Noor Jawad, Chaudhry Ahtshamullah, Batool Saima
Internal Medicine, St. Dominic Hospital, Jackson, USA.
Pathology, Nishtar Medical University, Multan, PAK.
Cureus. 2023 May 29;15(5):e39634. doi: 10.7759/cureus.39634. eCollection 2023 May.
Cancer screening techniques aim to detect premalignant lesions and enable early intervention to delay the onset of cancer while keeping incidence constant. Technology advancements have led to the development of powerful tools such as microfluidic technology, artificial intelligence, machine learning algorithms, and electrochemical biosensors to aid in early cancer detection. Non-invasive cancer screening methods like virtual colonoscopy and endoscopic ultrasonography have also been developed to provide comprehensive pictures of organs and detect cancer early. This review article provides an overview of recent advances in cancer screening in microfluidic technology, artificial intelligence, and biomarkers through a narrative literature search. Microfluidic devices enable easy handling of sub-microliter volumes and have become a promising tool for cancer detection, drug screening, and modeling angiogenesis and metastasis in cancer research. Machine learning and artificial intelligence have shown high accuracy in oncology-related diagnostic imaging, reducing the manual steps in lesion detection and providing standardized and accurate results, with potential for global standardization in areas like colon polyps, breast cancer, and primary and metastatic brain cancer. A biomarker-based cancer diagnosis is promising for early detection and effective therapy, and electrochemical biosensors integrated with nanoparticles offer multiplexing and amplification capabilities. Understanding these advanced technologies' basics, achievements, and challenges is crucial for advancing their use in oncology.
癌症筛查技术旨在检测癌前病变，并通过早期干预延缓癌症的发生，同时保持发病率不变。技术进步催生了诸如微流控技术、人工智能、机器学习算法和电化学生物传感器等强大工具，以助力早期癌症检测。虚拟结肠镜检查和内镜超声检查等非侵入性癌症筛查方法也已得到开发，用于提供器官的全面图像并早期检测癌症。本文通过叙述性文献检索，概述了微流控技术、人工智能和生物标志物在癌症筛查方面的最新进展。微流控设备能够轻松处理亚微升体积的样品，已成为癌症检测、药物筛选以及癌症研究中血管生成和转移建模的一种有前景的工具。机器学习和人工智能在肿瘤相关诊断成像中显示出高准确率，减少了病变检测中的人工步骤，并提供标准化和准确的结果，在结肠息肉、乳腺癌以及原发性和转移性脑癌等领域具有全球标准化的潜力。基于生物标志物的癌症诊断对于早期检测和有效治疗具有前景，与纳米颗粒集成的电化学生物传感器具有多重检测和信号放大能力。了解这些先进技术的基础、成就和挑战对于推动它们在肿瘤学中的应用至关重要。
