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关于人工智能软件在肺结节检测临床应用的研究与真实世界经验

[Studies and Real-World Experience Regarding the Clinical Application of Artificial Intelligence Software for Lung Nodule Detection].

作者信息

Kim Junghoon

出版信息

J Korean Soc Radiol. 2024 Jul;85(4):705-713. doi: 10.3348/jksr.2024.0044. Epub 2024 Jul 30.

DOI:10.3348/jksr.2024.0044
PMID:39130781
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11310431/
Abstract

This article discusses studies and real-world experiences related to the clinical application of artificial intelligence-based computer-aided detection (AI-CAD) software (LuCAS-plus, Monitor Corporation) in detecting pulmonary nodules. During clinical trials for lung cancer screening, AI-CAD exhibited performance comparable to that of medical professionals in terms of sensitivity and specificity. Studies revealed that applying AI-CAD for diagnosing pulmonary metastases led to high detection rates. The use of a nodule matching algorithm in diagnosing pulmonary metastases significantly reduced false non-metastasis results. In clinical settings, implementing AI-CAD enhanced the efficiency of pulmonary nodule detection, saving time and effort during CT reading. Overall, AI-CAD is expected to offer substantial support for lung cancer screening and the interpretation of chest CT scans for malignant tumor surveillance.

摘要

本文讨论了基于人工智能的计算机辅助检测（AI-CAD）软件（LuCAS-plus，Monitor公司）在检测肺结节方面的临床应用相关研究和实际经验。在肺癌筛查的临床试验中，AI-CAD在敏感性和特异性方面表现出与医学专业人员相当的性能。研究表明，应用AI-CAD诊断肺转移瘤可获得较高的检出率。在诊断肺转移瘤时使用结节匹配算法可显著减少假非转移结果。在临床环境中，实施AI-CAD提高了肺结节检测的效率，节省了CT阅片的时间和精力。总体而言，预计AI-CAD将为肺癌筛查以及胸部CT扫描用于恶性肿瘤监测的解读提供大力支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bdf/11310431/61cb189a645b/jksr-85-705-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bdf/11310431/c07ea3c4f880/jksr-85-705-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bdf/11310431/61cb189a645b/jksr-85-705-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bdf/11310431/c07ea3c4f880/jksr-85-705-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bdf/11310431/61cb189a645b/jksr-85-705-g002.jpg

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本文引用的文献

1
Usefulness of longitudinal nodule-matching algorithm in computer-aided diagnosis of new pulmonary metastases on cancer surveillance CT scans.纵向结节匹配算法在癌症监测CT扫描中对新肺转移灶的计算机辅助诊断中的应用价值。
Quant Imaging Med Surg. 2024 Feb 1;14(2):1493-1506. doi: 10.21037/qims-23-1174. Epub 2024 Jan 2.
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随机试验中 CT 容积筛查降低肺癌死亡率
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Comput Methods Programs Biomed. 2018 Aug;162:109-118. doi: 10.1016/j.cmpb.2018.05.006. Epub 2018 May 9.
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The utilisation of convolutional neural networks in detecting pulmonary nodules: a review.卷积神经网络在肺结节检测中的应用：综述
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Pulmonary metastasectomy: an overview.肺转移瘤切除术：概述
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