Opportunities to reduce the radiation exposure during computed tomography to assess the changes in the lungs in patients with COVID-19: use of adaptive statistical iterative reconstruction

BACKGROUND: Several COVID-19 patients are subjected to multiple imaging examinations during hospitalization, the cumulative effect of which can significantly increase total dose radiation received. The effective be reduced by lowering current and voltage X-ray tube, but this reduces image quality. One possible solution is use adaptive statistical iterative reconstruction technology on raw CT data. Recently, data efficacy low-dose (LDCT) in diagnosis have appeared literature. AIM: To analyze quality diagnostic value LDCT images lungs after applying an processing algorithm assess possibility reducing load patient when diagnosing COVID-19. MATERIALS AND METHODS: Patients from Infectious Diseases Department Moscow State University Hospital participated prospective study. were performed at time admission discharge repeated as needed hospitalization. In first study, a standard protocol with tube 120 kV automatic modulation range 200400 mA was used; scans, LDKT used parameters (100 or 110 kV) 40120 mA. comparison CT, survey conducted among doctors Radiation Diagnostics Hospital. questionnaire included two methods for identifying following pathological processes: ground-glass opacities, compaction lung tissue reticular changes, areas consolidation, lymphadenopathy. RESULTS: study 151 patients. average age 5814.2 years, men accounting 53.6% population. During 2.96 times average, CTDI 2.6 times, DLP 3.1 1.83 1.2 times. results indicate that effectiveness detecting main signs viral pneumonia assessing dynamics condition does not differ according protocol. CONCLUSIONS: show there no significant loss information reduced. Thus, chest successfully diagnose routine practice.