Selected article for: "CT imaging and early differential diagnosis"
Author: Congliang Miao; Mengdi Jin; Li Miao; Xinying Yang; Peng Huang; Huanwen Xiong; Peijie Huang; Qi Zhao; Jiang Du; Jiang Hong
Title: Early chest computed tomography to diagnose COVID-19 from suspected patients: A multicenter retrospective study
  • Document date: 2020_3_26
    • ID: g93dacvk_4
    Snippet: According to the latest Diagnosis and Treatment Program for COVID-19 of China [6] , the diagnosis of COVID-19 requires reverse-transcription polymerase-chainreaction (RT-PCR) test, while a certain rate of false negative results has been reported [7] . Its limited production and relatively long testing period might not be conducive for screening. Accumulated clinical experience suggests that early chest computed tomography might be helpful in diff.....
    Document: According to the latest Diagnosis and Treatment Program for COVID-19 of China [6] , the diagnosis of COVID-19 requires reverse-transcription polymerase-chainreaction (RT-PCR) test, while a certain rate of false negative results has been reported [7] . Its limited production and relatively long testing period might not be conducive for screening. Accumulated clinical experience suggests that early chest computed tomography might be helpful in differential diagnosis of suspected cases. Recently, Chung, Fang and Kanne etc. had reported the chest CT imaging features of COVID19 [8] [9] [10] . Fang and Ai further studied the sensitivity of Chest CT compared to RT-PCR with relatively small sample [9, 11] . However, there is no agreed standard for how to confirm a COVID-19 patient with these features. We retrospectively collected chest CT images of suspected pneumonia patients and divided them though RT-PCR test into positive and negative group, then compared the difference of CT features between two groups. Our purpose is to use statistics methods to distinguish the imaging features of COVID-19 with other chest infectious diseases and evaluate diagnostic value of chest CT for suspected patients.

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