MINI REVIEW article
Front. Med.
Sec. Geriatric Medicine
This article is part of the Research TopicGeriatric Oncology: Opportunities and ChallengesView all articles
Advancing Bone Tumor Detection in Older Adults: The Impact of AI-Enhanced Medical Imaging
Provisionally accepted
- 1Yantaishan Hospital - East Campus, Yantai, China
- 2Yantai Qishan Hospital, Yantai City, Shangdong, China
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Osteosarcoma presents unique challenges in diagnosis and management, particularly among older adults, who often experience distinct clinical presentations and treatment complications. As the global demographic of individuals aged 65 and older continues to expand, the need for effective strategies to address osteosarcoma in this group becomes increasingly urgent. Medical imaging plays a major role in the detection and monitoring of bone tumors, yet traditional imaging approaches face significant challenges when applied to older adults, including age-related physiological changes and comorbidities. Recent advancements in Artificial Intelligence provide transformative potential to enhance medical imaging for osteosarcoma detection in older adults. AI-driven technologies can improve image acquisition, reduce artifacts, and automate tumor detection and segmentation, thereby increasing diagnostic accuracy and optimizing treatment strategies. This mini-review explores the critical role of AI-enhanced medical imaging in overcoming the unique challenges of diagnosing osteosarcoma in older adults, emphasizing the need for tailored algorithms and protocols that consider the specific anatomical and physiological characteristics of this vulnerable population.
Keywords: Osteosarcoma, Elderly, artificial intelligence, medical imaging, Tumor detection, geriatric oncology
Received: 03 Sep 2025; Accepted: 03 Nov 2025.
Copyright: © 2025 Liang, Li, Feng and Wei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Sirong Wei, sirongw@outlook.com
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