The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations.

IF 3.4 2区 医学 Q2 ONCOLOGY BMC Cancer Pub Date : 2025-02-25 DOI:10.1186/s12885-025-13710-2
Feifei Huang, Xiujing Lin, Yuezhen Hong, Yue Li, Yonglin Li, Wei-Ti Chen, Weisheng Chen
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Abstract

Background: Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibility and cost-effectiveness analysis of a community-based program that used a mobile low-dose computed tomography (LDCT) scan unit and discuss the operational challenges faced during its implementation.

Methods: This study was conducted in rural areas in Fujian Province, China from July 2022 to August 2022. Individuals aged 40 years and above who had not previously undergone LDCT and who were socioeconomically marginalized were included. Participants received a LDCT program from a multidisciplinary research team. Physicians analyzed the images with the assistance of artificial intelligence "InferRead CT Lung Research" and completed structured reports on their impressions. The primary evaluation indicators for mobile LDCT screening effectiveness were the lung cancer detection rate and diagnosis rate, while the main evaluation indicators for cost-effective analysis were the cost-effective ratio and early detection cost index.

Results: A total of 10,159 individuals participated in this study. The detection rates of suspected lung cancer cases and confirmed cases were 1.06% (n = 108) and 0.7% (n = 71), respectively. The cost of lung cancer screening (LCS) was ¥1,203,504 (US$188,847.71), the average cost per screening was ¥118.47 (US$18.65), and the cost effective ratios for the detection of suspected lung cancer and confirmed lung cancer were ¥11,143.56 (US$1,753.29) and ¥16,950.76 (US$2,669.94), respectively. The early detection cost indices for suspected lung cancer were 0.09 and 0.13 for confirmed lung cancer, respectively.

Conclusion: This LDCT with artificial intelligence model for LCS holds economic promise for reducing health disparities in underserved areas and promote larger populations in similar low-income country.

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在服务不足的人群中使用基于人工智能的诊断系统实施移动低剂量计算机断层扫描的可行性和成本效益。
背景:低剂量计算机断层扫描(LDCT)可显著提高肺癌的早期检出率,并将肺癌相关死亡率降低20%。然而,许多重大的筛选障碍仍然存在。本研究对一个基于社区的项目进行了初步的可行性和成本效益分析,该项目使用移动低剂量计算机断层扫描(LDCT)扫描单元,并讨论了在实施过程中面临的操作挑战。方法:本研究于2022年7月至2022年8月在中国福建省农村地区进行。年龄在40岁及以上,以前没有接受过LDCT和社会经济边缘化的个体被包括在内。参与者接受了一个多学科研究小组的LDCT计划。医生在人工智能“interread CT肺研究”的帮助下分析图像,并完成结构化的印象报告。移动LDCT筛查效果的主要评价指标为肺癌检出率和诊断率,成本效益分析的主要评价指标为成本效益比和早期发现成本指标。结果:共有10159人参与了本研究。肺癌疑似病例检出率为1.06% (n = 108),确诊病例检出率为0.7% (n = 71)。肺癌筛查(LCS)费用为1203,504元(188,847.71美元),平均每次筛查费用为118.47元(18.65美元),检测疑似肺癌和确诊肺癌的成本效益比分别为11,143.56元(1,753.29美元)和16,950.76元(2,669.94美元)。疑似肺癌的早期发现成本指数为0.09,确诊肺癌的早期发现成本指数为0.13。结论:这种具有LCS人工智能模型的LDCT具有经济前景,可以减少服务不足地区的健康差距,并在类似的低收入国家推广更多人口。
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来源期刊
BMC Cancer
BMC Cancer 医学-肿瘤学
CiteScore
6.00
自引率
2.60%
发文量
1204
审稿时长
6.8 months
期刊介绍: BMC Cancer is an open access, peer-reviewed journal that considers articles on all aspects of cancer research, including the pathophysiology, prevention, diagnosis and treatment of cancers. The journal welcomes submissions concerning molecular and cellular biology, genetics, epidemiology, and clinical trials.
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