Longitudinal cognitive decline in mild cognitive impairment subjects with early amyloid-ß neocortical deposition.

PURPOSE: The rate of clinical progression of cognitive impairment in subjects with early amyloid deposition is unknown. The primary aim of the study was to follow the rate of cognitive decline over 1 year in patients with amnestic mild cognitive impairment (aMCI) by determining amyloid retention levels in terms of standardized uptake value ratios (SUVr) that ranged from 0.85 to 1.57. The secondary objective was to compare the rate of cognitive decline between subjects with and without early amyloid positivity. METHODS: Of 66 aMCI subjects evaluated with [18F]florbetaben PET imaging and neuropsychological tests at baseline, 41 completed the 1-year follow-up. Amyloid status was determined with SUVr cut-off values generated from baseline images by visual assessment by three independent certified readers. Repeated-measures ANOVA with amyloid load and neuropsychological scores as the main effects was use to test group, time and group-by-time interactions. The Tukey post-hoc test was used to analyse all significant interactions. RESULTS: Of the 41 aMCI subjects, 38 completed the assessment according to the study protocol. Amyloid-positive (Aß+ ) subjects (N = 18, age 75.6 ± 5.8 years, six men, 12 women) showed greater clinical deterioration according to the Mattis Dementia Rating Scale (MDRS) score (p = 0.006). Amyloid-negative (Aß-) subjects (N = 20, age 72.4 ± 5.8 years, 11 men, 6 women) showed no significant changes in MDRS score over 1 year. MDRS score significantly decreased (MDRS+) in 37% of the aMCI subjects, and remained stable (MDRS-) in the remaining 63%. Among subjects with cognitive deterioration, 86% were Aß+ and 14% were Aß-, while 25% of the MDRS- subjects were Aß+ and 75% were Aß- (χ2 = 13, P = 0.0003). SUVr above 1.21 identified individuals who would show significant progression over 1 year, with a sensitivity of 67% and a specificity of 90%, as compared to Aß- subjects. The positive predictive value, negative predictive value, and likelihood ratio were 86% (95% CI 70-94%), 75% (95% CI 58-87%), 7 (95% CI 5-10). CONCLUSION: This study demonstrated that early amyloid deposition predicts cognitive decline in subjects with aMCI, with a higher rate of decline in those with SUVr above a threshold of 1.21. Detection of early amyloid positivity may help in selecting the target population for preventive therapeutic interventions and in designing treatment trials (Trial number, EudraCT 2015-001184-39).

Performance comparison of two resolution modeling PET reconstruction algorithms in terms of physical figures of merit used in quantitative imaging.

PURPOSE: Resolution modeling (RM) of PET systems has been introduced in iterative reconstruction algorithms for oncologic PET. The RM recovers the loss of resolution and reduces the associated partial volume effect. While these methods improved the observer performance, particularly in the detection of small and faint lesions, their impact on quantification accuracy still requires thorough investigation. The aim of this study was to characterize the performances of the RM algorithms under controlled conditions simulating a typical (18)F-FDG oncologic study, using an anthropomorphic phantom and selected physical figures of merit, used for image quantification. METHODS: Measurements were performed on Biograph HiREZ (B_HiREZ) and Discovery 710 (D_710) PET/CT scanners and reconstructions were performed using the standard iterative reconstructions and the RM algorithms associated to each scanner: TrueX and SharpIR, respectively. RESULTS: RM determined a significant improvement in contrast recovery for small targets (≤17 mm diameter) only for the D_710 scanner. The maximum standardized uptake value (SUVmax) increased when RM was applied using both scanners. The SUVmax of small targets was on average lower with the B_HiREZ than with the D_710. Sharp IR improved the accuracy of SUVmax determination, whilst TrueX showed an overestimation of SUVmax for sphere dimensions greater than 22 mm. The goodness of fit of adaptive threshold algorithms worsened significantly when RM algorithms were employed for both scanners. CONCLUSIONS: Differences in general quantitative performance were observed for the PET scanners analyzed. Segmentation of PET images using adaptive threshold algorithms should not be undertaken in conjunction with RM reconstructions.