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Background The mechanism of synaptic loss in Alzheimer’s disease is poorly understood and may be associated with tau pathology. In this combined positron emission tomography (PET) and magnetoencephalography (MEG) study, we aimed to investigate spatial associations between regional tau pathology ([ 18 F]flortaucipir PET), synaptic density (synaptic vesicle 2A [ 11 C]UCB-J PET) and synaptic function (MEG) in Alzheimer’s disease. Methods Seven amyloid-positive Alzheimer’s disease subjects from the Amsterdam Dementia Cohort underwent dynamic 130-min [ 18 F]flortaucipir PET, dynamic 60-min [ 11 C]UCB-J PET with arterial sampling and 2 × 5-min resting-state MEG measurement. [ 18 F]flortaucipir- and [ 11 C]UCB-J-specific binding (binding potential, BP ND ) and MEG spectral measures (relative delta, theta and alpha power; broadband power; and peak frequency) were assessed in cortical brain regions of interest. Associations between regional [ 18 F]flortaucipir BP ND , [ 11 C]UCB-J BP ND and MEG spectral measures were assessed using Spearman correlations and generalized estimating equation models. Results Across subjects, higher regional [ 18 F]flortaucipir uptake was associated with lower [ 11 C]UCB-J uptake. Within subjects, the association between [ 11 C]UCB-J and [ 18 F]flortaucipir depended on within-subject neocortical tau load; negative associations were observed when neocortical tau load was high, gradually changing into opposite patterns with decreasing neocortical tau burden. Both higher [ 18 F]flortaucipir and lower [ 11 C]UCB-J uptake were associated with altered synaptic function, indicative of slowing of oscillatory activity, most pronounced in the occipital lobe. Conclusions These results indicate that in Alzheimer’s disease, tau pathology is closely associated with reduced synaptic density and synaptic dysfunction.

PurposeThe novel PET tracer [11C]SMW139 binds with high affinity to the P2X7 receptor, which is expressed on pro-inflammatory microglia. The purposes of this first in-man study were to characterise pharmacokinetics of [11C]SMW139 in patients with active relapsing remitting multiple sclerosis (RRMS) and healthy controls (HC) and to evaluate its potential to identify in vivo neuroinflammation in RRMS.MethodsFive RRMS patients and 5 age-matched HC underwent 90-min dynamic [11C]SMW139 PET scans, with online continuous and manual arterial sampling to generate a metabolite-corrected arterial plasma input function. Tissue time activity curves were fitted to single- and two-tissue compartment models, and the model that provided the best fits was determined using the Akaike information criterion.ResultsThe optimal model for describing [11C]SMW139 kinetics in both RRMS and HC was a reversible two-tissue compartment model with blood volume parameter and with the dissociation rate k4 fixed to the whole-brain value. Exploratory group level comparisons demonstrated an increased volume of distribution (VT) and binding potential (BPND) in RRMS compared with HC in normal appearing brain regions. BPND in MS lesions was decreased compared with non-lesional white matter, and a further decrease was observed in gadolinium-enhancing lesions. In contrast, increased VT was observed in enhancing lesions, possibly resulting from disruption of the blood-brain barrier in active MS lesions. In addition, there was a high correlation between parameters obtained from 60- to 90-min datasets, although analyses using 60-min data led to a slight underestimation in regional VT and BPND values.ConclusionsThis first in-man study demonstrated that uptake of [11C]SMW139 can be quantified with PET using BPND as a measure for specific binding in healthy controls and RRMS patients. Additional studies are warranted for further clinical evaluation of this novel neuroinflammation tracer.

Convolutional neural networks (CNNs) may improve response prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study was to investigate the feasibility of a CNN using maximum intensity projection (MIP) images from 18 F-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography (PET) baseline scans to predict the probability of time-to-progression (TTP) within 2 years and compare it with the International Prognostic Index (IPI), i.e. a clinically used score. 296 DLBCL 18 F-FDG PET/CT baseline scans collected from a prospective clinical trial (HOVON-84) were analysed. Cross-validation was performed using coronal and sagittal MIPs. An external dataset (340 DLBCL patients) was used to validate the model. Association between the probabilities, metabolic tumour volume and Dmax bulk was assessed. Probabilities for PET scans with synthetically removed tumors were also assessed. The CNN provided a 2-year TTP prediction with an area under the curve (AUC) of 0.74, outperforming the IPI-based model (AUC = 0.68). Furthermore, high probabilities (> 0.6) of the original MIPs were considerably decreased after removing the tumours (< 0.4, generally). These findings suggest that MIP-based CNNs are able to predict treatment outcome in DLBCL.

Fluorine-18 labelled N,N-diethyl-2-(2-[4-(2-fluoroethoxy)phenyl]-5,7-dimethylpyrazolo[1,5-α]pyrimidine-3-yl)acetamide ([18F] DPA-714) binds to the 18-kDa translocator protein (TSPO) with high affinity. The aim of this initial methodological study was to develop a plasma input tracer kinetic model for quantification of [18F]DPA-714 binding in healthy subjects and Alzheimer's disease (AD) patients, and to provide a preliminary assessment whether there is a disease-related signal. Ten AD patients and six healthy subjects underwent a dynamic positron emission tomography (PET) study along with arterial sampling and a scan protocol of 150 minutes after administration of 250 ± 10 MBq [18F]DPA-714. The model that provided the best fits to tissue time activity curves (TACs) was selected based on Akaike Information Criterion and F-test. The reversible two tissue compartment plasma input model with blood volume parameter was the preferred model for quantification of [18F]DPA-714 kinetics, irrespective of scan duration, volume of interest, and underlying volume of distribution (VT). Simplified reference tissue model (SRTM)-derived binding potential (BPND) using cerebellar gray matter as reference tissue correlated well with plasma input-based distribution volume ratio (DVR). These data suggest that [18F]DPA-714 cannot be used for separating individual AD patients from heathy subjects, but further studies including TSPO binding status are needed to substantiate these findings.

Purpose The tau tracer [ 18 F]AV1451, also known as flortaucipir, is a promising ligand for imaging tau accumulation in Alzheimer’s disease (AD). Most of the previous studies have quantified tau load using standardized uptake value ratios (SUVr) derived from a static [ 18 F]AV1451 scan. SUVr may, however, be flow dependent and, especially for longitudinal studies, should be validated against a fully quantitative approach. The objective of this study was to identify the optimal tracer kinetic model for measuring tau load using [ 18 F]AV1451. Procedures Following intravenous injection of 225 ± 16 MBq [ 18 F]AV1451, 130 min dynamic PET scans were performed in five biomarker confirmed AD patients and five controls. Arterial blood sampling was performed to obtain a metabolite-corrected plasma input function. Next, regional time–activity curves were generated using PVElab software. These curves were analysed using several pharmacokinetic models. Results The reversible single tissue compartment model (1T2k_V B ) was the preferred model for all but one control. For AD patients, however, model preference shifted towards a reversible two tissue compartmental model (2T4k_V B ). The simplified reference tissue model (SRTM) derived binding potential (BP ND ) showed good correlation (AD: r 2  = 0.87, slope = 1.06; controls: r 2  = 0.87, slope = 0.86) with indirect plasma input binding (distribution volume ratio-1). Standardized uptake value ratios (80–100 min) correlated well with DVR ( r 2  = 0.93, slope = 1.07) and SRTM-derived BP ND ( r 2  = 0.84, slope = 0.95). In addition, regional differences in tracer binding between subject groups in different tau-specific regions were observed. Conclusions Model preference of [ 18 F]AV1451 appears to depend on subject status and, in particular, V T . The relationship between model preference and V T suggests that (higher) tau load may be reflected by a second tissue compartment. Nevertheless, consistent results can be obtained using a 2T4k_V B model. In addition, SRTM can be used to derive BP ND .

Mechanical thrombectomy (MT) eligibility for acute ischemic stroke (AIS) patients depends upon clinical and advanced imaging assessments like CT perfusion (CTP). Assessment complexities and limited access to advanced imaging investigations are known challenges. We developed machine-learning models using routinely collected clinical and imaging data to predict MT eligibility. Age, National-Institutes-of-Health-Stroke-Scale-Score (NIHSS), last-known-well-time (LKWT), noncontrast-CT (NCCT) scan and CT-angiography (CTA) report from consecutive cohort of 260 AIS-suspected patients treated at a stroke centre during Apr'20 to Dec'23 were retrospectively collected. 160 underwent MT for anterior-circulation large vessel occlusion (LVOa); rest were MT ineligible. MT eligibility was determined based on clinical and imaging investigations including CTP during routine-care. The dataset was split into train:test sets (50:50 split). A commercially available artificial-intelligence algorithm calculated infarct volume and ASPECT score (ASPECTSq) from the NCCTs. We developed two supervised models using Gradient-Boosting-Machines. MODEL1 utilized age, NIHSS, LKWT, ASPECTSq and infarct volume as inputs; MODEL2 additionally included the presence/absence of LVOa as input. The target/response variable used for our supervised learning methods was whether the patients were MT eligible or not as determined during routine-care. Performance of the models were investigated using the test set. Among 130 patients (mean age ± standard-deviation: 67.4 ± 14.2 years; 61 males) in test set, 80 (61.5%) were MT eligible; rest were ineligible. The area-under-the-receiver-operating-characteristics-curve, sensitivity and specificity of MODEL1 were 0.76 (95% CI: 0.67-0.85), 85% (75.6-91.2) and 60% (46.2-72.4), respectively. They were 0.92 (0.88-0.96), 82.5% (72.7-89.3) and 82% (69.2-90.2), respectively, for MODEL2. The models showed promising results, demonstrating that NCCT, potentially with CTA, could be sufficient for MT eligibility determination. Such models can enable faster referrals of patients to higher centers.

[11C]UCB-J is a PET radioligand that binds to the presynaptic vesicle glycoprotein 2A. Therefore, [11C]UCB-J PET may serve as an in vivo marker of synaptic integrity. The main objective of this study was to evaluate the quantitative accuracy and the 28-day test–retest repeatability (TRT) of various parametric quantitative methods for dynamic [11C]UCB-J studies in Alzheimer’s disease (AD) patients and healthy controls (HC). Eight HCs and seven AD patients underwent two 60-min dynamic [11C]UCB-J PET scans with arterial sampling over a 28-day interval. Several plasma-input based and reference-region based parametric methods were used to generate parametric images using metabolite corrected plasma activity as input function or white matter semi-ovale as reference region. Different parametric outcomes were compared regionally with corresponding non-linear regression (NLR) estimates. Furthermore, the 28-day TRT was assessed for all parametric methods. Spectral analysis (SA) and Logan graphical analysis showed high correlations with NLR estimates. Receptor parametric mapping (RPM) and simplified reference tissue model 2 (SRTM2) BPND, and reference Logan (RLogan) distribution volume ratio (DVR) regional estimates correlated well with plasma-input derived DVR and SRTM BPND. Among the multilinear reference tissue model (MRTM) methods, MRTM1 had the best correspondence with DVR and SRTM BPND. Among the parametric methods evaluated, spectral analysis (SA) and SRTM2 were the best plasma-input and reference tissue methods, respectively, to obtain quantitatively accurate and repeatable parametric images for dynamic [11C]UCB-J PET.

Background Over the past decades, positron emission tomography (PET) imaging has become an increasingly useful research modality in the field of multiple sclerosis (MS) research, as PET can visualise molecular processes, such as neuroinflammation, in vivo. The second generation PET radioligand [ 18 F]DPA714 binds with high affinity to the 18-kDa translocator-protein (TSPO), which is mainly expressed on activated microglia. The aim of this proof of concept study was to evaluate this in vivo marker of neuroinflammation in primary and secondary progressive MS. Methods All subjects were genotyped for the rs6971 polymorphism within the TSPO gene, and low-affinity binders were excluded from participation in this study. Eight patients with progressive MS and seven age and genetic binding status matched healthy controls underwent a 60 min dynamic PET scan using [ 18 F]DPA714, including both continuous on-line and manual arterial blood sampling to obtain metabolite-corrected arterial plasma input functions. Results The optimal model for quantification of [ 18 F]DPA714 kinetics was a reversible two-tissue compartment model with additional blood volume parameter. For genetic high-affinity binders, a clear increase in binding potential was observed in patients with MS compared with age-matched controls. For both high and medium affinity binders, a further increase in binding potential was observed in T2 white matter lesions compared with non-lesional white matter. Volume of distribution, however, did not differentiate patients from healthy controls, as the large non-displaceable compartment of [ 18 F]DPA714 masks its relatively small specific signal. Conclusion The TSPO radioligand [ 18 F]DPA714 can reliably identify increased focal and diffuse neuroinflammation in progressive MS when using plasma input-derived binding potential, but observed differences were predominantly visible in high-affinity binders.

BackgroundOff-target binding in the choroid plexus (CP) may cause spill-in of the tau PET tracer [18F] flortaucipir into the adjacent hippocampus region. The impact of this spill-in on hippocampal uptake was assessed using a novel partial volume correction method (PVC).MethodsPVC was performed on 20 [18F] flortaucipir dynamic PET scans (10 probable AD and 10 controls). Volumes of interest (VOIs) were defined for both hippocampus and CP. The correlation between hippocampal and CP distribution volume (VT), with and without PVC, was determined. Both anatomically defined and eroded VOIs were used.ResultsFor controls, the correlation between hippocampal and CP VT was significantly reduced after using PVC along with an eroded VOI (r2 = 0.59, slope = 0.80 versus r2 = 0.15, slope = 0.15; difference: p < 0.05). The same was true for AD patients (p < 0.05).ConclusionPVC together with an optimized hippocampal VOI resulted in effective reduction of CP spill-in and improved accuracy of hippocampal VT.