Energy consumption in MRI: Determinants and management options.

J Neuroradiol

Service d'Imagerie Médicale, CHU Brest, Univ. Brest, Boulevard Tanguy Prigent, Brest CEDEX, 29609, France; INSERM UMR 1101, Laboratoire de Traitement de L'Information Médicale - LaTIM, Université de Bretagne Occidentale, 22, Avenue C. Desmoulins, Brest 29238 Cedex 3, France.

Published: March 2024

Background: Energy consumption awareness is a known concern, and radiology departments have energy-intensive consuming machines. The means of energy consumption management in MRI scanners have yet to be evaluated.

Purpose: To measure the MRI energy consumption and to evaluate the means to reduce it.

Materials And Methods: Data was retrieved for two MRI scanners through the hospital's automated energy consumption measurement software. After correlation with picture archiving and communication system (PACS) files, they were segmented by machine and mode (as follows: stand-by, idle and active) and analyzed. Active mode data for a specific brain MRI protocol have been isolated, and equivalent low energy consuming protocol was made. Both were performed on phantom and compared. Same protocol was performed on a phantom using 3.0T 16 and 32 head channels coils. Multiples sequences were acquired on phantom to evaluate power consumption.

Results: Stand-by mode accounted for 60 % of machine time and 40 % of energy consumption, active mode accounted for 20 % machine time and 40 % energy consumption, idle mode for 20 % imachine time and 20 % consumption. DWI and TOF sequences were the most consuming in our brain-MRI protocol. The low energy consuming protocol allowed a saving of approximately 10 % of energy consumption, which amounted for 0.20€ for each examination. This difference was mainly due to an energy consumption reduction of the DWI sequence. There were no difference in consumption between a 3.0T 16 and 32 channels head coils. Sequence's active power and duration (especially considering slice thickness) have to be taken into account when trying to optimize energy consumption.

Conclusion: There are two key factors to consider when trying to reduce MRI scan energy consumption. Stand-by mode energy consumption has to be taken into account when choosing an MRI scan, as it can't be changed further on. Active mode energy consumption is dependent of the MRI protocols used, and can be reduced with sequences adaptation, which must take into account sequence's active power and duration, on top of image quality.

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Source
http://dx.doi.org/10.1016/j.neurad.2023.12.001DOI Listing

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