Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies

Featured Application: Optimizing Magnetic Resonance Imaging (MRI) eco-efficiently using fast protocols and daily management increases the number of examinations while reducing costs. Among the idle modes, the “Restart” mode cuts consumption by 9–10.6%, saving 3581–4260 kWh annually per MRI, totaling 4759–5661 MWh for the French MRI fleet. AI protocols boost throughput by 36%, cut energy use by 32%, and enable 41 protocols in 12 h versus the standard 30. Optimized protocols on French outpatient MRIs save 7900–8800 kWh per unit annually, totaling 10,500–11,600 MWh and over 500 CO₂ tons, possibly more with energy mix variations. We evaluated the energy consumption of a 3T MRI using a central monitoring system, focusing on hospital energy costs during peak winter months from 2021 to 2023. We analyzed consumption during non-productive phases like end-of-day standby and assessed their impact. For active use, we compared standard and AI-enhanced protocols on phantoms, scheduling high-demand protocols during off-peak hours to benefit from lower energy prices. Standard protocols consumed 3.4 to 15 kWh, while optimized protocols used 2.3 to 10.6 kWh, reducing consumption by 32% on average. Savings per scan ranged from EUR 0.03 to EUR 3.7. The electrical consumption of a brain MRI protocol is equivalent to that of 3–4 knee protocols or 2–3 lumbar spine protocols. Using AI-optimized protocols and management, 41 protocols can be completed in 12 h, up from 30, reducing daily costs by EUR 2.38 to EUR 29.18. Annually, AI-optimized protocols could save 7900 to 8800 kWh per MRI unit, totaling 10,500 to 11,600 MWh across France’s MRI fleet, equivalent to the yearly consumption of about 4700 to 5300 people. Optimizing MRI resource use can expand patient access while significantly reducing the associated energy footprint. These findings support the implementation of more sustainable practices in medical imaging without compromising care quality.