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The review discusses the risks posed by conventional medical imaging methods, including radiation exposure, allergic reactions, and environmental contamination. It explores recent innovations, such as advanced modalities like photon-counting computed tomography (CT) scanners and ultra-high-field magnetic resonance imaging (MRI) systems, which provide high-resolution images with reduced radiation doses. Artificial intelligence (AI) further enhances the field by automating tasks, improving image analysis, and personalizing protocols, including real-time and predictive monitoring. Non-invasive techniques, such as elastography and photoacoustic imaging, are highlighted for minimizing reliance on ionizing radiation. AI-driven strategies also address environmental concerns through the use of biodegradable contrast agents and energy-efficient technologies. Economic assessments reveal the cost-effectiveness of imaging technologies and their impact on healthcare budgets while acknowledging persistent disparities in access. The review examines contrast agents and radiation: their long-term and broad-ranging adverse health impacts and how new imaging techniques aim to eliminate or mitigate these effects. It also considers how advancements in AI improve diagnostic accuracy and workflow efficiency. Also, the integration of imaging with genomics and telemedicine is discussed, alongside efforts to address economic and accessibility challenges and promote sustainable practices. Imaging technology and AI innovations are transforming diagnostic practices and addressing existing challenges, with ongoing innovation and collaboration essential for optimizing benefits for patients, medical staff, and the environment.
Kerna et al. (Sun,) studied this question.
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