A diagnostic and economic evaluation of the complex artificial intelligence algorithm aimed to detect 10 pathologies on the chest CT images

Abstract

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.