The rapid advancements in medical imaging over the past few decades hold great promise for future diagnostic and treatment options, with hybrid imaging techniques such as PET/CT, PET/MRI, and theranostics among the most recent developments.
However, challenges have also emerged, including the high costs associated with medical imaging and the increased workload for imaging specialists, which is not matched by a proportional increase in the workforce. To maintain healthcare costs at a manageable level and prevent burnout, attrition, and a decline in image interpretation quality, various strategies have been implemented to address the growing workload. While artificial intelligence shows promise for assisting with imaging interpretation tasks (IITs) and non-interpretative tasks (NITs), some of the latter primarily consist of labour-intensive manual activities, such as answering telephone calls, administrative duties, and logistics. In this regard, reading room assistants have been deployed to varying extents to support staff and residents.