journal article·2025-01-27Open access

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

Zélie Alerte, Mateusz Chodorowski, Samy Ammari, Alex Rovira, Julien Ognard, Douraied Ben Salem

Applied Sciences· Volume 15· Issue 3

Abstract

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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Climate Change and Health Impacts · Radiation Dose and Imaging · Ultrasound in Clinical Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Service d’Imagerie Médicale, CHU Brest, University of Brest, Boulevard Tanguy Prigent, 29609 Brest Cedex, France

Service d’Imagerie Médicale, Centre Hospitalier de Landerneau, 29800 Landerneau, France

Department of Radiology, Gustave Roussy Cancer Campus, Université Paris-Saclay, 94805 Villejuif, France

BioMaps (UMR1281), Université Paris-Saclay, CNRS, INSERM, CEA, Orsay and Gustave Roussy, 94805 Villejuif, France

Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d’Hebron, Universitat Autonoma de Barcelona, 08193 Barcelona, Spain

INSERM UMR 1101, Laboratoire de Traitement de L’Information Médicale—LaTIM, Université de Bretagne Occidentale, 22, Avenue C. Desmoulins, CEDEX 3, 29238 Brest, France

Department of Radiology, Mayo Clinic, Rochester, MN 55902, USA

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