Role of Radiology in Diagnostic Metastatic Disease: a Comprehensive Systematic Review
Year: 2025
Type: review
Study design: Systematic Review
Abstract: 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.
DOI: 10.61841/ptbr3t79
Authors: M Tegar Syahputra, Yonada Rahman, Rahmawati Rahman, Rahmi Zahra
Institution: Riau University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4409273736