Chinese Medical Sciences Journal ›› 2021, Vol. 36 ›› Issue (1): 66-71.doi: 10.24920/003788
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An Insight of the First Community Infected COVID-19 Patient in Beijing by Imported Case: Role of Deep Learning-Assisted CT Diagnosis
Dasheng Li1, *(
), Dawei Wang2, Nana Wang1, Haiwang Xu1, He Huang1, Jianping Dong3, Chen Xia2
- 1Department of Radiology, Beijing Haidian Section of Peking University Third Hospital (Beijing Haidian Hospital), Beijing 100080, China
2Institute of Advanced Research, Infervision Medical Technology Co., Ltd., Beijing 100025, China
3Department of Infection, Beijing Haidian Section of Peking University Third Hospital (Beijing Haidian Hospital), Beijing 100080, China;
-
Received:2020-05-28Accepted:2020-07-16Published:2021-03-31 -
Contact:Dasheng Li E-mail:724501143@qq.com
Cite this article
Dasheng Li,Dawei Wang,Nana Wang,Haiwang Xu,He Huang,Jianping Dong,Chen Xia. An Insight of the First Community Infected COVID-19 Patient in Beijing by Imported Case: Role of Deep Learning-Assisted CT Diagnosis[J].Chinese Medical Sciences Journal, 2021, 36(1): 66-71.
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Table 1
Summary of pulmonary lesions of the first imported COVID-19 patient in Beijing interpreted by a DL-based diagnostic system"
| Lesion No. | Location | Density type | Volume a (mm3) | Alerts | ||
|---|---|---|---|---|---|---|
| First visit | Second visit | Alteration b | ||||
| 1 | APLU | Solid | ND | 8.41 | + | / |
| 2 | APLU | Solid | 35.83 | 39.34 | + | / |
| 3 | ARU | Solid | ND | 3.98 | + | / |
| 4 | ARU | Solid | 9.03 | 14.76 | + | / |
| 5 | ARU | Solid | 17.97 | 21.27 | + | / |
| 6 | ARU | Solid | 9.07 | 5.28 | - | / |
| 7 | APLU | Solid | 10.24 | 23.03 | ++ | / |
| 8 | AnRU | GGO | ND | 10.40 | ++ | / |
| 9 | AnRU | Solid | 9.00 | 7.09 | - | / |
| 10 | APLU | Solid | ND | 13.60 | + | / |
| 11 | AnLU | Solid | ND | 11.53 | ++ | / |
| 12 | DRL | Solid | ND | 20.38 | ++ | / |
| 13 | DLL | Solid | 5.97 | 4.21 | - | / |
| 14 | PRU | Solid | ND | 4.85 | + | / |
| 15 | PBRL | GGO | ND | 606.17 | +++ | / |
| 16 | PBLL | Solid | ND | 11.06 | ++ | / |
| 17 | Interlobular | Solid | ND | 16.28 | ++ | / |
| 18 | MBRL | GGO | 309.42 | 140.04 | - - - | Suspected Pneumonia |
| 19 | MBRL | SM | ND | 4713.95 | ++++ | Suspected Pneumonia |
| 20 | MRM | Solid | 3.47 | 6.65 | + | / |
| 21 | PBRL | SM | 105.08 | 7784.19 | ++++ | Suspected Pneumonia |
| 22 | PBRL | GGO | ND | 46.98 | ++ | / |
| 23 | LBRL | GGO | ND | 35.46 | ++ | / |
| 24 | MBRL | GGO | ND | 215.55 | +++ | Suspected Pneumonia |
| 25 | PBRL | GGO | ND | 202.37 | +++ | / |
| 26 | PBRL | GGO | ND | 54.07 | ++ | / |
| 27 | PBRL | SM | 34.17 | 5136.25 | ++++ | Suspected Pneumonia |
| 28 | PBRL | GGO | ND | 32.30 | ++ | / |
| 29 | PBRL | SM | ND | 4821.64 | ++++ | Suspected Pneumonia |
| 30 | LBRL | mGGO | ND | 207.56 | +++ | Suspected Pneumonia |
| 31 | LBRL | GGO | ND | 43.72 | ++ | / |
| 32 | APLU | Solid | 17.11 | ND | NA | NA |
Table 1
Figure 1.
Image findings of a COVID-19 patient analyzed using deep learning (DL)-based CT diagnostic systems. (A) Ground glass opacity nodular detected on the prior CT scan developed to pneumonia-like lesions on the primary CT scan. The DL-based diagnostic system (CT Lung) detected it and quantitatively monitored the growth. (B) A new nodule on the primary CT scan was alerted as medium risk for malignancy. (C) A ground glass opacity detected in the medial basal segment of the right lower lobe on the primary CT scan was automatically registered and compared with the prior one quantitatively, with a significant volume increase to 15.68 times, which suggested the rapid development pattern of inflammatory lesion. (D) The DL-based diagnostic system (CT Pneumonia) alerted the lesion in (C) as a suspected COVID-19 lesion on the primary CT scan, which was consistent to the diagnosis by the CT Lung system. Its volume proportions of the whole lungs and of the selected pulmonary lobes were calculated."
Figure 1.
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