【摘要】 目的探索基于CT影像的人工智能(Artificial Intelligence,AI)辅诊系统在新型冠状病毒肺炎(Coronavirus Disease2019,COVID-19)与其他社区获得性肺炎(Community Acquired Pneumonia,CAP)鉴别诊断中的应用价值。方法收集2019年1月27日至2020年2月20日103例肺炎患者,其中29例COVID-19患者,74例为排除COVID-19的CAP患者。两组患者均行MSCT扫描,应用常规阅片+AI辅诊系统辅助阅片方式对CT图像进行评价,并使用AI辅诊系统对两组患者的感染区域进行定量测量,比较两组诊断结果差异。结果 COVID-19组的AI测量值密度HU(-750,-300)感染体积和感染占比平均水平均显著高于CAP组(P<0.05)。其他测量值结果在两组间无统计学差异(P>0.05)。结论基于AI测量的结果可以作为鉴别COVID-19和CAP的补充依据,结合AI定量测量结果和人工判断可以更方便和快捷地为COVID-19提供可靠的鉴别诊断依据。更多还原

【Abstract】 Objective To explore the application value of CT images-based artificial intelligence(AI) auxiliary diagnosis system in the differential diagnosis of coronavirus disease 2019(COVID-19) and community acquired pneumonia(CAP). Methods A total of 103 patients with pneumonia from January 27, 2019 to February 20, 2020 were collected, including 29 COVID-19 patients and 74 CAP patients without COVID-19. MSCT scanning was performed in both groups. CT images were evaluated by the methods of conventional film reading and AI auxiliary diagnosis system, and the infected areas in the two groups were quantitatively measured by AI auxiliary diagnosis system. The difference of diagnosis results between the two groups were compared. Results The infection volume and infection percentage under AI measured density of HU(-750,-300) in the COVID-19 group were significantly higher than that in the CAP groups(P<0.05). There was no significant difference in other measurements beteen the two groups(P>0.05). Conclusion The results based on AI measurement can be used as a supplementary basis for identifying COVID-19 and CAP. Combining the quantitative measurement results of AI with the manual judgment can provide a more convenient and rapid identification of COVID-19.更多还原