Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism.

Nowadays, presynaptic dopaminergic positron emission tomography, which assesses deficiencies in dopamine synthesis, storage, and transport, is widely utilized for early diagnosis and differential diagnosis of parkinsonism. This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism. We conducted a thorough literature search using reputable databases such as PubMed and Web of Science. Selection criteria involved identifying peer-reviewed articles published within the last 5 years, with emphasis on their relevance to clinical applications. The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis. Moreover, when employed in conjunction with other imaging modalities and advanced analytical methods, presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker. This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion. In summary, the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials, ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

Impaired glymphatic function as a biomarker for subjective cognitive decline: An exploratory dual cohort study.

BACKGROUND: Subjective cognitive decline (SCD) has been recognized as a potential risk stage for progression to Alzheimer's disease (AD), while glymphatic dysfunction is considered an important characteristic of AD. We hypothesize that glymphatic dysfunction occurs during the SCD stage, aiming to discover potential biomarkers for SCD. METHODS: Participants from two independent studies, Sino Longitudinal Study on Cognitive Decline (SILCODE, n = 654) and the Alzheimer's Disease Neuroimaging Initiative (ADNI, n = 650), representing different ethnicities and disease stages, were included to assess glymphatic function using diffusion tensor image analysis along the perivascular space (DTI-ALPS). RESULTS: Abnormal glymphatic function occurs during the SCD stage, with the ALPS index demonstrating excellent classification performance for SCD and normal controls (area under the receiver operating characteristic curve [AUC]SILCODE = 0.816, AUCADNI = 0.797). Lower ALPS index indicates higher risk of cognitive progression, which is negatively correlated with Subjective Cognitive Decline Questionnaire 9 scores and amyloid positron emission tomography burden. DISSCUSION: Our study suggests the ALPS index has the potential to serve as a biomarker for SCD. HIGHLIGHTS: Glymphatic function characterized by the analysis along the perivascular space (ALPS) index becomes abnormal in subjective cognitive decline (SCD), the earliest symptomatic manifestation and preclinical stage of Alzheimer's disease (AD). The ALPS index demonstrates excellent classification performance for SCD and normal controls in the East Asian and Western cohorts. Participants with a lower ALPS index show a higher risk of clinical progression. The ALPS index is closely associated with serval cognitive scales and amyloid beta burden.

Heterogeneity of fibroblast activation protein expression in the microenvironment of an intracranial tumor cohort: head-to-head comparison of gallium-68 FAP inhibitor-04 (68Ga-FAPi-04) and fluoride-18 fluoroethyl-L-tyrosine (18F-FET) in positron emission tomography-computed tomography imaging.

Background: Cancer-associated fibroblasts (CAFs) within the tumor microenvironment (TME) can interact with tumor parenchymal cells to promote tumor growth and migration. Fibroblast activation protein (FAP) expressed by CAFs can be targeted with positron emission tomography (PET) tracers, but studies on FAP expression patterns in intracranial tumors remain scarce. We aimed to evaluate FAP expression patterns in intracranial tumors with gallium-68 FAP inhibitor-04 (68Ga-FAPi-04) and immunohistochemical staining and to observe the interactions between CAFs and tumor cells with a head-to-head comparison of 68Ga-FAPi-04 and fluoride-18 fluoroethyl-L-tyrosine (18F-FET) for PET quantification analysis. Methods: We prospectively enrolled 22 adult patients with intracranial mass lesions. 68Ga-FAPi-04 and 18F-FET PET-computed tomography (PET/CT) brain imaging were applied before surgery. Maximal tumor-to-brain ratio (TBRmax), metabolic tumor volume (MTV), and total lesion tracer uptake (TLU) was obtained, and different thresholds were used for 68Ga-FAPi-04-positive lesion delineation owing to the lack of relevant guidelines. The MTV and TLU ratios of both tracers were calculated. Linear regression was applied to observe the differential efficacy of semiquantitative PET parameters. Results: A total of 22 patients with a mean age of 50±13 years (range, 27-69 years) were enrolled. Heterogeneous patterns of 68Ga-FAPi-04 uptake [median of maximal standardized uptake value (SUVmax) =3.8; range, 0.1-19.1] were found. More malignant tumors, including brain metastasis, glioblastoma, and medulloblastoma, generally exhibited more significant 68Ga-FAPi-04 uptake than did the less malignant tumors, while the SUVmax and TBRmax exhibited nonsignificant differences across three intracranial lesion groups of primary brain tumor, brain metastasis, and noncancerous disease (SUVmax: P=0.092; TBRmax: P=0.189). Immunohistochemistry staining showed different stromal FAP expression status in various intracranial lesions. In 15 patients with positive 68Ga-FAPi-04 intracranial tumor uptake, the MTVFAPi:MTVFET ratio had differential efficacy in various types of intracranial tumors [95% confidence interval (CI): 0.572-7.712; P=0.027], and further quantification analyses confirmed the differential ability of the MTVFAPi:MTVFET ratio (95% CI: -0.045 to 11.013, P=0.052; 95% CI: 0.044-17.903, P=0.049; 95% CI: -1.131 to 30.596, P=0.065) with different isocontour volumetric thresholds. Conclusions: This head-to-head study demonstrated heterogeneous FAP expression in intracranial tumors. The FAP expression volume percentage in tumor parenchyma may therefore offer benefit with respect to differentiating between intracranial tumor types.

Radiomics-Guided Deep Learning Networks Classify Differential Diagnosis of Parkinsonism.

The differential diagnosis between atypical Parkinsonian syndromes may be challenging and critical. We aimed to proposed a radiomics-guided deep learning (DL) model to discover interpretable DL features and further verify the proposed model through the differential diagnosis of Parkinsonian syndromes. We recruited 1495 subjects for 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) scanning, including 220 healthy controls and 1275 patients diagnosed with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA), or progressive supranuclear palsy (PSP). Baseline radiomics and two DL models were developed and tested for the Parkinsonian diagnosis. The DL latent features were extracted from the last layer and subsequently guided by radiomics. The radiomics-guided DL model outperformed the baseline radiomics approach, suggesting the effectiveness of the DL approach. DenseNet showed the best diagnosis ability (sensitivity: 95.7%, 90.1%, and 91.2% for IPD, MSA, and PSP, respectively) using retained DL features in the test dataset. The retained DL latent features were significantly associated with radiomics features and could be interpreted through biological explanations of handcrafted radiomics features. The radiomics-guided DL model offers interpretable high-level abstract information for differential diagnosis of Parkinsonian disorders and holds considerable promise for personalized disease monitoring.

In vivo reactive astrocyte imaging using [18F]SMBT-1 in tauopathy and familial Alzheimer's disease mouse models: A multi-tracer study.

BACKGROUND: Reactive astrocytes play an important role in the development of Alzheimer's disease and primary tauopathies. Here, we aimed to investigate the relationships between reactive astrocytes. Microgliosis and glucose metabolism with Tau and amyloid beta pathology by using multi-tracer imaging in widely used tauopathy and familial Alzheimer's disease mouse models. RESULTS: Positron emission tomography imaging using [18F]PM-PBB3 (tau), [18F]florbetapir (amyloid-beta), [18F]SMBT-1 (monoamine oxidase-B), [18F]DPA-714 (translocator protein) and [18F]fluorodeoxyglucose was carried out in 3- and 7-month-old rTg4510 tau mice, 5 × FAD familial Alzheimer's disease mice and wild-type mice. Immunofluorescence staining was performed to validate the pathological distribution in the mouse brain after in vivo imaging. We found increased regional levels of [18F]PM-PBB3, [18F]SMBT-1, and [18F]DPA-714 and hypoglucose metabolism in the brains of 7-month-old rTg4510 mice compared to age-matched wild-type mice. Increased [18F]SMBT-1 uptake was observed in the brains of 3, 7-month-old 5 × FAD mice, with elevated regional [18F]florbetapir and [18F]DPA-714 uptakes in the brains of 7-month-old 5 × FAD mice, compared to age-matched wild-type mice. Positive correlations were shown between [18F]SMBT-1 and [18F]PM-PBB3, [18F]DPA-714 and [18F]PM-PBB3 in rTg4510 mice, and between [18F]florbetapir and [18F]DPA-714 SUVRs in 5 × FAD mice. CONCLUSION: In summary, these findings provide in vivo evidence that reactive astrocytes, microglial activation, and cerebral hypoglucose metabolism are associated with tau and amyloid pathology development in animal models of tauopathy and familial Alzheimer's disease.

Characterization of tau propagation pattern and cascading hypometabolism from functional connectivity in Alzheimer's disease.

Tau pathology and its spatial propagation in Alzheimer's disease (AD) play crucial roles in the neurodegenerative cascade leading to dementia. However, the underlying mechanisms linking tau spreading to glucose metabolism remain elusive. To address this, we aimed to examine the association between pathologic tau aggregation, functional connectivity, and cascading glucose metabolism and further explore the underlying interplay mechanisms. In this prospective cohort study, we enrolled 79 participants with 18F-Florzolotau positron emission tomography (PET), 18F-fluorodeoxyglucose PET, resting-state functional, and anatomical magnetic resonance imaging (MRI) images in the hospital-based Shanghai Memory Study. We employed generalized linear regression and correlation analyses to assess the associations between Florzolotau accumulation, functional connectivity, and glucose metabolism in whole-brain and network-specific manners. Causal mediation analysis was used to evaluate whether functional connectivity mediates the association between pathologic tau and cascading glucose metabolism. We examined 22 normal controls and 57 patients with AD. In the AD group, functional connectivity was associated with Florzolotau covariance (ß = .837, r = 0.472, p < .001) and glucose covariance (ß = 1.01, r = 0.499, p < .001). Brain regions with higher tau accumulation tend to be connected to other regions with high tau accumulation through functional connectivity or metabolic connectivity. Mediation analyses further suggest that functional connectivity partially modulates the influence of tau accumulation on downstream glucose metabolism (mediation proportion: 49.9%). Pathologic tau may affect functionally connected neurons directly, triggering downstream glucose metabolism changes. This study sheds light on the intricate relationship between tau pathology, functional connectivity, and downstream glucose metabolism, providing critical insights into AD pathophysiology and potential therapeutic targets.

Relationship Between Reactive Astrocytes, by [18F]SMBT-1 Imaging, with Amyloid-Beta, Tau, Glucose Metabolism, and TSPO in Mouse Models of Alzheimer's Disease.

Reactive astrocytes play an important role in the development of Alzheimer's disease (AD). Here, we aimed to investigate the temporospatial relationships among monoamine oxidase-B, tau and amyloid-ß (Aß), translocator protein, and glucose metabolism by using multitracer imaging in AD transgenic mouse models. Positron emission tomography (PET) imaging with [18F]SMBT-1 (monoamine oxidase-B), [18F]florbetapir (Aß), [18F]PM-PBB3 (tau), [18F]fluorodeoxyglucose (FDG), and [18F]DPA-714 (translocator protein) was carried out in 5- and 10-month-old APP/PS1, 11-month-old 3×Tg mice, and aged-matched wild-type mice. The brain regional referenced standard uptake value (SUVR) was computed with the cerebellum as the reference region. Immunofluorescence staining was performed on mouse brain tissue slices. [18F]SMBT-1 and [18F]florbetapir SUVRs were greater in the cortex and hippocampus of 10-month-old APP/PS1 mice than in those of 5-month-old APP/PS1 mice and wild-type mice. No significant difference in the regional [18F]FDG or [18F]DPA-714 SUVRs was observed in the brains of 5- or 10-month-old APP/PS1 mice or wild-type mice. No significant difference in the SUVRs of any tracer was observed between 11-month-old 3×Tg mice and age-matched wild-type mice. A positive correlation between the SUVRs of [18F]florbetapir and [18F]DPA-714 in the cortex and hippocampus was observed among the transgenic mice. Immunostaining validated the distribution of MAO-B and limited Aß and tau pathology in 11-month-old 3×Tg mice; and Aß deposits in brain tissue from 10-month-old APP/PS1 mice. In summary, these findings provide in vivo evidence that an increase in astrocyte [18F]SMBT-1 accompanies Aß accumulation in APP/PS1 models of AD amyloidosis.

Detection of individual brain tau deposition in Alzheimer's disease based on latent feature-enhanced generative adversarial network.

OBJECTIVE: The conventional methods for interpreting tau PET imaging in Alzheimer's disease (AD), including visual assessment and semi-quantitative analysis of fixed hallmark regions, are insensitive to detect individual small lesions because of the spatiotemporal neuropathology's heterogeneity. In this study, we proposed a latent feature-enhanced generative adversarial network model for the automatic extraction of individual brain tau deposition regions. METHODS: The latent feature-enhanced generative adversarial network we propose can learn the distribution characteristics of tau PET images of cognitively normal individuals and output the abnormal distribution regions of patients. This model was trained and validated using 1131 tau PET images from multiple centres (with distinct races, i.e., Caucasian and Mongoloid) with different tau PET ligands. The overall quality of synthetic imaging was evaluated using structural similarity (SSIM), peak signal to noise ratio (PSNR), and mean square error (MSE). The model was compared to the fixed templates method for diagnosing and predicting AD. RESULTS: The reconstructed images archived good quality, with SSIM = 0.967 ± 0.008, PSNR = 31.377 ± 3.633, and MSE = 0.0011 ± 0.0007 in the independent test set. The model showed higher classification accuracy (AUC = 0.843, 95 % CI = 0.796-0.890) and stronger correlation with clinical scales (r = 0.508, P < 0.0001). The model also achieved superior predictive performance in the survival analysis of cognitive decline, with a higher hazard ratio: 3.662, P < 0.001. INTERPRETATION: The LFGAN4Tau model presents a promising new approach for more accurate detection of individualized tau deposition. Its robustness across tracers and races makes it a potentially reliable diagnostic tool for AD in practice.

Reduced SV2A and GABAA receptor levels in the brains of type 2 diabetic rats revealed by [18F]SDM-8 and [18F]flumazenil PET.

PURPOSE: Type 2 diabetes mellitus (T2DM) is associated with a greater risk of Alzheimer's disease. Synaptic impairment and protein aggregates have been reported in the brains of T2DM models. Here, we assessed whether neurodegenerative changes in synaptic vesicle 2 A (SV2A), γ-aminobutyric acid type A (GABAA) receptor, amyloid-ß, tau and receptor for advanced glycosylation end product (RAGE) can be detected in vivo in T2DM rats. METHODS: Positron emission tomography (PET) using [18F]SDM-8 (SV2A), [18F]flumazenil (GABAA receptor), [18F]florbetapir (amyloid-ß), [18F]PM-PBB3 (tau), and [18F]FPS-ZM1 (RAGE) was carried out in 12-month-old diabetic Zucker diabetic fatty (ZDF) and SpragueDawley (SD) rats. Immunofluorescence staining, Thioflavin S staining, proteomic profiling and pathway analysis were performed on the brain tissues of ZDF and SD rats. RESULTS: Reduced cortical [18F]SDM-8 uptake and cortical and hippocampal [18F]flumazenil uptake were observed in 12-month-old ZDF rats compared to SD rats. The regional uptake of [18F]florbetapir and [18F]PM-PBB3 was comparable in the brains of 12-month-old ZDF and SD rats. Immunofluorescence staining revealed Thioflavin S-negative, phospho-tau-positive inclusions in the cortex and hypothalamus in the brains of ZDF rats and the absence of amyloid-beta deposits. The level of GABAA receptors was lower in the cortex of ZDF rats than SD rats. Proteomic analysis further demonstrated that, compared with SD rats, synaptic-related proteins and pathways were downregulated in the hippocampus of ZDF rats. CONCLUSION: These findings provide in vivo evidence for regional reductions in SV2A and GABAA receptor levels in the brains of aged T2DM ZDF rats.

Incremental value of amyloid PET in a tertiary memory clinic setting in China.

INTRODUCTION: The objective of this study is to investigate the incremental value of amyloid positron emission tomography (Aß-PET) in a tertiary memory clinic setting in China. METHODS: A total of 1073 patients were offered Aß-PET using 18F-florbetapir. The neurologists determined a suspected etiology (Alzheimer's disease [AD] or non-AD) with a percentage estimate of their confidence and medication prescription both before and after receiving the Aß-PET results. RESULTS: After disclosure of the Aß-PET results, etiological diagnoses changed in 19.3% of patients, and diagnostic confidence increased from 69.3% to 85.6%. Amyloid PET results led to a change of treatment plan in 36.5% of patients. Compared to the late-onset group, the early-onset group had a more frequent change in diagnoses and a higher increase in diagnostic confidence. DISCUSSION: Aß-PET has significant impacts on the changes of diagnoses and management in Chinese population. Early-onset cases are more likely to benefit from Aß-PET than late-onset cases. HIGHLIGHTS: Amyloid PET contributes to diagnostic changes and its confidence in Chinese patients. Amyloid PET leads to a change of treatment plans in Chinese patients. Early-onset cases are more likely to benefit from amyloid PET than late-onset cases.

Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson's disease: a systematic review and meta-analysis.

Artificial intelligence (AI)-assisted PET imaging is emerging as a promising tool for the diagnosis of Parkinson's disease (PD). We aim to systematically review the diagnostic accuracy of AI-assisted PET in detecting PD. The Ovid MEDLINE, Ovid Embase, Web of Science, and IEEE Xplore databases were systematically searched for related studies that developed an AI algorithm in PET imaging for diagnostic performance from PD and were published by August 17, 2023. Binary diagnostic accuracy data were extracted for meta-analysis to derive outcomes of interest: area under the curve (AUC). 23 eligible studies provided sufficient data to construct contingency tables that allowed the calculation of diagnostic accuracy. Specifically, 11 studies were identified that distinguished PD from normal control, with a pooled AUC of 0.96 (95% CI: 0.94-0.97) for presynaptic dopamine (DA) and 0.90 (95% CI: 0.87-0.93) for glucose metabolism (18F-FDG). 13 studies were identified that distinguished PD from the atypical parkinsonism (AP), with a pooled AUC of 0.93 (95% CI: 0.91 - 0.95) for presynaptic DA, 0.79 (95% CI: 0.75-0.82) for postsynaptic DA, and 0.97 (95% CI: 0.96-0.99) for 18F-FDG. Acceptable diagnostic performance of PD with AI algorithms-assisted PET imaging was highlighted across the subgroups. More rigorous reporting standards that take into account the unique challenges of AI research could improve future studies.

Influence of Gender on Tau Precipitation in Alzheimer's Disease According to ATN Research Framework.

Tau proteins accumulation and their spreading pattern were affected by gender in cognitive impairment patients, especially in the progression of Alzheimer's disease (AD). However, it was unclear whether the gender effects for tau deposition influenced by amyloid deposition. The aim of this study was to investigate gender differences for tau depositions in Aß positive (A+) subjects. In this study, tau and amyloid positron emission tomography images, structural magnetic resonance imaging images, and demographic information were collected from 179 subjects in Alzheimer's Disease Neuroimaging Initiative (ADNI) database and 63 subjects from Huashan Hospital. Subjects were classified as T+ or T- according to the presence or absence of tau (T) biomarkers. We used two-sample t test and one-way analysis of variance test to analyze the effect of gender with adjusting for age, years of education, and Minimum Mental State Examination. In the ADNI cohort, we found differences in Tau deposition in fusiform gyrus, inferior temporal gyrus, middle temporal gyrus and parahippocampal gyrus between the female T+ (FT+) and male T+ (MT+) groups (p < 0.05). Tau deposition did not differ significantly between female T- (FT-) and male T- (MT-) subjects (p > 0.05). In the Huashan Hospital cohort, there was no difference in Tau deposition between FT+ and MT+ (p > 0.05). The results show that tau depositions significantly increased in females in above brain regions. Our findings suggest that tau deposition is influenced by gender in the A+ subjects. This result has important clinical implications for the development of gender-guided early interventions for patients with both Tau and Amyloid depositions. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00076-9.