In the context of the COVID19 pandemic and containment, chest CT is currently frequently performed on admission, looking for suggestive signs and basic abnormalities of COVID19 compatible viral pneumonitis pending confirmation of identification of viral RNA by reverse-transcription polymerase chain reaction(PCR), with a reported sensitivity of 56-88% in the first few days, slightly higher than PCR (60%) (1). Nevertheless, currently established radiological abnormalities are not specific for COVID19 and the specificity of the chest CT is ~25% when PCR is used as a reference (1). Deconfinement and its consequences will complicate the triage of COVID patients and the role of the scanner, with the expected impact of a decrease in the prevalence of infection in the emergency department and an increase in the number of "all-round" patients, including patients with non-COVID viral infiltrates or pneumopathies. In addition, there are currently no imaging criteria to complement the clinical and biological data that can predict the progression of lung disease from the initial data.
In image processing, computational medical imaging has demonstrated its ability to predict a
therapeutic response or a particular evolution after extracting relevant anatomical,
functional or even non-visually perceptible information from the volume of images, making it
possible to construct a powerful radiomic signature or to use robust anatomical/functional
measurements to provide estimates of ventilation or vascular state. By combining these data
extracted from the scanner with the standard clinical-biological data produced at admission
during triage, our ambition is to build a predictive model using unsupervised classification
approaches capable of helping predict clinical evolution with the aim of optimizing the
management of the resource.
Other: CT-Scan
Chest CT scan on admission to the hospital
Inclusion Criteria:
- age ≥ 18 years
- clinical suspicion of COVID-19 confirmed by RT-PCR
- CT scan at ER admission
- RT-PCR sampling
Exclusion Criteria:
- CT scan failure or loss of CT data
- RT-PCR initial results unavailable
Chu Saint-Etienne
Saint-Étienne, France
Pierre CROISILLE, PhD, Principal Investigator
CHU SAINT-ETIENNE