Luca Presotto

Axonal damage and loss of connectivity in nigrostriatal and mesolimbic dopamine pathways in early Parkinson's disease

A progressive loss of dopamine neurons in the substantia nigra (SN) is considered the main feature of idiopathic Parkinsons 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 in vivo PD, and also to the mesolimbic system has not been investigated yet. We used [11C]FeCIT 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) (η2 = 0.84), whereas the SN was the less affected region (η2 = 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 η2 = 0.71 and VTA η2 = 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.

Metabolic connectomics targeting brain pathology in dementia with Lewy bodies

Dementia with Lewy bodies is characterized by α-synuclein accumulation and degeneration of dopaminergic and cholinergic pathways. To gain an overview of brain systems affected by neurodegeneration, we characterized the [18F]FDG-PET metabolic connectivity in 42 dementia with Lewy bodies patients, as compared to 42 healthy controls, using sparse inverse covariance estimation method and graph theory. We performed whole-brain and anatomically driven analyses, targeting cholinergic and dopaminergic pathways, and the α-synuclein spreading. The first revealed substantial alterations in connectivity indexes, brain modularity, and hubs configuration. Namely, decreases in local metabolic connectivity within occipital cortex, thalamus, and cerebellum, and increases within frontal, temporal, parietal, and basal ganglia regions. There were also long-range disconnections among these brain regions, all supporting a disruption of the functional hierarchy characterizing the normal brain. The anatomically driven analysis revealed alterations within brain structures early affected by α-synuclein pathology, supporting Braak’s early pathological staging in dementia with Lewy bodies. The dopaminergic striato-cortical pathway was severely affected, as well as the cholinergic networks, with an extensive decrease in connectivity in Ch1-Ch2, Ch5-Ch6 networks, and the lateral Ch4 capsular network significantly towards the occipital cortex. These altered patterns of metabolic connectivity unveil a new in vivo scenario for dementia with Lewy bodies underlying pathology in terms of changes in whole-brain metabolic connectivity, spreading of α-synuclein, and neurotransmission impairment.

Evaluation of image reconstruction algorithms encompassing Time-Of-Flight and Point Spread Function modelling for quantitative cardiac PET: Phantom studies

BackgroundTo perform kinetic modelling quantification, PET dynamic data must be acquired in short frames, where different critical conditions are met. The accuracy of reconstructed images influences quantification. The added value of Time-Of-Flight (TOF) and Point Spread Function (PSF) in cardiac image reconstruction was assessed.MethodsA static phantom was used to simulate two extreme conditions: (i) the bolus passage and (ii) the steady uptake. Various count statistics and independent noise realisations were considered. A moving phantom filled with two different radionuclides was used to simulate: (i) a great range of contrasts and (ii) the cardio/respiratory motion. Analytical and iterative reconstruction (IR) algorithms also encompassing TOF and PSF modelling were evaluated.ResultsBoth analytic and IR algorithms provided good results in all the evaluated conditions. The amount of bias introduced by IR was found to be limited. TOF allowed faster convergence and lower noise levels. PSF achieved near full myocardial activity recovery in static conditions. Motion degraded performances, but the addition of both TOF and PSF maintained the best overall behaviour.ConclusionsIR accounting for TOF and PSF can be recommended for the quantification of dynamic cardiac PET studies as they improve the results compared to analytic and standard IR.

Gender differences in healthy aging and Alzheimer's Dementia: A 18F‐FDG‐PET study of brain and cognitive reserve

Cognitive reserve (CR) and brain reserve (BR) are protective factors against age‐associated cognitive decline and neurodegenerative disorders. Very limited evidence exists about gender effects on brain aging and on the effect of CR on brain modulation in healthy aging and Alzheimers Dementia (AD). We investigated gender differences in brain metabolic activity and resting‐state network connectivity, as measured by 18F‐FDG‐PET, in healthy aging and AD, also considering the effects of education and occupation. The clinical and imaging data were retrieved from large datasets of healthy elderly subjects (HE) (225) and AD patients (282). In HE, males showed more extended age‐related reduction of brain metabolism than females in frontal medial cortex. We also found differences in brain modulation as metabolic increases induced by education and occupation, namely in posterior associative cortices in HE males and in the anterior limbic‐affective and executive networks in HE females. In AD patients, the correlations between education and occupation levels and brain hypometabolism showed gender differences, namely a posterior temporo‐parietal association in males and a frontal and limbic association in females, indicating the involvement of different networks. Finally, the metabolic connectivity in both HE and AD aligned with these results, suggesting greater efficiency in the posterior default mode network for males, and in the anterior frontal executive network for females. The basis of these brain gender differences in both aging and AD, obtained exploring cerebral metabolism, metabolic connectivity and the effects of education and occupation, is likely at the intersection between biological and sociodemographic factors. Hum Brain Mapp 38:4212–4227, 2017.

Cerebral collateral therapeutics in acute ischemic stroke: A randomized preclinical trial of four modulation strategies

Cerebral collaterals are dynamically recruited after arterial occlusion and highly affect tissue outcome in acute ischemic stroke. We investigated the efficacy and safety of four pathophysiologically distinct strategies for acute modulation of collateral flow (collateral therapeutics) in the rat stroke model of transient middle cerebral artery (MCA) occlusion. A composed randomization design was used to assign rats (n = 118) to receive phenylephrine (induced hypertension), polygeline (intravascular volume load), acetazolamide (cerebral arteriolar vasodilation), head down tilt (HDT) 15° (cerebral blood flow diversion), or no treatment, starting 30 min after MCA occlusion. Compared to untreated animals, treatment with collateral therapeutics was associated with lower infarct volumes (62% relative mean difference; 51.57 mm3 absolute mean difference; p < 0.001) and higher chance of good functional outcome (OR 4.58, p < 0.001). Collateral therapeutics acutely increased cerebral perfusion in the medial (+40.8%; p < 0.001) and lateral (+19.2%; p = 0.016) MCA territory compared to pretreatment during MCA occlusion. Safety indicators were treatment-related mortality and cardiorespiratory effects. The highest efficacy and safety profile was observed for HDT. Our findings suggest that acute modulation of cerebral collaterals is feasible and provides a tissue-saving effect in the hyperacute phase of ischemic stroke prior to recanalization therapy.

Altered brain metabolic connectivity at multiscale level in early Parkinson’s disease

To explore the effects of PD pathology on brain connectivity, we characterized with an emergent computational approach the brain metabolic connectome using [18F]FDG-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.

Motion-Tracking Hardware and Advanced Applications in PET and PET/CT

Respiratory and cardiac motions represent important sources of image degradation in both PET and computed tomography (CT) studies that need to be taken into account and compensated to improve image quality and quantitative accuracy. This review describes the hardware needed to perform respiratory and cardiac gating with PET and PET/CT systems. In particular, most of the proposed motion-tracking devices for the management of respiratory, cardiac, and multidimensional movements are described and compared. Some advanced applications in PET and PET/CT made possible by the gating technology are considered and analyzed.

FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort

Background/aims 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 Alzheimers disease (AD) dementia and non-AD dementias. Methods 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. Results 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). Conclusions 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.

Simultaneous reconstruction of attenuation and activity in cardiac PET can remove CT misalignment artifacts

BackgroundMisalignment between positron emission tomography (PET) and computed tomography (CT) data is known to generate artifactual defects in cardiac PET images due to imprecise attenuation correction (AC). In this work, the use of a maximum likelihood attenuation and activity (MLAA) algorithm is proposed to avoid such artifacts in time-of-flight (TOF) PET.MethodsMLAA was implemented and tested using a thorax/heart phantom and retrospectively on fourteen 13N-ammonia PET/CT perfusion studies. Global and local misalignments between PET and CT data were generated by shifting matched CT images or using CT data representative of the end-inspiration phase. PET images were reconstructed with MLAA and a 3D-ordered-subsets-expectation-maximization (OSEM)-TOF algorithm. Images obtained with 3D-OSEM-TOF and matched CT were used as references. These images were compared (qualitatively and semi-quantitatively) with those reconstructed with 3D-OSEM-TOF and MLAA for which a misaligned CT was used, respectively, for AC and initialization.ResultsPhantom experiment proved the capability of MLAA to converge toward the correct emission and attenuation distributions using, as input, only PET emission data, but convergence was very slow. Initializing MLAA with phantom CT images markedly improved convergence speed. In patient studies, when shifted or end-inspiration CT images were used for AC, 3D-OSEM-TOF reconstructions showed artifacts of increasing severity, size, and frequency with increasing mismatch. Such artifacts were absent in the corresponding MLAA images.ConclusionThe proposed implementation of the MLAA algorithm is a feasible and robust technique to avoid AC mismatch artifacts in cardiac PET studies provided that a CT of the source is available, even if poorly aligned.

Single-subject SPM FDG-PET patterns predict risk of dementia progression in Parkinson disease

Objective To 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). Methods Fifty-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. Results The 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. Conclusions This study suggests that FDG-PET SPM at the single-subject level might help in identifying patients with PD at risk of developing dementia.