Afat Saif, Wohlers Julian, Herrmann Judith, Brendlin Andreas S, Gassenmaier Sebastian, Almansour Haidara, Werner Sebastian, Brendel Jan M, Mika Alexander, Scherieble Christoph, Notohamiprodjo Mike, Gatidis Sergios, Nikolaou Konstantin, Küstner Thomas
Department of Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany.
Department of Magnetic Resonance Product Management, Siemens Healthineers, Erlangen, Germany.
Eur Radiol. 2025 Apr;35(4):1993-2004. doi: 10.1007/s00330-024-11056-0. Epub 2024 Sep 7.
The unprecedented surge in energy costs in Europe, coupled with the significant energy consumption of MRI scanners in radiology departments, necessitates exploring strategies to optimize energy usage without compromising efficiency or image quality. This study investigates MR energy consumption and identifies strategies for improving energy efficiency, focusing on musculoskeletal MRI. We assess the potential savings achievable through (1) optimizing protocols, (2) incorporating deep learning (DL) accelerated acquisitions, and (3) optimizing the cooling system.
Energy consumption measurements were performed on two MRI scanners (1.5-T Aera, 1.5-T Sola) in practices in Munich, Germany, between December 2022 and March 2023. Three levels of energy reduction measures were implemented and compared to the baseline. Wilcoxon signed-rank test with Bonferroni correction was conducted to evaluate the impact of sequence scan times and energy consumption.
Our findings showed significant energy savings by optimizing protocol settings and implementing DL technologies. Across all body regions, the average reduction in energy consumption was 72% with DL and 31% with economic protocols, accompanied by time reductions of 71% (DL) and 18% (economic protocols) compared to baseline. Optimizing the cooling system during the non-scanning time showed a 30% lower energy consumption.
Implementing energy-saving strategies, including economic protocols, DL accelerated sequences, and optimized magnet cooling, can significantly reduce energy consumption in MRI scanners. Radiology departments and practices should consider adopting these strategies to improve energy efficiency and reduce costs.
MRI scanner energy consumption can be substantially reduced by incorporating protocol optimization, DL accelerated acquisition, and optimized magnetic cooling into daily practice, thereby cutting costs and environmental impact.
Optimization of protocol settings reduced energy consumption by 31% and imaging time by 18%. DL technologies led to a 72% reduction in energy consumption of and a 71% reduction in time, compared to the standard MRI protocol. During non-scanning times, activating Eco power mode (EPM) resulted in a 30% reduction in energy consumption, saving 4881 € ($5287) per scanner annually.
欧洲能源成本前所未有的飙升，再加上放射科MRI扫描仪的大量能源消耗，使得有必要探索在不影响效率或图像质量的情况下优化能源使用的策略。本研究调查了MR能源消耗，并确定了提高能源效率的策略，重点是肌肉骨骼MRI。我们评估了通过以下方式可实现的潜在节能效果：（1）优化协议；（2）纳入深度学习（DL）加速采集；（3）优化冷却系统。
2022年12月至2023年3月期间，在德国慕尼黑的两家医疗机构对两台MRI扫描仪（1.5-T Aera、1.5-T Sola）进行了能源消耗测量。实施了三个级别的节能措施，并与基线进行比较。采用Bonferroni校正的Wilcoxon符号秩检验来评估序列扫描时间和能源消耗的影响。
我们的研究结果表明，通过优化协议设置和实施DL技术可显著节能。在所有身体部位，DL使能源消耗平均降低72%，经济协议使能源消耗平均降低31%，与基线相比，时间分别减少了71%（DL）和18%（经济协议）。在非扫描时间优化冷却系统，能源消耗降低了30%。
实施节能策略，包括经济协议、DL加速序列和优化的磁体冷却，可显著降低MRI扫描仪的能源消耗。放射科和医疗机构应考虑采用这些策略来提高能源效率并降低成本。
将协议优化、DL加速采集和优化的磁体冷却纳入日常实践可大幅降低MRI扫描仪的能源消耗，从而降低成本和环境影响。
协议设置的优化使能源消耗降低了31%，成像时间缩短了18%。与标准MRI协议相比，DL技术使能源消耗降低了72%，时间减少了71%。在非扫描时间激活节能模式（EPM）可使能源消耗降低30%，每台扫描仪每年节省4881欧元（5287美元）。
