Advancements in oligometastatic breast cancer: a comprehensive review of current strategies and the role of artificial intelligence

In the dynamic landscape of Breast Cancer (BC), Oligo- Metastatic Breast Cancer (OMBC) presents unique challenges and opportunities. This comprehensive review delves into current strategies for addressing OMBC, covering locoregional and site-specific metastasis management, and addressing both surgic...

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Bibliographic Details
Published in:Journal of the Pakistan Medical Association 2024-04, Vol.74 (4 (Supple-4)), p.S117-S125
Main Authors: Mooghal, Mehwish, Ali, Muhammad Maisam, Khan, Wajiha, Ahmer, Areeba, Akbar, Maha Ghulam, Vohra, Lubna Mushtaq
Format: Article
Language:English
Subjects:
Artificial Intelligence
Breast Neoplasms - pathology
Breast Neoplasms - therapy
Female
Humans
Neoplasm Metastasis
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Summary:In the dynamic landscape of Breast Cancer (BC), Oligo- Metastatic Breast Cancer (OMBC) presents unique challenges and opportunities. This comprehensive review delves into current strategies for addressing OMBC, covering locoregional and site-specific metastasis management, and addressing both surgical and minimally invasive therapies as essential components. Moreover, the transformative role of Artificial Intelligence (AI) is spotlighted. However, while the future looks promising, several limitations need addressing, including the need for further research, especially in diverse patient populations and resource-challenged settings. AI implementation may require overcoming the lack of Electronic Health Records acceptance in resource-challenged countries, which contributes to a scarcity of large datasets for AI training. As AI continues to evolve, validation and regulatory aspects must be continually addressed for seamless integration into clinical practice. In summary, this review outlines the evolving landscape of OMBC management, emphasizing the need for comprehensive research, global collaboration, and innovative AI solutions to enhance patient care and outcomes.
ISSN:0030-9982
0030-9982
DOI:10.47391/JPMA.AKU-9S-18