Nome e qualifica del proponente del progetto: 
sb_p_2218535
Anno: 
2020
Abstract: 

Purpose:
The aim of the study is to investigate if there are any correlation between radiological features and fat deposition between patients with a COVID-19 diagnosis, and to evaluate if adiposity parameters are associated with worse clinical outcomes such as the need of mechanical ventilation.

Materials:
It's a retrospective study in which will be enrolled Patients admitted at the Emergency Department of Sant'Andrea Hospital, Rome, Italy, who tested positive for SARS-Cov-2 and underwent a chest CT scan in March 2020. Will be included patients suspicious for COVID-19 infection tested with naso- and oro-pharyngeal swabs and that underwent chest CT. Patients whose CT could not be evaluated due to severe motion artifact or other technical issues such as restricted field of view for adipose tissue quantification or CT acquired with contrast medium will be excluded, as well as those for whom investigated clinical outcomes will be unavailable.
Data about demographic characteristics will be collected. An outcome score, Lung Severity Score (LSS) will be conferred based on the clinical and radiological assessment: 1) home discharge, 2) sub intensive hospitalization and 3) intensive care (ICU) hospitalization.
Quantification of adiposity will be performed by two different radiology resident in consensus on a commercially available workstation computer. Adiposity parameters of VAT (Visceral Adipose Tissue), TAT (Total Adipose Tissue), SAT (Subcutaneous Adipose Tissue) will be collected.

Expected results:
150 patients were identified that reflect the inclusion criteria. Preliminary data on 30 patients described that abdominal fat, and most importantly its visceral deposition, is significantly associated with radiological severity and clinical outcomes, suggesting that this may be a risk factor for SARS-CoV-2 related complications.

Conclusion:
Adiposity parameters in COVID-19 Patients could be helpful to predict the severity of disease and the Patients' outcome.

ERC: 
LS7_1
LS7_3
Componenti gruppo di ricerca: 
sb_cp_is_2814835
Innovatività: 

The use of semi-automatic software is an innovative side-tools to evaluate radiological images through the analysis of specific quantitative parameters. It could be an opportunity for progress in the management and evaluation of lung disease patients. Furthermore, having standardized data, it will be possible to compare studies with each other in order to significantly reduce the bias.

Codice Bando: 
2218535

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