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

Rashed Shaikh - srashed40@outlook.com

Royal Bolton Hospital


Introduction:

With the NHS accounting for 4% of the United Kingdom’s CO2 emissions – the annual carbon footprint of Sri Lanka - and hospital radiology departments representing some of the most energy-intensive services [1], the question isn’t whether imaging services can afford to go green – it’s whether we can afford not to.  Climate change is the single biggest health threat facing humanity – rising temperatures will have a catastrophic and irreversible impact on life on Earth. Given these implications, the field of radiology is currently at a crossroads between rationalising imaging requests and providing diagnostic excellence.

Radiology departments utilise energy-intensive equipment such as CT scanners, MRI systems and interventional suites. Heye et al. estimated that the annual energy consumption of a department with three CT scanners and four MRI scanners was 614,825 kWh/yr - roughly the annual consumption of almost 140 typical UK households [2]. The use of gadolinium-based contrast agents (GBCAs) in MRI scans has also led to harmful ions entering water reservoirs through urinary excretion [3]. UV purification treatments further degrade GBCAs, leading to the release of gadolinium ions and an increased risk of adverse health effects such as nephrogenic fibrosis [4]. Interventional radiology suites pose a different challenge, in the form of single-use plastic instruments and the use of HVAC systems. A study examining the environmental impact of a single interventional radiology department in New York, USA, found that it produced an average of 23,500 kg of CO2 per week. It would take 389 young trees 10 years to eliminate this amount of carbon [5]. The increasing implementation of Artificial Intelligence (AI) in radiology poses an interesting paradox, potentially streamlining operations but also negatively affecting the environment, as the technology relies on energy-hungry infrastructure.

There is a traditional viewpoint that a “sustainable” approach in radiology compromises the speed and quality of services. However, evidence from leading institutions around the world demonstrates that sustainable practices not only significantly reduce emissions but also enhance diagnostic quality, efficiency, and patient satisfaction – proving that ‘going green’ means moving forward, not backwards. Achieving this vision requires an approach focused on three main tenets: energy optimisation, workflow transformation and resource management.


Energy Optimisation: The Low-Hanging Fruit:

A staggering amount of energy consumption happens when not actively scanning patients - in fact, a recent systematic review found that 40–91% of the energy consumed by radiological devices was classified as “non-productive” (devices “on” but not working) [1]. We wouldn’t leave our cars running overnight, yet we leave million-pound scanners idle! Shutting down these machines during idle periods not only showed huge reductions in annual energy consumption but also outlined annual cost-savings ranging from £6,766 to £10,509 per device [1]. 

Computer workstations have been identified as an easy way to reduce emissions without workflow disruptions. A 2024 study by Walters et al demonstrated that implementing an automatic power-off/on protocol for workstations out of hours, at a UK tertiary hospital, led to an annual energy saving of 17 MWh and a financial saving of £5,000, without any complaints or disturbances to normal practice [6]. These strategies are easily implementable, translating to immediate wins. When coupled with digital transformation strategies, these benefits can be multiplied exponentially.


Workflow Transformation and Digitalisation:

Radiology constantly evolves and adapts to modern-day healthcare needs. By the early 2000s, the field had naturally gravitated towards digital systems from film-based processes, both improving imaging services and acting as a catalyst for sustainable change. The COVID-19 pandemic further propagated the concept of remote work in the healthcare industry. Teleradiology and hybrid work-from-home models have been proven to lead to quicker report turnaround times (RTAT), reduced rates of physician burnout and improved patient care. A 2021 survey of US radiologists working in a hybrid teleradiology system revealed some interesting figures - 64.8% reported reduced stress levels and less workroom disturbances. 79% reported no changes in RTAT and no loss of inter-professional communication [7]. Staff commuting to and from the hospital is a considerable source of carbon emissions - implementing these work models can both curtail a trust’s carbon footprint and simultaneously boost the well-being of staff.  

The clinical potential of Artificial Intelligence (AI) in radiology cannot be understated. However, until recently, the environmental repercussions of AI have been mostly disregarded. A single large language training run can generate 200,000-850,000 kg of CO2 – the equivalent of 400-1,700 transatlantic flights [8]. Data storage centers use enormous amounts of energy and water, both for server operations and cooling. Although healthcare is adopting cloud-based solutions instead of on-site storage systems, these technologies continue to present sustainability challenges, with global cloud storage emissions surpassing the entire airline industry [8]. Radiology departments can incorporate AI tools sustainably by [8]:

  1. Sharing resources, encouraging collaboration and reusing open-source models as opposed to training new ones.

  2. Utilising energy-efficient hardware such as low-power processing units.

  3. Deploying rapid-access, low-energy storage for frequently accessed data while uploading dormant data onto slower storage media that requires less power.

  4. Partnering with data storage providers who are committed to renewable energy sources.

  5. Using non-interpretational AI tools to devise protocols such as automatic system shutdowns for scanners and screening pathways to avoid the need for low-value imaging.

Adopting a sustainable approach with AI will allow us to both maximise its capabilities and enable better resource management. 


Intelligent resource management:

Dr Sarah Sheard (consultant radiologist at Imperial College Healthcare) once said that the greenest scan is the one you don't need to do. A conservative estimate of 10 billion medical examinations per year globally implies that medical imaging accounts for approximately 1% of the overall carbon footprint. Strikingly, MRI scans produce approximately 17 times the carbon cost of an ultrasound scan, while CT scans generate roughly 6 times more emissions than ultrasound [9]. A combination of strict clinical decision-making pathways and AI informatics tools may help suggest greener modalities with similar diagnostic values. For example, it would be prudent to initially examine a gallbladder using ultrasound rather than a CT scan, if clinical needs allow.

Equipment refurbishment (instead of replacement), contrast agent recovery from hospital wastewater and pack optimisation for interventional radiology (IR) procedures (to reduce unnecessary items) are some of the many supply chain innovations that have been developed recently. The GREENWATER study from 2024 yielded some exciting findings: by asking patients to stay back for an extra 60 minutes to collect their first post-scan urine, they identified a potential recovery rate of 51% for iodinated contrast agents and 13% for gadolinium-based contrast agents. Most patients were happy to accept a prolonged hospital stay [10].

Clements et al discovered that 76% of interventional radiology equipment packaging was potentially recyclable, with more than half of it being deemed as excessive and unnecessary [11]. The Imperial College Healthcare NHS Trust accomplished annual CO2 emission savings of 234,660 kg and cost savings of £27,131, simply by switching to reusable sterile gowns in interventional radiology [12]. By implementing automated HVAC settings in IR suites and building staff awareness, we can make sure that these energy-intensive systems are switched off during non-productive hours.

A real-life success story is that of the Champalimaud Clinical Centre in Portugal – by entering a partnership with Philips HealthTech, they have slashed emissions by an immense 24% per exam, by replacing older equipment with AI-enabled equipment, integrating circular practices and transitioning to renewable energy sources. Astute waste management schemes have allowed Champalimaud to retrieve parts from older equipment and reuse them for refurbishment, mitigating landfill accumulation [13]. This proves that sustainable radiology isn’t just conceptual – it’s achievable and scalable.





Conclusion:

As healthcare workers, our duties extend beyond individual patients to global health. An ever-increasing demand for imaging will only contribute to the climate crisis. The evidence is clear - sustainable practices develop smarter workflows, increase efficiency and result in notable cost reductions. With the NHS aiming to become the world’s first net zero health service by 2040 [14], we must act now. The field of radiology has always put patients at the forefront of its ethos – now we must extend the same stewardship towards our planet.




Reference list:

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

  2. Woolen, S.A., Kim, C.J., Hernandez, A.M., Becker, A., Martin, A.J., Kuoy, E., Pevec, W.C. and Tutton, S. (2022). Radiology Environmental Impact: What Is Known and How Can We Improve? Academic Radiology, [online] 30(4). doi:https://doi.org/10.1016/j.acra.2022.10.021.

  3. Dekker, H.M., Stroomberg, G.J. and Prokop, M. (2022). Tackling the increasing contamination of the water supply by iodinated contrast media. Insights into Imaging, 13(1). doi:https://doi.org/10.1186/s13244-022-01175-x.

  4. Marckmann, P., Skov, L., Rossen, K., Dupont, A., Damholt, M.B., Heaf, J.G. and Thomsen, H.S. (2006). Nephrogenic Systemic Fibrosis: Suspected Causative Role of Gadodiamide Used for Contrast-Enhanced Magnetic Resonance Imaging. Journal of the American Society of Nephrology, 17(9), pp.2359–2362. doi:https://doi.org/10.1681/asn.2006060601.

  5. Mariampillai, J., Rockall, A., Manuellian, C., Cartwright, S., Taylor, S., Deng, M.C. and Sheard, S. (2023). Die grüne und nachhaltige Radiologieabteilung. Die Radiologie, 63. doi:https://doi.org/10.1007/s00117-023-01189-6.

  6. Walters, H., Bowden, K. and Limphaibool, N. (2024). Reducing the carbon footprint of radiology through automatic workstation shutdown protocols. Clinical Radiology, [online] 79(11), pp.e1284–e1287. doi:https://doi.org/10.1016/j.crad.2024.07.022.

  7. Petscavage-Thomas, J.M., Hardy, S. and Chetlen, A. (2022). Mitigation tactics discovered during COVID-19 with long-term RTAT and burnout reduction benefits. Academic Radiology. doi:https://doi.org/10.1016/j.acra.2022.04.016.

  8. Doo, F.X., Vosshenrich, J., Cook, T.S., Moy, L., Eduardo P.R.P. Almeida, Woolen, S.A., Judy Wawira Gichoya, Heye, T. and Hanneman, K. (2024). Environmental Sustainability and AI in Radiology: A Double-Edged Sword. Radiology, 310(2). doi:https://doi.org/10.1148/radiol.232030.

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

  10. Zanardo, M., Ambrogi, F., Asmundo, L., Cardani, R., Cirillo, G., Colarieti, A., Cozzi, A., Cressoni, M., Dambra, I., Di Leo, G., Monti, C.B., Nicotera, L., Pomati, F., Renna, L.V., Secchi, F., Versuraro, M., Vitali, P. and Sardanelli, F. (2024). The GREENWATER study: patients’ green sensitivity and potential recovery of injected contrast agents. European Radiology. doi:https://doi.org/10.1007/s00330-024-11150-3.

  11. Clements, W., Chow, J., Corish, C., Tang, V.D. and Houlihan, C. (2020). Assessing the Burden of Packaging and Recyclability of Single-Use Products in Interventional Radiology. CardioVascular and Interventional Radiology, 43(6), pp.910–915. doi:https://doi.org/10.1007/s00270-020-02427-3.

  12. DesRoche, C., Castillo, F., Sharma, S., Zigmund, B., Dobranowski, J., Sergeant, M., Varangu, L. and Hanneman, K. (2025). Climate resilient and environmentally sustainable radiology: a framework for implementation. Radiology Advances, 2(2). doi:https://doi.org/10.1093/radadv/umaf014.

  13. Philips (2024). Cutting carbon in diagnostic imaging. [online] Philips. Available at: https://www.philips.com/a-w/about/news/archive/case-studies/halving-the-carbon-footprint-of-diagnostic-imaging-at-the-champalimaud-foundation.html.

  14. NHS England (2022). Delivering a net zero NHS. [online] www.england.nhs.uk. Available at: https://www.england.nhs.uk/greenernhs/a-net-zero-nhs/.

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