COMPANY
Siemens Healthineers
Healthcare technology company based in Erlangen, Germany
Founded 1847Erlangen, Germany
AI versus radiologists in quantifying lung opacities from CT pulmonary angiography in COVID-19 patients
Product: AI-Rad Companion Chest X-ray Company: Siemens Healthineers
Quantitative assessment of lung opacities from CT of pulmonary artery imaging data in COVID-19 patients: artificial intelligence versus radiologist
BJR, Open, 2025
Abstract
Objectives
Artificial intelligence (AI) deep learning algorithms trained on non-contrast CT scans effectively detect and quantify acute COVID-19 lung involvement. Our study explored whether radiological contrast affects the accuracy of AI-measured lung opacities, potentially impacting clinical decisions. We compared lung opacity measurements from AI software with visual assessments by radiologists using CT pulmonary angiography (CTPA) images of early-stage COVID-19 patients.
Methods
This prospective single-centre study included 18 COVID-19 patients who underwent CTPA due to suspected pulmonary embolism. Patient demographics, clinical data, and 30-day and 90-day mortality were recorded. AI tool (Pulmonary Density Plug-in, AI-Rad Companion Chest CT, SyngoVia; Siemens Healthineers, Forchheim, Germany) was used to estimate the quantity of opacities. Visual quantitative assessments were performed independently by 2 radiologists.
Results
There was a positive correlation between radiologist estimations (r2 = 0.57) and between the AI data and the mean of the radiologists’ estimations (r2 = 0.70). Bland-Altman plot analysis showed a mean bias of +3.06% between radiologists and −1.32% between the mean radiologist vs AI, with no outliers outside 2×SD for respective comparison.
The AI protocol facilitated a quantitative assessment of lung opacities and showed a strong correlation with data obtained from 2 independent radiologists, demonstrating its potential as a complementary tool in clinical practice.
Conclusion
In assessing COVID-19 lung opacities in CTPA images, AI tools trained on non-contrast images, provide comparable results to visual assessments by radiologists.
Advances in knowledge
The Pulmonary Density Plug-in enables quantitative analysis of lung opacities in COVID-19 patients using contrast-enhanced CT images, potentially streamlining clinical workflows and supporting timely decision-making.