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DOI 10.1016/j.ejrad.2026.113128

Медицинская библиотека · European journal of radiology · 2026

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

Flavell Joshua, Shaw Thomas B, Logan Benignus, Ahern Emily Gm, McElligott Caitlin At, Nestor Peter J

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Аннотация

INTRODUCTION

Differentiating behavioural variant frontotemporal dementia (bvFTD) from psychiatric misdiagnoses of the disease (often referred to as 'phenocopies') remains a major diagnostic challenge, particularly at early presentation. Although Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is often used in such cases, concomitantly acquired serial computed tomography (CT) scans are typically not analysed quantitatively for atrophy. We investigated whether longitudinal CT data could be used to distinguish bvFTD from psychiatric misdiagnoses of bvFTD, using an automated image-processing pipeline.

METHODS

In this retrospective proof-of-concept study, 112 patients from a tertiary cognitive disorders clinic who were referred with suspected bvFTD; had behavioural syndromes compatible with bvFTD; and had serial CT imaging available were screened. After image quality control, 30 patients with bvFTD and 30 psychiatric misdiagnoses of bvFTD were included. Longitudinal regional volume statistics were extracted using SynthSR for CT to Magnetic Resonance Imaging (MRI) synthesis and FastSurfer (longitudinal stream) for segmentation.

RESULTS

Annualised whole frontotemporal atrophy normalised to intracranial volume (Δ(wFT/eTIV)) and its anterior subregion counterpart (Δ(aFT/eTIV)) both significantly differed between groups after FDR correction (all q < 0.001). Δ(wFT/eTIV) showed a large effect size (Hedges' g = -1.14) and yielded an optimism-corrected area under the curve of 0.79 (95 % CI 0.66-0.89), with 80 % sensitivity, 70 % specificity, and 75 % accuracy at the Youden-optimal cutoff. Higher-resolution CT acquisitions were associated with improved synthetic MRI quality metrics.

CONCLUSION

In this proof-of-concept study, the findings show that longitudinal analysis of routinely acquired CT 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 CT and could potentially be incorporated in dementia pathways to improve bvFTD diagnosis.

Для цитирования: Flavell Joshua, Shaw Thomas B, Logan Benignus, Ahern Emily Gm, McElligott Caitlin At, Nestor Peter J. Differentiating behavioural variant frontotemporal dementia from misdiagnoses by deriving atrophy through deep-learning-based CT to MRI synthesis: A proof-of-concept study.. European journal of radiology. 2026. DOI: 10.1016/j.ejrad.2026.113128.

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