Validation of image-derived input function using a long axial field of view PET/CT scanner for two different tracers.

BACKGROUND: Accurate image-derived input function (IDIF) from highly sensitive large axial field of view (LAFOV) PET/CT scanners could avoid the need of invasive blood sampling for kinetic modelling. The aim is to validate the use of IDIF for two kinds of tracers, 3 different IDIF locations and 9 different reconstruction settings. METHODS: Eight [18F]FDG and 10 [18F]DPA-714 scans were acquired respectively during 70 and 60 min on the Vision Quadra PET/CT system. PET images were reconstructed using various reconstruction settings. IDIFs were taken from ascending aorta (AA), descending aorta (DA), and left ventricular cavity (LV). The calibration factor (CF) extracted from the comparison between the IDIFs and the manual blood samples as reference was used for IDIFs accuracy and precision assessment. To illustrate the effect of various calibrated-IDIFs on Patlak linearization for [18F]FDG and Logan linearization for [18F]DPA-714, the same target time-activity curves were applied for each calibrated-IDIF. RESULTS: For [18F]FDG, the accuracy and precision of the IDIFs were high (mean CF ≥ 0.82, SD ≤ 0.06). Compared to the striatum influx (Ki) extracted using calibrated AA IDIF with the updated European Association of Nuclear Medicine Research Ltd. standard reconstruction (EARL2), Ki mean differences were < 2% using the other calibrated IDIFs. For [18F]DPA714, high accuracy of the IDIFs was observed (mean CF ≥ 0.86) except using absolute scatter correction, DA and LV (respectively mean CF = 0.68, 0.47 and 0.44). However, the precision of the AA IDIFs was low (SD ≥ 0.10). Compared to the distribution volume (VT) in a frontal region obtained using calibrated continuous arterial sampler input function as reference, VT mean differences were small using calibrated AA IDIFs (for example VT mean difference = -5.3% using EARL2), but higher using calibrated DA and LV IDIFs (respectively + 12.5% and + 19.1%). CONCLUSIONS: For [18F]FDG, IDIF do not need calibration against manual blood samples. For [18F]DPA-714, AA IDIF can replace continuous arterial sampling for simplified kinetic quantification but only with calibration against arterial blood samples. The accuracy and precision of IDIF from LAFOV PET/CT system depend on tracer, reconstruction settings and IDIF VOI locations, warranting careful optimization.

Association Between Years of Education and Amyloid Burden in Patients With Subjective Cognitive Decline, MCI, and Alzheimer Disease.

OBJECTIVES: Higher-educated patients with Alzheimer disease (AD) can harbor greater neuropathologic burden than those with less education despite similar symptom severity. In this study, we assessed whether this observation is also present in potential preclinical AD stages, namely in individuals with subjective cognitive decline and clinical features increasing AD likelihood (SCD+). METHODS: Amyloid-PET information ([18F]Flutemetamol or [18F]Florbetaben) of individuals with SCD+, mild cognitive impairment (MCI), and AD were retrieved from the AMYPAD-DPMS cohort, a multicenter randomized controlled study. Group classification was based on the recommendations by the SCD-I and NIA-AA working groups. Amyloid PET images were acquired within 8 months after initial screening and processed with AMYPYPE. Amyloid load was based on global Centiloid (CL) values. Educational level was indexed by formal schooling and subsequent higher education in years. Using linear regression analysis, the main effect of education on CL values was tested across the entire cohort, followed by the assessment of an education-by-diagnostic-group interaction (covariates: age, sex, and recruiting memory clinic). To account for influences of non-AD pathology and comorbidities concerning the tested amyloid-education association, we compared white matter hyperintensity (WMH) severity, cardiovascular events, depression, and anxiety history between lower-educated and higher-educated groups within each diagnostic category using the Fisher exact test or χ2 test. Education groups were defined using a median split on education (Md = 13 years) in a subsample of the initial cohort, for whom this information was available. RESULTS: Across the cohort of 212 individuals with SCD+ (M(Age) = 69.17 years, F 42.45%), 258 individuals with MCI (M(Age) = 72.93, F 43.80%), and 195 individuals with dementia (M(Age) = 74.07, F 48.72%), no main effect of education (ß = 0.52, 95% CI -0.30 to 1.58), but a significant education-by-group interaction on CL values, was found (p = 0.024) using linear regression modeling. This interaction was driven by a negative association of education and CL values in the SCD+ group (ß = -0.11, 95% CI -4.85 to -0.21) and a positive association in the MCI group (ß = 0.15, 95% CI 0.79-5.22). No education-dependent differences in terms of WMH severity and comorbidities were found in the subsample (100 cases with SCD+, 97 cases with MCI, 72 cases with dementia). DISCUSSION: Education may represent a factor oppositely modulating subjective awareness in preclinical stages and objective severity of ongoing neuropathologic processes in clinical stages.

Neuropsychological functioning after COVID-19: minor differences between individuals with and without persistent complaints after SARS-CoV-2 infection.

Objective: It is unclear how self-reported severe fatigue and difficulty concentrating after SARS-CoV-2 infection relate to objective neuropsychological functioning. The study aimed to compare neuropsychological functioning between individuals with and without these persistent subjective complaints. Method: Individuals with and without persistent severe fatigue (Checklist Individual Strength (CIS) fatigue ≥ 35) and difficulty concentrating (CIS concentration ≥ 18) at least 3 months after SARS-CoV-2 infection were included. Neuropsychological assessment was performed on overall cognitive functioning, attention, processing speed, executive functioning, memory, visuo-construction, and language (18 tests). T-scores -1.5 SD below population normative data (T ≤ 35) were classified as "impaired". Results: 230 participants were included in the study, of whom 22 were excluded from the analysis due to invalid performance. Of the participants included in the analysis, 111 reported persistent complaints of severe fatigue and difficulty concentrating and 97 did not. Median age was 54 years, 59% (n = 126) were female, and participants were assessed a median of 23 months after first infection (IQR: 16-28). With bivariate logistic regression, individuals with persistent complaints had an increased likelihood of slower information processing speed performance on the Stroop word reading (OR = 2.45, 95%CI = 1.02-5.84) compared to those without persistent complaints. Demographic or clinical covariates (e.g. hospitalization) did not influence this association. With linear regression techniques, persistent complaints were associated with lower t-scores on the D2 CP, TMT B, and TMT B|A. There were no differences in performance on the other neuropsychological tests. Conclusions: Individuals with subjective severe fatigue and difficulty concentrating after COVID-19 do not typically demonstrate cognitive impairment on extensive neuropsychological testing.