Purpose
An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating 18FFDG PET brain datasets of healthy controls (HC), based on ...publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level.
Methods
Selection of HC images was based on visual rating, after Cook’s distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB.
Results
Two-step Cook’s distance analysis and the subsequent jack-knife analysis resulted in the selection of
n
= 125 subjects from the AIMN-HC dataset and
n
= 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes.
Conclusions
The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.
OBJECTIVETo evaluate the statistical parametric mapping (SPM) procedure for fluorodeoxyglucose (FDG)-PET imaging as a possible single-subject marker of progression to dementia in Parkinson disease ...(PD).
METHODSFifty-four consecutive patients with PD without dementia (age at onset of 59.9 ± 10.1 years, disease duration of 5.3 ± 3.4 years) entered the study. The patients underwent an extensive motor and cognitive assessment and a single-subject FDG-PET SPM evaluation at baseline. A 4-year follow-up provided disease progression and dementia diagnosis.
RESULTSThe FDG-PET SPM was evaluated by 2 expert raters allowing the identification of a “typical PD pattern” in 29 patients, whereas 25 patients presented with “atypical patterns,” namely, dementia with Lewy bodies (DLB)-like (n = 12), Alzheimer disease (AD)-like (n = 6), corticobasal syndrome (CBS)-like (n = 5), and frontotemporal dementia (FTD)-like (n = 2). At 4-year follow-up, 13 patients, all showing atypical brain metabolic patterns at baseline, progressed to dementia (PD dementia). The DLB- and AD-like SPM patterns were the best predictor for incident dementia (p < 0.005, sensitivity 85%, specificity 88%), independently from demographics or cognitive baseline classification.
CONCLUSIONSThis study suggests that FDG-PET SPM at the single-subject level might help in identifying patients with PD at risk of developing dementia.
To explore the effects of PD pathology on brain connectivity, we characterized with an emergent computational approach the brain metabolic connectome using 18FFDG-PET in early idiopathic PD patients. ...We applied whole-brain and pathology-based connectivity analyses, using sparse-inverse covariance estimation in thirty-four cognitively normal PD cases and thirty-four age-matched healthy subjects for comparisons. Further, we assessed high-order resting state networks by interregional correlation analysis. Whole-brain analysis revealed altered metabolic connectivity in PD, with local decreases in frontolateral cortex and cerebellum and increases in the basal ganglia. Widespread long-distance decreases were present within the frontolateral cortex as opposed to connectivity increases in posterior cortical regions, all suggestive of a global-scale connectivity reconfiguration. The pathology-based analyses revealed significant connectivity impairment in the nigrostriatal dopaminergic pathway and in the regions early affected by α-synuclein pathology. Notably, significant connectivity changes were present in several resting state networks especially in frontal regions. These findings expand previous imaging evidence of altered connectivity in cognitively stable PD patients by showing pathology-based connectivity changes and disease-specific metabolic architecture reconfiguration at multiple scale levels, from the earliest PD phases. These alterations go well beyond the known striato-cortical connectivity derangement supporting in vivo an extended neural vulnerability in the PD synucleinopathy.
Early-onset Alzheimer's disease (EOAD) is characterized by young age of onset (< 65 years), severe neurodegeneration, and rapid disease progression, thus differing significantly from typical ...late-onset Alzheimer's disease. Growing evidence suggests a primary role of neuroinflammation in AD pathogenesis. However, the role of microglia activation in EOAD remains a poorly explored field. Investigating microglial activation and its influence on the development of synaptic dysfunction and neuronal loss in EOAD may contribute to the understanding of its pathophysiology and to subject selection in clinical trials. In our study, we aimed to assess the amount of neuroinflammation and neurodegeneration and their relationship in EOAD patients, through positron emission tomography (PET) measures of microglia activation and brain metabolic changes.
We prospectively enrolled 12 EOAD patients, classified according to standard criteria, who underwent standard neurological and neuropsychological evaluation, CSF analysis, brain MRI, and both
F-FDG PET and
C-(R)-PK11195 PET. Healthy controls databases were used for statistical comparison.
F-FDG PET brain metabolism in single subjects and as a group was assessed by an optimized SPM voxel-wise single-subject method.
C-PK11195 PET binding potentials were obtained using reference regions selected with an optimized clustering procedure followed by a parametric analysis. We performed a topographic interaction analysis and correlation analysis in AD-signature metabolic dysfunctional regions and regions of microglia activation. A network connectivity analysis was performed using the interaction regions of hypometabolism and
C-PK11195 PET BP increases.
EOAD patients showed a significant and extended microglia activation, as
C-PK11195 PET binding potential increases, and hypometabolism in typical AD-signature brain regions, i.e., temporo-parietal cortex, with additional variable frontal and occipital hypometabolism in the EOAD variants. There was a spatial concordance in the interaction areas and significant correlations between the two biological changes. The network analysis showed a disruption of frontal connectivity induced by the metabolic/microglia effects.
The severe microglia activation characterizing EOAD and contributing to neurodegeneration may be a marker of rapid disease progression. The coupling between brain glucose hypometabolism and local immune response in AD-signature regions supports their biological interaction.
In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to ...Alzheimer's disease (AD) dementia and non-AD dementias.
We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as “typical-AD”, “atypical-AD” (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), “non-AD” (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or “negative” patterns. To perform the statistical analyses, the individual patterns were grouped either as “AD dementia vs. non-AD dementia (all diseases)” or as “FTD vs. non-FTD (all diseases)”. Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated.
The multivariate logistic model identified FDG-PET “AD” SPM classification (Expβ = 19.35, 95% C.I. 4.8–77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64–25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The “FTD” SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1–63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55–70.46, p < 0.001).
Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.
•Appropriate biomarkers measures improve early dementia diagnosis in MCI.•FDG-PET-SPM maps and CSF Aβ42 are the best predictors of AD dementia conversion.•FDG-PET-SPM maps accurately predict conversion to different dementia conditions.•A negative FDG-PET-SPM pattern characterizes stable or reverter MCI cases.
Background Preclinical and pathology evidence suggests an involvement of brain dopamine (DA) circuitry in Alzheimer's disease (AD). We in vivo investigated if, when, and in which target regions ...123IFP-CIT-SPECT regional binding and molecular connectivity are damaged along the AD course. Methods We retrospectively selected 16 amyloid-positive subjects with mild cognitive impairment due to AD (AD-MCI), 22 amyloid-positive patients with probable AD dementia (AD-D), and 74 healthy controls, all with available 123IFP-CIT-SPECT imaging. We tested whether nigrostriatal vs. mesocorticolimbic dopaminergic targets present binding potential loss, via MANCOVA, and alterations in molecular connectivity, via partial correlation analysis. Results were deemed significant at p < 0.05, after Bonferroni correction for multiple comparisons. Results We found significant reductions of 123IFP-CIT binding in both AD-MCI and AD-D compared to controls. Binding reductions were prominent in the major targets of the ventrotegmental-mesocorticolimbic pathway, namely the ventral striatum and the hippocampus, in both clinical groups, and in the cingulate gyrus, in patients with dementia only. Within the nigrostriatal projections, only the dorsal caudate nucleus showed reduced 123IFP-CIT binding, in both groups. Molecular connectivity assessment revealed a widespread loss of inter-connections among subcortical and cortical targets of the mesocorticolimbic network only (poor overlap with the control group as expressed by a Dice coefficient less than or equai to 0.25) and no alterations of the nigrostriatal network (high overlap with controls, Dice coefficient = 1). Conclusion Local- and system-level alterations of the mesocorticolimbic dopaminergic circuitry characterize AD, already in prodromal disease phases. These results might foster new therapeutic strategies for AD. The clinical correlates of these findings deserve to be carefully considered within the emergence of both neuropsychiatric symptoms and cognitive deficits. Keywords: Biomarker, Dopamine, Molecular connectivity, Substantia nigra, Ventral tegmental area
The G2019S mutation of LRRK2 represents a risk factor for idiopathic Parkinson's disease. Here, we investigate whether LRRK2 kinase activity regulates susceptibility to the environmental toxin ...1-methyl-4-phenyl-1,2,5,6-tetrahydropyridine (MPTP). G2019S knock-in mice (bearing enhanced kinase activity) showed greater nigro-striatal degeneration compared to LRRK2 knock-out, LRRK2 kinase-dead and wild-type mice following subacute MPTP treatment. LRRK2 kinase inhibitors PF-06447475 and MLi-2, tested under preventive or therapeutic treatments, protected against nigral dopamine cell loss in G2019S knock-in mice. MLi-2 also rescued striatal dopaminergic terminal degeneration in both G2019S knock-in and wild-type mice. Immunoblot analysis of LRRK2 Serine935 phosphorylation levels confirmed target engagement of LRRK2 inhibitors. However, MLi-2 abolished phosphoSerine935 levels in the striatum and midbrain of both wild-type and G2019S knock-in mice whereas PF-06447475 partly reduced phosphoSerine935 levels in the midbrain of both genotypes. In vivo and ex vivo uptake of the 18-kDa translocator protein (TSPO) ligand 18F-VC701 revealed a similar TSPO binding in MPTP-treated wild-type and G2019S knock-in mice which was consistent with an increased GFAP striatal expression as revealed by Real Time PCR. We conclude that LRRK2 G2019S, likely through enhanced kinase activity, confers greater susceptibility to mitochondrial toxin-induced parkinsonism. LRRK2 kinase inhibitors are neuroprotective in this model.
•MPTP causes greater nigro-striatal degeneration in G2019S LRRK2 knock-in mice.•LRRK2 inhibitors rescue MPTP-induced nigral dopamine cell loss in G2019S KI mice.•MLi-2 rescues MPTP-induced striatal terminal loss in wild-type and G2019S KI mice.•MPTP elevates 18F-VC701 uptake and GFAP expression.
A progressive loss of dopamine neurons in the substantia nigra (SN) is considered the main feature of idiopathic Parkinson's disease (PD). Recent neuropathological evidence however suggests that the ...axons of the nigrostriatal dopaminergic system are the earliest target of α-synuclein accumulation in PD, thus the principal site for vulnerability. Whether this applies to
PD, and also to the mesolimbic system has not been investigated yet. We used
CFeCIT PET to measure presynaptic dopamine transporter (DAT) activity in both nigrostriatal and mesolimbic systems, in 36 early PD patients (mean disease duration in months ± SD 21.8 ± 10.7) and 14 healthy controls similar for age. We also performed anatomically-driven partial correlation analysis to evaluate possible changes in the connectivity within both the dopamine networks at an early clinical phase. In the nigrostriatal system, we found a severe DAT reduction in the afferents to the dorsal putamen (DPU) (η
= 0.84), whereas the SN was the less affected region (η
= 0.31). DAT activity in the ventral tegmental area (VTA) and the ventral striatum (VST) were also reduced in the patient group, but to a lesser degree (VST η
= 0.71 and VTA η
= 0.31). In the PD patients compared to the controls, there was a marked decrease in dopamine network connectivity between SN and DPU nodes, supporting the significant derangement in the nigrostriatal pathway. These results suggest that neurodegeneration in the dopamine pathways is initially more prominent in the afferent axons and more severe in the nigrostriatal system. Considering PD as a disconnection syndrome starting from the axons, it would justify neuroprotective interventions even if patients have already manifested clinical symptoms.
Background: Time-of-Flight (TOF) is a leading technological development of Positron Emission Tomography (PET) scanners. It reduces noise at the Maximum-Likelihood solution, depending on the ...coincidence–timing–resolution (CTR). However, in clinical applications, it is still not clear how to best exploit TOF information, as early stopped reconstructions are generally used. Methods: A contrast-recovery (CR) matching rule for systems with different CTRs and non-TOF systems is theoretically derived and validated using (1) digital simulations of objects with different contrasts and background diameters, (2) realistic phantoms of different sizes acquired on two scanners with different CTRs. Results: With TOF, the CR matching rule prescribes modifying the iterations number by the CTRs ratio. Without TOF, the number of iterations depends on the background dimension. CR matching was confirmed by simulated and experimental data. With TOF, image noise followed the square root of the CTR when the rule was applied on simulated data, while a significant reduction was obtained on phantom data. Without TOF, preserving the CR on larger objects significantly increased the noise. Conclusions: TOF makes PET reconstructions less dependent on background dimensions, thus, improving the quantification robustness. Better CTRs allows performing fewer updates, thus, maintaining accuracy while minimizing noise.
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