Differentiating behavioural variant frontotemporal dementia from misdiagnoses by deriving atrophy through deep-learning-based CT to MRI synthesis: A proof-of-concept study.

In this proof-of-concept study, the findings show that longitudinal analysis of routinely acquired computed tomography scans can capture disease-relevant atrophy trajectories and may provide a practical adjunct for differentiating bvFTD from psychiatric misdiagnoses of bvFTD, provided image quality and longitudinal consistency are sufficient.

This approach can re-purpose routinely acquired computed tomography and could potentially be incorporated in dementia pathways to improve bvFTD diagnosis.