Spatial covariance analysis of FDG-PET and HMPAO-SPECT for the differential diagnosis of dementia with Lewy bodies and Alzheimer's disease. (June 2022) - Ingram, Matthew; Colloby, Sean J.; Firbank, Michael J.; Lloyd, Jim J.; O'Brien, John T.; Taylor, John-Paul
Highlight: In the differential diagnosis of dementia with Lewy body and Alzhiemer's disease, spatial covariance analysis of FDG-PET significantly outperforms that of HMPAO-SPECT. With a relatively small derivation group, spatial covariance analysis of FDG-PET performed similarly to visual interpretation and a univariate quantification method. Unlike the univariate method, there was little concordance between spatial covariance analysis and visual interpretation of FDG-PET scans, implying that spatial covariance analysis and visual interpretation rely on different sources of variance to separate disease subgroups. Abstract: We investigated diagnostic characteristics of spatial covariance analysis (SCA) of FDG-PET and HMPAO-SPECT scans in the differential diagnosis of dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), in comparison with visual ratings and region of interest (ROI) analysis. Sixty-seven patients (DLB 29, AD 38) had both HMPAO-SPECT and FDG-PET scans. Spatial covariance patterns were used to separate AD and DLB in an initial derivation group (DLB n=15, AD n=19), before being forward applied to an independent group (DLB n=14, AD n=19). Visual ratings were by consensus, with ROI analysis utilising medial occipital/medial temporal uptake ratios. SCA of HMPAO-SPECT performed poorly (AUC 0.59±0.10), whilst SCA of FDG-PET (AUC 0.83±0.07) was significantly better. For FDG-PET, SCA showed similar diagnostic performance to ROI analysis (AUC 0.84±0.08) and visual rating (AUC 0.82±0.08). In contrast to ROI analysis, there was little concordance between SCA and visual ratings of FDG-PET scans. We conclude that SCA of FDG-PET outperforms that of HMPAO-SPECT. SCA of FDG-PET also performed similarly to the other analytical approaches, despite the limitations of a relatively small SCA derivation group. Compared to visual rating, SCA of FDG-PET relies on different sources of group variance to separate DLB from AD.