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Hindi Challenges and Breakthroughs in Non-Invasive Lung Cancer Detection Methods
*Corresponding Author:Received Date: Aug 03, 2024 / Published Date: Aug 31, 2024
Copyright: © 2024 . This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
The early detection of lung cancer is crucial for improving patient outcomes and survival rates. Non-invasive methods have emerged as promising alternatives to traditional diagnostic approaches, which often involve invasive procedures and radiation exposure. This review explores the current challenges and breakthroughs in non-invasive lung cancer detection, focusing on advancements in imaging technologies, biomarker analysis, and liquid biopsy techniques. Recent developments in imaging modalities, such as low-dose computed tomography (CT) and magnetic resonance imaging (MRI), have significantly enhanced the sensitivity and specificity of lung cancer detection. However, challenges remain in differentiating benign from malignant nodules and reducing false positives. Biomarker research has identified various potential targets, including circulating tumor cells (CTCs) and tumor DNA, which can be detected through blood tests, offering a less invasive approach compared to tissue biopsies. Despite these advancements, the clinical implementation of biomarkers is limited by issues such as standardization and validation across diverse populations. Liquid biopsy, a novel technique that analyzes cell-free DNA or RNA in bodily fluids, has shown promise in early cancer detection and monitoring. This method offers the advantage of minimal invasiveness and the ability to provide real-time insights into tumor dynamics. However, its widespread adoption is hindered by challenges related to assay sensitivity, specificity, and cost. This review highlights both the progress made and the ongoing challenges in non-invasive lung cancer detection. Future research must address these limitations and focus on integrating multiple modalities to improve early detection, accuracy, and patient outcomes in lung cancer care.
