University Hospitals of North Midlands (UHNM) has announced a £1.28 million AI upgrade to its radiology training facilities, thanks to funding from NHS England Midlands which aimed to support the development of a new training model at the Midlands Imaging Training Academy (MITA).
By utilising a newly-installed XRNET high speed education network and electronics and picture archiving suite (EPACS) workstations, remote trainers are now able to teach and observe trainees in real time. As a result, one consultant can train and supervise learners across regional academy sites, freeing up time for other consultants.
EPACS is also being piloted as “a platform to develop AI learning and cooperation in imaging academies, with eye tracking teaching the AI algorithms based on human behaviours”. The trust will use this alongside the extended reality lab at the Postgraduate Medical Centre, to enable trainees to be “immersed” in spaces including an MRI scanning suite or an A&E ward, “providing lifelike, high-quality simulation training to teams of clinicians”.
Dr Ingrid Britton, director of MITA and UHNM gastrointestinal radiologist, said: “The investment from NHS England has allowed us to upgrade our facilities to provide state of the art imaging training to our imaging staff, with the potential to link classrooms across the Midlands. This expands the capacity for training and has allowed us to increase the number of trainees providing diagnostic and therapeutic services to patients on emergency, elective and cancer pathways. The new simulation facilities for ultrasound supervision, CT and vascular diagnostic and interventional procedural work provide excellent learning practice to get students work ready for the fast-paced clinical environment.”
Also from radiology, the East of England NHS Collaborative Procurement Hub has opened an opportunity to procure teleradiology services through a four-year contract worth an estimated £40 million.
From academic research, an article published last month in The Lancet, introduced the Medical AI Data for All (MAIDA) initiative, described as a “framework for global medical data sharing to address the shortage of public health data and enable rigorous evaluation of AI models across all populations”.
