Advances in pancreatic cancer diagnosis: from DNA methylation to AI-assisted imaging.

IF 3.9 3区医学 Q1 PATHOLOGY

Expert Review of Molecular Diagnostics Pub Date : 2025-07-01 Epub Date: 2025-05-21 DOI:10.1080/14737159.2025.2509022

Rohit Sharma, Kumari Komal, Sourabh Kumar, Rashmi Ghosh, Prachi Pandey, Ghanshyam Das Gupta, Manish Kumar

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引用次数: 0

Abstract

Introduction: Pancreatic Cancer (PC) is a highly aggressive tumor that is mainly diagnosed at later stages. Various imaging technologies, such as CT, MRI, and EUS, possess limitations in early PC diagnosis. Therefore, this review article explores the various innovative biomarkers for PC detection, such as DNA methylation, Noncoding RNAs, and proteomic biomarkers, and the role of AI in PC detection at early stages.

Area covered: Innovative biomarkers, such as DNA methylation genes, show higher specificity and sensitivity in PC diagnosis. Additionally, various non-coding RNAs, such as long non-coding RNAs (lncRNAs) and microRNAs, show high diagnostic accuracy and serve as diagnostic and prognostic biomarkers. Additionally, proteomic biomarkers retain higher diagnostic accuracy in different body fluids. Apart from this, the utilization of AI showed that AI surpassed the radiologist's diagnostic performance in PC detection.

Expert opinion: The combination of AI and advanced biomarkers can revolutionize early PC detection. However, large-scale, prospective studies are needed to validate its clinical utility. Further. standardization of biomarker panels and AI algorithms is a vital step toward their reliable applications in early PC detection, ultimately improving patient outcomes. [Figure: see text].

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胰腺癌诊断的进展：从DNA甲基化到人工智能辅助成像。

胰腺癌（PC）是一种高度侵袭性的肿瘤，主要在晚期诊断。各种成像技术，如CT、MRI和EUS，在早期PC诊断中都有局限性。因此，这篇综述文章探讨了用于PC检测的各种创新生物标志物，如DNA甲基化、非编码rna和蛋白质组学生物标志物，以及人工智能在早期PC检测中的作用。涉及领域：创新生物标志物，如DNA甲基化基因，在PC诊断中具有更高的特异性和敏感性。此外，多种非编码rna，如长链非编码rna （long non-coding rna, lncRNAs）和microRNAs，具有较高的诊断准确性，可作为诊断和预后的生物标志物。此外，蛋白质组生物标志物在不同的体液中保持更高的诊断准确性。除此之外，人工智能的使用表明，人工智能在PC检测方面的诊断性能超过了放射科医生。专家意见：人工智能和先进生物标志物的结合可以彻底改变早期PC检测。然而，需要大规模的前瞻性研究来验证其临床应用。进一步。生物标志物面板和人工智能算法的标准化是其在早期PC检测中可靠应用的重要一步，最终改善患者的治疗效果。

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

Expert Review of Molecular Diagnostics 医学-病理学

CiteScore

6.60

自引率

0.00%

发文量

审稿时长

1 months

期刊介绍： Expert Review of Molecular Diagnostics (ISSN 1473-7159) publishes expert reviews of the latest advancements in the field of molecular diagnostics including the detection and monitoring of the molecular causes of disease that are being translated into groundbreaking diagnostic and prognostic technologies to be used in the clinical diagnostic setting. Each issue of Expert Review of Molecular Diagnostics contains leading reviews on current and emerging topics relating to molecular diagnostics, subject to a rigorous peer review process; editorials discussing contentious issues in the field; diagnostic profiles featuring independent, expert evaluations of diagnostic tests; meeting reports of recent molecular diagnostics conferences and key paper evaluations featuring assessments of significant, recently published articles from specialists in molecular diagnostic therapy. Expert Review of Molecular Diagnostics provides the forum for reporting the critical advances being made in this ever-expanding field, as well as the major challenges ahead in their clinical implementation. The journal delivers this information in concise, at-a-glance article formats: invaluable to a time-constrained community.