During the lockdown we worked on a scientific research with a clinical partner and our work is now available as pre-print on the European Journal of Radiology. All the visualization has been done using our DICOM.Vision.

We quantified the volume of low perfusion lung tissue, independently by the amount of contrast media, using the following method. The previously mentioned range of HU for hypoperfused threshold (HU < -890) in the control group was on average 13.3% of the total HU range air to contrast media in pulmonary artery. We then assumed this percentage, and calculated patient-specific threshold for hypoperfused tissue, on the basis of HU range from air to pulmonary artery. To estimate the percentage of lung volume characterized by hypoperfusion, we segmented the lung volume of the CT scans by automatic lung segmentation using the u-net (R231) convolutional network, a model trained on a large dataset including COVID-19 CT slices. Segmentation on individual slices allowed to extract the right and left lung mask separately, with the trachea not included in the lung segmentation. We labeled each pixel inside the lung mask as low perfusion or normal perfusion based on the patient-specific thresholds

In the 5 patients studied with contrast media, 3 were those that reported dyspnea with minimal effort, while the other 2 had no such symptom. At CT evaluation, no signs of thromboembolism were present in all these patients. Of interest, in the 3 patients affected by dyspnea color map representation showed diffuse hypoperfused areas (dark red/violet) not uniform between the left and right lung. Quantification of hypoperfused lung volume showed that, while in normal controls this volume was in average 8.5%, in these patients, that reported dyspnea, the volume ranged from 21.0% to 48.4%. Of interest, tissue lung perfusion was normal in the two patients without dyspnea, with hypoperfused lung volume of 7.4% and 8.5%, respectively. Thus, the presence of dyspnea was associated with hypoperfused lung volume rather than with abnormal lung ventilation at CT.

In summary, the main message from our observation is that in discharged COVID-19 patients still reporting dyspnea, chest CT should be used to quantify the presence of lung perfusion dysfunction. This is important not only for diagnosis, but also to determine the incidence of these complications, whether this damage to the lung microcirculation will resolve with time and the need for specific pharmacological interventions. The second message is that it is important to follow COVID-19 patients during recovery to estimate the. Deeper knowledge of these pathological processes it is very important for this increasing in size patient population due to the ongoing SARS-CoV-2 outbreak. While extensive investigation with CT in discharged COVID19 patients is in progress by our center and by others, we believe it is urgent to draw attention to these lung complications.