Hybrid imaging in dementia: A semi-quantitative ((18)F)-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging approach in clinical practice

Neurodegenerative disorders may demonstrate typical lobar and regional patterns of volume loss with corresponding decreased glucose metabolism. In this retrospective study, we correlated semi-quantitative volumetric changes utilizing NeuroQuant morphometric analysis with decreased fluorodeoxyglucose (FDG) uptake age-matched calculated z-scores utilizing (18)F-FDG positron emission tomography/magnetic resonance imaging (PET/MRI). Eighty-nine patients (mean age 71.4) with clinical findings suggestive of various subtypes of dementia underwent PET/MR brain imaging. Cases were categorized as follows: Alzheimer's dementia (AD), frontotemporal lobar degeneration (FTLD), dementia with Lewy bodies (DLB), and corticobasal degeneration (CBD). NeuroQuant software provided semi-quantitative assessment of lobar-specific patterns of volume loss compared to age-matched controls. MIMneuro software provided semi-quantitative FDG uptake data, with metabolic z-scores generated in comparison to age-matched controls. Volumetric and metabolic data were then correlated for statistical significance. In 29 AD cases, Pearson correlation coefficient between z-score and lobar volume was 0.3 (P = 0.120) and 0.38 (P < 0.05), for parietal and temporal lobes, respectively. In 34 FTLD cases, it was 0.35 (P = 0.051) and 0.02 (P = 0.916), for frontal and temporal lobes, respectively. In 14 DLB cases, it was 0.42 (P = 0.130), 0.5 (P = 0.067), and 0.22 (P = 0.447) for the occipital lobes, middle occipital gyrus, and parietal lobes, respectively. In 12 CBD cases, it was 0.58 (P < 0.05) for the superior parietal lobule. Semi-quantitative (F18)-FDG PET/MRI analysis demonstrated a positive relationship between volumetric loss and hypometabolism within certain lobar-specific regions, depending on neurodegenerative disorder subtype. Our findings may add diagnostic confidence in the accurate imaging diagnosis of neurodegenerative disease.