Ivan O. Avetisov’s scientific contributions

BACKGROUND: Artificial intelligence technology can help solve the significant problem of missed findings in radiology studies. An important issue is assessing the economic benefits of implementing artificial intelligence. AIM: To evaluate the frequency of missed pathologies detection and the economic potential of artificial intelligence technology for chest computed tomography compared and validated by experienced radiologists. MATERIALS AND METHODS: This was an observational, single-center retrospective study. The study included chest computed tomography without IV contrast from June 1 to July 31, 2022, in Clinical Hospital in Yauza, Moscow. The computed tomography was processed using a complex artificial intelligence algorithm for 10 pathologies: pulmonary infiltrates, typical for viral pneumonia (COVID-19 in pandemic conditions); lung nodules; pleural effusion; pulmonary emphysema; thoracic aortic dilatation; pulmonary trunk dilatation; coronary artery calcification; adrenal hyperplasia; and osteoporosis (vertebral body height and density changes). Two experts analyzed computed tomography and compared results with artificial intelligence. Further routing was determined according to clinical guidelines for all findings initially detected and missed by radiologists. The hospital price list determined the potential revenue loss for each patient. RESULTS: From the final 160 computed tomographies, the artificial intelligence identified 90 studies (56%) with pathologies, of which 81 (51%) were missing at least one pathology in the report. The second-stage lost potential revenue for all pathologies from 81 patients was RUB 2,847,760 ($37,251 or CNY 256,218). Lost potential revenue only for those pathologies missed by radiologists but detected by artificial intelligence was RUB 2,065,360 ($27,017 or CNY 185,824). CONCLUSION: Using artificial intelligence as an assistant to the radiologist for chest computed tomography can dramatically minimize the number of missed abnormalities. Compared with the normal model without artificial intelligence, using artificial intelligence can provide 3.6 times more benefits. Using advanced artificial intelligence for chest computed tomography can save money.

Background: Artificial intelligence (AI) technologies can help solve the significant problem of missed findings in radiology studies. An important issue is assessing the economic benefits of implementing AI. Aim: to evaluate the frequency of missed pathologies detection and the economic potential of AI technology for chest CT, validated by expert radiologists, compared with radiologists without access to AI in a private medical center. Methods: An observational, single-center retrospective study was conducted. The study included chest CTs without IV contrast performed from 01.06.2022 to 31.07.2022 in "Yauza Hospital" LLC, Moscow. The CTs were processed using a complex AI algorithm for ten pathologies: pulmonary infiltrates, typical for viral pneumonia (COVID-19 in pandemic conditions); lung nodules; pleural effusion; pulmonary emphysema; thoracic aortic dilatation; pulmonary trunk dilatation; coronary artery calcification; adrenal hyperplasia; osteoporosis (vertebral body height and density changes). Two experts analyzed CTs and compared results with AI. Further routing was determined according to clinical guidelines for all findings initially detected and missed by radiologists. The lost potential revenue (LPR) was calculated for each patient according to the hospital price list. Results: From the final 160 CTs, the AI identified 90 studies (56%) with pathologies, of which 81 studies (51%) were missing at least one pathology in the report. The "second-stage" LPR for all pathologies from 81 patients was RUB 2,847,760 (＄37,251 or CNY 256,218). LPR only for those pathologies missed by radiologists but detected by AI was RUB 2,065,360 (＄27,017 or CNY 185,824). Conclusion: Using AI for chest CTs as an "assistant" to the radiologist can significantly reduce the number of missed abnormalities. AI usage can bring 3.6 times more benefits compared to the standard model without AI. The use of complex AI for chest CT can be cost-effective.