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Sustainability in Radiology: How Can Imaging Services Go Green Without Compromising Care?

Anastasia Constantinou - anastasia.constantinou@wales.nhs.uk

University Hospital of Wales


Introduction


The health and social care sector accounts for approximately 6.3% of England’s total carbon footprint (1). As outlined in its constitution, the National Health Service (NHS) has a duty to address climate change by ensuring the “sustainable use of finite resources.” In line with this commitment, the NHS aims to achieve net-zero direct carbon emissions by 2040 (2).


In recent years, a landmark position paper by multiple international radiology societies has called for urgent and coordinated action to improve environmental sustainability within the field of radiology (3). Evidence suggests that radiology services contribute roughly 9% of the total carbon emissions within healthcare, primarily due to the high electricity demand of energy-intensive imaging equipment such as CT scanners, MRI systems, and computer workstations (4–6). These represent direct sources of emissions, while indirect sources include staff and patient travel, procurement of medical supplies, and waste management processes.


Although most research and recent systematic reviews focus on strategies to reduce energy consumption within radiology departments, this essay adopts a broader perspective. Drawing on the four key principles of sustainable healthcare proposed by the Centre for Sustainable Healthcare namely (1) disease prevention, (2) patient empowerment, (3) lean care systems, and (4) low-carbon alternatives, I will draw examples from literature to examine how these principles can be applied within radiology to promote sustainability without compromising clinical care (7).


Disease Prevention as a way of reducing the need for imaging


It has been argued that certain imaging screening programmes and early disease detection, not only can improve patient outcomes, but also reduce the carbon emissions associated with advanced stage-care. A review article by Amin et al (2025), discusses mammography, lung, hepatocellular and colorectal cancer screenings. While there is no direct quantification of the environmental benefits, they use health care expenditure and resource utilisation as proxies arguing that detection of cancer at a later stage results in more resource utilisation, including more frequent and more complex scanning. However, the effect of false positives/overdiagnosis should also be factored in. As such, many studies have highlighted that the need for further research to properly evaluate this is essential (8, 9). 


Patient empowerment as a means of reducing low value imaging


Referrers and Practitioners have a responsibility to organise clinically appropriate imaging that improves patient outcomes. However, patient involvement can play a huge role in influencing the need for imaging. Shared-decision making is essential for providing patient-centred and value-based care. The important risks and benefits of imaging need to be discussed with patients, as patients may decline ongoing surveillance scans. Empowered patients can express when repeated imaging does not improve their quality of life, reducing “habitual surveillance” that lacks evidence. Wilson et al 2024, highlight that surveillance imaging after curative intent treatment may increase patient anxiety, and have negative financial impacts and argue that a move towards personalised surveillance programmes based on patient reported symptoms and wishes will not only improve patient experience, but also reduce low value imaging (10). A further way of encouraging patient-decision making is by including the carbon footprint of a scan for decision making, analogous to “eco-labeling” in food/energy. Pilot work suggests patients value sustainability when it does not compromise care (21). 


Lean Service Delivery - Reducing unnecessary use of resources whilst maintaining service quality.


Lean service delivery in radiology focuses on reducing waste, optimizing workflow, and cutting unnecessary energy use without compromising patient care. However, In order to be able to suggest solutions for reducing waste, it is essential that we understand the main contributors of carbon footprint in the radiology department. Energy-intensive medical devices such as CT scanners, MRI systems, workstations as well as energy consumption generated by the enterprise picture archiving and communication systems (PACS) are the main culprits. This is exacerbated since a significant portion of medical equipment has been reported to remain on and non-productive for one third of the day (11). So what can be done to address this?

Reducing energy use can be achieved by powering down CT and MRI scanners or switching to “power-save” modes during idle hours. For instance, Woolen at al 2023 have shown that this can lower energy consumption by up to 25–33% and save 8–15 tonnes of CO₂ per scanner annually (12). Minimizing nonproductive equipment time through automatic workstation shutdowns and “Turn It Off” campaigns can further save thousands of kWh and several tonnes of CO₂ each year (13).

Moreover, scanning protocol optimisation and staff training can help reduce unnecessary scans, patient radiation dose and energy consumption. Simple interventions such as ensuring correct positioning and reducing unneeded scan coverage can have a significant impact on a large scale. For instance, Siegelman and Gress [14) noted a decrease in repeat rate for head CT from 13% to 0% after changes were made to acquisition protocols, technologist training, and reformat parameters. Interestingly, Schoen at al 2023, identified that reducing CT scanning times through optimising protocols, reduced energy consumption but to a much lower extent than by reducing idle state energy use (15). Additionally, a recent systematic review showed that better clinical pathways and specialist input can help reduce the need for acute CT scanning in the Emergency Department with no increase in missed diagnosis or patient harm (17).

Improving workflow efficiency by optimising how the activities in the radiology department are orchestrated can enhance patient throughput. Brodebeck et al 2019, developed a model to study patient flow in the department and associated energy consumption patterns. Besides optimising scanning times, idle time, and resource use, workflow efficiency may refer to optimising patient scheduling times and radiology workforce scheduling to reduce unnecessary commute and associated carbon emissions. Artificial intelligence (AI) tools might play an important role in this, for example by coordinating radiology appointments with other clinical appointments, booking the patient to an imaging centre closer to their home address, or identifying patients with a history of no-show and providing targeted interventions such as personalised reminders (16). 


Low carbon alternatives 

Low carbon alternatives in radiology refer to diagnostic imaging approaches that deliver equivalent or acceptable clinical outcomes while generating fewer greenhouse gas emissions across their life cycle. Ultrasound (US) has been shown to have significantly less environmental impact compared to CT or MRI. Many studies are now looking at how US (in any form including point-of-care US, or contrast-enhanced US) may be implemented to reduce need for cross-sectional imaging. A recent study demonstrated significant cost and environmental savings through the use of POCUS for detection of small bowel obstruction with comparable test characteristics (18). Significant environmental  benefits were also demonstrated in using the US for Inflammatory Bowel disease imaging (19). There is also a huge potential of using low carbon alternative equipment in the context of interventional radiology services. Shum et al 2022, have produced an excellent review illustrating ways of achieving this. For instance, using reusable equipment significantly reduces the carbon footprint with no reported difference in surgical site infections or wound contamination. 


The bigger picture

Hopefully, I have demonstrated that multiple interventions are available to enhance the environmental sustainability of imaging services. This discussion is by no means exhaustive; nevertheless, it highlights key principles and frameworks used to address the carbon footprint of radiology.

Importantly, environmental accountability is shared across all stakeholders including patients, referring clinicians, radiology staff, estate and waste managers, procurement officers, policy makers, and equipment manufacturers. Encouragingly, growing awareness within the radiology workforce has been matched by national initiatives, such as Siemens and other industry leaders working to decarbonise the supply chain, as well as regional efforts, for example, in my local hospital, to achieve the NHS target of a net-zero carbon footprint (20)

Simple measures, such as fully powering down unused equipment overnight, can significantly reduce emissions without compromising patient care. However, the impact of other interventions is more nuanced. Firstly, many studies fail to conduct a full life-cycle assessment (LCA) which is the gold standard for evaluating environmental impact across production, use, and disposal phases. For example, while artificial intelligence (AI) is often promoted for its potential to streamline imaging workflows and reduce waste, the substantial emissions associated with AI model development, training, and deployment are rarely accounted for. Secondly, broader implications including financial costs, patient satisfaction, clinical outcomes, and social dimensions such as health equity are seldom addressed in depth.

To advance truly sustainable imaging practice, further research is needed, particularly well-designed comparative and randomised controlled trials evaluating different imaging modalities, protocols, and operational strategies. Such evidence will be essential to ensure that efforts to decarbonise radiology remain clinically safe, economically feasible, and socially responsible.


References:

  1. NHS Sustainable Development Unit. (2018). Reducing the use of natural resources in health and social care: 2018 report. NHS England. https://www.england.nhs.uk/greenernhs/a-net-zero-nhs/

  2. NHS England. (no date) A net zero NHS. Available at: https://www.england.nhs.uk/greenernhs/a-net-zero-nhs/ (Accessed: 15 October 2025).

  3. Malik, A., Padget, M., Carter, S., et al. (2021). Environmental impacts of Australia’s largest health system. Resources, Conservation & Recycling, 169, 105556. https://doi.org/10.1016/j.resconrec.2021.105556

  4. Schoen, J., McGinty, G. B., & Quirk, C. (2021). Radiology in our changing climate: A call to action. Journal of the American College of Radiology, 18(7), 1041–1043. https://doi.org/10.1016/j.jacr.2021.02.009

  5. Mariampillai, J., Rockall, A., Manuellian, C., et al. (2023). The green and sustainable radiology department. Radiologie (Heidelberg). https://doi.org/10.1007/s00117-023-01189-6

  6. Rockall, A. G., Allen, B., Brown, M. J., El-Diasty, T., Fletcher, J., Gerson, R. F., Goergen, S., Marrero González, A. P., Grist, T. M., Hanneman, K., Hess, C. P., Ho, E. L. M., Salama, D. H., Schoen, J., & Sheard, S. (2025). Sustainability in radiology: Position paper and call to action from ACR, AOSR, ASR, CAR, CIR, ESR, ESRNM, ISR, IS3R, RANZCR, and RSNA. European Radiology, 35(9), 5427–5436. https://doi.org/10.1007/s00330-025-11413-7

  7. Centre for Sustainable Healthcare. (n.d.). The principles of sustainable healthcare. https://sustainablehealthcare.org.uk/about/our-story/the-principles-of-sustainable-healthcare/

  8. Vachon, C. M., et al. (2025). Decarbonising medical imaging: Insights and strategies for sustainable practice. Canadian Association of Radiologists Journal. https://journals.sagepub.com/doi/full/10.1177/08465371251323107

  9. McAlister, S., McGain, F., Petersen, M., Story, D., Charlesworth, K., Ison, G., & Barratt, A. (2022). The carbon footprint of hospital diagnostic imaging in Australia. The Lancet Regional Health – Western Pacific, 24, 100459. https://doi.org/10.1016/j.lanwpc.2022.100459

  10. DeSouza, M. N., & Charlesworth, K. (2023). Greener oncology imaging pathways: From innovation to implementation. Journal of Clinical Oncology. https://ascopubs.org/doi/10.1200/JCO.23.02475

  11. Roletto, A., Zanardo, M., Bonfitto, G. R., Catania, D., Sardanelli, F., & Zanoni, S. (2024). The environmental impact of energy consumption and carbon emissions in radiology departments: A systematic review. European Radiology Experimental, 8(1), 35. https://doi.org/10.1186/s41747-024-00424-6

  12. Woolen, S. A., Becker, A. E., Martin, A. J., et al. (2023). Ecodesign and operational strategies to reduce the carbon footprint of MRI for energy cost savings. Radiology, 307(2), e230441. https://doi.org/10.1148/radiol.230441

  13. Heye, T., Meyer, M. T., Merkle, E. M., & Vosshenrich, J. (2023). Turn it off! A simple method to save energy and CO₂ emissions in a hospital setting with focus on radiology by monitoring nonproductive energy-consuming devices. Radiology, 307(2), e230162. https://doi.org/10.1148/radiol.230162

  14. Siegelman, J. R. Q. W., & Gress, D. A. (2013). Radiology stewardship and quality improvement: The process and costs of implementing a CT radiation dose optimization committee in a medium-sized community hospital system. Journal of the American College of Radiology, 10(6), 416–422. https://doi.org/10.1016/j.jacr.2013.01.017

  15. Sachs, J. R., Schoen, J. H., Burdette, J. H., West, T. G., Geer, C. P., & Lipford, M. E. (2023). Savings in CT net scan energy consumption: Assessment using dose report metrics and comparison with savings in idle state energy consumption. Wake Forest University Medical Center Technical Report.

  16. Doo, F. X., Vosshenrich, J., Cook, T. S., Moy, L., Almeida, E. P. R. P., Woolen, S. A., Gichoya, J. W., Heye, T., & Hanneman, K. (2024). Environmental sustainability and AI in radiology: A double-edged sword. Radiology, 310(2), e232030. https://doi.org/10.1148/radiol.232030

  17. Dunne, C. L., Elzinga, J. L., Vorobeichik, A., Sudershan, S., Keto-Lambert, D., Lang, E., & Dowling, S. (2022). A systematic review of interventions to reduce computed tomography usage in the emergency department. Annals of Emergency Medicine, 80(6), 548–560. https://doi.org/10.1016/j.annemergmed.2022.06.001

  18. Brower, C. H., Baugh, C. W., Shokoohi, H., Liteplo, A. S., Duggan, N., Havens, J., Askari, R., Rehani, M. M., Kapur, T., & Goldsmith, A. J. (2022). Point-of-care ultrasound-first for the evaluation of small bowel obstruction: National cost savings, length of stay reduction, and preventable radiation exposure. Academic Emergency Medicine, 29(7), 824–834. https://doi.org/10.1111/acem.14464

  19. Massironi, S., Zilli, A., Furfaro, F., Allocca, M., Peyrin-Biroulet, L., Jairath, V., & Danese, S. (2025). Systematic review: Ultrasound goes echo-decarbonising inflammatory bowel disease care through intestinal ultrasound. Alimentary Pharmacology & Therapeutics. https://doi.org/10.1111/apt.70385

  20. NHS Supply Chain. (2024). Decarbonising diagnostics: How Siemens and NHS Supply Chain are driving sustainable innovation. https://www.supplychain.nhs.uk/news-article/decarbonising-diagnostics-how-siemens-and-nhs-supply-chain-are-driving-sustainable-innovation/

  21. Mariampillai, J., Rockall, A., Manuellian, C., Cartwright, S., Taylor, S., Deng, M., & Sheard, S. (2023). The green and sustainable radiology department. Radiologie (Heidelberg), 63(Suppl 2), 21–26. https://doi.org/10.1007/s00117-023-01189-6

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