WHO Adopts Resolution to Boost Global Medical Imaging with AI Focus
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The World Health Organization's (WHO) member states have adopted a resolution aimed at addressing stark global inequalities in access to medical imaging technologies, highlighting the potential role of artificial intelligence in bridging these gaps amid rising demands from non-communicable diseases.
Resolution Adoption
The 78th World Health Assembly, held in Geneva from May 19-27, 2025, passed the resolution on strengthening medical imaging capacity on May 27, following its endorsement by the WHO Executive Board in February. The measure urges countries to develop national strategies for imaging services, including equipment procurement, workforce training, and quality assurance programs. It outlines 18 specific actions for WHO to support expansion in underserved areas, focusing on diagnostic tools like X-rays, CT scans, MRI, and ultrasound.
Background on Disparities
Global access to medical imaging remains uneven, with high-income nations boasting far superior resources. For instance, high-income countries average nearly 40 CT scanners per million people, compared to fewer than one in low- and middle-income countries (LMICs). Roughly two-thirds of the world's population lacks reliable diagnostic imaging, exacerbating challenges in detecting conditions such as cancer, heart disease, and injuries. This gap stems from limited infrastructure, funding shortages, and workforce deficits in LMICs, where non-communicable diseases now account for 74% of deaths worldwide. Demand is surging due to aging populations and increasing chronic illnesses, prompting the WHO to prioritize imaging as a cost-effective diagnostic pillar.
Reasons for the Push
The resolution responds to long-standing calls from health advocates and organizations like the International Society of Radiology, which have documented how inadequate imaging delays diagnoses and worsens outcomes in infectious diseases, pregnancies, and trauma cases. Proposed amid post-pandemic recovery efforts, it aligns with broader WHO goals to combat rising cancer burdens and improve equity in healthcare systems strained by geographical and economic barriers.
AI's Central Role
AI is positioned as a key enabler in the resolution's implementation, with potential to automate image analysis, accelerate scans, and provide decision-support tools. Healthcare firm Philips, among supporters, stated that AI could enhance workflows and make diagnostics more accessible in remote areas, though it emphasized the need for holistic strategies including data management and training. Carla Goulart Peron, Philips' chief medical officer, said: "Through the meaningful application of artificial intelligence to medical imaging, Philips is continuously improving image quality, speeding up scans, enhancing workflows, and providing automated insights to support clinical decision-making". Collaborations like Philips' partnership with Nvidia aim to develop AI models for MRI, potentially increasing resolution by up to 65% or tripling scan speeds.
Pros and Cons of AI Integration
AI offers advantages such as higher diagnostic accuracy, reduced human error, and faster processing, enabling radiologists to handle more cases efficiently. In under-resourced settings, it could support telehealth models where AI assists less-experienced operators in acquiring quality images. However, general drawbacks in AI applications include risks of algorithmic bias, over-reliance leading to performance dips among radiologists, and challenges in data privacy or integration with existing systems. Studies show AI can sometimes interfere with human judgment, potentially lowering accuracy if not calibrated properly.
Potential Impact
If implemented, the resolution could reduce diagnostic delays, lower mortality from treatable conditions, and promote sustainable healthcare models through partnerships with governments, NGOs, and private sectors. Analysts project it may help LMICs build capacity, though success hinges on funding and technology assessments to avoid outdated investments. Broader effects include cost savings from efficient imaging, but inequities persist if AI adoption favours wealthier nations.
Future Trends
Looking ahead, AI in medical imaging is expected to evolve toward cloud-based platforms, real-time 4D visualization, and integration with photon-counting CT for sharper images.blog.medicai.io+2 more Trends also point to AI aiding image-guided treatments for interventions like tumor ablation, though ethical concerns over bias and accessibility must be addressed to ensure equitable global rollout.
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