Innovative technologies and their clinical prospects for early lung cancer screening.

IF 3.5 4区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Zisu Deng, Xiaocao Ma, Shubiao Zou, Liling Tan, Tingting Miao
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引用次数: 0

Abstract

Background: Lung cancer remains the leading cause of cancer-related mortality worldwide, due to lacking effective early-stage screening approaches. Imaging, such as low-dose CT, poses radiation risk, and biopsies can induce some complications. Additionally, traditional serum tumor markers lack diagnostic specificity. This highlights the urgent need for precise and non-invasive early detection techniques.

Purpose: This systematic review aims to evaluate the limitations of conventional screening methods (imaging/biopsy/tumor markers), seek breakthroughs in liquid biopsy for early lung cancer detection, and assess the potential value of Artificial Intelligence (AI), thereby providing evidence-based insights for establishing an optimal screening framework.

Methods: We systematically searched the PubMed database for the literature published up to May 2025. Key words include "Artificial Intelligence", "Early Lung cancer screening", "Imaging examination", "Innovative technologies", "Liquid biopsy", and "Puncture biopsy". Our inclusion criteria focused on studies about traditional and innovative screening methods, with an emphasis on original research concerning diagnostic performance or high-quality reviews. This approach helps identify critical studies in early lung cancer screening.

Conclusions: Novel liquid biopsy techniques are non-invasive and have superior diagnostic efficacy. AI-assisted diagnostics further enhance accuracy. We propose three development directions: establishing risk-based liquid biopsy screening protocols, developing a stepwise "imaging-AI-liquid biopsy" diagnostic workflow, and creating standardized biomarker panel testing solutions. Integrating traditional methodologies, novel liquid biopsies, and AI to establish a comprehensive early lung cancer screening model is important. These innovative strategies aim to significantly increase early detection rates, substantially enhancing lung cancer control. This review provides both theoretical guidance for clinical practice and future research.

肺癌早期筛查的创新技术及其临床前景。
背景:由于缺乏有效的早期筛查方法,肺癌仍然是全球癌症相关死亡的主要原因。成像,如低剂量CT,有辐射风险,活检可能引起一些并发症。此外,传统的血清肿瘤标志物缺乏诊断特异性。这突出了对精确和非侵入性早期检测技术的迫切需要。目的:本系统综述旨在评估常规筛查方法(影像学/活检/肿瘤标志物)的局限性,寻求液体活检在早期肺癌检测中的突破,评估人工智能(AI)的潜在价值,从而为建立最佳筛查框架提供循证见解。方法:系统检索PubMed数据库中截至2025年5月发表的文献。关键词:“人工智能”、“早期肺癌筛查”、“影像学检查”、“创新技术”、“液体活检”、“穿刺活检”。我们的纳入标准侧重于传统和创新筛查方法的研究,重点是关于诊断性能或高质量评价的原始研究。这种方法有助于确定早期肺癌筛查的关键研究。结论:新型液体活检技术无创,诊断效果好。人工智能辅助诊断进一步提高了准确性。我们提出了三个发展方向:建立基于风险的液体活检筛查方案,开发逐步的“成像-人工智能液体活检”诊断流程,以及创建标准化的生物标志物面板检测解决方案。将传统方法、新型液体活检和人工智能相结合,建立全面的早期肺癌筛查模型具有重要意义。这些创新策略旨在显著提高早期检出率,大大加强肺癌的控制。本文综述为临床实践和今后的研究提供理论指导。
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
Clinical and Experimental Medicine
Clinical and Experimental Medicine 医学-医学:研究与实验
CiteScore
4.80
自引率
2.20%
发文量
159
审稿时长
2.5 months
期刊介绍: Clinical and Experimental Medicine (CEM) is a multidisciplinary journal that aims to be a forum of scientific excellence and information exchange in relation to the basic and clinical features of the following fields: hematology, onco-hematology, oncology, virology, immunology, and rheumatology. The journal publishes reviews and editorials, experimental and preclinical studies, translational research, prospectively designed clinical trials, and epidemiological studies. Papers containing new clinical or experimental data that are likely to contribute to changes in clinical practice or the way in which a disease is thought about will be given priority due to their immediate importance. Case reports will be accepted on an exceptional basis only, and their submission is discouraged. The major criteria for publication are clarity, scientific soundness, and advances in knowledge. In compliance with the overwhelmingly prevailing request by the international scientific community, and with respect for eco-compatibility issues, CEM is now published exclusively online.
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