Chest Imaging - Review

A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019

10.5152/dir.2019.20294

  • Rintaro Ito
  • Shingo Iwano
  • Shinji Naganawa

Received Date: 27.04.2020 Accepted Date: 03.05.2020 Diagn Interv Radiol 2020;26(5):443-448

The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of COVID-19 pneumonia. PubMed, arXiv, medRxiv, and Google scholar were used to search for AI studies. There were 15 studies of COVID-19 that used AI for medical imaging. Of these, 11 studies used AI for computed tomography (CT) and 4 used AI for chest radiography. Eight studies presented independent test data, 5 used disclosed data, and 4 disclosed the AI source codes. The number of datasets ranged from 106 to 5941, with sensitivities ranging from 0.67–1.00 and specificities ranging from 0.81–1.00 for prediction of COVID-19 pneumonia. Four studies with independent test datasets showed a breakdown of the data ratio and reported prediction of COVID-19 pneumonia with sensitivity, specificity, and area under the curve (AUC). These 4 studies showed very high sensitivity, specificity, and AUC, in the range of 0.9–0.98, 0.91–0.96, and 0.96–0.99, respectively.