ROLE OF RADIOLOGY IN DIAGNOSTIC METASTATIC DISEASE: A COMPREHENSIVE SYSTEMATIC REVIEW
Background: Radiology plays a pivotal role in detecting, characterization, and managing metastatic disease. Advanced imaging modalities like ultrasound (USG), computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and hybrid techniques have become indispensable tools. AI and deep learning applications enhance diagnostic accuracy. Challenges remain in balancing sensitivity, specificity, and patient safety, but ongoing research refines techniques for early detection and precise characterization.Methods: This systematic review adhered to PRISMA 2020 principles and focused exclusively on full-text papers published in English between 2015 and 2025. Editorials and review articles without a DOI were omitted to preserve the integrity of high-quality sources. A literature review was conducted utilizing esteemed databases like ScienceDirect, PubMed, and SagePub to discover relevant studies.Result: The preliminary database search yielded over 400 relevant publications on the topic. Following a comprehensive three-stage screening process, eight papers met the specified inclusion criteria and were selected for in-depth analysis. Each study underwent a comprehensive critical assessment, enabling a thorough understanding of the role of radiology in diagnosing metastatic disease. This methodical method guaranteed that the analysis relied on high-quality evidence, corresponded with the study's aims, and was capable of producing substantial insights into this intricate relationship. Conclusion: Imaging techniques like USG, MRI, and CT are essential for detecting metastatic disease. A multimodal approach, combining strengths of these techniques, is often necessary for accurate assessment. Future advancements in imaging technology, including artificial intelligence and hybrid techniques, may further refine diagnostic precision, improving metastatic disease detection and patient outcomes.
Authors
- Yanuar Rahman (ORCID: https://orcid.org/0000-0001-9795-3809)
- Muhammad Syahputra
- Reham A. Abd El Rahman
- Rahmi Zahra
Institutions
- State Duma (RU)
- Riau University (ID)
Publication Details
- Journal
- Journal of Advance Research in Medical & Health Science (ISSN 2208-2425)
- Published
- 2025-04-08
- DOI
- https://doi.org/10.61841/ptbr3t79
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00