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.

Pilot implementation of the revised criteria for staging of Alzheimer's disease by the Alzheimer's Association Workgroup in a tertiary memory clinic.

INTRODUCTION: We aimed to evaluate the feasibility of the 2024 Alzheimer's Association Workgroup's integrated clinical-biological staging scheme in outpatient settings within a tertiary memory clinic. METHODS: The 2018 syndromal cognitive staging system, coupled with a binary biomarker classification, was implemented for 236 outpatients with cognitive concerns. The 2024 numeric clinical staging framework, incorporating biomarker staging, was specifically applied to 154 individuals within the Alzheimer's disease (AD) continuum. RESULTS: The 2024 staging scheme accurately classified 95.5% AD. Among these, 56.5% exhibited concordant clinical and biological stages (canonical), 34.7% demonstrated more advanced clinical stages than biologically expected (susceptible), and 8.8% displayed the inverse pattern (resilient). The susceptible group was characterized by a higher burden of neurodegeneration and inflammation than anticipated from tau, whereas the resilient group showed the opposite. DISCUSSION: The 2024 staging scheme is generally feasible. A discrepancy between clinical and biological stages is relatively frequent among symptomatic patients with AD. HIGHLIGHTS: The 2024 AA staging scheme is generally feasible in a tertiary memory clinic. A discrepancy between clinical and biological stages is relatively frequent in AD. The mismatch may be influenced by a non-specific pathological process involved in AD. Individual profiles like aging and lifestyles may contribute to such a mismatch. Matched and mismatched cases converge toward similar clinical outcomes.

Effects of brain radiotherapy strategies on survival in the era of MRI for patients with limited stage small cell lung cancer.

BACKGROUND AND PURPOSE: In the context of the widespread availability of magnetic resonance imaging (MRI) and aggressive salvage irradiation techniques, there has been controversy surrounding the use of prophylactic cranial irradiation (PCI) for small-cell lung cancer (SCLC) patients. This study aimed to explore whether regular brain MRI plus salvage brain irradiation (SBI) is not inferior to PCI in patients with limited-stage SCLC (LS-SCLC). METHODS: This real-world multicenter study, which was conducted between January 2014 and September 2020 at three general hospitals, involved patients with LS-SCLC who had a good response to initial chemoradiotherapy and no brain metastasis confirmed by MRI. Overall survival (OS) was compared between patients who did not receive PCI for various reasons but chose regular MRI surveillance and followed salvage brain irradiation (SBI) when brain metastasis was detected and patients who received PCI. RESULTS: 120 patients met the inclusion criteria. 55 patients received regular brain MRI plus SBI (SBI group) and 65 patients received PCI (PCI group). There was no statistically significant difference in median OS between the two groups (27.14 versus 33.00 months; P = 0.18). In the SBI group, 32 patients underwent whole brain radiotherapy and 23 patients underwent whole brain radiotherapy + simultaneous integrated boost. On multivariate analysis, only extracranial metastasis was independently associated with poor OS in the SBI group. CONCLUSION: The results of this real-world study showed that MRI surveillance plus SBI is not inferior to PCI in OS for LS-SCLC patients who had a good response to initial chemoradiotherapy.

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.

Sensitive, Semiquantitative, and Portable Nucleic Acid Detection of Rabies Virus Using a Personal Glucose Meter.

Rabies is a zoonotic infection with the potential to infect all mammals and poses a significant threat to mortality. Although enzyme-linked immunosorbent tests and real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) have been established for rabies virus (RABV) detection, they require skilled staff. Here, we introduce a personal glucose meter (PGM)-based nucleic acid (NA-PGM) detection method to diagnose RABV. This method ensures sensitive and convenient RABV diagnosis through hybridization of reverse transcription-recombinase aided amplification (RT-RAA) amplicons with probes labeled with sucrose-converting enzymes, reaching a detection level as low as 6.3 copies/µL equivalent to 12.26 copies. NA-PGM allows for the differentiation of RABV from other closely related viruses. In addition, NA-PGM showed excellent performance on 65 clinical samples with a 100% accuracy rate compared with the widely adopted RT-qPCR method. Thus, our developed NA-PGM method stands out as sensitive, semiquantitative, and portable for RABV detection, showcasing promise as a versatile platform for a wide range of pathogens.

Temporal regulation of MDA5 inactivation by Caspase-3 dependent cleavage of 14-3-3η.

The kinetics of type I interferon (IFN) induction versus the virus replication compete, and the result of the competition determines the outcome of the infection. Chaperone proteins that involved in promoting the activation kinetics of PRRs rapidly trigger antiviral innate immunity. We have previously shown that prior to the interaction with MAVS to induce type I IFN, 14-3-3η facilitates the oligomerization and intracellular redistribution of activated MDA5. Here we report that the cleavage of 14-3-3η upon MDA5 activation, and we identified Caspase-3 activated by MDA5-dependent signaling was essential to produce sub-14-3-3η lacking the C-terminal helix (αI) and tail. The cleaved form of 14-3-3η (sub-14-3-3η) could strongly interact with MDA5 but could not support MDA5-dependent type I IFN induction, indicating the opposite functions between the full-length 14-3-3η and sub-14-3-3η. During human coronavirus or enterovirus infections, the accumulation of sub-14-3-3η was observed along with the activation of Caspase-3, suggesting that RNA viruses may antagonize 14-3-3η by promoting the formation of sub-14-3-3η to impair antiviral innate immunity. In conclusion, sub-14-3-3η, which could not promote MDA5 activation, may serve as a negative feedback to return to homeostasis to prevent excessive type I IFN production and unnecessary inflammation.

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.

AgentLens: Visual Analysis for Agent Behaviors in LLM-based Autonomous Systems.

Recently, Large Language Model based Autonomous System (LLMAS) has gained great popularity for its potential to simulate complicated behaviors of human societies. One of its main challenges is to present and analyze the dynamic events evolution of LLMAS. In this work, we present a visualization approach to explore the detailed statuses and agents' behavior within LLMAS. Our approach outlines a general pipeline that organizes raw execution events from LLMAS into a structured behavior model. We leverage a behavior summarization algorithm to create a hierarchical summary of these behaviors, arranged according to their sequence over time. Additionally, we design a cause trace method to mine the causal relationship between agent behaviors. We then develop AgentLens, a visual analysis system that leverages a hierarchical temporal visualization for illustrating the evolution of LLMAS, and supports users to interactively investigate details and causes of agents' behaviors. Two usage scenarios and a user study demonstrate the effectiveness and usability of our AgentLens.

The status and influencing factors of lung ventilation function in employees exposed to dust in enterprises of the XPCC, China.

Background: Occupational health is closely related to harmful factors in the workplace. Dust is the primary contributing factor causing impaired lung ventilation function among employees with dust exposure, and their lung ventilation function may also be influenced by other factors. We aimed at assessing the status and influencing factors of lung ventilation function among employees exposed to dust in the enterprises of the Eighth Division located in the Xinjiang Production and Construction Corps (XPCC), China. Methods: Employees exposed to dust in enterprises of the Eighth Division located in the XPCC in 2023 were selected as the subjects of this cross-sectional study. Their lung ventilation function indicators were extracted from health examination records, and an on-site electronic questionnaire survey was conducted among them. Binary logistic regression analyses were conducted to evaluate the factors influencing lung ventilation function. Results: According to the fixed value criteria, the abnormal rates of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), and FEV1/FVC were 31.6, 1.4, and 0.4%, respectively. The lower limit of normal (LLN) criteria could overestimate the rate of abnormal lung ventilation function. Several factors were related to impaired lung ventilation function, including gender, age, education level, marital status, body mass index (BMI), smoking status, physical activity, the type of dust, industry, enterprise scale, occupation, length of service, working shift, monthly income, and respiratory protection. Conclusions: A relatively low abnormal rate of lung ventilation function was observed among employees exposed to dust in enterprises of the Eighth Division, XPCC, and their lung ventilation function was associated with various factors. Effective measures should be taken urgently to reduce the effects of adverse factors on lung ventilation function, thereby further protecting the health of the occupational population.

Diagnostic and prognostic nomograms for laryngeal carcinoma patients with lung metastasis: a SEER-based study.

PURPOSE: To establish two nomograms to quantify the risk of lung metastasis (LM) in laryngeal carcinoma (LC) and predict the overall survival of LC patients with LM. METHODS: Totally 9515 LC patients diagnosed histologically from 2000 to 2019 were collected from the Surveillance, Epidemiology, and End Results database. The independent diagnostic factors for LM in LC patients and prognostic factors for LC patients with LM were identified by logistic and Cox regression analysis, respectively. Nomograms were established based on regression coefficients and evaluated by receiver operating characteristic curve, calibration curves, and decision curve analysis. RESULTS: Patients with supraglottis, higher pathological grade, higher N stage, and distant metastasis (bone, brain, or liver) were more likely to have LM (P < 0.05). Chemotherapy, surgery and radiotherapy were independent factors of the overall survival of LC patients with LM (P < 0.05). The area under curve of diagnostic nomogram were 0.834 and 0.816 in the training and validation cohort respectively. For the prognostic nomogram, the area under curves of 1-, 2-, and 3-years were 0.735, 0.734, and 0.709 in the training cohort and 0.705, 0.803, and 0.809 in the validation cohort. The calibration curves and decision curve analysis indicated good performance of the nomograms. CONCLUSION: Distant metastasis (bone, brain, or liver) and N stage should be considered for prediction of LM in LC patients. Chemotherapy is the most significant influencing prognostic factor improving the survival of LC patients with LM. Two nomograms may benefit for providing better precautionary measures and treatment decision.

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.

Colocalization of Increased Midbrain Signals in Neuroinflammation and Tau PET Imaging Suggests the Diagnosis of Progressive Supranuclear Palsy.

ABSTRACT: Clinical overlap with multiple other neurological diseases makes the diagnosis of autoimmune encephalitis challenging; consequently, a broad range of neurological diseases are misdiagnosed as autoimmune encephalitis. A 58-year-old man presented with abnormal behavior, irritability for 3 years, oculomotor disturbance, unsteady walking, and dysphagia and was suspected as having anti-dipeptidyl-peptidase-like protein 6 (DPPX) encephalitis as the anti-DPPX antibody was positive in the serum. However, the therapeutic effect of immunotherapy was unsatisfactory. Subsequently, colocalization of increased midbrain signals was observed in neuroinflammation PET using [ 18 F]DPA-714 and in tau PET using [ 18 F]florzolotau, suggesting the diagnosis of progressive supranuclear palsy.

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.

International consensus on clinical use of presynaptic dopaminergic positron emission tomography imaging in parkinsonism.

PURPOSE: Presynaptic dopaminergic positron emission tomography (PET) imaging serves as an essential tool in diagnosing and differentiating patients with suspected parkinsonism, including idiopathic Parkinson's disease (PD) and other neurodegenerative and non-neurodegenerative diseases. The PET tracers most commonly used at the present time mainly target dopamine transporters (DAT), aromatic amino acid decarboxylase (AADC), and vesicular monoamine type 2 (VMAT2). However, established standards for the imaging procedure and interpretation of presynaptic dopaminergic PET imaging are still lacking. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform presynaptic dopaminergic PET imaging. METHOD: A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for presynaptic dopaminergic PET imaging in parkinsonism, focusing on standardized recommendations, procedures, interpretation, and reporting. CONCLUSION: This international consensus and practice guideline will help to promote the standardized use of presynaptic dopaminergic PET imaging in parkinsonism. It will become an international standard for this purpose in clinical practice.

PD-1 inhibitors plus chemotherapy as first-line therapy for stage IV ESCC.

To evaluate the anti-tumor efficacy and tolerability of programmed cell death protein 1 (PD-1) inhibitors plus chemotherapy versus chemotherapy alone as first-line therapy for unresectable esophageal squamous cell carcinoma (ESCC) patients at stage IV in a real-world cohort. All unresectable ESCC patients at stage IV who initiated first-line therapy with PD-1 inhibitors plus chemotherapy between August 2018 and March 2021 in a general hospital in China were retrospectively analyzed in this study. Propensity score matching (1:1) with control patients receiving chemotherapy alone was performed. Overall survival (OS) and progression-free survival (PFS) were assessed by the Kaplan-Meier method. In this study, fifty patients (n = 25 each group) were included, all of whom could be evaluated for efficacy. PD-1 inhibitors plus chemotherapy exhibited better OS than chemotherapy alone (median 15.8 vs 12.4 months, hazard ratio [HR] 0.46 [95% CI 0.23-0.95]; P = 0.036). The median PFS for the PD-1 inhibitors plus chemotherapy group was 8.7 months compared with 6.1 months for the chemotherapy group (HR 0.48 [95% CI 0.26-0.90]; P = 0.014). Adverse events (AEs) of grade 3 or above related to treatment were found in 24.0% and 32.0% of the PD-1 inhibitors plus chemotherapy and chemotherapy alone groups, respectively. PD-1 inhibitors plus chemotherapy exhibited durable anti-tumor activity and relatively controllable safety as first-line therapy for unresectable ESCC patients at stage IV, but these results need to be confirmed by further research.

Differentiable Design Galleries: A Differentiable Approach to Explore the Design Space of Transfer Functions.

The transfer function is crucial for direct volume rendering (DVR) to create an informative visual representation of volumetric data. However, manually adjusting the transfer function to achieve the desired DVR result can be time-consuming and unintuitive. In this paper, we propose Differentiable Design Galleries, an image-based transfer function design approach to help users explore the design space of transfer functions by taking advantage of the recent advances in deep learning and differentiable rendering. Specifically, we leverage neural rendering to learn a latent design space, which is a continuous manifold representing various types of implicit transfer functions. We further provide a set of interactive tools to support intuitive query, navigation, and modification to obtain the target design, which is represented as a neural-rendered design exemplar. The explicit transfer function can be reconstructed from the target design with a differentiable direct volume renderer. Experimental results on real volumetric data demonstrate the effectiveness of our method.

Uncovering distinct progression patterns of tau deposition in progressive supranuclear palsy using [18F]Florzolotau PET imaging and subtype/stage inference algorithm.

BACKGROUND: Progressive supranuclear palsy (PSP) is a primary 4-repeat tauopathy with diverse clinical phenotypes. Previous post-mortem studies examined tau deposition sequences in PSP, but in vivo scrutiny is lacking. METHODS: We conducted [18F]Florzolotau tau positron emission tomography (PET) scans on 148 patients who were clinically diagnosed with PSP and 20 healthy controls. We employed the Subtype and Stage Inference (SuStaIn) algorithm to identify PSP subtype/stage and related tau patterns, comparing clinical features across subtypes and assessing PSP stage-clinical severity association. We also evaluated functional connectivity differences among subtypes through resting-state functional magnetic resonance imaging. FINDINGS: We identified two distinct subtypes of PSP: Subtype1 and Subtype2. Subtype1 typically exhibits a sequential progression of the disease, starting from subcortical and gradually moving to cortical regions. Conversely, Subtype2 is characterized by an early, simultaneous onset in both regions. Interestingly, once the disease is initiated, Subtype1 tends to spread more rapidly within each region compared to Subtype2. Individuals categorized as Subtype2 are generally older and exhibit less severe dysfunctions in areas such as cognition, bulbar, limb motor, and general motor functions compared to those with Subtype1. Moreover, they have a more favorable prognosis in terms of limb motor function. We found significant correlations between several clinical variables and the identified PSP SuStaIn stages. Furthermore, Subtype2 displayed a remarkable reduction in functional connectivity compared to Subtype1. INTERPRETATION: We present the evidence of distinct in vivo spatiotemporal tau trajectories in PSP. Our findings can contribute to precision medicine advancements for PSP. FUNDING: This work was supported by grants from the National Natural Science Foundation of China (number 82272039, 81971641, 82021002, and 92249302); Swiss National Science Foundation (number 188350); the STI2030-Major Project of China (number 2022ZD0211600); the Clinical Research Plan of Shanghai Hospital Development Center of China (number SHDC2020CR1038B); and the National Key R&D Program of China (number 2022YFC2009902, 2022YFC2009900), the China Scholarship Council (number 202006100181); the Deutsche Forschungsgemeinschaft (DFG) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy, ID 390857198).

Incidence and risk factors for occult lesions in low-risk papillary thyroid microcarcinoma patients with tumor characteristics appropriate for thermal ablation: A retrospective study.

In recent years, thermal ablation has been increasingly employed for the treatment of low-risk papillary thyroid microcarcinoma (PTMC) across various institutions. Its use as a standard or initial treatment continues to be a subject of debate. Retrospective analyses of the surgical pathology in post-ablation patients have indicated that occult lesions are not uncommon. This retrospective study aimed to examine the incidence and risk factors of occult lesions via postoperative pathology in low-risk PTMC patients who fulfilled the criteria for thermal ablation therapy. We examined the medical records of patients who underwent thyroid surgery and had a Bethesda classification V or VI based on fine needle aspiration cytology between November 22, 2020, and December 31, 2022. A total of 413 patients with preoperative tumor characteristics appropriate for thermal ablation were included in this study. Occult lesions, encompassing ipsilateral or contralateral occult carcinoma or central lymph node metastases may have occurred in 34.7% of patients. Male gender (OR: 2.526, 95% CI: 1.521-4.195, P = .000), tumor location in the lower pole (OR: 1.969, 95% CI: 1.186-3.267, P = .009), multiple microcalcifications (OR: 5.620, 95% CI: 2.837-11.134, P = .000), and Hashimoto's thyroiditis (OR: 2.245, 95% CI: 1.292-3.899, P = .004) were independent risk factors for the presence of occult lesions. In low-risk PTMC patients exhibiting tumor characteristics amenable to thermal ablation, over one-third of the patients may present with occult lesions. Meticulous evaluation of the presence of additional lesions is necessary before performing thermal ablation, particularly in patients exhibiting high-risk factors for occult lesions.

Improved interpretation of 18F-florzolotau PET in progressive supranuclear palsy using a normalization-free deep-learning classifier.

While 18F-florzolotau tau PET is an emerging biomarker for progressive supranuclear palsy (PSP), its interpretation has been hindered by a lack of consensus on visual reading and potential biases in conventional semi-quantitative analysis. As clinical manifestations and regions of elevated 18F-florzolotau binding are highly overlapping in PSP and the Parkinsonian type of multiple system atrophy (MSA-P), developing a reliable discriminative classifier for 18F-florzolotau PET is urgently needed. Herein, we developed a normalization-free deep-learning (NFDL) model for 18F-florzolotau PET, which achieved significantly higher accuracy for both PSP and MSA-P compared to semi-quantitative classifiers. Regions driving the NFDL classifier's decision were consistent with disease-specific topographies. NFDL-guided radiomic features correlated with clinical severity of PSP. This suggests that the NFDL model has the potential for early and accurate differentiation of atypical parkinsonism and that it can be applied in various scenarios due to not requiring subjective interpretation, MR-dependent, and reference-based preprocessing.

International Nuclear Medicine Consensus on the Clinical Use of Amyloid Positron Emission Tomography in Alzheimer's Disease.

Alzheimer's disease (AD) is the main cause of dementia, with its diagnosis and management remaining challenging. Amyloid positron emission tomography (PET) has become increasingly important in medical practice for patients with AD. To integrate and update previous guidelines in the field, a task group of experts of several disciplines from multiple countries was assembled, and they revised and approved the content related to the application of amyloid PET in the medical settings of cognitively impaired individuals, focusing on clinical scenarios, patient preparation, administered activities, as well as image acquisition, processing, interpretation and reporting. In addition, expert opinions, practices, and protocols of prominent research institutions performing research on amyloid PET of dementia are integrated. With the increasing availability of amyloid PET imaging, a complete and standard pipeline for the entire examination process is essential for clinical practice. This international consensus and practice guideline will help to promote proper clinical use of amyloid PET imaging in patients with AD.