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People with Parkinson's disease can show premotor neurochemical changes in the dopaminergic and non-dopaminergic systems. Using PET, we assessed whether dopaminergic and serotonin transporter changes are similar in LRRK2 mutation carriers with Parkinson's disease and individuals with sporadic Parkinson's disease, and whether LRRK2 mutation carriers without motor symptoms show PET changes. We did two cross-sectional PET studies at the Pacific Parkinson's Research Centre in Vancouver, BC, Canada. We included LRRK2 mutation carriers with or without manifest Parkinson's disease, people with sporadic Parkinson's disease, and age-matched healthy controls, all aged 18 years or older. People with Parkinson's disease were diagnosed by a neurologist with movement disorder training, in accordance with the UK Parkinson's Disease Society Brain Bank criteria. LRRK2 carrier status was confirmed by bidirectional Sanger sequencing. In the first study, LRRK2 mutation carriers with or without manifest Parkinson's disease who were referred for investigation between July, 1999, and January, 2012, were scanned with PET tracers for the membrane dopamine transporter, and dopamine synthesis and storage (18F-6-fluoro-L-dopa; 18F-FDOPA). We compared findings with those in people with sporadic Parkinson's disease and age-matched healthy controls. In the second study, distinct groups of LRRK2 mutation carriers, individuals with sporadic Parkinson's disease, and age-matched healthy controls seen from November, 2012, to May, 2016, were studied with tracers for the serotonin transporter and vesicular monoamine transporter 2 (VMAT2). Striatal dopamine transporter binding, VMAT2 binding, 18F-FDOPA uptake, and serotonin transporter binding in multiple brain regions were compared by ANCOVA, adjusted for age. Between January, 1997, and January, 2012, we obtained data for our first study from 40 LRRK2 mutation carriers, 63 individuals with sporadic Parkinson's disease, and 35 healthy controls. We identified significant group differences in striatal dopamine transporter binding (all age ranges in caudate and putamen, p<0·0001) and 18F-FDOPA uptake (in caudate: age ≤50 years, p=0·0002; all other age ranges, p<0·0001; in putamen: all age ranges, p<0·0001). LRRK2 mutation carriers with manifest Parkinson's disease (n=15) had reduced striatal dopamine transporter binding and 18F-FDOPA uptake, comparable with amounts seen in individuals with sporadic Parkinson's disease of similar duration. LRRK2 mutation carriers without manifest Parkinson's disease (n=25) had greater 18F-FDOPA uptake and dopamine transporter binding than did individuals with sporadic Parkinson's disease, with 18F-FDOPA uptake comparable with controls and dopamine transporter binding lower than in controls. Between November, 2012, and May, 2016, we obtained data for our second study from 16 LRRK2 mutation carriers, 13 individuals with sporadic Parkinson's disease, and nine healthy controls. Nine LRRK2 mutation carriers without manifest Parkinson's disease had significantly elevated serotonin transporter binding in the hypothalamus (compared with controls, individuals with LRRK2 Parkinson's disease, and people with sporadic Parkinson's disease, p<0·0001), striatum (compared with people with sporadic Parkinson's disease, p=0·02), and brainstem (compared with LRRK2 mutation carriers with manifest Parkinson's disease, p=0·01), after adjustment for age. Serotonin transporter binding in the cortex did not differ significantly between groups after age adjustment. Striatal VMAT2 binding was reduced in all individuals with manifest Parkinson's disease and reduced asymmetrically in one LRRK2 mutation carrier without manifest disease. Dopaminergic and serotonergic changes progress in a similar fashion in LRRK2 mutation carriers with manifest Parkinson's disease and individuals with sporadic Parkinson's disease, but LRRK2 mutation carriers without manifest Parkinson's disease show increased serotonin transporter binding in the striatum, brainstem, and hypothalamus, possibly reflecting compensatory changes in serotonergic innervation preceding the motor onset of Parkinson's disease. Increased serotonergic innervation might contribute to clinical differences in LRRK2 Parkinson's disease, including the emergence of non-motor symptoms and, potentially, differences in the long-term response to levodopa. Canada Research Chairs, Michael J Fox Foundation, National Institutes of Health, Pacific Alzheimer Research Foundation, Pacific Parkinson's Research Institute, National Research Council of Canada.

Background Abnormal activation of immune system is an important pathogenesis of Parkinson’s disease, but the relationship between peripheral inflammation, central microglia activation and dopaminergic degeneration remains unclear. Objectives To evaluate the brain regional microglia activation and its relationship with clinical severity, dopaminergic presynaptic function, and peripheral inflammatory biomarkers related to adaptive immunity. Methods In this case–control study, we recruited 23 healthy participants and 24 participants with early-stage Parkinson’s disease. 18 F-PBR06 PET/MR for microglia activation, 18 F-FP-DTBZ for dopaminergic denervation, total account of T cells and subpopulations of T helper (Th1/Th2/Th17) cells, and the levels of serum inflammatory cytokines were assessed. Sanger sequencing was used to exclude the mix-affinity binders of 18 F-PBR06-PET. Results Compared to healthy controls, patients with Parkinson’s disease had an increased 18 F-PBR06-PET standardized uptake value ratio (SUVR) in the putamen, particularly in the ipsilateral side of the motor onset. 18 F-PBR06-PET SUVR was positively associated with 18 F-FP-DTBZ-PET SUVR in the brainstem and not associated with disease severity measured by Hoehn and Yahr stage, MDS-UPDRS III scores. Patients with Parkinson’s disease had elevated frequencies of Th1 cells and serum levels of IL10 and IL17A as compared to healthy controls. No significant association between peripheral inflammation markers and microglia activation in the brain of PD was observed. Conclusion Parkinson’s disease is associated with early putaminal microglial activation and peripheral phenotypic Th1 bias. Peripheral adaptive immunity might be involved in microglia activation in the process of neurodegeneration in PD indirectly, which may be a potential biomarker for the early detection and the target for immunomodulating therapy.

•Long-COVID is heterogeneous in its symptoms, severity, and illness duration.•There was no association between long-COVID and cognitive performance.•Cognitive symptoms may represent functional cognitive disorders.•Long-COVID had lower mean diffusivity on diffusion imaging than normal recovery.•Diffusion imaging differences may suggest gliosis as a mechanism of long-COVID. The pathophysiology of protracted symptoms after COVID-19 is unclear. This study aimed to determine if long-COVID is associated with differences in baseline characteristics, markers of white matter diffusivity in the brain, and lower scores on objective cognitive testing. Individuals who experienced COVID-19 symptoms for more than 60 days post-infection (long-COVID) (n = 56) were compared to individuals who recovered from COVID-19 within 60 days of infection (normal recovery) (n = 35). Information regarding physical and mental health, and COVID-19 illness was collected. The National Institute of Health Toolbox Cognition Battery was administered. Participants underwent magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI). Tract-based spatial statistics were used to perform a whole-brain voxel-wise analysis on standard DTI metrics (fractional anisotropy, axial diffusivity, mean diffusivity, radial diffusivity), controlling for age and sex. NIH Toolbox Age-Adjusted Fluid Cognition Scores were used to compare long-COVID and normal recovery groups, covarying for Age-Adjusted Crystallized Cognition Scores and years of education. False discovery rate correction was applied for multiple comparisons. There were no significant differences in age, sex, or history of neurovascular risk factors between the groups. The long-COVID group had significantly (p < 0.05) lower mean diffusivity than the normal recovery group across multiple white matter regions, including the internal capsule, anterior and superior corona radiata, corpus callosum, superior fronto-occiptal fasciculus, and posterior thalamic radiation. However, the effect sizes of these differences were small (all β<|0.3|) and no significant differences were found for the other DTI metrics. Fluid cognition composite scores did not differ significantly between the long-COVID and normal recovery groups (p > 0.05). Differences in diffusivity between long-COVID and normal recovery groups were found on only one DTI metric. This could represent subtle areas of pathology such as gliosis or edema, but the small effect sizes and non-specific nature of the diffusion indices make pathological inference difficult. Although long-COVID patients reported many neuropsychiatric symptoms, significant differences in objective cognitive performance were not found.

•Diffusion MRI has been used to compare COVID-19 patients with healthy controls.•COVID-19 patients tend to have widespread lower anisotropy than healthy controls.•More severe COVID-19 illness is associated with more dMRI differences.•Systemic inflammation is a possible mechanism for dMRI changes after COVID-19. Most COVID-19 neuroimaging research focuses on clinically evident lesions occurring during the acute period after infection. Chronic effects on brain structure, especially at a microstructural level, are less well defined. Existing advanced neuroimaging studies report inconsistent differences in white matter integrity after COVID-19 infection. Our aim was to systematically evaluate the advanced neuroimaging literature with a specific focus on examining diffusion MRI (dMRI) abnormalities observable after the resolution of the acute phase of COVID-19 illness. A search of the literature was conducted on PubMed, Embase, and Scopus on May 27th, 2023, and an updated search was performed September 20th, 2024. Inclusion criteria were a quantitative comparison of dMRI metrics between COVID-19 patients and non-COVID-19 volunteers with MRI acquired >6 weeks after COVID-19. Studies that included only subgroups of COVID-19 patients with specific symptoms, case reports, and post-mortem studies were excluded. Forwards and backwards citation chasing were performed. The initial search identified 1709 unique records, and 11 met inclusion criteria. Most studies included hospitalized COVID-19 patients, with brain MRI acquired between 2 and 6 months after COVID-19 infection. The majority of studies reported lower fractional anisotropy and higher mean diffusivity in the post-COVID-19 cohort, compared to non-COVID-19 controls. However, there were inconsistent findings, with one study reporting higher fractional anisotropy after COVID-19 infection. Cohorts with a more severe acute COVID-19 illness tended to have lower fractional anisotropy and higher mean diffusivity than cohorts with a milder illness course. Compared to shorter follow-up periods, a longer time between COVID-19 and MRI was associated with fewer differences between COVID-19 patients and non-COVID-19 volunteers. A review of the literature indicates that the heterogeneity of findings regarding dMRI metrics after the resolution of the acute phase of COVID-19 illness may be due in part to the severity of COVID-19 illness and the time between COVID-19 and MRI. Future studies should also consider how different SARS-CoV-2 variants differentially affect the structural brain differences after COVID-19.

Markers of neuroinflammation are increased in some patients with LRRK2 Parkinson's disease compared with individuals with idiopathic Parkinson's disease, suggesting possible differences in disease pathogenesis. Previous PET studies have suggested amplified dopamine turnover and preserved serotonergic innervation in LRRK2 mutation carriers. We postulated that patients with LRRK2 mutations might show abnormalities of central cholinergic activity, even before the diagnosis of Parkinson's disease. Between June, 2009, and December, 2015, we recruited participants from four movement disorder clinics in Canada, Norway, and the USA. Patients with Parkinson's disease were diagnosed by movement disorder neurologists on the basis of the UK Parkinson's Disease Society Brain Bank criteria. LRRK2 carrier status was confirmed by bidirectional Sanger sequencing. We used the PET tracer N-11C-methyl-piperidin-4-yl propionate to scan for acetylcholinesterase activity. The primary outcome measure was rate of acetylcholinesterase hydrolysis, calculated using the striatal input method. We compared acetylcholinesterase hydrolysis rates between groups using ANCOVA, with adjustment for age based on the results of linear regression analysis. We recruited 14 patients with LRRK2 Parkinson's disease, 16 LRRK2 mutation carriers without Parkinson's disease, eight patients with idiopathic Parkinson's disease, and 11 healthy controls. We noted significant between-group differences in rates of acetylcholinesterase hydrolysis in cortical regions (average cortex p=0·009, default mode network-related regions p=0·006, limbic network-related regions p=0·020) and the thalamus (p=0·008). LRRK2 mutation carriers without Parkinson's disease had increased acetylcholinesterase hydrolysis rates compared with healthy controls in the cortex (average cortex, p=0·046). Patients with LRRK2 Parkinson's disease had significantly higher acetylcholinesterase activity in some cortical regions (average cortex p=0·043, default mode network-related regions p=0·021) and the thalamus (thalamus p=0·004) compared with individuals with idiopathic disease. Acetylcholinesterase hydrolysis rates in healthy controls were correlated inversely with age. LRRK2 mutations are associated with significantly increased cholinergic activity in the brain in mutation carriers without Parkinson's disease compared with healthy controls and in LRRK2 mutation carriers with Parkinson's disease compared with individuals with idiopathic disease. Changes in cholinergic activity might represent early and sustained attempts to compensate for LRRK2-related dysfunction, or alteration of acetylcholinesterase in non-neuronal cells. Michael J Fox Foundation, National Institutes of Health, and Pacific Alzheimer Research Foundation.

-COVID-19 patients tend to have smaller brain volumes than healthy controls.-More severe COVID-19 illness is associated with more brain volume differences.-Hypoxia or inflammation may be a mechanism for brain differences after COVID-19. The majority of COVID-19 neuroimaging literature focuses on the acute period after infection and clinically evident lesions. The chronic effects of COVID-19 on brain structure are less well defined. There are inconsistencies in the existing structural neuroimaging studies regarding differences in brain volumes after COVID-19 infection. It was thus our aim to systematically evaluate the structural neuroimaging literature focusing on volumetric differences between patients with COVID-19, and volunteers without COVID-19, at greater than 6 weeks post-infection. PubMed, Embase, and Scopus were searched in May 2023 with an updated search in September 2024, for studies with a quantitative comparison of brain volumes between COVID-19 patients and non-COVID-19 volunteers with MRI acquired more than 6-weeks after COVID-19. Exclusion criteria included COVID-19 patients selected for the presence of specific symptoms, case reports and case studies, and post-mortem studies. Forwards and backwards citation chasing were performed. Sixteen studies met inclusion criteria. The majority of studies reported smaller grey matter volumes amongst COVID-19 patients compared to healthy volunteers. However, there were inconsistent findings, with 3 studies reporting larger grey matter volumes in the COVID-19 groups. Additionally, studies with COVID-19 cohorts with more severe presentations, characterized by admission to the hospital or the ICU, were more likely to report smaller grey matter volumes compared to healthy volunteers, than studies that were focused on patients who recovered at home. A systematic review of the literature indicates that COVID-19 illness severity may explain some of the heterogeneity in brain volume differences between COVID-19 patients and healthy volunteers. More longitudinal follow-up studies are needed to assess the longitudinal course of COVID-19′s effects on brain volumes.

PurposeQuantitative analysis of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) images can enhance diagnostic confidence and improve their potential as a biomarker to monitor the progression of Parkinson’s disease (PD). In the present work, we aim to predict motor outcome from baseline DAT SPECT imaging radiomic features and clinical measures using machine learning techniques.ProceduresWe designed and trained artificial neural networks (ANNs) to analyze the data from 69 patients within the Parkinson’s Progressive Marker Initiative (PPMI) database. The task was to predict the unified PD rating scale (UPDRS) part III motor score in year 4 from 92 imaging features extracted on 12 different regions as well as 6 non-imaging measures at baseline (year 0). We first performed univariate screening (including the adjustment for false discovery) to select 4 regions each having 10 features with significant performance in classifying year 4 motor outcome into two classes of patients (divided by the UPDRS III threshold of 30). The leave-one-out strategy was then applied to train and test the ANNs for individual and combinations of features. The prediction statistics were calculated from 100 rounds of experiments, and the accuracy in appropriate prediction (classification of year 4 outcome) was quantified.ResultsOut of the baseline non-imaging features, only the UPDRS III (at year 0) was predictive, while multiple imaging features depicted significance. The different selected features reached a predictive accuracy of 70 % if used individually. Combining the top imaging features from the selected regions significantly improved the prediction accuracy to 75 % (p < 0.01). The combination of imaging features with the year 0 UPDRS III score also improved the prediction accuracy to 75 %.ConclusionThis study demonstrated the added predictive value of radiomic features extracted from DAT SPECT images in serving as a biomarker for PD progression tracking.

An international group of experts in pharmacokinetic modeling recommends a consensus nomenclature to describe in vivo molecular imaging of reversibly binding radioligands.An international group of experts in pharmacokinetic modeling recommends a consensus nomenclature to describe in vivo molecular imaging of reversibly binding radioligands.

Despite significant insights into the neural mechanisms of acute placebo responses, less is known about longer-term placebo responses, such as those seen in clinical trials, or their interactions with brain disease. We examined brain correlates of placebo responses in a randomized trial of a then controversial and now disproved endovascular treatment for multiple sclerosis. Patients received either balloon or sham extracranial venoplasty and were followed for 48 weeks. Venoplasty had no therapeutic effect, but a subset of both venoplasty- and sham-treated patients reported a transient improvement in health-related quality of life, suggesting a placebo response. Placebo responders did not differ from non-responders in total MRI T2 lesion load, count or location, nor were there differences in normalized brain volume, regional grey or white matter volume or cortical thickness (CT). However, responders had higher lesion activity. Graph theoretical analysis of CT covariance showed that non-responders had a more small-world-like CT architecture. In non-responders, lesion load was inversely associated with CT in somatosensory, motor and association areas, precuneus, and insula, primarily in the right hemisphere. In responders, lesion load was unrelated to CT. The neuropathological process in MS may produce in some a cortical configuration less capable of generating sustained placebo responses.

BackgroundThe need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations—partial volume effects and radiometabolite correction among the most important—and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome.Main bodyThis paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field’s opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners—inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production—is included, providing a pathway for future use of IDIF.ConclusionImprovements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.