Radiology is experiencing unprecedented technological evolution, driven by artificial intelligence (AI), machine learning, advanced image reconstruction, hybrid imaging, and image-guided interventions. While these developments have transformed diagnostic workflows, their impact on Radiology and Imaging Technology education within Allied Health Sciences requires urgent academic attention. Conventional allied health radiology curricula primarily emphasize equipment handling and standard imaging protocols. However, contemporary practice increasingly demands familiarity with AI-assisted image acquisition, dose optimization tools, structured reporting interfaces, quantitative imaging biomarkers, and informatics-based workflow management. Inadequate exposure to these evolving domains risks creating a skills gap between academic training and clinical practice, potentially limiting professional competence and employ-ability.
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