Longitudinal flortaucipir, metabolism and volume differ between phonetic and prosodic speech apraxia.

Progressive apraxia of speech (PAOS) is a neurodegenerative motor-speech disorder that most commonly arises from a four-repeat tauopathy. Recent studies have established that progressive apraxia of speech is not a homogenous disease but rather there are distinct subtypes: the phonetic subtype is characterized by distorted sound substitutions, the prosodic subtype by slow and segmented speech and the mixed subtype by a combination of both but lack of predominance of either. There is some evidence that cross-sectional patterns of neurodegeneration differ across subtypes, although it is unknown whether longitudinal patterns of neurodegeneration differ. We examined longitudinal patterns of atrophy on MRI, hypometabolism on 18F-fluorodeoxyglucose-PET and tau uptake on flortaucipir-PET in a large cohort of subjects with PAOS that had been followed for many years. Ninety-one subjects with PAOS (51 phonetic, 40 prosodic) were recruited by the Neurodegenerative Research Group. Of these, 54 (27 phonetic, 27 prosodic) returned for annual follow-up, with up to seven longitudinal visits (total visits analysed = 217). Volumes, metabolism and flortaucipir uptake were measured for subcortical and cortical regions, for all scans. Bayesian hierarchical models were used to model longitudinal change across imaging modalities with PAOS subtypes being compared at baseline, 4 years from baseline, and in terms of rates of change. The phonetic group showed smaller volumes and worse metabolism in Broca's area and the striatum at baseline and after 4 years, and faster rates of change in these regions, compared with the prosodic group. There was also evidence of faster spread of hypometabolism and flortaucipir uptake into the temporal and parietal lobes in the phonetic group. In contrast, the prosodic group showed smaller cerebellar dentate, midbrain, substantia nigra and thalamus volumes at baseline and after 4 years, as well as faster rates of atrophy, than the phonetic group. Greater hypometabolism and flortaucipir uptake were also observed in the cerebellar dentate and substantia nigra in the prosodic group. Mixed findings were observed in the supplementary motor area and precentral cortex, with no clear differences observed across phonetic and prosodic groups. These findings support different patterns of disease spread in PAOS subtypes, with corticostriatal patterns in the phonetic subtype and brainstem and thalamic patterns in the prosodic subtype, providing insight into the pathophysiology and heterogeneity of PAOS.

Uncovering the distinct macro-scale anatomy of dysexecutive and behavioural degenerative diseases.

There is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behaviour and personality. This is due to an incomplete understanding of the macro-scale anatomy underlying these symptomatologies, a partial overlap in clinical features and the fact that both phenotypes can emerge from the same pathology and vice versa. We collected data from a patient cohort of which 52 had dysexecutive Alzheimer's disease, 30 had behavioural variant frontotemporal dementia (bvFTD), seven met clinical criteria for bvFTD but had Alzheimer's disease pathology (behavioural Alzheimer's disease) and 28 had amnestic Alzheimer's disease. We first assessed group-wise differences in clinical and cognitive features and patterns of fluorodeoxyglucose (FDG) PET hypometabolism. We then performed a spectral decomposition of covariance between FDG-PET images to yield latent patterns of relative hypometabolism unbiased by diagnostic classification, which are referred to as 'eigenbrains'. These eigenbrains were subsequently linked to clinical and cognitive data and meta-analytic topics from a large external database of neuroimaging studies reflecting a wide range of mental functions. Finally, we performed a data-driven exploratory linear discriminant analysis to perform eigenbrain-based multiclass diagnostic predictions. Dysexecutive Alzheimer's disease and bvFTD patients were the youngest at symptom onset, followed by behavioural Alzheimer's disease, then amnestic Alzheimer's disease. Dysexecutive Alzheimer's disease patients had worse cognitive performance on nearly all cognitive domains compared with other groups, except verbal fluency which was equally impaired in dysexecutive Alzheimer's disease and bvFTD. Hypometabolism was observed in heteromodal cortices in dysexecutive Alzheimer's disease, temporo-parietal areas in amnestic Alzheimer's disease and frontotemporal areas in bvFTD and behavioural Alzheimer's disease. The unbiased spectral decomposition analysis revealed that relative hypometabolism in heteromodal cortices was associated with worse dysexecutive symptomatology and a lower likelihood of presenting with behaviour/personality problems, whereas relative hypometabolism in frontotemporal areas was associated with a higher likelihood of presenting with behaviour/personality problems but did not correlate with most cognitive measures. The linear discriminant analysis yielded an accuracy of 82.1% in predicting diagnostic category and did not misclassify any dysexecutive Alzheimer's disease patient for behavioural Alzheimer's disease and vice versa. Our results strongly suggest a double dissociation in that distinct macro-scale underpinnings underlie predominant dysexecutive versus personality/behavioural symptomatology in dementia syndromes. This has important implications for the implementation of criteria to diagnose and distinguish these diseases and supports the use of data-driven techniques to inform the classification of neurodegenerative diseases.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning.

Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer's disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging's use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

Imaging of the brain-heart axis: prognostic value in a European setting.

BACKGROUND AND AIMS: Increasing data suggest that stress-related neural activity (SNA) is associated with subsequent major adverse cardiovascular events (MACE) and may represent a therapeutic target. Current evidence is exclusively based on populations from the U.S. and Asia where limited information about cardiovascular disease risk was available. This study sought to investigate whether SNA imaging has clinical value in a well-characterized cohort of cardiovascular patients in Europe. METHODS: In this single-centre study, a total of 963 patients (mean age 58.4 ± 16.1 years, 40.7% female) with known cardiovascular status, ranging from 'at-risk' to manifest disease, and without active cancer underwent 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography between 1 January 2005 and 31 August 2019. Stress-related neural activity was assessed with validated methods and relations between SNA and MACE (non-fatal stroke, non-fatal myocardial infarction, coronary revascularization, and cardiovascular death) or all-cause mortality by time-to-event analysis. RESULTS: Over a maximum follow-up of 17 years, 118 individuals (12.3%) experienced MACE, and 270 (28.0%) died. In univariate analyses, SNA significantly correlated with an increased risk of MACE (sub-distribution hazard ratio 1.52, 95% CI 1.05-2.19; P = .026) or death (hazard ratio 2.49, 95% CI 1.96-3.17; P < .001). In multivariable analyses, the association between SNA imaging and MACE was lost when details of the cardiovascular status were added to the models. Conversely, the relationship between SNA imaging and all-cause mortality persisted after multivariable adjustments. CONCLUSIONS: In a European patient cohort where cardiovascular status is known, SNA imaging is a robust and independent predictor of all-cause mortality, but its prognostic value for MACE is less evident. Further studies should define specific patient populations that might profit from SNA imaging.

Astrocytic Ca2+ activation by chemogenetics mitigates the effect of kainic acid-induced excitotoxicity on the hippocampus.

Astrocytes play a multifaceted role regulating brain glucose metabolism, ion homeostasis, neurotransmitters clearance, and water dynamics being essential in supporting synaptic function. Under different pathological conditions such as brain stroke, epilepsy, and neurodegenerative disorders, excitotoxicity plays a crucial role, however, the contribution of astrocytic activity in protecting neurons from excitotoxicity-induced damage is yet to be fully understood. In this work, we evaluated the effect of astrocytic activation by Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) on brain glucose metabolism in wild-type (WT) mice, and we investigated the effects of sustained astrocyte activation following an insult induced by intrahippocampal (iHPC) kainic acid (KA) injection using 2-deoxy-2-[18F]-fluoro-D-glucose (18F-FDG) positron emission tomography (PET) imaging, along with behavioral test, nuclear magnetic resonance (NMR) spectroscopy and histochemistry. Astrocytic Ca2+ activation increased the 18F-FDG uptake, but this effect was not found when the study was performed in knock out mice for type-2 inositol 1,4,5-trisphosphate receptor (Ip3r2-/-) nor in floxed mice to abolish glucose transporter 1 (GLUT1) expression in hippocampal astrocytes (GLUT1ΔGFAP). Sustained astrocyte activation after KA injection reversed the brain glucose hypometabolism, restored hippocampal function, prevented neuronal death, and increased hippocampal GABA levels. The findings of our study indicate that astrocytic GLUT1 function is crucial for regulating brain glucose metabolism. Astrocytic Ca2+ activation has been shown to promote adaptive changes that significantly contribute to mitigating the effects of KA-induced damage. This evidence suggests a protective role of activated astrocytes against KA-induced excitotoxicity.

Evaluation of the 2023 Duke-International Society of Cardiovascular Infectious Diseases Criteria in a Multicenter Cohort of Patients With Suspected Infective Endocarditis.

BACKGROUND: Since publication of Duke criteria for infective endocarditis (IE) diagnosis, several modifications have been proposed. We aimed to evaluate the diagnostic performance of the Duke-ISCVID (International Society of Cardiovascular Infectious Diseases) 2023 criteria compared to prior versions from 2000 (Duke-Li 2000) and 2015 (Duke-ESC [European Society for Cardiology] 2015). METHODS: This study was conducted at 2 university hospitals between 2014 and 2022 among patients with suspected IE. A case was classified as IE (final IE diagnosis) by the Endocarditis Team. Sensitivity for each version of the Duke criteria was calculated among patients with confirmed IE based on pathological, surgical, and microbiological data. Specificity for each version of the Duke criteria was calculated among patients with suspected IE for whom IE diagnosis was ruled out. RESULTS: In total, 2132 episodes with suspected IE were included, of which 1101 (52%) had final IE diagnosis. Definite IE by pathologic criteria was found in 285 (13%), 285 (13%), and 345 (16%) patients using the Duke-Li 2000, Duke-ESC 2015, or the Duke-ISCVID 2023 criteria, respectively. IE was excluded by histopathology in 25 (1%) patients. The Duke-ISCVID 2023 clinical criteria showed a higher sensitivity (84%) compared to previous versions (70%). However, specificity of the new clinical criteria was lower (60%) compared to previous versions (74%). CONCLUSIONS: The Duke-ISCVID 2023 criteria led to an increase in sensitivity compared to previous versions. Further studies are needed to evaluate items that could increase sensitivity by reducing the number of IE patients misclassified as possible, but without having detrimental effect on specificity of Duke criteria.

A 3D convolutional neural network to classify subjects as Alzheimer's disease, frontotemporal dementia or healthy controls using brain 18F-FDG PET.

With the arrival of disease-modifying drugs, neurodegenerative diseases will require an accurate diagnosis for optimal treatment. Convolutional neural networks are powerful deep learning techniques that can provide great help to physicians in image analysis. The purpose of this study is to introduce and validate a 3D neural network for classification of Alzheimer's disease (AD), frontotemporal dementia (FTD) or cognitively normal (CN) subjects based on brain glucose metabolism. Retrospective [18F]-FDG-PET scans of 199 CE, 192 FTD and 200 CN subjects were collected from our local database, Alzheimer's disease and frontotemporal lobar degeneration neuroimaging initiatives. Training and test sets were created using randomization on a 90 %-10 % basis, and training of a 3D VGG16-like neural network was performed using data augmentation and cross-validation. Performance was compared to clinical interpretation by three specialists in the independent test set. Regions determining classification were identified in an occlusion experiment and Gradient-weighted Class Activation Mapping. Test set subjects were age- and sex-matched across categories. The model achieved an overall 89.8 % accuracy in predicting the class of test scans. Areas under the ROC curves were 93.3 % for AD, 95.3 % for FTD, and 99.9 % for CN. The physicians' consensus showed a 69.5 % accuracy, and there was substantial agreement between them (kappa = 0.61, 95 % CI: 0.49-0.73). To our knowledge, this is the first study to introduce a deep learning model able to discriminate AD and FTD based on [18F]-FDG PET scans, and to isolate CN subjects with excellent accuracy. These initial results are promising and hint at the potential for generalization to data from other centers.

Evaluation of the Therapeutical Effect of Matricaria Chamomilla Extract vs. Galantamine on Animal Model Memory and Behavior Using 18F-FDG PET/MRI.

The memory-enhancing activity of Matricaria chamomilla hydroalcoholic extract (MCE) is already being investigated by behavioral and biochemical assays in scopolamine-induced amnesia rat models, while the effects of scopolamine (Sco) on cerebral glucose metabolism are examined as well. Nevertheless, the study of the metabolic profile determined by an enriched MCE has not been performed before. The present experiments compared metabolic quantification in characteristic cerebral regions and behavioral characteristics for normal, only diseased, diseased, and MCE- vs. Galantamine (Gal)-treated Wistar rats. A memory deficit was induced by four weeks of daily intraperitoneal Sco injection. Starting on the eighth day, the treatment was intraperitoneally administered 30 min after Sco injection for a period of three weeks. The memory assessment comprised three maze tests. Glucose metabolism was quantified after the 18F-FDG PET examination. The right amygdala, piriform, and entorhinal cortex showed the highest differential radiopharmaceutical uptake of the 50 regions analyzed. Rats treated with MCE show metabolic similarity with normal rats, while the Gal-treated group shows features closer to the diseased group. Behavioral assessments evidenced a less anxious status and a better locomotor activity manifested by the MCE-treated group compared to the Gal-treated group. These findings prove evident metabolic ameliorative qualities of MCE over Gal classic treatment, suggesting that the extract could be a potent neuropharmacological agent against amnesia.

Advanced imaging for earlier diagnosis and morbidity prevention in multiple myeloma: A British Society of Haematology and UK Myeloma Society Good Practice Paper.

This Good Practice Paper provides recommendations for the use of advanced imaging for earlier diagnosis and morbidity prevention in multiple myeloma. It describes how advanced imaging contributes to optimal healthcare resource utilisation by in newly diagnosed and relapsed myeloma, and provides a perspective on future directions of myeloma imaging, including machine learning assisted reporting.

18F-FDG PET/CT for early prediction of pathological complete response in breast cancer neoadjuvant therapy: a retrospective analysis.

BACKGROUND: Neoadjuvant treatment has been developed as a systematic approach for patients with early breast cancer and has resulted in improved breast-conserving rate and survival. However, identifying treatment-sensitive patients at the early phase of therapy remains a problem, hampering disease management and raising the possibility of disease progression during treatment. METHODS: In this retrospective analysis, we collected 2-deoxy-2-[F-18] fluoro-d-glucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) images of primary tumor sites and axillary areas and reciprocal clinical pathological data from 121 patients who underwent neoadjuvant treatment and surgery in our center. The univariate and multivariate logistic regression analyses were performed to investigate features associated with pathological complete response (pCR). An 18F-FDG PET/CT-based prediction model was trained, and the performance was evaluated by receiver operating characteristic curves (ROC). RESULTS: The maximum standard uptake values (SUVmax) of 18F-FDG PET/CT were a powerful indicator of tumor status. The SUVmax values of axillary areas were closely related to metastatic lymph node counts (R = 0.62). Moreover, the early SUVmax reduction rates (between baseline and second cycle of neoadjuvant treatment) were statistically different between pCR and non-pCR patients. The early SUVmax reduction rates-based model showed great ability to predict pCR (AUC = 0.89), with all molecular subtypes (HR+HER2-, HR+HER2+, HR-HER2+, and HR-HER2-) considered. CONCLUSION: Our research proved that the SUVmax reduction rate of 18F-FDG PET/CT contributed to the early prediction of pCR, providing rationales for utilizing PET/CT in NAT in the future.

Topographic metabolism-function relationships in Alzheimer's disease: A simultaneous PET/MRI study.

Disruptions of neural metabolism and function occur in parallel during Alzheimer's disease (AD). While many studies have shown diverse metabolic-functional relationships in specific brain regions, much less is known about how large-scale network-level functional activity is associated with the topology of metabolism in AD. In this study, we took the advantages of simultaneous PET/MRI and multivariate analyses to investigate the associations between AD-related stereotypical spatial patterns (topographies) of glucose metabolism, measured by fluorodeoxyglucose PET, and functional connectivity, measured by resting-state functional MRI. A total of 101 participants, including 37 patients with AD, 25 patients with mild cognitive impairment (MCI), and 39 cognitively normal controls, underwent PET/MRI scans and cognitive assessments. Three pairs of distinct but optimally correlated metabolic and functional topographies were identified, encompassing large-scale networks including the default-mode, executive and control, salience, attention, and subcortical networks. Importantly, the metabolic-functional associations were not only limited to one-to-one-corresponding regions, but also occur in remote and non-overlapping regions. Furthermore, both glucose metabolism and functional connectivity, as well as their linkages, exhibited various degrees of disruptions in patients with MCI and AD, and were correlated with cognitive decline. In conclusion, our results support distributed and heterogeneous topographic associations between metabolism and function, which are jeopardized by AD. Findings of this study may deepen our understanding of the pathological mechanism of AD through the perspectives of both local energy efficiency and long-term interactions between synaptic disruption and functional disconnection contributing to the clinical symptomatology in AD.

Clinical implications of non-breast cancer related findings on FDG-PET/CT scan prior to neoadjuvant chemotherapy in patients with breast cancer.

PURPOSE: Breast cancer (BC) patients undergoing FDG-PET/CT scans for neoadjuvant chemotherapy (NAC) may have additional non-BC related findings. The aim of this study is to describe the clinical implications of these findings. METHODS: We included BC patients who underwent an FDG-PET/CT scan in our institute between 2011-2020 prior to NAC. We focused on patients with an additional non-BC related finding (i.e. BC metastases were excluded) for which diagnostic work-up was performed. Information about the diagnostic work-up and the clinical consequences was retrospectively gathered. A revision of all FDG-PET/CT scans was conducted by an independent physician to assess the suspicion level of the additional findings. RESULTS: Of the 1337 patients who underwent FDG-PET/CT, 202 patients (15%) had an non-BC related additional finding for which diagnostic work-up was conducted, resulting in 318 examinations during the first year. The non-BC related findings were mostly detected in the endocrine region (26%), gastro-intestinal region (16%), or the lungs (15%). Seventeen patients (17/202: 8%, 17/1337: 1.3%) had a second primary malignancy. Only 8 patients (8/202: 4%, 8/1337: 0.6%) had a finding that was considered more prognosis-determining than their BC disease. When revising all FDG-PET/CT scans, 57 (202/57: 28%) of the patients had an additional finding categorized as low suspicious, suggesting no indication for diagnostic work-up. CONCLUSION: FDG-PET/CT scans used for dissemination imaging in BC patients detect a high number of non-BC related additional findings, often clinically irrelevant and causing a large amount of unnecessary work-up. However, in 8% of the patients undergoing diagnostic work-up for an additional finding, a second primary malignancy was detected, warranting diagnostic attention in selected patients.

Therapeutic impact of 18F-FDG PET/CT for initial staging in patients with clinical stage I and IIA, HER2-positive, or triple-negative breast cancer.

PURPOSE: While 18F-FDG PET/CT (FDG-PET/CT) is consensual for clinical stage ≥ IIB breast cancers (BC), its benefit for stage I or IIA HER2+ or triple-negative breast cancer (TNBC) patients lacks sufficient evidence. We reported a single-institution, retrospective study evaluating FDG-PET/CT impact on patient management and staging for stage I or IIA HER2+ or Triple-Negative BC. METHODS: Patients who underwent FDG-PET/CT staging before any treatment between January 2015 and December 2020 at Oscar Lambret Center were included. EXCLUSIONS: patients with symptoms or conventional imaging suggestive of metastatic dissemination, or with prior malignancies. Initial stage was determined from mammography, breast ultrasound, breast MRI, and clinical examination. Staging and therapeutic impact based on FDG-PET/CT findings collected, including intra- (modification of dose/site/strategy in a type of management previously indicated) and inter-modality (modification of planned treatment strategy) changes. RESULTS: The cohort included 287 female patients with clinical stage I or IIA, HER2+ , or TNBC. Therapeutic impact observed for 18% of patients (n = 52), with 2% (n = 7) undergoing inter-modality change with omission of planned surgery. The impact on patient management was higher for stage IIA patients (20%, 47/237) than for stage I patients (10%, 5/50). Among stage IIA disease, changes in management were more important for T2N0 patients (22%, 44/205) than for T1N1 patients (9%, 3/32). While not statistically significant, trends suggest usefulness of FDG-PET/CT for T2N0 patients. CONCLUSION: Considering substantial therapeutic implications, our study suggests the usefulness of FDG-PET/CT for patients with stage IIA, HER2-positive, or Triple-Negative BC with tumor size > 2 cm (T2N0).

Improved Diagnostic Accuracy for Polymyalgia Rheumatica using FDG-PET/CT with Clinical Diagnosis or 2012 ACR/EULAR Classification Criteria.

PURPOSE: In routine care, clinicians may employ 2-[18F]fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) computed tomography (CT) to validate their initial clinical diagnosis of polymyalgia rheumatica (PMR). Nevertheless, the diagnostic utility of combining FDG-PET/CT findings with clinical presentation has not been explored. Therefore, this study aimed to investigate whether the diagnostic accuracy for PMR could be enhanced by combining FDG-PET/CT findings with the clinical baseline diagnosis or the 2012 ACR/EULAR clinical classification criteria for PMR. METHODS: An investigation and a validation cohort were included from two countries, encompassing 66/27 and 36/21 PMR/non-PMR patients, respectively. The cohorts comprised treatment-naïve patients suspected of PMR, who initially received a clinical baseline diagnosis and underwent FDG-PET/CT scans. The FDG-PET/CT Leuven-score was applied to classify patients as either PMR or non-PMR and combined with the clinical baseline diagnosis. Final diagnoses were established through clinical follow-up after twelve or six months in the investigation and validation cohorts, respectively. RESULTS: In the investigation cohort, a clinical baseline diagnosis yielded a sensitivity/specificity of 94%/82%, compared with 78%/70% using the ACR/EULAR criteria. Combining the clinical baseline diagnosis with a positive Leuven-score showed a sensitivity/specificity of 80%/93%, compared with 80%/82% for an ACR/EULAR-Leuven-score. In the validation cohort, the baseline diagnosis revealed a sensitivity/specificity of 100%/91%, compared with 92%/76% using the ACR/EULAR criteria. Combining FDG-PET/CT with the baseline diagnosis demonstrated a sensitivity/specificity of 83%/95% compared with 89%/81% for the ACR/EULAR-Leuven-score. CONCLUSION: Combining FDG-PET/CT findings with the clinical baseline diagnosis or ACR/EULAR clinical classification criteria can improve the diagnostic specificity for PMR.

Prognostic value of hypermetabolic bone sarcoidosis observed by 18F-fluorodeoxyglucose positron emission tomography.

OBJECTIVES: Sarcoidosis is a multisystemic granulomatosis diagnosed mainly in young adults.18F-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET-CT) is useful in sarcoidosis cases to search for a biopsiable site or assess disease activity.18F-FDG PET-CT can reveal bone hypermetabolism in sarcoidosis patients, even in the absence of osteoarticular symptoms. The aim of this study was to describe metabolic bone involvement in sarcoidosis patients and to evaluate its prognostic impact. METHODS: This was an observational, comparative, retrospective, monocentric study. Inclusion criteria were a confirmed diagnosis of sarcoidosis according to the World Association of Sarcoidosis and Other Granulomatous Diseases (WASOG) criteria and at least one 18F-FDG PET-CT scan during follow-up. Metabolic bone involvement of sarcoidosis was defined as focal bone hypermetabolism with no argument for a differential diagnosis of bone 18F-FDG uptake. Patients with and without bone involvement were compared. RESULTS: Among the 175 included patients, 32 (18%) had metabolic bone involvement of sarcoidosis. The metabolic bone involvement was mainly axial and mostly without bone abnormalities on CT. Metabolic bone involvement was associated with intrathoracic and extrathoracic lymph node involvement and with a higher number of organs involved. Patients with metabolic bone involvement more frequently received corticosteroids, methotrexate and tumor necrosis factor (TNF)-α inhibitors and a higher number of treatments. Relapse of sarcoidosis occurred sooner in patients with metabolic bone involvement. CONCLUSION: These results suggest that metabolic bone involvement is associated with more diffuse and more severe sarcoidosis.

Low incidence of late-onset giant cell arteritis during the first year in patients with polymyalgia rheumatica-a repeated imaging study.

OBJECTIVE: The objective was to investigate the incidence of late-onset giant cell arteritis (GCA) within the first year in patients diagnosed with polymyalgia rheumatica (PMR). METHODS: In this prospective study, treatment-naïve individuals with a new clinical diagnosis of PMR and without GCA symptoms underwent baseline assessments, including vascular ultrasonography and 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography computed tomography (FDG-PET/CT). To prevent biased inclusion, rapid referral clinics were established for all patients suspected of PMR. Additionally, the patients underwent GCA monitoring during clinical visits at weeks 8 and 10, which involved vascular ultrasonography and FDG-PET/CT scans. After one year, a follow-up visit was performed to confirm the PMR diagnosis and perform vascular ultrasonography. RESULTS: A final PMR diagnosis was assigned to 62 patients, excluding 2 patients with concurrent subclinical GCA and PMR at baseline, corresponding to a baseline prevalence of subclinical GCA of 3%. During the one-year follow-up, two PMR patients developed late-onset GCA corresponding to an incidence rate of 32 per 1000 person-years. One patient developed GCA 14 weeks after the PMR diagnosis, exhibiting cranial symptoms and positive vascular ultrasonography. The other patient presented with subclinical large vessel GCA at the one-year visit detected with vascular ultrasonography and confirmed by FDG-PET/CT. CONCLUSION: This study is the first to demonstrate a low incidence rate of late-onset GCA in PMR patients within the first year, employing repeated imaging to exclude GCA at baseline and diagnose GCA during follow-up. Additionally, it provides evidence of a low prevalence of subclinical GCA across the entire PMR population. TRIAL REGISTRATION: ClinicalTrials.Gov, NCT04519580.

Advances in the diagnosis of myocarditis in idiopathic inflammatory myopathies: an overview of diagnostic tests.

Cardiac involvement in idiopathic inflammatory myopathies (IIM) purports to worse clinical outcomes, and therefore early identification is important. Research has focused on blood biomarkers and basic investigations such as ECG and echocardiography, which have the advantage of wide availability and low cost but are limited in their sensitivity and specificity. Imaging the myocardium to directly look for inflammation and scarring has therefore been explored, with a number of new methods for doing this gaining wider research interest and clinical availability. Cardiovascular magnetic resonance (CMR) with contemporary multiparametric mapping techniques and late gadolinium enhancement imaging, is an extremely valuable and increasingly used non-invasive imaging modality for the diagnosis of myocarditis. The recently updated CMR-based Lake Louise Criteria for the diagnosis of myocarditis incorporate the newer T1 and T2 mapping techniques, which have greatly improved the diagnostic accuracy for IIM myocarditis.18F-FDG-PET/CT is a well-utilized imaging modality in the diagnosis of malignancies in IIM, and it also has a role for the diagnosis of myocarditis in multiple systemic inflammatory diseases. Endomyocardial biopsy, however, remains the gold standard technique for the diagnosis of myocarditis and is necessary for the diagnosis of specific cases of myocarditis. This article provides an overview of the important tests and imaging modalities that clinicians should consider when faced with an IIM patient with potential myocarditis.

18F-FDG PET/CT Radiomics-Based Multimodality Fusion Model for Preoperative Individualized Noninvasive Prediction of Peritoneal Metastasis in Advanced Gastric Cancer.

PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fusion (MMF) model using 18F-fluorodeoxyglucose (FDG) PET/CT radiomics and kernelled support tensor machine (KSTM), integrated with clinical factors and nuclear medicine experts' diagnoses to individually predict peritoneal metastasis (PM) in advanced gastric cancer (AGC). METHODS: A total of 167 patients receiving preoperative PET/CT and subsequent surgery were included between November 2006 and September 2020 and were divided into a training and testing cohort. The PM status was confirmed via laparoscopic exploration and postoperative pathology. The PET/CT signatures were constructed by classic radiomic, handcrafted-feature-based model and KSTM self-learning-based model. The clinical nomogram was constructed by independent risk factors for PM. Lastly, the PET/CT signatures, clinical nomogram, and experts' diagnoses were fused using evidential reasoning to establish the MMF model. RESULTS: The MMF model showed excellent performance in both cohorts (area under the curve [AUC] 94.16% and 90.84% in training and testing), and demonstrated better prediction accuracy than clinical nomogram or experts' diagnoses (net reclassification improvement p < 0.05). The MMF model also had satisfactory generalization ability, even in mucinous adenocarcinoma and signet ring cell carcinoma which have poor uptake of 18F-FDG (AUC 97.98% and 89.71% in training and testing). CONCLUSIONS: The 18F-FDG PET/CT radiomics-based MMF model may have significant clinical implications in predicting PM in AGC, revealing that it is necessary to combine the information from different modalities for comprehensive prediction of PM.

Sex-specific differences in myocardial glucose metabolic rate in non-diabetic, pre-diabetic and type 2 diabetic subjects.

BACKGROUND: Evidence has shown that women with type 2 diabetes (T2DM) have a higher excess risk for cardiovascular disease (CVD) than men with T2DM. Subjects with either T2DM or prediabetes exhibit myocardial insulin resistance, but it is still unsettled whether sex-related differences in myocardial insulin resistance occur in diabetic and prediabetic subjects. METHODS: We aimed to evaluate sex-related differences in myocardial glucose metabolic rate (MRGlu), assessed using dynamic PET with 18F-FDG combined with euglycemic-hyperinsulinemic clamp, in subjects with normal glucose tolerance (NGT; n = 20), prediabetes (n = 11), and T2DM (n = 26). RESULTS: Women with prediabetes or T2DM exhibited greater relative differences in myocardial MRGlu than men with prediabetes or T2DM when compared with their NGT counterparts. As compared with women with NGT, those with prediabetes exhibited an age-adjusted 35% lower myocardial MRGlu value (P = 0.04) and women with T2DM a 74% lower value (P = 0.006), respectively. Conversely, as compared with men with NGT, men with T2DM exhibited a 40% lower myocardial MRGlu value (P = 0.004), while no significant difference was observed between men with NGT and prediabetes. The statistical test for interaction between sex and glucose tolerance on myocardial MRGlu (P < 0.0001) was significant suggesting a sex-specific association. CONCLUSIONS: Our data suggest that deterioration of glucose homeostasis in women is associated with a greater impairment in myocardial glucose metabolism as compared with men. The sex-specific myocardial insulin resistance could be an important factor responsible for the greater effect of T2DM on the excess risk of cardiovascular disease in women than in men.

Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission.

PURPOSE: Metabolic network analysis of FDG-PET utilizes an index of inter-regional correlation of resting state glucose metabolism and has been proven to provide complementary information regarding the disease process in parkinsonian syndromes. The goals of this study were (i) to evaluate pattern similarities of glucose metabolism and network connectivity in dementia with Lewy bodies (DLB) subjects with subthreshold dopaminergic loss compared to advanced disease stages and to (ii) investigate metabolic network alterations of FDG-PET for discrimination of patients with early DLB from other neurodegenerative disorders (Alzheimer's disease, Parkinson's disease, multiple system atrophy) at individual patient level via principal component analysis (PCA). METHODS: FDG-PETs of subjects with probable or possible DLB (n = 22) without significant dopamine deficiency (z-score < 2 in putamen binding loss on DaT-SPECT compared to healthy controls (HC)) were scaled by global-mean, prior to volume-of-interest-based analyses of relative glucose metabolism. Single region metabolic changes and network connectivity changes were compared against HC (n = 23) and against DLB subjects with significant dopamine deficiency (n = 86). PCA was applied to test discrimination of patients with DLB from disease controls (n = 101) at individual patient level. RESULTS: Similar patterns of hypo- (parietal- and occipital cortex) and hypermetabolism (basal ganglia, limbic system, motor cortices) were observed in DLB patients with and without significant dopamine deficiency when compared to HC. Metabolic connectivity alterations correlated between DLB patients with and without significant dopamine deficiency (R2 = 0.597, p < 0.01). A PCA trained by DLB patients with dopamine deficiency and HC discriminated DLB patients without significant dopaminergic loss from other neurodegenerative parkinsonian disorders at individual patient level (area-under-the-curve (AUC): 0.912). CONCLUSION: Disease-specific patterns of altered glucose metabolism and altered metabolic networks are present in DLB subjects without significant dopaminergic loss. Metabolic network alterations in FDG-PET can act as a supporting biomarker in the subgroup of DLB patients without significant dopaminergic loss at symptoms onset.