Human biodistribution and radiation dosimetry for the tau tracer [18F]Florzolotau in healthy subjects.

BACKGROUND: Tau pathology plays a crucial role in neurodegeneration diseases including Alzheimer's disease (AD) and non-AD diseases such as progressive supranuclear palsy. Tau positron emission tomography (PET) is an in-vivo and non-invasive medical imaging technique for detecting and visualizing tau deposition within a human brain. In this work, we aim to investigate the biodistribution of the dosimetry in the whole body and various organs for the [18F]Florzolotau tau-PET tracer. A total of 12 healthy controls (HCs) were enrolled at Chang Gung Memorial Hospital. All subjects were injected with approximately 379.03 ± 7.03 MBq of [18F]Florzolotau intravenously, and a whole-body PET/CT scan was performed for each subject. For image processing, the VOI for each organ was delineated manually by using the PMOD 3.7 software. Then, the time-activity curve of each organ was acquired by optimally fitting an exponential uptake and clearance model using the least squares method implemented in OLINDA/EXM 2.1 software. The absorbed dose for each target organ and the effective dose were finally calculated. RESULTS: From the biodistribution results, the elimination of [18F]Florzolotau is observed mainly from the liver to the intestine and partially through the kidneys. The highest organ-absorbed dose occurred in the right colon wall (255.83 µSv/MBq), and then in the small intestine (218.67 µSv/MBq), gallbladder wall (151.42 µSv/MBq), left colon wall (93.31 µSv/MBq), and liver (84.15 µSv/MBq). Based on the ICRP103, the final computed effective dose was 34.9 µSv/MBq with CV of 10.07%. CONCLUSIONS: The biodistribution study of [18F]Florzolotau demonstrated that the excretion of [18F]Florzolotau are mainly through the hepatobiliary and gastrointestinal pathways. Therefore, a routine injection of 370 MBq or 185 MBq of [18F]Florzolotau leads to an estimated effective dose of 12.92 or 6.46 mSv, and as a result, the radiation exposure to the whole-body and each organ remains within acceptable limits and adheres to established constraints. TRIAL REGISTRATION: Retrospectively Registered at Clinicaltrials.gov (NCT03625128) on 12 July, 2018, https://clinicaltrials.gov/study/NCT03625128 .

Dominance of Tau Burden in Cortical Over Subcortical Regions Mediates Glymphatic Activity and Clinical Severity in PSP.

BACKGROUND: Progressive supranuclear palsy (PSP) is a tauopathy that involves subcortical regions but also extends to cortical areas. The clinical impact of different tau protein sites and their influence on glymphatic dysfunction have not been investigated. PATIENTS AND METHODS: Participants (n = 55; 65.6 ± 7.1 years; 29 women) with PSP (n = 32) and age-matched normal controls (NCs; n = 23) underwent 18 F-Florzolotau tau PET, MRI, PSP Rating Scale (PSPRS), and Mini-Mental State Examination. Cerebellar gray matter (GM) and parametric estimation of reference signal intensity were used as references for tau burden measured by SUV ratios. Glymphatic activity was measured by diffusion tensor image analysis along the perivascular space (DTI-ALPS). RESULTS: Parametric estimation of reference signal intensity is a better reference than cerebellar GM to distinguish tau burden between PSP and NCs. PSP patients showed higher cortical and subcortical tau SUV ratios than NCs ( P < 0.001 and <0.001). Cortical and subcortical tau deposition correlated with PSPRS, UPDRS, and Mini-Mental State Examination scores (all P 's < 0.05). Cortical tau deposition was further associated with the DTI-ALPS index and frontal-temporal-parietal GM atrophy. The DTI-ALPS indexes showed a significantly negative correlation with the PSPRS total scores ( P < 0.01). Finally, parietal and occipital lobe tau depositions showed mediating effects between the DTI-ALPS index and PSPRS score. CONCLUSIONS: Cortical tau deposition is associated with glymphatic dysfunction and plays a role in mediating glymphatic dysfunction and clinical severity. Our results provide a possible explanation for the worsening of clinical severity in patients with PSP.

Classification Prediction of Alzheimer's Disease and Vascular Dementia Using Physiological Data and ECD SPECT Images.

Alzheimer's disease (AD) and vascular dementia (VaD) are the two most common forms of dementia. However, their neuropsychological and pathological features often overlap, making it difficult to distinguish between AD and VaD. In addition to clinical consultation and laboratory examinations, clinical dementia diagnosis in Taiwan will also include Tc-99m-ECD SPECT imaging examination. Through machine learning and deep learning technology, we explored the feasibility of using the above clinical practice data to distinguish AD and VaD. We used the physiological data (33 features) and Tc-99m-ECD SPECT images of 112 AD patients and 85 VaD patients in the Taiwanese Nuclear Medicine Brain Image Database to train the classification model. The results, after filtering by the number of SVM RFE 5-fold features, show that the average accuracy of physiological data in distinguishing AD/VaD is 81.22% and the AUC is 0.836; the average accuracy of training images using the Inception V3 model is 85% and the AUC is 0.95. Finally, Grad-CAM heatmap was used to visualize the areas of concern of the model and compared with the SPM analysis method to further understand the differences. This research method can quickly use machine learning and deep learning models to automatically extract image features based on a small amount of general clinical data to objectively distinguish AD and VaD.

The application of machine learning on brain imaging features of different narcolepsy subtypes.

STUDY OBJECTIVES: Narcolepsy is a central hypersomnia disorder, and differential diagnoses between its subtypes can be difficult. Hence, we applied machine learning to analyze the positron emission tomography (PET) data of patients with type 1 or type 2 narcolepsy, and patients with type 1 narcolepsy and comorbid schizophrenia, to construct predictive models to facilitate the diagnosis. METHODS: This is a retrospective and prospective case-control study of adolescent and young adult patients with type 1 or type 2 narcolepsy, and type 1 narcolepsy and comorbid schizophrenia. All participants received 18-F-fluorodeoxy glucose PET, sleep studies, neurocognitive tests, sleep questionnaires, and human leukocyte antigen typing. The collected PET data were analyzed by feature selections and classification methods in machine learning to construct predictive models. RESULTS: A total of 314 participants with narcolepsy were enrolled; 204 had type 1 narcolepsy, 90 had type 2 narcolepsy, and 20 had type 1 narcolepsy and comorbid schizophrenia. We used three filter methods for feature selection followed by a comparative analysis of classification methods. To apply a small number of regions of interest (ROI) and high classification accuracy, the Naïve Bayes classifier with the Term Variance as feature selection achieved the goal with only three ROIs (left basal ganglia, left Heschl, and left striatum) and produced an accuracy of higher than 99%. CONCLUSIONS: The accuracy of our predictive model of PET data are promising and can aid clinicians in the diagnosis of narcolepsy subtypes. Future research with a larger sample size could further refine the predictive model of narcolepsy.

A Radiotherapy Dose Map-Guided Deep Learning Method for Predicting Pathological Complete Response in Esophageal Cancer Patients after Neoadjuvant Chemoradiotherapy Followed by Surgery.

Esophageal cancer is a deadly disease, and neoadjuvant chemoradiotherapy can improve patient survival, particularly for patients achieving a pathological complete response (ypCR). However, existing imaging methods struggle to accurately predict ypCR. This study explores computer-aided detection methods, considering both imaging data and radiotherapy dose variations to enhance prediction accuracy. It involved patients with node-positive esophageal squamous cell carcinoma undergoing neoadjuvant chemoradiotherapy and surgery, with data collected from 2014 to 2017, randomly split into five subsets for 5-fold cross-validation. The algorithm DCRNet, an advanced version of OCRNet, integrates RT dose distribution into dose contextual representations (DCR), combining dose and pixel representation with ten soft regions. Among the 80 enrolled patients (mean age 55.68 years, primarily male, with stage III disease and middle-part lesions), the ypCR rate was 28.75%, showing no significant demographic or disease differences between the ypCR and non-ypCR groups. Among the three summarization methods, the maximum value across the CTV method produced the best results with an AUC of 0.928. The HRNetV2p model with DCR performed the best among the four backbone models tested, with an AUC of 0.928 (95% CI, 0.884-0.972) based on 5-fold cross-validation, showing significant improvement compared to other models. This underscores DCR-equipped models' superior AUC outcomes. The study highlights the potential of dose-guided deep learning in ypCR prediction, necessitating larger, multicenter studies to validate the results.

Visual reading for [18F]Florzolotau ([18F]APN-1607) tau PET imaging in clinical assessment of Alzheimer's disease.

Introduction: Tau-targeted positron emission tomography (tau-PET) is a potential tool for the differential diagnosis of Alzheimer's disease (AD) and to clarify the distribution of tau deposition. In addition to the quantitative analysis of tau-PET scans, visual reading supports the assessment of tau loading for clinical diagnosis. This study aimed to propose a method for visually interpreting tau-PET using the [18F] Florzolotau tracer and investigate the performance and utility of the visual reading. Materials and methods: A total number of 46 individuals with 12 cognitively unimpaired subjects (CU), 20 AD patients with mild cognitive impairment (AD-MCI), and 14 AD with dementia (AD-D) patients with both [18F]Florbetapir amyloid PET and [18F]Florzolotau tau PET scans were included. Clinical information, cognitive assessment, and amyloid PET scan results were recorded. For visual interpretation, a modified rainbow colormap was created and a regional tau uptake scoring system was proposed to evaluate the degree of tracer uptake and its spatial distribution within five cortical regions. Each region was scored on a scale of [0, 2] as compared to the background, and that resulted in a global scale range of [0, 10]. Four readers interpreted [18F]Florzolotau PET using the visual scale. The global and regional standardized uptake value ratios (SUVr) were also calculated for analysis. Results: The result indicates the average global visual scores were 0 ± 0 in the CU group, 3.43 ± 3.35 in the AD-MCI group, and 6.31 ± 2.97 in the AD-D group (p < 0.001). The consensus among the four observers on image scores was high with an intraclass correlation coefficient of 0.880 (95% CI: 0.767-0.936). The average global visual score was significantly associated with global SUVr (r = 0.884, p < 0.0001) and with the CDR-sum of box (r = 0.677, p < 0.0001). Conclusion: The visual reading method generated a visual score of [18F]Florzolotau tau-PET with good sensitivity and specificity to identify AD-D or CU individuals from the other patients. The preliminary result also showed that the global visual scores are significantly and reliably correlated with global cortical SUVr, and associated well with the clinical diagnosis and cognitive performance.

Gold-Nanoparticles-Enhanced Production of Reactive Oxygen Species in Cells at Spread-Out Bragg Peak under Proton Beam Radiation.

This study investigates the radiobiological effects of gold nanoparticles (GNPs) as radiosensitizers for proton beam therapy (PBT). Specifically, we explore the enhanced production of reactive oxygen species (ROS) in GNP-loaded tumor cells irradiated by a 230 MeV proton beam in a spread-out Bragg peak (SOBP) zone obtained by a passive scattering system. Our findings indicate that the radiosensitization enhancement factor is 1.24 at 30% cell survival fraction, 8 days after 6 Gy proton beam irradiation. Since protons deposit the majority of their energy at the SOBP region and interact with GNPs to induce more ejected electrons from the high-Z GNPs, these ejected electrons then react with water molecules to produce excessive ROS that can damage cellular organelles. Laser scanning confocal microscopy reveals the excessive ROS induced inside the GNP-loaded cells immediately after proton irradiation. Furthermore, the damage to cytoskeletons and mitochondrial dysfunction in GNP-loaded cells caused by the induced ROS becomes significantly severe, 48 h after proton irradiation. Our biological evidence suggests that the cytotoxicity of GNP-enhanced ROS production has the potential to increase the tumoricidal efficacy of PBT.

Atrophy, hypometabolism and implication regarding pathology in late-life major depression with suspected non-alzheimer pathophysiology (SNAP).

BACKGROUND: A substantial proportion of individuals with late-life major depression could be classified as having a suspected non-Alzheimer disease pathophysiology (SNAP), as indicated by a negative test for the biomarker ß-amyloid (Aß-) but a positive test for neurodegeneration (ND+). This study investigated the clinical features, characteristic patterns of brain atrophy and hypometabolism, and implications regarding pathology in this population. METHODS: Forty-six amyloid-negative patients with late-life major depressive disorder (MDD) patients, including 23 SNAP (Aß-/ND+) and 23 Aß-/ND- MDD subjects, and 22 Aß-/ND-healthy control subjects were included in this study. Voxel-wise group comparisons between the SNAP MDD, Aß-/ND- MDD and control subjects were performed, adjusting for age, gender and level of education. For exploratory comparisons, 8 Aß+/ND- and 4 Aß+/ND + MDD patients were included in the Supplementary Material. RESULTS: The SNAP MDD patients had atrophy extending to regions outside the hippocampus, predominately in the medial temporal, dorsomedial and ventromedial prefrontal cortex; hypometabolism involving a large portion of the lateral and medial prefrontal cortex in addition to the bilateral temporal, parietal and precuneus cortex within typical Alzheimer disease regions were observed. Metabolism ratios of the inferior to the medial temporal lobe were significantly elevated in the SNAP MDD patients. We further discussed the implications with regards to underlying pathologies. CONCLUSION: The present study demonstrated characteristic patterns of atrophy and hypometabolism in patients with late-life major depression with SNAP. Identifying individuals with SNAP MDD may provide insights into currently unspecified neurodegenerative processes. Future refinement of neurodegeneration biomarkers is essential in order to identify potential pathological correlates while in vivo reliable pathological biomarkers are not forthcoming.

Magnetic Resonance Images Implicate That Glymphatic Alterations Mediate Cognitive Dysfunction in Alzheimer Disease.

OBJECTIVE: The glymphatic system cleans amyloid and tau proteins from the brain in animal studies of Alzheimer disease (AD). However, there is no direct evidence showing this in humans. METHODS: Participants (n = 50, 62.6 ± 5.4 years old, 36 women) with AD and normal controls underwent amyloid positron emission tomography (PET), tau PET, structural T1-weighted magnetic resonance imaging, and neuropsychological evaluation. Whole-brain glymphatic activity was measured by diffusion tensor image analysis along the perivascular space (DTI-ALPS). RESULTS: ALPS-indexes showed negative correlations with deposition of amyloid and tau on PET images and positive correlations with cognitive scores even after adjusting for age, sex, years of education, and APOE4 genotype covariates in multiple AD-related brain regions (all p < 0.05). Mediation analysis showed that ALPS-index acted as a significant mediator between regional standardized uptake value ratios of amyloid and tau images and cognitive dysfunction even after correcting for multiple covariates in AD-related brain regions. These regions are responsible for attention, memory, and executive function, which are vulnerable to sleep deprivation. INTERPRETATION: Glymphatic system activity may act as a significant mediator in AD-related cognitive dysfunction even after adjusting for multiple covariates and gray matter volumes. ALPS-index may provide useful disease progression or treatment biomarkers for patients with AD as an indicator of modulation of glymphatic activity. ANN NEUROL 2023;93:164-174.

Decreased Cerebral Amyloid-ß Depositions in Patients With a Lifetime History of Major Depression With Suspected Non-Alzheimer Pathophysiology.

Cerebral amyloid-ß (Aß) depositions in depression in old age are controversial. A substantial proportion of individuals with late-life major depressive disorder (MDD) could be classified as having suspected non-Alzheimer's disease pathophysiology (SNAP) by a negative test for the biomarker amyloid-ß (Aß-) but positive neurodegeneration (ND+). This study aimed to evaluate subthreshold Aß loads in amyloid-negative MDD, particularly in SNAP MDD patients. This study included 46 amyloid-negative MDD patients: 23 SNAP (Aß-/ND+) MDD and 23 Aß-/ND- MDD, and 22 Aß-/ND- control subjects. All subjects underwent 18F-florbetapir PET, FDG-PET, and MRI. Regions of interest (ROIs) and voxel-wise group comparisons were performed with adjustment for age, gender, and level of education. The SNAP MDD patients exhibited significantly deceased 18F-florbetapir uptakes in most cortical regions but not the parietal and precuneus cortex, as compared with the Aß-/ND- MDD and control subjects (FDR correction, p < 0.05). No correlations of neuropsychological tests or depression characteristics with global cortical uptakes, but significant positive correlations between cognitive functions and adjusted hippocampal volumes among different groups were observed. The reduced Aß depositions in the amyloid-negative MDD patients might be attributed mainly to the SNAP MDD patients. Our results indicated that meaningfully low amounts of subclinical Aß might contain critical information on the non-amyloid-mediated pathogenesis.

Impact of Three-Month Androgen Deprivation Therapy on [68Ga]Ga-PSMA-11 PET/CT Indices in Men with Advanced Prostate Cancer-Results from a Pilot Prospective Study.

Purpose: The purpose of this pilot prospective study is to examine the gallium-68-prostate-specific membrane antigen-11 ([68Ga]Ga-PSMA-11) positron emission tomography/computed tomography (PET/CT) imaging response in patients with advanced or metastatic hormone-naïve prostate cancer (PC) after 3 months of androgen deprivation therapy (ADT). Methods: We prospectively included men with untreated, clinical stage III or IV PC scheduled to receive ADT for at least 6 months. [68Ga]Ga-PSMA-11 PET/CT images were obtained before the start of ADT and 10−14 weeks thereafter. The following indices were examined: maximum standardized uptake value (SUVmax), mean SUV, PSMA total volume, and PSMA total lesion values of the prostate, nodes, bones, and whole-body. The therapeutic response was assessed using the modified PET response criteria in solid tumors 1.0. A subgroup analysis of patients with the International Society of Urological Pathology (ISUP) grade group 5 versus <5 was also performed. Results: A total of 30 patients were eligible. All PSMA PET/CT indices were significantly reduced (p < 0.001) after 3 months of ADT. Twenty-four (80%) patients showed partial response. Complete response, stable disease, and disease progression were observed in two patients each. Sixteen patients with ISUP grade group 5 showed a less prominent SUVmax reduction (p = 0.006), and none of them reached complete response. Conclusions: Three months of ADT in patients with untreated, advanced PC significantly reduced PSMA PET/CT indices. While most participants partially responded to ADT, patients with ISUP grade group 5 showed a less prominent SUVmax reduction. Collectively, our pilot results indicate that [68Ga]Ga-PSMA-11 PET/CT imaging holds promise to monitor treatment response after the first three months of ADT.

Comparisons of vesicular monoamine transporter type 2 signals in Parkinson's disease and parkinsonism secondary to carbon monoxide poisoning.

Parkinson's disease (PD) and carbon monoxide (CO) poisoning demonstrate parkinsonian features related to presynaptic dopaminergic deficits. However, their clinical features and treatment responses are different, indicating other roles of neurotransmitters in symptomatic modulation. In this study, we used 18F-FP-(+)-DTBZ PET to explore vesicular monoamine transporter type 2 (VMAT2) distributions in 31 patients with PD, 39 patients with CO poisoning and parkinsonian features (n = 39), and 24 age-matched controls. In addition to the disease-specific VMAT2 topographies in PD and CO poisoning, we also constructed feature-specific functional networks. The cardinal features included tremor, rigidity, akinesia, and rapid alternating movements (RAM), and the overall motor severity was scored using Unified Parkinson Disease Rating Scale (UPDRS) and modified Hoehn-Yahr (mH-Y) Scale scores. Our results suggested that a reduction in VMAT2 signals in the caudate, amygdala, and hippocampus were more specific to CO poisoning, while low uptake in the putamen and substantia nigra was more specific to PD. UPDRS and mH-Y scores were related to striatum signals in both groups and hippocampus and raphe in the CO poisoning group. With regards to the cardinal features, the putamen was related to akinesia in both groups. The substantia nigra was related to rigidity in PD, and the caudate and nucleus accumbens were related to akinesia, RAM and rigidity in CO poisoning. Our study enhances the current understanding of different patterns of monoaminergic terminal deficits in patients with CO poisoning and PD.

Neurodegeneration and Vascular Burden on Cognition After Midlife: A Plasma and Neuroimaging Biomarker Study.

Background and Objectives: Neurodegeneration and vascular burden are the two most common causes of post-stroke cognitive impairment. However, the interrelationship between the plasma beta-amyloid (Aß) and tau protein, cortical atrophy and brain amyloid accumulation on PET imaging in stroke patients is undetermined. We aimed to explore: (1) the relationships of cortical thickness and amyloid burden on PET with plasma Aß40, Aß42, tau protein and their composite scores in stroke patients; and (2) the associations of post-stroke cognitive presentations with these plasma and neuroimaging biomarkers. Methods: The prospective project recruited first-ever ischemic stroke patients around 3 months after stroke onset. The plasma Aß40, Aß42, and total tau protein were measured with the immunomagnetic reduction method. Cortical thickness was evaluated on MRI, and cortical amyloid plaque deposition was evaluated by 18F-florbetapir PET. Cognition was evaluated with Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), Dementia Rating Scale-2 (DRS-2). Results: The study recruited 24 stroke patients and 13 normal controls. The plasma tau and tau*Aß42 levels were correlated with mean cortical thickness after age adjustment. The Aß42/Aß40 ratio was correlated with global cortical 18F-florbetapir uptake value. The DRS-2 and GDS scores were associated with mean cortical thickness and plasma biomarkers, including Aß42/Aß40, tau, tau*Aß42, tau/Aß42, and tau/Aß40 levels, in stroke patients. Conclusion: Plasma Aß, tau, and their composite scores were associated with cognitive performance 3 months after stroke, and these plasma biomarkers were correlated with corresponding imaging biomarkers of neurodegeneration. Further longitudinal studies with a larger sample size are warranted to replicate the study results.

The Feasibility of Differentiating Lewy Body Dementia and Alzheimer's Disease by Deep Learning Using ECD SPECT Images.

The correct differential diagnosis of dementia has an important impact on patient treatment and follow-up care strategies. Tc-99m-ECD SPECT imaging, which is low cost and accessible in general clinics, is used to identify the two common types of dementia, Alzheimer's disease (AD) and Lewy body dementia (LBD). Two-stage transfer learning technology and reducing model complexity based on the ResNet-50 model were performed using the ImageNet data set and ADNI database. To improve training accuracy, the three-dimensional image was reorganized into three sets of two-dimensional images for data augmentation and ensemble learning, then the performance of various deep learning models for Tc-99m-ECD SPECT images to distinguish AD/normal cognition (NC), LBD/NC, and AD/LBD were investigated. In the AD/NC, LBD/NC, and AD/LBD tasks, the AUC values were around 0.94, 0.95, and 0.74, regardless of training models, with an accuracy of 90%, 87%, and 71%, and F1 scores of 89%, 86%, and 76% in the best cases. The use of transfer learning and a modified model resulted in better prediction results, increasing the accuracy by 32% for AD/NC. The proposed method is practical and could rapidly utilize a deep learning model to automatically extract image features based on a small number of SPECT brain perfusion images in general clinics to objectively distinguish AD and LBD.

Detection of Alzheimer's disease using ECD SPECT images by transfer learning from FDG PET.

OBJECTIVE: To develop a practical method to rapidly utilize a deep learning model to automatically extract image features based on a small number of SPECT brain perfusion images in general clinics to objectively evaluate Alzheimer's disease (AD). METHODS: For the properties of low cost and convenient access in general clinics, Tc-99-ECD SPECT imaging data in brain perfusion detection was used in this study for AD detection. Two-stage transfer learning based on the Inception v3 network model was performed using the ImageNet dataset and ADNI database. To improve training accuracy, the three-dimensional image was reorganized into three sets of two-dimensional images for data augmentation and ensemble learning. The effect of pre-training parameters for Tc-99m-ECD SPECT image to distinguish AD from normal cognition (NC) was investigated, as well as the effect of the sample size of F-18-FDG PET images used in pre-training. The same model was also fine-tuned for the prediction of the MMSE score from the Tc-99m-ECD SPECT image. RESULTS: The AUC values of w/wo pre-training parameters for Tc-99m-ECD SPECT image to distinguish AD from NC were 0.86 and 0.90. The sensitivity, specificity, precision, accuracy, and F1 score were 100%, 75%, 76%, 86%, and 86%, respectively for the training model with 1000 cases of F-18-FDG PET image for pre-training. The AUC values for various sample sizes of the training dataset (100, 200, 400, 800, 1000 cases) for pre-training were 0.86, 0.91, 0.95, 0.97, and 0.97. Regardless of the pre-training condition ECD dataset used, the AUC value was greater than 0.85. Finally, predicting cognitive scores and MMSE scores correlated (R2 = 0.7072). CONCLUSIONS: With the ADNI pre-trained model, the sensitivity and accuracy of the proposed deep learning model using SPECT ECD perfusion images to differentiate AD from NC were increased by approximately 30% and 10%, respectively. Our study indicated that the model trained on PET FDG metabolic imaging for the same disease could be transferred to a small sample of SPECT cerebral perfusion images. This model will contribute to the practicality of SPECT cerebral perfusion images using deep learning technology to objectively recognize AD.

Different positron emission tomography findings in schizophrenia and narcolepsy type 1 in adolescents and young adults: a preliminary study.

STUDY OBJECTIVES: The association between schizophrenia and narcolepsy has been controversial. We conducted a prospective case control study of schizophrenia and comorbid narcolepsy type 1 in adolescents compared with patients with either diagnosis alone and healthy controls using 18F-fluorodeoxy glucose positron emission tomography, sleep studies, and neurocognitive tests. METHODS: We included 11 patients (9-20 years old) with schizophrenia and comorbid narcolepsy type 1, 11 with narcolepsy type 1, 11 with schizophrenia, and 11 controls. All groups were matched for age and sex. Participants were required to submit to clinical interviews for sleep and psychiatric disorders, sleep questionnaires, continuous performance test, Wisconsin card sorting test, sleep studies including polysomnography, multiple sleep latency test and actigraphy, and positron emission tomography studies. All data were analyzed to compare the differences between the 4 groups. RESULTS: The positron emission tomography results demonstrated significant differences in the dual diagnoses group compared with the 3 other groups. Compared with the controls, the dual diagnoses group had a significant presence of hypometabolism in the right mid-frontal, right orbital inferior frontal, and right posterior cingulum and a significant presence of hypermetabolism in the left amygdala, bilateral striatum, bilateral substantia nigra, bilateral basal ganglia, and bilateral thalamus. Continuous performance tests and Wisconsin card sorting tests showed that the dual diagnoses group had the worst performance. CONCLUSIONS: Patients with schizophrenia and comorbid narcolepsy type 1 had different positron emission tomography findings than those with either schizophrenia or narcolepsy type 1 alone. They also had more neurocognitive impairments and required additional interventions.

18F-THK5351 PET imaging in patients with progressive supranuclear palsy: associations with core domains and diagnostic certainty.

The associations of 18F-THK5351 tau positron emission tomography (PET) findings with core domains of progressive supranuclear palsy (PSP) and its diagnostic certainty have yet to be fully elucidated. The 18F-THK5351 PET patterns of 17 patients with PSP (68.9 ± 6.5 years; 8 women) were compared with those observed in 28 age-matched and sex-matched (66.2 ± 4.5 years, 18 women) control subjects (CS). Tracer accumulation-as reflected by standardized uptake value ratios (SUVRs) and z-scores-was correlated with core domains of PSP and different levels of diagnostic certainty. Compared with CS, patients with PSP showed an increased 18F-THK5351 uptake in the globus pallidus and red nucleus. Patients with PSP and oculomotor dysfunction had significantly higher SUVRs in the midbrain, red nucleus, and raphe nucleus than those without. In addition, cases who meet criteria for level 1 (highest) certainty in the postural instability domain showed significantly higher SUVRs in the frontal, parietal, precuneus, and sensory-motor cortex. Patients with probable PSP had significantly higher SUVR values than those with possible PSP in multiple cortical (i.e., frontal, parietal, temporal, anterior cingulate gyrus, precuneus, and sensory-motor gyrus) and subcortical (i.e., putamen, thalamus, and raphe nucleus) regions. Patterns of 18F-THK5351 uptake were correlated to core domains of PSP-including oculomotor dysfunction and postural instability. Moreover, the degree of diagnostic certainty for PSP was appreciably associated with 18F-THK5351 PET findings.

Investigation of reactive astrogliosis effect on post-stroke cognitive impairment.

BACKGROUND: The aim of this study is to investigate the associations between post-stroke cognitive impairment (PSCI) severity and reactive astrogliosis (RA) extent on normalized 18F-THK-5351 positron-emission tomography (PET) imaging in amyloid-negative patients with first-ever stroke. METHODS: We prospectively enrolled 63 amyloid-negative patients with first-ever stroke. Neurocognitive evaluation, MRI, 18F-THK-5351, and 18F-florbetapir PET were performed around 3 months after stroke. The 18F-THK-5351 uptake intensity was normalized using a signal distribution template to obtain the Z-SUM scores as the RA extent in the whole brain and cerebral hemisphere ipsilateral to stroke lesion. We evaluated stroke volume, leukoaraiosis, and brain atrophy on MRI. We used a comprehensive neurocognitive battery to obtain composite cognitive scores, and defined PSCI as a general cognitive function score < - 1. We analyzed the influence of Z-SUM scores on PSCI severity after adjusting for demographic, vascular, and neurodegenerative variables. RESULTS: Twenty-five of 63 stroke patients had PSCI. Patients with PSCI had older age, lower education, and more severe cortical atrophy and total Z-SUM scores. Total Z-SUM scores were significantly associated with general cognitive and executive functions at multiple regression models. Path analyses showed that stroke can exert cognitive influence directly by stroke itself as well as indirectly through RA, including total and ipsilateral Z-SUM scores, in patients with either right or left hemisphere stroke. CONCLUSION: The patterns and intensity of 18F-THK-5351 uptake in amyloid-negative patients with first-ever stroke were associated with PSCI manifestations, which suggests that RA presents a modulating effect in PSCI development.

The Imaging Features and Clinical Associations of a Novel Tau PET Tracer-18F-APN1607 in Alzheimer Disease.

PURPOSE OF THE REPORT: In vivo tau PET imaging could help clarify the spatial distribution of tau deposition in Alzheimer disease (AD) and aid in the differential diagnosis of tauopathies. To date, there have been no in vivo F-APN1607 tau PET studies in patients with AD. METHODS: We applied tau tracer in 12 normal controls (NCs) and 10 patients in the mild to moderate stage of probable AD. Detailed clinical information, cognitive measurements, and disease severity were documented. Regional SUV ratios (SUVRs) from F-AV-45 (florbetapir), F-APN1607 PET images, and regional gray matter (GM) atrophic ratios were calculated for further analysis. RESULTS: Quantitative analyses showed significantly elevated SUVRs in the frontal, temporal, parietal, occipital lobes, anterior and posterior cingulate gyri, precuneus, and parahippocampal region (all P's < 0.01) with medium to large effect sizes (0.44-0.75). The SUVRs from F-APN1607 PET imaging showed significant correlations with the Alzheimer's Disease Assessment Scale (ADAS-cog) scores (all P's < 0.01) and strong correlation coefficients (R ranged from 0.54 to 0.68), even adjusted for age and sex effects. Finally, the SUVRs from F-APN1607 PET imaging of the parahippocampal region showed rapid saturation as the ADAS-cog scores increased, and the SUVRs of the posterior cingulate gyrus and the temporal, frontal, parietal, and occipital regions slowly increased. The combined SUVRs from amyloid, tau PET, and regional GM atrophic ratio showed regional specific patterns as the ADAS-cog scores increased. CONCLUSIONS: Our findings suggest that the F-APN1607 tau tracer correlated well with cognitive changes and demonstrated the spatial pattern of amyloid, tau deposition, and GM atrophy in the progression of AD.