Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies
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 standa...
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MDPI AG
2025-01-01
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| Online Access: | https://www.mdpi.com/2076-3417/15/3/1305 |
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| author | Zélie Alerte Mateusz Chodorowski Samy Ammari Alex Rovira Julien Ognard Ben Salem Douraied |
| author_facet | Zélie Alerte Mateusz Chodorowski Samy Ammari Alex Rovira Julien Ognard Ben Salem Douraied |
| author_sort | Zélie Alerte |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-96feab9eca084ffcb03e14cd1effa8aa |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-96feab9eca084ffcb03e14cd1effa8aa2025-08-20T02:12:38ZengMDPI AGApplied Sciences2076-34172025-01-01153130510.3390/app15031305Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction StrategiesZélie Alerte0Mateusz Chodorowski1Samy Ammari2Alex Rovira3Julien Ognard4Ben Salem Douraied5Service d’Imagerie Médicale, CHU Brest, University of Brest, Boulevard Tanguy Prigent, 29609 Brest Cedex, FranceService d’Imagerie Médicale, Centre Hospitalier de Landerneau, 29800 Landerneau, FranceDepartment of Radiology, Gustave Roussy Cancer Campus, Université Paris-Saclay, 94805 Villejuif, FranceSection of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Universitat Autonoma de Barcelona, 08193 Barcelona, SpainService d’Imagerie Médicale, CHU Brest, University of Brest, Boulevard Tanguy Prigent, 29609 Brest Cedex, FranceService d’Imagerie Médicale, CHU Brest, University of Brest, Boulevard Tanguy Prigent, 29609 Brest Cedex, FranceWe 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.https://www.mdpi.com/2076-3417/15/3/1305MRIAIenergy consumptiongreen radiologycost reduction |
| spellingShingle | Zélie Alerte Mateusz Chodorowski Samy Ammari Alex Rovira Julien Ognard Ben Salem Douraied Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies Applied Sciences MRI AI energy consumption green radiology cost reduction |
| title | Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies |
| title_full | Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies |
| title_fullStr | Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies |
| title_full_unstemmed | Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies |
| title_short | Towards Sustainable Magnetic Resonance Neuro Imaging: Pathways for Energy Optimization and Cost Reduction Strategies |
| title_sort | towards sustainable magnetic resonance neuro imaging pathways for energy optimization and cost reduction strategies |
| topic | MRI AI energy consumption green radiology cost reduction |
| url | https://www.mdpi.com/2076-3417/15/3/1305 |
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