Brain magnetic resonance imaging software to support dementia diagnosis in routine clinical practice: a barrier to adoption study in the National Health Service (NHS) England
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
With the rise in numbers of people living with dementia and new disease modifying therapies entering the market, there is increasing need for brain magnetic resonance imaging (MRI) for diagnosis and safety monitoring. The number of scans that need reporting is expected to rapidly grow. Clinical radiology reports are currently largely qualitative and variable in structure and content. By contrast, research software typically uses automated methods to extract quantitative metrics from brain scans.
To better understand the unmet clinical need for brain reporting software for dementia we conducted a barrier to adoption study using the Lean Assessment Process (LAP)methodology. We first assessed the role of brain imaging in the diagnostic pathway for people with suspected dementia in the NHS in England. We then explored the views of (neuro)radiologists, neurologists and psychiatrists on the potential benefits and level of acceptance of software to support brain MRI analysis, using the FMRIB software library (FSL) as a technology exemplar.
The main perceived utilities of the proposed software were: increased diagnostic confidence; support for delivery of disease modifying therapies; and the possibility to compare individual results with population norms. In addition to assessment of global atrophy, hippocampal atrophy and white matter hyperintensities, additional user requirements included assessment of microbleeds, segmentation of multiple brain structures, clear information about the control population used for reference, and possibility to compare multiple scans. The main barriers to adoption related to the limited availability of 3T MRI scanners in the UK, integration into the clinical workflow, and the need to demonstrate cost-effectiveness. These findings will guide future technical development, clinical validation, and health economic evaluation.
