zhao, Xiang Wang, Ke Sun, Han Kang, Kai Zhang, Hongkun Yin, Kai Liu, Yi Xiao, Shiyuan Liu
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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 χ 2 test, χ 2 test, and analysis of variance.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":49974,"journal":{"name":"Journal of Thoracic Imaging","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Correlation Between Intranodular Vessels and Tumor Invasiveness of Lung Adenocarcinoma Presenting as Ground-glass Nodules: A Deep Learning 3-Dimensional Reconstruction Algorithm-based Quantitative Analysis on Noncontrast Computed Tomography Images.\",\"authors\":\"Baolian Zhao, Xiang Wang, Ke Sun, Han Kang, Kai Zhang, Hongkun Yin, Kai Liu, Yi Xiao, Shiyuan Liu\",\"doi\":\"10.1097/RTI.0000000000000731\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>To evaluate the role of quantitative features of intranodular vessels based on deep learning in distinguishing pulmonary adenocarcinoma invasiveness.</p><p><strong>Materials and methods: </strong>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 χ 2 test, χ 2 test, and analysis of variance.</p><p><strong>Results: </strong>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). 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引用次数: 0
摘要
目的:探讨基于深度学习的结节内血管定量特征在鉴别肺腺癌侵袭性中的作用。材料和方法:本回顾性研究包括474例确诊的512例磨玻璃结节,其中241例为前体腺病变(PGL), 126例为微创腺癌(MIA), 145例为侵袭性腺癌(IAC)。利用基于深度学习的区域分割和区域生长技术在非对比计算机断层扫描图像上重建肺血管。根据自动计算血管患病率、血管种类和血管体积百分比来评估是否存在结节内血管。采用Mantel-Haenszel χ 2检验、χ 2检验和方差分析进一步比较不同侵袭组间的差异。结果:PGL的结节内血管检出率(33.2%)明显低于MIA (46.8%, P = 0.011)和IAC (55.2%, P < 0.001),而血管类型相似(均P > 0.05)。与PGL相比,IAC和MIA的血管改变更为常见,主要表现为血管体积百分比增加(12.4±19.0% vs. 6.3±13.1% vs. 3.9±9.4%,P < 0.001)。IAC组平均结内动、静脉体积百分比(7.5±14.0%和5.0±10.1%)高于PGL组(2.1±6.9%和1.7±5.8%)和MIA组(3.2±9.1%和3.1±8.7%),差异均有统计学意义(P < 0.05)。结论:非对比ct图像对结节内血管的定量分析表明,内血管患病率和体积百分比增加的磨玻璃结节具有更高的肿瘤侵袭可能性。
Correlation Between Intranodular Vessels and Tumor Invasiveness of Lung Adenocarcinoma Presenting as Ground-glass Nodules: A Deep Learning 3-Dimensional Reconstruction Algorithm-based Quantitative Analysis on Noncontrast Computed Tomography Images.
Purpose: To evaluate the role of quantitative features of intranodular vessels based on deep learning in distinguishing pulmonary adenocarcinoma invasiveness.
Materials and methods: 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 χ 2 test, χ 2 test, and analysis of variance.
Results: 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).
Conclusions: 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.
期刊介绍:
Journal of Thoracic Imaging (JTI) provides authoritative information on all aspects of the use of imaging techniques in the diagnosis of cardiac and pulmonary diseases. Original articles and analytical reviews published in this timely journal provide the very latest thinking of leading experts concerning the use of chest radiography, computed tomography, magnetic resonance imaging, positron emission tomography, ultrasound, and all other promising imaging techniques in cardiopulmonary radiology.
Official Journal of the Society of Thoracic Radiology:
Japanese Society of Thoracic Radiology
Korean Society of Thoracic Radiology
European Society of Thoracic Imaging.