ROLE OF RADIOLOGY IN DIAGNOSTIC METASTATIC DISEASE: A COMPREHENSIVE SYSTEMATIC REVIEW
DOI:
https://doi.org/10.61841/ptbr3t79Keywords:
USG, CT Scan, MRI, imaging, metastaticAbstract
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.
References
Isaac, A., Dalili, D., Dalili, D., & Weber, M. A. (2020). State-of-the-art imaging for diagnosis of metastatic bone disease. Modernste Bildgebung zur Diagnose von Knochenmetastasen. Der Radiologe, 60(Suppl 1), 1–16. https://doi.org/10.1007/s00117-020-00666-6
Islam, S., & Walker, R. C. (2013). Advanced imaging (positron emission tomography and magnetic resonance imaging) and image-guided biopsy in initial staging and monitoring of therapy of lung cancer. Cancer journal (Sudbury, Mass.), 19(3), 208–216. https://doi.org/10.1097/PPO.0b013e318295185f
Mitsea, A., Christoloukas, N., Koutsipetsidou, S., Papavasileiou, P., Oikonomou, G., & Angelopoulos, C. (2025). Positron Emission Tomography–Magnetic Resonance Imaging, a new hybrid imaging modality for Dentomaxillofacial Malignancies—A Systematic Review. Diagnostics, 15(6), 654. https://doi.org/10.3390/diagnostics15060654
Lecouvet, F. E., Chabot, C., Taihi, L., Kirchgesner, T., Triqueneaux, P., & Malghem, J. (2024). Present and future of whole-body MRI in metastatic disease and myeloma: how and why you will do it. Skeletal radiology, 53(9), 1815–1831. https://doi.org/10.1007/s00256-024-04723-2
Najjar R. (2023). Redefining Radiology: A Review of Artificial Intelligence Integration in Medical Imaging. Diagnostics (Basel, Switzerland), 13(17), 2760. https://doi.org/10.3390/diagnostics13172760
Zheng, Q., Yang, L., Zeng, B., Li, J., Guo, K., Liang, Y., & Liao, G. (2020). Artificial intelligence performance in detecting tumor metastasis from medical radiology imaging: A systematic review and meta-analysis. EClinicalMedicine, 31, 100669. https://doi.org/10.1016/j.eclinm.2020.100669
Ong, W., Lee, A., Tan, W. C., Fong, K. T. D., Lai, D. D., Tan, Y. L., Low, X. Z., Ge, S., Makmur, A., Ong, S. J., Ting, Y. H., Tan, J. H., Kumar, N., & Hallinan, J. T. P. D. (2024). Oncologic Applications of Artificial Intelligence and Deep Learning Methods in CT Spine Imaging-A Systematic Review. Cancers, 16(17), 2988. https://doi.org/10.3390/cancers16172988
Zhan, Y., Zhang, G., Li, M., & Zhou, X. (2021). Whole-Body MRI vs. PET/CT for the Detection of Bone Metastases in Patients With Prostate Cancer: A Systematic Review and Meta-Analysis. Frontiers in Oncology, 11. https://doi.org/10.3389/fonc.2021.633833
Ohshika, S., Saruga, T., Ogawa, T., Ono, H., & Ishibashi, Y. (2021). Distinction between benign and malignant soft tissue tumors based on an ultrasonographic evaluation of vascularity and elasticity. Oncology letters, 21(4), 281. https://doi.org/10.3892/ol.2021.12542
O’Sullivan, G. J. (2015). Imaging of bone metastasis: An update. World Journal of Radiology, 7(8), 202. https://doi.org/10.4329/wjr.v7.i8.202
Rani, A., Panchaksharappa, M., Mellekatte, N., & Annigeri, R. (2016). Multimodal imaging techniques in the diagnosis of metastatic lesions. Journal of Indian Academy of Oral Medicine and Radiology, 28(4), 409. https://doi.org/ 10.4103/0972-1363.200629
Pesapane, F., Downey, K., Rotili, A., Cassano, E., & Koh, D. (2020). Imaging diagnosis of metastatic breast cancer. Insights Into Imaging, 11(1). https://doi.org/10.1186/s13244-020-00885-4
Rhee, H., & Park, M. (2020). The role of imaging in current treatment strategies for pancreatic adenocarcinoma. Korean Journal of Radiology, 22(1), 23. https://doi.org/10.3348/kjr.2019.0862
Derks, S. H. a. E., Van Der Veldt, A. a. M., & Smits, M. (2021). Brain metastases: the role of clinical imaging. British Journal of Radiology, 95(1130). https://doi.org/10.1259/bjr.20210944
Hafizar, Rahman, F., Rumanter, R., Hamid, A. R. a. H., Mochtar, C. A., Umbas, R., & Matondang, S. B. (2022). ROLE OF MAGNETIC RESONANCE IMAGING IN NODAL AND METASTATIC STAGING OF PROSTATE CANCER: A SYSTEMATIC REVIEW AND META-ANALYSIS. Indonesian Journal of Urology, 29(1). https://doi.org/10.32421/juri.v29i1.733
Armando, B., Setiawati, R., Edward, M., & Mustokoweni, S. (2023). Conventional Radiological Profile of metastatic bone Disease based on its histopathological results: A 3-Year Experience. JUXTA Jurnal Ilmiah Mahasiswa Kedokteran Universitas Airlangga, 14(2), 76–82. https://doi.org/10.20473/juxta.v14i22023.76-82
Khan, A. (2023). Role of Radiology in the Detection of Bone Metastases. Neoplasm Metastasis. https://doi.org/10.31219/osf.io/xw8jg
Dinnes, J., Ferrante di Ruffano, L., Takwoingi, Y., Cheung, S. T., Nathan, P., Matin, R. N., Chuchu, N., Chan, S. A., Durack, A., Bayliss, S. E., Gulati, A., Patel, L., Davenport, C., Godfrey, K., Subesinghe, M., Traill, Z., Deeks, J. J., Williams, H. C., & Cochrane Skin Cancer Diagnostic Test Accuracy Group (2019). Ultrasound, CT, MRI, or PET-CT for staging and re-staging of adults with cutaneous melanoma. The Cochrane database of systematic reviews, 7(7), CD012806. https://doi.org/10.1002/14651858.CD012806.pub2
Freitas, P. S., Janicas, C., Veiga, J., Matos, A. P., Herédia, V., & Ramalho, M. (2021). Imaging evaluation of the liver in oncology patients: A comparison of techniques. World journal of hepatology, 13(12), 1936–1955. https://doi.org/10.4254/wjh.v13.i12.1936
Miao J. H. (2023). The art and science of ultrasound imaging: medical applications of ultrasound in diagnosis and therapy and its impact on patient care. Cardiovascular diagnosis and therapy, 13(1), 109–111. https://doi.org/10.21037/cdt-22-537
Chudobiński, C., Świderski, B., Antoniuk, I., & Kurek, J. (2024). Enhancements in radiological detection of metastatic lymph nodes utilizing AI-Assisted ultrasound imaging data and the lymph node reporting and Data System Scale. Cancers, 16(8), 1564. https://doi.org/10.3390/cancers16081564
Hu, A., Tian, J., Deng, X., Wang, Z., Li, Y., Wang, J., Liu, L., & Li, Q. (2024). The diagnosis and management of small and indeterminate lymph nodes in papillary thyroid cancer: preoperatively and intraoperatively. Frontiers in Endocrinology, 15. https://doi.org/10.3389/fendo.2024.1484838
Miwa, S., & Otsuka, T. (2017). Practical use of imaging technique for management of bone and soft tissue tumors. Journal of Orthopaedic Science, 22(3), 391–400. https://doi.org/10.1016/j.jos.2017.01.006
Maccioni, F., Busato, L., Valenti, A., Cardaccio, S., Longhi, A., & Catalano, C. (2023). Magnetic Resonance Imaging of the Gastrointestinal Tract: Current Role, Recent Advancements and Future Prospectives. Diagnostics (Basel, Switzerland), 13(14), 2410. https://doi.org/10.3390/diagnostics13142410
Ahn, S. J., Kwon, H., Yang, J., Park, M., Cha, Y. J., Suh, S. H., & Lee, J. (2020). Contrast-enhanced T1-weighted image radiomics of brain metastases may predict EGFR mutation status in primary lung cancer. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-65470-7
Robert, P., Vives, V., Rasschaert, M., Hao, J., Soares, M., Lemaître, M., Dencausse, A., & Catoen, S. (2023). Detection of brain metastases by Contrast-Enhanced MRI: Comparison of gadopiclenol and gadobenate in a mouse model. Investigative Radiology, 59(2), 131–139. https://doi.org/10.1097/rli.0000000000001032
Yang, H., Liu, T., Wang, X., Xu, Y., & Deng, S. (2011). Diagnosis of bone metastases: a meta-analysis comparing 18FDG PET, CT, MRI and bone scintigraphy. European Radiology, 21(12), 2604–2617. https://doi.org/10.1007/s00330-011-2221-4
Zhang, C., Liang, Z., Liu, W., Zeng, X., & Mo, Y. (2023). Comparison of whole-body 18F-FDG PET/CT and PET/MRI for distant metastases in patients with malignant tumors: a meta-analysis. BMC Cancer, 23(1). https://doi.org/10.1186/s12885-022-10493-8
Taylor, S. A., Mallett, S., Miles, A., Morris, S., Quinn, L., Clarke, C. S., Beare, S., Bridgewater, J., Goh, V., Janes, S., Koh, D. M., Morton, A., Navani, N., Oliver, A., Padhani, A., Punwani, S., Rockall, A., & Halligan, S. (2019). Whole-body MRI compared with standard pathways for staging metastatic disease in lung and colorectal cancer: the Streamline diagnostic accuracy studies. Health technology assessment (Winchester, England), 23(66), 1–270. https://doi.org/10.3310/hta23660
Lecouvet, F. E., Chabot, C., Taihi, L., Kirchgesner, T., Triqueneaux, P., & Malghem, J. (2024). Present and future of whole-body MRI in metastatic disease and myeloma: how and why you will do it. Skeletal Radiology, 53(9), 1815–1831. https://doi.org/10.1007/s00256-024-04723-2
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