In La Radiologia medica
The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already assumed pandemic proportions, affecting over 100 countries in few weeks. A global response is needed to prepare health systems worldwide. Covid-19 can be diagnosed both on chest X-ray and on computed tomography (CT). Asymptomatic patients may also have lung lesions on imaging. CT investigation in patients with suspicion Covid-19 pneumonia involves the use of the high-resolution technique (HRCT). Artificial intelligence (AI) software has been employed to facilitate CT diagnosis. AI software must be useful categorizing the disease into different severities, integrating the structured report, prepared according to subjective considerations, with quantitative, objective assessments of the extent of the lesions. In this communication, we present an example of a good tool for the radiologist (Thoracic VCAR software, GE Healthcare, Italy) in Covid-19 diagnosis (Pan et al. in Radiology, 2020. https://doi.org/10.1148/radiol.2020200370). Thoracic VCAR offers quantitative measurements of the lung involvement. Thoracic VCAR can generate a clear, fast and concise report that communicates vital medical information to referring physicians. In the post-processing phase, software, thanks to the help of a colorimetric map, recognizes the ground glass and differentiates it from consolidation and quantifies them as a percentage with respect to the healthy parenchyma. AI software therefore allows to accurately calculate the volume of each of these areas. Therefore, keeping in mind that CT has high diagnostic sensitivity in identifying lesions, but not specific for Covid-19 and similar to other infectious viral diseases, it is mandatory to have an AI software that expresses objective evaluations of the percentage of ventilated lung parenchyma compared to the affected one.
Belfiore Maria Paola, Urraro Fabrizio, Grassi Roberta, Giacobbe Giuliana, Patelli Gianluigi, Cappabianca Salvatore, Reginelli Alfonso
Artificial intelligence, Sars-Cov-2, Structured report