Artificial intelligence-enabled rapid diagnosis of patients with COVID-19
Artificial intelligence-enabled rapid diagnosis of patients with COVID-19
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DOI：
10.1038/s41591-020-0931-3
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发表时间：
2020-05-19
期刊：
影响因子：
82.9
通讯作者：
Yang, Yang
中科院分区：
文献类型：
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作者：
Mei, Xueyan;Lee, Hao-Chih;Yang, Yang
对于2019冠状病毒病（COVID-19）的诊断，常规使用SARS-CoV-2病毒特异性逆转录酶聚合酶链反应（RT-PCR）检测。然而，这一检测可能需要长达2天的时间才能完成，可能需要进行系列检测以排除假阴性结果的可能性，目前RT-PCR检测试剂盒短缺，这突显出迫切需要替代方法来快速准确地诊断COVID-19患者。胸部计算机断层扫描（CT）是评估疑似SARS-CoV-2感染患者的有价值的组成部分。尽管如此，单独的CT对排除SARS-CoV-2感染的阴性预测值可能有限，因为一些患者在疾病的早期阶段可能有正常的放射学表现。在这项研究中，我们使用人工智能（AI）算法将胸部CT结果与临床症状、暴露史和实验室检测相结合，以快速诊断COVID-19阳性患者。在通过实时RT-PCR检测和下一代测序RT-PCR检测的总共905名患者中，419名（46.3%）检测出SARS-CoV-2阳性。在279名患者的测试集中，AI系统的曲线下面积为0.92，与高级胸部放射科医生相比具有相同的灵敏度。AI系统还通过RT-PCR提高了对CT扫描正常的COVID-19阳性患者的检测，正确识别了25名患者中的17名（68%），而放射科医生将所有这些患者归类为COVID-19阴性。当CT扫描和相关的临床病史可用时，拟议的人工智能系统可以帮助快速诊断COVID-19患者。与高级放射科医生相比，集成胸部计算机断层扫描和临床信息的人工智能算法可以诊断COVID-19。
For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of patients with COVID-19. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiological findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history and laboratory testing to rapidly diagnose patients who are positive for COVID-19. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of patients who were positive for COVID-19 via RT-PCR who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.Artificial intelligence algorithms integrating chest computed tomography scans and clinical information can diagnose COVID-19 with similar accuracy as compared to a senior radiologist.