Sustainability in Radiology: Position Paper and Call to Action from ACR, AOSR, ASR, CAR, CIR, ESR, ESRNM, ISR, IS3R, RANZCR, and RSNA
Notice bibliographique
Résumé
The urgency for climate action is recognized by international government and healthcare organizations, including the United Nations (UN) and World Health Organization (WHO). Climate change, biodiversity loss, and pollution negatively impact all life on earth. All populations are impacted but not equally; the most vulnerable are at highest risk, an inequity further exacerbated by differences in access to healthcare globally. The delivery of healthcare exacerbates the planetary health crisis through greenhouse gas emissions, largely due to combustion of fossil fuels for medical equipment production and operation, creation of medical and non-medical waste, and contamination of water supplies. As representatives of radiology societies from across the globe who work closely with industry, and both governmental and non-governmental leaders in multiple capacities, we advocate together for urgent, impactful, and measurable changes to the way we deliver care by further engaging our members, policymakers, industry partners, and our patients. Simultaneous challenges including global health disparities, resource allocation, and access to care must inform these efforts. Climate literacy should be increasingly added to radiology training programs. More research is required to understand and measure the environmental impact of radiological services and inform mitigation, adaptation, and monitoring efforts. Deeper collaboration with industry partners is necessary to support innovations in the supply chain, energy utilization, and circular economy. Many solutions have been proposed and are already available, but we must understand and address barriers to implementation of current and future sustainable innovations. Finally, there is a compelling need to partner with patients to ensure that trust in the excellence of clinical care is maintained during the transition to sustainable radiology. By fostering a culture of global cooperation and rapid sharing of solutions amongst the broader imaging community, we can transform radiological practice to mitigate its environmental impact, adapt and develop resilience to current and future climate and environmental threats, and simultaneously improve access to care. This article is simultaneously published in the Canadian Association of Radiologists Journal (DOI 10.1177/08465371241321390), European Radiology (DOI 10.1007/s00330-025-11413-7), Journal of Medical Imaging and Radiation Oncology (DOI 10.1111/1754-9485.13842), Journal of the American College of Radiology (DOI 10.1016/j.jacr.2025.02.009), Korean Journal of Radiology (DOI 10.3348/kjr.2025.0125) and Radiology (DOI 10.1148/radiol.250325). The articles are identical except for minor stylistic and spelling differences in keeping with each journal’s style. Either DOI can be used when citing this article. Keywords: Climate Change, Sustainability, Resource Allocation, Radiology, Health Services Accessibility Published under a CC BY 4.0 license. © The Author(s) 2025. Editor's Note: The RSNA Board of Directors has endorsed this article.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».