Sachithanandan, Anand and Lockman, Hilmi and Raja Aman, Raja Rizal Azman and Mun, Tho Lye and Eng-Zhuan, Ban and Varughese, Ramon (2024) The potential role of artificial intelligence-assisted chest X-ray imaging in detecting early-stage lung cancer in the community—a proposed algorithm for lung cancer screening in Malaysia. Medical Journal of Malaysia, 79 (1). 9 – 14. ISSN 0300-5283,
Full text not available from this repository.Abstract
Introduction: The poor prognosis of lung cancer has been largely attributed to the fact that most patients present with advanced stage disease. Although low dose computed tomography (LDCT) is presently considered the optimal imaging modality for lung cancer screening, its use has been hampered by cost and accessibility. One possible approach to facilitate lung cancer screening is to implement a risk-stratification step with chest radiography, given its ease of access and affordability. Furthermore, implementation of artificial-intelligence (AI) in chest radiography is expected to improve the detection of indeterminate pulmonary nodules, which may represent early lung cancer. Materials and Methods: This consensus statement was formulated by a panel of five experts of primary care and specialist doctors. A lung cancer screening algorithm was proposed for implementation locally. Results: In an earlier pilot project collaboration, AI-assisted chest radiography had been incorporated into lung cancer screening in the community. Preliminary experience in the pilot project suggests that the system is easy to use, affordable and scalable. Drawing from experience with the pilot project, a standardised lung cancer screening algorithm using AI in Malaysia was proposed. Requirements for such a screening programme, expected outcomes and limitations of AI-assisted chest radiography were also discussed. Conclusion: The combined strategy of AI-assisted chest radiography and complementary LDCT imaging has great potential in detecting early-stage lung cancer in a timely manner, and irrespective of risk status. The proposed screening algorithm provides a guide for clinicians in Malaysia to participate in screening efforts. © 2024, Malaysian Medical Association. All rights reserved.
| Item Type: | Article |
|---|---|
| Funders: | AstraZeneca Malaysia |
| Uncontrolled Keywords: | Artificial intelligence; Cancer screening; Chest radiography; Low-dose computed tomography; Lung cancer |
| Subjects: | R Medicine |
| Divisions: | Faculty of Medicine > Biomedical Imaging Department |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 03 May 2024 08:26 |
| Last Modified: | 03 May 2024 08:26 |
| URI: | http://eprints.um.edu.my/id/eprint/44933 |
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