人工智能(AI)和液体活检改变胃肠道肿瘤肝转移的早期检测。

IF 3.5 4区 医学 Q3 ONCOLOGY
Thilagesh P, Anand Kumar S, Aiswarya Nair U, Rabiniraj S, Shobana P, Subramani M, Sriram K
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引用次数: 0

摘要

胃肠道(GI)肿瘤的肝转移在肿瘤学中提出了重大挑战,通常预示着预后不良。传统的检测方法,如成像和组织活检在敏感性、特异性和肿瘤异质性表征方面存在局限性。在机器学习、算法和数据科学进步的推动下,人工智能(AI)在医疗保健领域的出现,为肝转移的早期检测和管理提供了一个有前景的前沿。这篇综述探讨了人工智能和液体活检技术的结合,作为主动检测胃肠道恶性肿瘤引起的肝转移的变革性工具。液体活检是一种非侵入性方法,分析体液中的循环肿瘤细胞(CTCs)、游离细胞DNA (cfDNA)和循环肿瘤DNA (ctDNA)。它提供了肿瘤异质性的全面概述,并能够实时监测肿瘤的发展和治疗反应。尽管液体活检具有优势,但也面临着一些挑战,如对早期转移的敏感性低、肝脏滤过导致的可检出性降低以及技术限制。人工智能通过卷积神经网络(cnn)和自然语言处理(NLP)等先进算法提高诊断准确性,增强了液体活检的潜力。这些人工智能模型分析复杂的生物医学数据,为癌症检测提供更高的灵敏度和特异性。人工智能和液体活检之间的协同作用有望实现早期检测、更好的疾病监测和个性化治疗策略。这篇综述强调了人工智能和液体活检技术给肿瘤精准医学带来的重大进步,特别是在提高胃肠道肿瘤转移患者的总生存期(OS)和无病生存期(DFS)方面。随着我们进入精准医疗时代,这些技术的整合有可能重新定义癌症治疗和患者管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence (AI) and Liquid Biopsy Transforming Early Detection of Liver Metastases in Gastrointestinal Cancers.

Liver metastases from Gastrointestinal (GI) cancers present significant challenges in oncology, often signaling poor prognosis. Traditional detection methods like imaging and tissue biopsies have limitations in sensitivity, specificity, and tumor heterogeneity represen-tation. The advent of artificial intelligence (AI) in healthcare, driven by advancements in ma-chine learning, algorithms, and data science, offers a promising frontier for early detection and management of liver metastases. This review explores the integration of AI and liquid biopsy technologies as transformative tools in the proactive detection of liver metastases aris-ing from GI malignancies. Liquid biopsy, a non-invasive method, analyzes circulating tumor cells (CTCs), cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA) in bodily fluids. It provides a compre-hensive overview of tumor heterogeneity and enables real-time monitoring of tumor evolu-tion and treatment response. Despite its advantages, liquid biopsy faces challenges such as low sensitivity for early-stage metastases, reduced detectability due to liver filtration, and technical limitations. AI enhances the potential of liquid biopsies by improving diagnostic accuracy through ad-vanced algorithms like Convolutional Neural Networks (CNNs) and Natural Language Pro-cessing (NLP). These AI models analyze complex biomedical data, offering higher sensitivity and specificity in cancer detection. The synergy between AI and liquid biopsies promises early detection, better disease monitoring, and personalized treatment strategies. This review underscores the significant advancements AI and liquid biopsy technologies bring to oncological precision medicine, particularly in improving overall survival (OS) and disease-free survival (DFS) for patients with GI cancer metastases. As we transition into the era of precision medicine, the integration of these technologies holds the potential to redefine cancer care and patient management.

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来源期刊
Current cancer drug targets
Current cancer drug targets 医学-肿瘤学
CiteScore
5.40
自引率
0.00%
发文量
105
审稿时长
1 months
期刊介绍: Current Cancer Drug Targets aims to cover all the latest and outstanding developments on the medicinal chemistry, pharmacology, molecular biology, genomics and biochemistry of contemporary molecular drug targets involved in cancer, e.g. disease specific proteins, receptors, enzymes and genes. Current Cancer Drug Targets publishes original research articles, letters, reviews / mini-reviews, drug clinical trial studies and guest edited thematic issues written by leaders in the field covering a range of current topics on drug targets involved in cancer. As the discovery, identification, characterization and validation of novel human drug targets for anti-cancer drug discovery continues to grow; this journal has become essential reading for all pharmaceutical scientists involved in drug discovery and development.
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