Lung Cancer Network Malaysia, Subang Jaya, Selangor, Malaysia.
AstraZeneca Malaysia, Mutiara Damansara, Petaling Jaya, Selangor, Malaysia.
Med J Malaysia. 2024 Jan;79(1):9-14.
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.
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.
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.
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.
肺癌预后不良的主要原因是大多数患者在疾病晚期就诊。虽然低剂量计算机断层扫描(LDCT)目前被认为是肺癌筛查的最佳影像学方法,但由于成本和可及性问题,其应用受到了阻碍。一种可能的方法是通过胸部 X 线摄影进行风险分层,因为它易于获取且价格合理。此外,人工智能(AI)在胸部 X 线摄影中的应用有望提高对不确定肺部结节的检测能力,这些结节可能代表早期肺癌。
本共识声明由五名基层医疗和专科医生组成的专家组制定。提出了一种用于局部实施的肺癌筛查算法。
在早期的试点项目合作中,AI 辅助的胸部 X 线摄影已经被纳入社区的肺癌筛查中。试点项目的初步经验表明,该系统易于使用、价格合理且具有可扩展性。根据试点项目的经验,提出了一种在马来西亚使用 AI 的标准化肺癌筛查算法。还讨论了这种筛查计划的要求、预期结果和 AI 辅助胸部 X 线摄影的局限性。
AI 辅助的胸部 X 线摄影和补充的 LDCT 成像相结合的策略具有很大的潜力,可以及时检测早期肺癌,而不论风险状况如何。所提出的筛查算法为马来西亚的临床医生参与筛查工作提供了指导。