Quantitative analysis of imaging characteristics in lung adenocarcinoma in situ using artificial intelligence.

IF 2.3 3区医学 Q3 ONCOLOGY Thoracic Cancer Pub Date : 2024-10-30 DOI:10.1111/1759-7714.15447

Wensong Shi, Yuzhui Hu, Yulun Yang, Yinsen Song, Guotao Chang, He Qian, Zhengpan Wei, Liang Gao, Yingli Sun, Ming Li, Hang Yi, Sikai Wu, Kun Wang, Yousheng Mao, Siyuan Ai, Liang Zhao, Huiyu Zheng, Xiangnan Li

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Abstract

Background: With the rising incidence of pulmonary nodules (PNs), lung adenocarcinoma in situ (AIS) is a critical early stage of lung cancer, necessitating accurate diagnosis for early intervention. This study applies artificial intelligence (AI) for quantitative imaging analysis to differentiate AIS from atypical adenomatous hyperplasia (AAH) and minimally invasive adenocarcinoma (MIA), aiming to enhance clinical diagnosis and prevent misdiagnosis.

Methods: The study analyzed 1215 PNs with confirmed AAH, AIS, and MIA from six centers using the Shukun AI diagnostic module. Parameters evaluated included demographic data and various CT imaging metrics to identify indicators for clinical application, focusing on the mean CT value's predictive value.

Results: Significant differences were found in several parameters between AAH and AIS, with nodule mass showing the highest predictive value. When comparing AIS to MIA, total nodule volume was the best predictor, followed by the maximum CT value.

Conclusion: The mean CT value has limited discriminative power for AIS diagnosis. Instead, the maximum CT value and maximum 3D diameter are recommended for clinical differentiation. Nodule mass and volume of solid components are strong indicators for differentiating AIS from AAH and MIA, respectively.

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利用人工智能对肺原位腺癌的成像特征进行定量分析。

背景：随着肺结节（PNs）发病率的上升，肺原位腺癌（AIS）是肺癌早期的一个关键阶段，需要准确诊断以便早期干预。本研究应用人工智能（AI）进行定量成像分析，以区分肺原位腺癌（AIS）与非典型腺瘤性增生（AAH）和微侵袭性腺癌（MIA），旨在提高临床诊断水平，防止误诊：研究使用舒坤 AI 诊断模块分析了来自六个中心的 1215 例确诊 AAH、AIS 和 MIA 的 PN。评估参数包括人口统计学数据和各种 CT 成像指标，以确定临床应用指标，重点是 CT 平均值的预测价值：结果：发现 AAH 和 AIS 的多个参数存在显著差异，其中结节肿块的预测值最高。在比较 AIS 和 MIA 时，结节总体积是最佳预测指标，其次是 CT 最大值：结论：CT 平均值对 AIS 诊断的鉴别力有限。结论：CT 平均值对 AIS 诊断的鉴别力有限，建议使用 CT 最大值和最大三维直径进行临床鉴别。结节质量和固体成分体积分别是区分 AIS 与 AAH 和 MIA 的有力指标。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Thoracic Cancer ONCOLOGY-RESPIRATORY SYSTEM

CiteScore

5.20

自引率

3.40%

发文量

439

审稿时长

2 months

期刊介绍： Thoracic Cancer aims to facilitate international collaboration and exchange of comprehensive and cutting-edge information on basic, translational, and applied clinical research in lung cancer, esophageal cancer, mediastinal cancer, breast cancer and other thoracic malignancies. Prevention, treatment and research relevant to Asia-Pacific is a focus area, but submissions from all regions are welcomed. The editors encourage contributions relevant to prevention, general thoracic surgery, medical oncology, radiology, radiation medicine, pathology, basic cancer research, as well as epidemiological and translational studies in thoracic cancer. Thoracic Cancer is the official publication of the Chinese Society of Lung Cancer, International Chinese Society of Thoracic Surgery and is endorsed by the Korean Association for the Study of Lung Cancer and the Hong Kong Cancer Therapy Society. The Journal publishes a range of article types including: Editorials, Invited Reviews, Mini Reviews, Original Articles, Clinical Guidelines, Technological Notes, Imaging in thoracic cancer, Meeting Reports, Case Reports, Letters to the Editor, Commentaries, and Brief Reports.