Fluorodeoxyglucose Positron Emission Tomography Research Articles

ImmunoPET imaging of LAG-3 expression in tumor microenvironment with 68Ga-labelled cyclic peptides tracers: from bench to bedside

BackgroundLymphocyte activation gene 3 (LAG-3) has been considered as the next generation of immune checkpoint and a promising prognostic biomarker of immunotherapy. As with programmed cell death protein-1/programmed death-ligand 1...

Impact of cognitive behavioural therapy on neural, inflammatory, & autonomic markers in a sample with PTSD and cardiovascular risk: protocol for a pilot randomised controlled trial

ABSTRACT Background: Individuals with posttraumatic stress disorder (PTSD) are at heightened risk for cardiovascular disease (CVD) compared to the general population. Inflammation and autonomic dysfunction are candidate mechanisms of CVD risk in PTSD; however, these mechanisms have not been well-characterised in the PTSD-CVD link. Further, these mechanisms may operate through altered stress-related neural activity (SNA). Yet, it remains unknown if changes in PTSD are associated with changes in CVD risk mechanisms. Objective: This manuscript describes the design and procedures of a pilot randomised controlled trial to assess the impact of a first-line treatment for PTSD (Cognitive Processing Therapy; CPT) versus waitlist control on mechanisms of CVD risk. Further, this study will test the hypothesis that CPT reduces CVD risk through its effects on inflammation and autonomic function and that these changes are driven by changes in SNA. Methods: Adults with PTSD and CVD risk (N = 30) will be randomised to CPT or waitlist control. Participants complete two laboratory visits (baseline and post-treatment) that include surveys, brain and peripheral imaging via 18F-fluorodeoxyglucose positron emission tomography (FDG-PET), and resting measures of autonomic function. Primary outcomes include arterial inflammation and heart rate variability. Secondary outcomes include leukopoiesis (bone marrow uptake), heart rate, and blood pressure. The indirect effects of PTSD treatment on changes in inflammation and autonomic function through SNA will also be examined. Conclusions: This study seeks to characterise candidate neuroimmune mechanisms of the PTSD-CVD link to identify treatment targets and develop personalised interventions to reduce CVD events in PTSD populations. Trial registration: ClinicalTrials.gov identifier: NCT06429293..

Imaging Recommendations for Diagnosis and Management of Primary Parathyroid Pathologies: A Comprehensive Review.

Parathyroid pathologies are suspected based on the biochemical alterations and clinical manifestations, and the predominant roles of imaging in primary hyperparathyroidism are localisation of tumour within parathyroid glands, surgical planning, and to look for any ectopic parathyroid tissue in the setting of recurrent disease. This article provides a comprehensive review of embryology and anatomical variations of parathyroid glands and their clinical relevance, surgical anatomy of parathyroid glands, differentiation between multiglandular parathyroid disease, solitary adenoma, atypical parathyroid tumour, and parathyroid carcinoma. The roles, advantages and limitations of ultrasound, four-dimensional computed tomography (4DCT), radiolabelled technetium-99 (99mTc) sestamibi or dual tracer 99mTc pertechnetate and 99mTc-sestamibi with or without single photon emission computed tomography (SPECT) or SPECT/CT, dynamic enhanced magnetic resonance imaging (4DMRI), and fluoro-choline positron emission tomography (18F-FCH PET) or [11C] Methionine (11C -MET) PET in the management of parathyroid lesions have been extensively discussed in this article. The role of fluorodeoxyglucose PET (FDG-PET) has also been elucidated in this article. Management guidelines for parathyroid carcinoma proposed by the American Society of Clinical Oncology (ASCO) have also been described. An algorithm for management of parathyroid lesions has been provided at the end to serve as a quick reference guide for radiologists, clinicians and surgeons.

Multimodal Imaging Approach for Tumor Treatment Response Evaluation in the Era of Immunotherapy.

Immunotherapy is likely the most remarkable advancement in lung cancer treatment during the past decade. Although immunotherapy provides substantial benefits, their therapeutic responses differ from those of conventional chemotherapy and targeted therapy, and some patients present unique immunotherapy response patterns that cannot be judged under the current measurement standards. Therefore, the response monitoring of immunotherapy can be challenging, such as the differentiation between real response and pseudo-response. This review outlines the various tumor response patterns to immunotherapy and discusses methods for quantifying computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) in the field of lung cancer. Emerging technologies in magnetic resonance imaging (MRI) and non-FDG PET tracers are also explored. With immunotherapy responses, the role for imaging is essential in both anatomical radiological responses (CT/MRI) and molecular changes (PET imaging). Multiple aspects must be considered when assessing treatment responses using CT and PET. Finally, we introduce multimodal approaches that integrate imaging and nonimaging data, and we discuss future directions for the assessment and prediction of lung cancer responses to immunotherapy.

Alzheimer's disease stage recognition from MRI and PET imaging data using Pareto-optimal quantum dynamic optimization

The threat posed by Alzheimer's disease (AD) to human health has grown significantly. However, the precise diagnosis and classification of AD stages remain a challenge. Neuroimaging methods such as structural magnetic resonance imaging (sMRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to diagnose and categorize AD. However, feature selection approaches that are frequently used to extract additional data from multimodal imaging are prone to errors. This paper suggests using a static pulse-coupled neural network and a Laplacian pyramid to combine sMRI and FDG-PET data. After that, the fused images are used to train the Mobile Vision Transformer (MViT), optimized with Pareto-Optimal Quantum Dynamic Optimization for Neural Architecture Search, while the fused images are augmented to avoid overfitting and then classify unfused MRI and FDG-PET images obtained from the AD Neuroimaging Initiative (ADNI) and Open Access Series of Imaging Studies (OASIS) datasets into various stages of AD. The architectural hyperparameters of MViT are optimized using Quantum Dynamic Optimization, which ensures a Pareto-optimal solution. The Peak Signal-to-Noise Ratio (PSNR), the Mean Squared Error (MSE), and the Structured Similarity Indexing Method (SSIM) are used to measure the quality of the fused image. We found that the fused image was consistent in all metrics, having 0.64 SIMM, 35.60 PSNR, and 0.21 MSE for the FDG-PET image. In the classification of AD vs. cognitive normal (CN), AD vs. mild cognitive impairment (MCI), and CN vs. MCI, the precision of the proposed method is 94.73%, 92.98% and 89.36%, respectively. The sensitivity is 90. 70%, 90. 70%, and 90. 91% while the specificity is 100%, 100%, and 85. 71%, respectively, in the ADNI MRI test data.

Stereo electroencephalography-guided radiofrequency ablation in focal epilepsia partialis continua: illustrative case.

Epilepsia partialis continua (EPC) is a variant of focal motor status epilepticus that can occur as a single or repetitive episode with progressive or nonprogressive characteristics. The authors describe the feasibility of identifying focal EPC in a 33-year-old woman using video electroencephalography (VEEG), electroencephalography source localization, [18F]fluorodeoxyglucose positron emission tomography, magnetic resonance imaging, and psychiatric and neuropsychological assessments and of treating it with stereo electroencephalography-guided radiofrequency (SEEG-RF) ablation. EPC comprised recurrent myoclonus of the right thigh and iliopsoas with a progressive pain syndrome after left anterior-temporo-mesial resection. Switching between VEEG under regular and epidural block helped to define myoclonus as the presenting ictal symptom with a suspected seizure onset zone in the left parietal paramedian lobule. After the epileptic network was identified, SEEG-RF ablation abolished all seizures. No correlation was found between pain and VEEG/SEEG abnormalities. Rehabilitation began 3 days after the SEEG-RF ablation. By 1 year of follow-up, the patient had no EPC and could walk with assistance in rehabilitation; however, due to the abrupt abolishment of EPC and underlying psychological factors, the patient perceived her pain as overriding, which prevented her from walking. The application of SEEG-RF ablation is an efficient therapeutic option for focal EPC with special concerns regarding concurrent nonepileptic pain. https://thejns.org/doi/10.3171/CASE23611.

Contemporary Role of Positron Emission Tomography (PET) in Endocarditis: A Narrative Review.

Endocarditis, a serious infectious disease, remains a diagnostic challenge in contemporary clinical practice. The advent of advanced imaging modalities has contributed significantly to the improved understanding and management of this complex disease. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) imaging has shown remarkable potential in improving the diagnostic accuracy of endocarditis. In the update of the Modified Duke Criteria, in 2023, The International Society for Cardiovascular Infectious Diseases (ISCVID) Working Group recognized specific 18F-FDG PET/CT findings as a major diagnostic criterion, particularly in patient with prosthetic valve endocarditis. The ability of PET to visualize metabolic activity allows for the identification of infective foci and could differentiate between infective and non-infective processes. This review examines the clinical utility of PET in differentiating infective endocarditis from other cardiovascular pathologies, highlighting its sensitivity and specificity in detecting native and prosthetic valve infections, including patients with transcatheter aortic valve implantation (TAVI), cardiac implantable devices (CIEDs), and left ventricular assistance devices (LVAD). Also, practical aspects and indications are illustrated to optimize the quality of imaging and reduce potential false positive results. In conclusion, the current use of PET in endocarditis has become a valuable diagnostic tool; as technological advances continue, PET will play an increasingly important role in the multidisciplinary approach to the management of endocarditis.

Mitigating the impact of image processing variations on tumour [18F]-FDG-PET radiomic feature robustness

Radiomics analysis of [18F]-fluorodeoxyglucose ([18F]-FDG) PET images could be leveraged for personalised cancer medicine. However, the inherent sensitivity of radiomic features to intensity discretisation and voxel interpolation complicates its clinical translation. In this work, we evaluated the robustness of tumour [18F]-FDG-PET radiomic features to 174 different variations in intensity resolution or voxel size, and determined whether implementing parameter range conditions or dependency corrections could improve their robustness. Using 485 patient images spanning three cancer types: non-small cell lung cancer (NSCLC), melanoma, and lymphoma, we observed features were more sensitive to intensity discretisation than voxel interpolation, especially texture features. In most of our investigations, the majority of non-robust features could be made robust by applying parameter range conditions. Correctable features, which were generally fewer than conditionally robust, showed systematic dependence on bin configuration or voxel size that could be minimised by applying corrections based on simple mathematical equations. Melanoma images exhibited limited robustness and correctability relative to NSCLC and lymphoma. Our study provides an in-depth characterisation of the sensitivity of [18F]-FDG-PET features to image processing variations and reinforces the need for careful selection of imaging biomarkers prior to any clinical application.

Extensive Multiorgan and Neurological Involvement on F-18 FDG PET-CT in a Case of Rosai-Dorfman Disease

AbstractRosai-Dorfman disease (RDD) is a rare benign proliferative disorder. Lymph nodes are the usual and common sites of involvement. Involvement of the extranodal site is also documented in the literature. 18F-fluorodeoxyglucose positron emission tomography computed tomography (F18-FDG PET CT) is a valuable whole-body imaging modality in staging and treatment response of various lymphoproliferative and solid organ malignancy. Similarly, PET CT survey can detect the involved sites of various body systems, infective or inflammatory diseases, and provide guidance for biopsy and to reach to diagnosis. Here, we present a case of RDD, who presented with neurological manifestations and on F18-FDG PET CT, diagnosed with multiorgan involvement.

Segmentation-Free Outcome Prediction from Head and Neck Cancer PET/CT Images: Deep Learning-Based Feature Extraction from Multi-Angle Maximum Intensity Projections (MA-MIPs).

We introduce an innovative, simple, effective segmentation-free approach for survival analysis of head and neck cancer (HNC) patients from PET/CT images. By harnessing deep learning-based feature extraction techniques and multi-angle maximum intensity projections (MA-MIPs) applied to Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) images, our proposed method eliminates the need for manual segmentations of regions-of-interest (ROIs) such as primary tumors and involved lymph nodes. Instead, a state-of-the-art object detection model is trained utilizing the CT images to perform automatic cropping of the head and neck anatomical area, instead of only the lesions or involved lymph nodes on the PET volumes. A pre-trained deep convolutional neural network backbone is then utilized to extract deep features from MA-MIPs obtained from 72 multi-angel axial rotations of the cropped PET volumes. These deep features extracted from multiple projection views of the PET volumes are then aggregated and fused, and employed to perform recurrence-free survival analysis on a cohort of 489 HNC patients. The proposed approach outperforms the best performing method on the target dataset for the task of recurrence-free survival analysis. By circumventing the manual delineation of the malignancies on the FDG PET-CT images, our approach eliminates the dependency on subjective interpretations and highly enhances the reproducibility of the proposed survival analysis method. The code for this work is publicly released.

Biopsy of the facial nerve in slow-onset facial palsy

IntroductionPrimary squamous cell carcinoma of the parotid gland typically presents as a palpable, often painless mass. Peripheral facial palsy as the only sign of malignant neoplasia is rare. In these cases, the diagnosis is regularly confirmed by radiological imaging followed by surgical exploration and biopsy. However, if there is no detection of malignant lesions and no evidence of a tumor, the reluctance to take a biopsy of an unremarkable nerve can lead to misdiagnoses.Case reportA 40-year-old female patient without medical history presented to our clinic with a complete right-sided peripheral facial palsy that had slowly progressed for 2.5 years. All other otorhinolaryngological examination findings were within normal limits. Magnetic resonance imaging examination of the head and neck and 18-fluorodeoxyglucose positron emission tomography showed unremarkable results. We proceeded with surgical exploration, which revealed no evidence of a tumor and an externally completely unremarkable facial nerve. A biopsy from the main trunk area of the nerve revealed an infiltration by a squamous cell carcinoma. Total parotidectomy with resection and reconstruction of the facial nerve and neck dissection was performed. Considering the absence of a primary tumor and other tumor formations the diagnosis of a completely regressive primary squamous cell carcinoma of the parotid gland was confirmed.ConclusionIn conclusion, in the case of slow-onset peripheral facial palsy that persists without signs of recovery, a gadolinium-enhanced MRI should be performed. If imaging is unremarkable and there is no primary tumor detection along the course of the facial nerve, a surgical exploration with biopsy of the facial nerve is necessary.

Role of Textural Analysis Parameters Derived from FDG PET/CT in Diagnosing Cardiac Sarcoidosis

Abstract Introduction Texture and radiomic analysis characterize the lesion's phenotype and evaluate its microenvironment in quantitative terms. The aim of this study was to investigate the role of textural features of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography–computed tomography (PET/CT) images in differentiating patients with cardiac sarcoidosis (CS) from patients with physiologic myocardial uptake. Methods This is a retrospective, single-center study of 67 patients, 17 diagnosed CS patients, and 50 non-CS patients. These patients underwent FDG PET/CT for the diagnosis of CS. The non-CS group underwent 18F-FDG PET/CT for other oncological indications. The PET/CT images were then processed in a commercially available textural analysis software. Region of interest was drawn over primary tumor with a 40% threshold and was processed further to derive 92 textural and radiomic parameters. These parameters were then compared between the CS group and the non-CS group. Receiver operating characteristics (ROC) curves were used to identify cutoff values for textural features with a p-value < 0.05 for statistical significance. These parameters were then passed through a principle component analysis algorithm. Five different machine learning classifiers were then tested on the derived parameters. Results A retrospective study of 67 patients, 17 diagnosed CS patients, and 50 non-CS patients, was done. Twelve textural analysis parameters were significant in differentiating between the CS group and the non-CS group. Cutoff values were calculated for these parameters according to the ROC curves. The parameters were Discretized_HISTO_Entropy, GLCM_Homogeneity, GLCM_Energy, GLRLM_LRE, GLRLM_LGRE, GLRLM_SRLGE, GLRLM_LRLGE, NGLDM_Coarseness, GLZLM_LZE, GLZLM_LGZE, GLZLM_SZLGE, and GLZLM_LZLGE. The gradient boosting classifier gave best results on these parameters with 85.71% accuracy and an F1 score of 0.86 (max 1.0) on both classes, indicating the classifier is performing well on both classes. Conclusion Textural analysis parameters could successfully differentiate between the CS and non-CS groups noninvasively. Larger multicenter studies are needed for better clinical prognostication of these parameters.

Comprehensive considerations for dermatologists: the application of FDG-PET in evaluating cutaneous lesions in pediatric Langerhans cell histiocytosis.

Langerhans cell histiocytosis (LCH) is a complex disorder characterized by the clonal proliferation of Langerhans cells, primarily affecting children and adolescents. This condition exhibits a wide spectrum of clinical presentations, necessitating a multidisciplinary approach for diagnosis, treatment, and follow-up. Cutaneous manifestations of LCH are significant, mimicking common dermatoses and posing diagnostic challenges. [18F]Fluorodeoxyglucose-Positron Emission Tomography (FDG-PET) has emerged as an important tool in the evaluation of pediatric LCH, offering insights into disease activity, extent, and therapeutic response. Moreover, FDG-PET provides a non-invasive means to distinguish between active LCH skin lesions and other dermatological conditions with similar clinical appearances, enhancing diagnostic accuracy and aiding in disease monitoring. This educational review summarizes the utility of nuclear imaging techniques, with a focus on PET scans, in the diagnosis and management of cutaneous pediatric LCH. A comprehensive literature search identified seven relevant articles, including retrospective studies and case reports. These studies highlight the efficacy of FDG-PET in localizing active LCH skin lesions, monitoring disease activity, and guiding treatment decisions. FDG-PET represents a valuable imaging modality for dermatologists, oncologists, and pediatricians managing pediatric LCH patients with cutaneous involvement. This non-invasive technique contributes to improved diagnostic accuracy and facilitates early intervention, ultimately enhancing patient care and outcomes.

Advancing Cancer Theranostics Through Integrin αVβ3-Targeted Peptidomimetic IAC: From Bench to Bedside.

Introduction: The expression of alpha-five beta-three (αVβ3) integrins is upregulated in various malignancies undergoing angiogenesis. The development of integrin antagonists as diagnostic probes makes the αVβ3 integrin a suitable candidate for targeting tumor angiogenesis. The goal of this study was to optimize the radiolabeling and evaluate the potential of conjugated integrin antagonist carbamate (IAC), a peptidomimetic, as a theranostic radiopharmaceutical for targeting tumor angiogenesis. Methodology: Radiolabeling of DOTAGA [2,2',2" -{10-(2,6-dioxotetrahydro-2H-pyran-3-yl)-1,4,7,10-tetraazacyclododecane-1,4,7-triyl} triacetic-acid]-IAC with [68Ga]Ga, [177Lu]Lu, and [225Ac]Ac was optimized. The binding affinity (Kd) of DOTAGA-IAC for the αVβ3 receptor and cancer cell lines was quantified. The biodistribution studies were conducted in healthy Wistar rats. Dosimetry analysis was performed on [177Lu]Lu-DOTAGA-IAC distribution data. A pilot study of [68Ga]Ga-DOTAGA-IAC and [18F]FDG Positron Emission Tomography (PET/CT) imaging was performed in five patients with histopathologically confirmed breast cancer. PET/CT findings were compared between [68Ga]Ga-DOTAGA-IAC and [18F]FDG in these patients. Results: Radiopharmaceuticals were prepared with high radiochemical purity (>99.9%). Kd and Bmax measurements were 15.02 nM and 417 fmol for αVβ3 receptor protein: 115.7 nM and 295.3 fmol for C6 glioma cells. Biodistribution studies in rats suggested the excretion via kidneys and partially through the hepatobiliary route. The effective dose of [177Lu]Lu-DOTAGA-IAC was found to be 0.17 mSv/MBq. The dynamic study in patients revealed the optimal imaging time to be 30-35 mins postadministration. Out of the cohort, [68Ga]Ga-DOTAGA-IAC detected the primary lesions in all five patients with a mean standard uptake value (SUVmax) of 3.94 ± 0.58 compared with [18F]FDG (SUVmax 13.8 ± 6.53). Conclusion: The study demonstrates that DOTAGA-IAC exhibits strong binding to αVβ3 integrin, positioning it as a promising PET agent for assessing primary and metastatic cancers. The outcomes from the pilot study suggest the potential of [68Ga]Ga-DOTAGA-IAC PET/CT in breast carcinoma diagnosis. While recognizing the theranostic potential of DOTAGA-IAC for αVβ3 integrin-expressing tumors, further clinical investigations are warranted to comprehensively assess therapeutic efficacy.

Ultrasensitive detection of uveal melanoma using [18F]AlF-NOTA-PRGD2 PET imaging

BackgroundUveal melanoma (UM) is the most common primary intraocular tumor in adults, and early detection is critical to improve the clinical outcome of this disease. In this study, the diagnostic effectiveness of [18F]AlF-NOTA-PRGD2 (an investigational medicinal product) positron emission tomography (PET) imaging in UM xenografts and UM patients were evaluated. The cell uptake, cell binding ability and in vitro stability of [18F]AlF-NOTA-PRGD2 were evaluated in 92-1 UM cell line. MicroPET imaging and biodistribution study of [18F]AlF-NOTA-PRGD2 were conducted in 92-1 UM xenografts. Then, UM patients were further recruited for evaluating the diagnostic effectiveness of [18F]AlF-NOTA-PRGD2 PET imaging (approval no. NCT02441972 in clinicaltrials.gov). In addition, comparison of [18F]AlF-NOTA-PRGD2 and 18F-labelled fluorodeoxyglucose ([18F]FDG) PET imaging in UM xenografts and UM patients were conducted.ResultsThe in vitro data showed that [18F]AlF-NOTA-PRGD2 had a high cell uptake, cell binding ability and in vitro stability in 92-1 UM cell line. The in vivo data indicated that 92-1 UM tumors were clearly visualized with the [18F]AlF-NOTA-PRGD2 tracer in the subcutaneous and ocular primary UM xenografts model at 60 min post-injection. And the tumor uptake of the tracer was 2.55 ± 0.44%ID/g and 1.73 ± 0.15%ID/g at these two tissue locations respectively, at 7 days after animal model construction. The clinical data showed that tumors in UM patients were clearly visualized with the [18F]AlF-NOTA-PRGD2 tracer at 60 min post-injection. In addition, [18F]AlF-NOTA-PRGD2 tracer showed higher sensitivity and specificity for PET imaging in UM xenografts and UM patients compared to [18F]FDG tracer.Conclusion[18F]AlF-NOTA-PRGD2 PET imaging may be a more preferred approach in the diagnosis of primary UM compared to [18F]FDG PET imaging. Additionally, due to the high tumor-to-background ratio, [18F]AlF-NOTA-PRGD2 PET imaging seems also to be applicable for the diagnosis of UM patients with liver metastasis.Trial registration: ClinicalTrials.gov: NCT02441972, Registered 1 January 2012, https://clinicaltrials.gov/study/NCT02441972.

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.

Patterns of brain volume and metabolism predict clinical features in the progressive supranuclear palsy spectrum.

Progressive supranuclear palsy (PSP) is a neurodegenerative tauopathy that presents with highly heterogenous clinical syndromes. We perform cross-sectional data-driven discovery of independent patterns of brain atrophy and hypometabolism across the entire PSP spectrum. We then use these patterns to predict specific clinical features and to assess their relationship to phenotypic heterogeneity. We included 111 patients with PSP (60 with Richardson syndrome and 51 with cortical and subcortical variant subtypes). Ninety-one were used as the training set and 20 as a test set. The presence and severity of granular clinical variables such as postural instability, parkinsonism, apraxia and supranuclear gaze palsy were noted. Domains of akinesia, ocular motor impairment, postural instability and cognitive dysfunction as defined by the Movement Disorders Society criteria for PSP were also recorded. Non-negative matrix factorization was used on cross-sectional MRI and fluorodeoxyglucose-positron emission tomography (FDG-PET) scans. Independent models for each as well as a combined model for MRI and FDG-PET were developed and used to predict the granular clinical variables. Both MRI and FDG-PET were better at predicting presence of a symptom than severity, suggesting identification of disease state may be more robust than disease stage. FDG-PET predicted predominantly cortical abnormalities better than MRI such as ideomotor apraxia, apraxia of speech and frontal dysexecutive syndrome. MRI demonstrated prediction of cortical and more so sub-cortical abnormalities, such as parkinsonism. Distinct neuroanatomical foci were predictive in MRI- and FDG-PET-based models. For example, vertical gaze palsy was predicted by midbrain atrophy on MRI, but frontal eye field hypometabolism on FDG-PET. Findings also differed by scale or instrument used. For example, prediction of ocular motor abnormalities using the PSP Saccadic Impairment Scale was stronger than with the Movement Disorders Society Diagnostic criteria for PSP oculomotor impairment designation. Combination of MRI and FDG-PET demonstrated enhanced detection of parkinsonism and frontal syndrome presence and apraxia, cognitive impairment and bradykinesia severity. Both MRI and FDG-PET patterns were able to predict some measures in the test set; however, prediction of global cognition measured by Montreal Cognitive Assessment was the strongest. MRI predictions generalized more robustly to the test set. PSP leads to neurodegeneration in motor, cognitive and ocular motor networks at cortical and subcortical foci, leading to diverse yet overlapping clinical syndromes. To advance understanding of phenotypic heterogeneity in PSP, it is essential to consider data-driven approaches to clinical neuroimaging analyses.

Data-driven retrieval of population-level EEG features and their role in neurodegenerative diseases.

Electrophysiologic disturbances due to neurodegenerative disorders such as Alzheimer's disease and Lewy Body disease are detectable by scalp EEG and can serve as a functional measure of disease severity. Traditional quantitative methods of EEG analysis often require an a-priori selection of clinically meaningful EEG features and are susceptible to bias, limiting the clinical utility of routine EEGs in the diagnosis and management of neurodegenerative disorders. We present a data-driven tensor decomposition approach to extract the top 6 spectral and spatial features representing commonly known sources of EEG activity during eyes-closed wakefulness. As part of their neurologic evaluation at Mayo Clinic, 11 001 patients underwent 12 176 routine, standard 10-20 scalp EEG studies. From these raw EEGs, we developed an algorithm based on posterior alpha activity and eye movement to automatically select awake-eyes-closed epochs and estimated average spectral power density (SPD) between 1 and 45 Hz for each channel. We then created a three-dimensional (3D) tensor (record × channel × frequency) and applied a canonical polyadic decomposition to extract the top six factors. We further identified an independent cohort of patients meeting consensus criteria for mild cognitive impairment (30) or dementia (39) due to Alzheimer's disease and dementia with Lewy Bodies (31) and similarly aged cognitively normal controls (36). We evaluated the ability of the six factors in differentiating these subgroups using a Naïve Bayes classification approach and assessed for linear associations between factor loadings and Kokmen short test of mental status scores, fluorodeoxyglucose (FDG) PET uptake ratios and CSF Alzheimer's Disease biomarker measures. Factors represented biologically meaningful brain activities including posterior alpha rhythm, anterior delta/theta rhythms and centroparietal beta, which correlated with patient age and EEG dysrhythmia grade. These factors were also able to distinguish patients from controls with a moderate to high degree of accuracy (Area Under the Curve (AUC) 0.59-0.91) and Alzheimer's disease dementia from dementia with Lewy Bodies (AUC 0.61). Furthermore, relevant EEG features correlated with cognitive test performance, PET metabolism and CSF AB42 measures in the Alzheimer's subgroup. This study demonstrates that data-driven approaches can extract biologically meaningful features from population-level clinical EEGs without artefact rejection or a-priori selection of channels or frequency bands. With continued development, such data-driven methods may improve the clinical utility of EEG in memory care by assisting in early identification of mild cognitive impairment and differentiating between different neurodegenerative causes of cognitive impairment.

Relationships between plasma biomarkers, tau PET, FDG PET, and volumetric MRI in mild to moderate Alzheimer's disease patients.

The "A/T/N" (amyloid/tau/neurodegeneration) framework provides a biological basis for Alzheimer's disease (AD) diagnosis and can encompass additional changes such as inflammation ("I"). A spectrum of T/N/I imaging and plasma biomarkers was acquired in a phase 2 clinical trial of rasagiline in mild to moderate AD patients. We evaluated these to understand biomarker distributions and relationships within this population. Plasma biomarkers of pTau-181, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), other inflammation-related proteins, imaging measures including fluorodeoxyglucose (FDG) positron emission tomography (PET), flortaucipir PET, and volumetric magnetic resonance imaging (MRI), and cognitive endpoints were analyzed to assess characteristics and relationships for the overall population (N = 47 at baseline and N = 21 for longitudinal cognitive comparisons) and within age-decade subgroups (57-69, 70-79, 80-90 years). Data demonstrate wide clinical and biomarker heterogeneity in this population influenced by age and sex. Plasma pTau-181 and GFAP correlate with tau PET, most strongly in left inferior temporal cortex (p = 0.0002, p = 0.0006, respectively). In regions beyond temporal cortex, tau PET uptake decreased with age for the same pTau-181 or GFAP concentrations. FDG PET and brain volumes correlate with tau PET in numerous regions (such as inferior temporal: p = 0.0007, p = 0.00001, respectively). NfL, GFAP, and all imaging modalities correlate with baseline MMSE; subsequent MMSE decline is predicted by baseline parahippocampal and lateral temporal tau PET (p = 0.0007) and volume (p = 0.0006). Lateral temporal FDG PET (p = 0.006) and volume (p = 0.0001) are most strongly associated with subsequent ADAS-cog decline. NfL correlates with FDG PET and baseline MMSE but not tau PET. Inflammation biomarkers are intercorrelated but correlated with other biomarkers in only the youngest group. Associations between plasma biomarkers, imaging biomarkers, and cognitive status observed in this study provide insight into relationships among biological processes in mild to moderate AD. Findings show the potential to characterize AD patients regarding likely tau pathology, neurodegeneration, prospective clinical decline, and the importance of covariates such as age. Plasma pTau-181 and GFAP correlated with regional and global tau PET in mild to moderate AD.NfL correlated with FDG PET and cognitive endpoints but not plasma pTau-181 or tau PET.Volume and FDG PET showed strong relationships to tau PET, one another, and cognitive status.Temporal volumes most strongly predicted decline in both MMSE and ADAS-cog.Volume and plasma biomarkers can enrich for elevated tau PET with age a significant covariate.

Non-invasive mapping of brown adipose tissue activity with magnetic resonance imaging

Thermogenic brown adipose tissue (BAT) has a positive impact on whole-body metabolism. However, in vivo mapping of BAT activity typically relies on techniques involving ionizing radiation, such as [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) and computed tomography (CT). Here we report a noninvasive metabolic magnetic resonance imaging (MRI) approach based on creatine chemical exchange saturation transfer (Cr-CEST) contrast to assess in vivo BAT activity in rodents and humans. In male rats, a single dose of the β3-adrenoceptor agonist (CL 316,243) or norepinephrine, as well as cold exposure, triggered a robust elevation of the Cr-CEST MRI signal, which was consistent with the [18F]FDG PET and CT data and 1H nuclear magnetic resonance measurements of creatine concentration in BAT. We further show that Cr-CEST MRI detects cold-stimulated BAT activation in humans (both males and females) using a 3T clinical scanner, with data-matching results from [18F]FDG PET and CT measurements. This study establishes Cr-CEST MRI as a promising noninvasive and radiation-free approach for in vivo mapping of BAT activity.