3663 - Quantifying Energy Consumption in Radiation Oncology Using Multi Modality Assessment for Sustainability and Efficiency
Presenter(s)
K. Lichter1, G. Silva2, J. Tompkins3, C. Ruschke3, and A. Witztum4; 1University of California, San Francisco Department of Radiation Oncology, San Francisco, CA, 2UCSF, San Francisco, CA, 3Mazzetti, San Francisco, CA, 4University of Oxford, Oxford, United Kingdom
Purpose/Objective(s): To quantify energy consumption across multiple imaging and treatment modalities in radiation oncology and identify opportunities for efficiency improvements by analyzing operational power states and usage patterns.
Materials/Methods: Energy usage data were collected from six imaging and treatment modalities over two-week periods: technology system medical linear accelerator LINAC, a frameless robotic radiosurgery system, GE LightSpeed VCT CT Scanner, a technology company's PET/CT Scanner, GE Discovery MR750 MRI Scanner, and GE Ultrasound LOGIQ E10. Direct metering recorded power draw across various operational states, including low-power, power-save, ready-to-scan, and scan modes. Load duration curves were generated to assess energy distribution, and manufacturer-reported specifications were compared to real-world power consumption to identify inefficiencies.
Results: A significant portion of total energy use occurred during idle periods. The medical linear accelerator LINAC spent 58.5% of its operational time in low-power mode (3.99 kW), while the frameless robotic radiosurgery system was in low-power mode 72.9% of the time (1.43 kW). The PET/CT scanner operated in low-power mode 65.4% of the time (4.69 kW), and the MRI scanner spent 65.9% of the time in low-power mode (7.98 kW), with additional cooling demands. The CT scanner had the highest idle time (83.7%, 2.69 kW), while the Ultrasound LOGIQ E10 had the lowest overall energy consumption, remaining off 49.3% of the time, with a peak draw of 1 kVA.
Conclusion: Findings highlight substantial energy expenditure in idle states, emphasizing opportunities for improved power management. Comparing metered data with manufacturer specifications suggests that enhanced auto-sleep functions, optimized power scheduling, and more efficient cooling cycles could reduce energy waste. Adoption of Energy Star-aligned efficiency features and automated standby modes could improve sustainability without impacting clinical workflows. Future efforts should focus on demonstrating long-term cost benefits, integrating energy-monitoring technologies into clinical infrastructure, and strengthening clinician advocacy. These findings support policies that incorporate energy efficiency into equipment standards and hospital infrastructure planning.