EANM procedure guidelines for brain PET imaging using [18F]FDG, version 3

18F-FDG PET can effectively rule out conversion to dementia and the presence of CSF biomarker of neurodegeneration: a real-world data analysis

BACKGROUND

Precisely defining the delay in onset of dementia is a particular challenge for early diagnosis. Brain [18F] fluoro-2-deoxy-2-D-glucose (18F-FDG) Positron Emission Tomography (PET) is a particularly interesting tool for the early diagnosis of neurodegenerative diseases, through the measurement of the cerebral glucose metabolic rate. There is currently a lack of longitudinal studies under real-life conditions, with sufficient patients, to accurately evaluate the predictive values of brain 18F-FDG PET scans. Here, we aimed to estimate the value of brain 18F-FDG PET for predicting the risk of dementia conversion and the risk of occurrence of a neurodegenerative pathology.

METHODS

Longitudinal data for a cohort of patients with no diagnosis of dementia at the time of recruitment referred by a tertiary memory clinic for brain 18F-FDG PET were matched with (Prince M, Wimo A, Guerchet Maëlenn, Ali G-C, Wu Y-T et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. [Research Report] Alzheimer's Disease International. 2015. 2015.) data from the French National Health Data System (NHDS), (Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-62.) data from the National Alzheimer Bank (NAB), and (Davis M, O`Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer's Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia. CAR. 2018;15(8):777-88.) lumbar puncture (LP) biomarker data. The criteria for dementia conversion were the designation, within the three years after the brain 18F-FDG PET scan, of a long-term condition for dementia in the NHDS and a dementia stage of cognitive impairment in the NAB. The criterion for the identification of a neurodegenerative disease in the medical records was the determination of LP biomarker levels.

RESULTS

Among the 403 patients (69.9 ± 11.4 years old, 177 women) from the initial cohort with data matched with the NHDS data, 137 were matched with the NAB data, and 61 were matched with LP biomarker data. Within three years of the scan, a 18F-FDG PET had negative predictive values of 85% for dementia conversion (according to the NHDS and NAB datasets) and 95% for the presence of LP neurodegeneration biomarkers.

CONCLUSION

A normal brain 18F-FDG PET scan can help rule out the risk of dementia conversion and the presence of cerebrospinal fluid (CSF) biomarker of neurodegeneration early with high certainty, allowing modifications to patient management regimens in the short term.

TRIAL REGISTRATION

Clinical Trials database (NCT04804722). March 18, 2021. Retrospectively registered.

FDG-PET/MRI in the presurgical evaluation of pediatric epilepsy

In patients with drug-resistant epilepsy, difficulties in identifying the epileptogenic zone are well known to correlate with poorer clinical outcomes post-surgery. The integration of PET and MRI in the presurgical assessment of pediatric patients likely improves diagnostic precision by confirming or widening treatment targets. PET and MRI together offer superior insights compared to either modality alone. For instance, PET highlights abnormal glucose metabolism, while MRI precisely localizes structural anomalies, providing a comprehensive understanding of the epileptogenic zone. Furthermore, both methodologies, whether utilized through simultaneous PET/MRI scanning or the co-registration of separately acquired PET and MRI data, present unique advantages, having complementary roles in lesional and non-lesional cases. Simultaneous FDG-PET/MRI provides precise co-registration of functional (PET) and structural (MR) imaging in a convenient one-stop-shop approach, which minimizes sedation time and reduces radiation exposure in children. Commercially available fusion software that allows retrospective co-registration of separately acquired PET and MRI images is a commonly used alternative. This review provides an overview and illustrative cases that highlight the role of combining 18F-FDG-PET and MRI imaging and shares the authors' decade-long experience utilizing simultaneous PET/MRI in the presurgical evaluation of pediatric epilepsy.

Added value of FDG-PET for detection of progressive supranuclear palsy

BACKGROUND

Diagnostic criteria for progressive supranuclear palsy (PSP) include midbrain atrophy in MRI and hypometabolism in [18F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) as supportive features. Due to limited data regarding their relative and sequential value, there is no recommendation for an algorithm to combine both modalities to increase diagnostic accuracy. This study evaluated the added value of sequential imaging using state-of-the-art methods to analyse the images regarding PSP features.

METHODS

The retrospective study included 41 PSP patients, 21 with Richardson's syndrome (PSP-RS), 20 with variant PSP phenotypes (vPSP) and 46 sex- and age-matched healthy controls. A pretrained support vector machine (SVM) for the classification of atrophy profiles from automatic MRI volumetry was used to analyse T1w-MRI (output: MRI-SVM-PSP score). Covariance pattern analysis was applied to compute the expression of a predefined PSP-related pattern in FDG-PET (output: PET-PSPRP expression score).

RESULTS

The area under the receiver operating characteristic curve for the detection of PSP did not differ between MRI-SVM-PSP and PET-PSPRP expression score (p≥0.63): about 0.90, 0.95 and 0.85 for detection of all PSP, PSP-RS and vPSP. The MRI-SVM-PSP score achieved about 13% higher specificity and about 15% lower sensitivity than the PET-PSPRP expression score. Decision tree models selected the MRI-SVM-PSP score for the first branching and the PET-PSPRP expression score for a second split of the subgroup with normal MRI-SVM-PSP score, both in the whole sample and when restricted to PSP-RS or vPSP.

CONCLUSIONS

FDG-PET provides added value for PSP-suspected patients with normal/inconclusive T1w-MRI, regardless of PSP phenotype and the methods to analyse the images for PSP-typical features.

Validation and Evaluation of a Vendor-Provided Head Motion Correction Algorithm on the uMI Panorama PET/CT System

Brain PET imaging often faces challenges from head motion (HM), which can introduce artifacts and reduce image resolution, crucial in clinical settings for accurate treatment planning, diagnosis, and monitoring. United Imaging Healthcare has developed NeuroFocus, an HM correction (HMC) algorithm for the uMI Panorama PET/CT system, using a data-driven, statistics-based approach. The HMC algorithm automatically detects HM using a centroid-of-distribution technique, requiring no parameter adjustments. This study aimed to validate NeuroFocus and assess the prevalence of HM in clinical short-duration 18F-FDG scans. Methods: The study involved 317 patients undergoing brain PET scans, divided into 2 groups: 15 for HMC validation and 302 for evaluation. Validation involved patients undergoing 2 consecutive 3-min single-bed-position brain 18F-FDG scans-one with instructions to remain still and another with instructions to move substantially. The evaluation examined 302 clinical single-bed-position brain scans for patients with various neurologic diagnoses. Motion was categorized as small or large on the basis of a 5% SUV change in the frontal lobe after HMC. Percentage differences in SUVmean were reported across 11 brain regions. Results: The validation group displayed a large negative difference (-10.1%), with variation of 5.2% between no-HM and HM scans. After HMC, this difference decreased dramatically (-0.8%), with less variation (3.2%), indicating effective HMC application. In the evaluation group, 38 of 302 patients experienced large HM, showing a 10.9% ± 8.9% SUV increase after HMC, whereas most exhibited minimal uptake changes (0.1% ± 1.3%). The HMC algorithm not only enhanced the image resolution and contrast but also aided in disease identification and reduced the need for repeat scans, potentially optimizing clinical workflows. Conclusion: The study confirmed the effectiveness of NeuroFocus in managing HM in short clinical 18F-FDG studies on the uMI Panorama PET/CT system. It found that approximately 12% of scans required HMC, establishing HMC as a reliable tool for clinical brain 18F-FDG studies.

Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain

PURPOSE

The human brain is characterized by interacting large-scale functional networks fueled by glucose metabolism. Since former studies could not sufficiently clarify how these functional connections shape glucose metabolism, we aimed to provide a neurophysiologically-based approach.

METHODS

51 healthy volunteers underwent simultaneous PET/MRI to obtain BOLD functional connectivity and [18F]FDG glucose metabolism. These multimodal imaging proxies of fMRI and PET were combined in a whole-brain extension of metabolic connectivity mapping. Specifically, functional connectivity of all brain regions were used as input to explain glucose metabolism of a given target region. This enabled the modeling of postsynaptic energy demands by incoming signals from distinct brain regions.

RESULTS

Functional connectivity input explained a substantial part of metabolic demands but with pronounced regional variations (34 - 76%). During cognitive task performance this multimodal association revealed a shift to higher network integration compared to resting state. In healthy aging, a dedifferentiation (decreased segregated/modular structure of the brain) of brain networks during rest was observed. Furthermore, by including data from mRNA maps, [11C]UCB-J synaptic density and aerobic glycolysis (oxygen-to-glucose index from PET data), we show that whole-brain functional input reflects non-oxidative, on-demand metabolism of synaptic signaling. The metabolically-derived directionality of functional inputs further marked them as top-down predictions. In addition, the approach uncovered formerly hidden networks with superior efficiency through metabolically informed network partitioning.

CONCLUSIONS

Applying multimodal imaging, we decipher a crucial part of the metabolic and neurophysiological basis of functional connections in the brain as interregional on-demand synaptic signaling fueled by anaerobic metabolism. The observed task- and age-related effects indicate promising future applications to characterize human brain function and clinical alterations.

Brain Glucose Metabolism as a Readout of the Central Nervous System Impact of Cigarette Smoke Exposure and Withdrawal and the Effects of NFL-101, as an Immune-Based Drug Candidate for Smoking Cessation Therapy

Neuroimaging biomarkers are needed to investigate the impact of smoking withdrawal on brain function. NFL-101 is a denicotinized aqueous extract of tobacco leaves currently investigated as an immune-based smoking cessation therapy in humans. However, the immune response to NFL-101 and its ability to induce significant changes in brain function remain to be demonstrated. Brain glucose metabolism was investigated using [18F]fluoro-deoxy-glucose ([18F]FDG) PET imaging in a mouse model of cigarette smoke exposure (CSE, 4-week whole-body inhalation, twice daily). Compared with control animals, the relative uptake of [18F]FDG in CSE mice was decreased in the thalamus and brain stem (p < 0.001, n = 14 per group) and increased in the hippocampus, cortex, cerebellum, and olfactory bulb (p < 0.001). NFL-101 induced a humoral immune response (specific IgGs) in mice and activated human natural-killer lymphocytes in vitro. In CSE mice, but not in control mice, single-dose NFL-101 significantly increased [18F]FDG uptake in the thalamus (p < 0.01), thus restoring normal brain glucose metabolism after 2-day withdrawal in this nicotinic receptor-rich region. In tobacco research, [18F]FDG PET imaging provides a quantitative method to evaluate changes in the brain function associated with the withdrawal phase. This method also showed the CNS effects of NFL-101, with translational perspectives for future clinical evaluation in smokers.

Role of F-18 FDG PET-CT in neuropsychiatric systemic lupus erythematosus

BACKGROUND

Neuropsychiatric systemic lupus erythematosus (NPSLE) is a major contributor to morbidity and mortality in systemic lupus erythematosus (SLE) patients. To date no single clinical, laboratory or imaging test has proven accurate for NPSLE diagnosis which is a testament to the intricate and multifactorial pathophysiological mechanisms suspected to exist. Functional imaging with FDG PET-CT has shown promise in NPSLE diagnosis, detecting abnormalities prior to changes evident on anatomical imaging. Research indicates that NPSLE may be more aggressive in people of African descent with higher mortality rates, making rapid and correct diagnosis even more important in the African context.

METHODS

In this narrative review, we provide a thorough appraisal of the current literature on the role of FDG PET-CT in NPSLE. Large, well-known databases were searched using appropriate search terms. Manual searches of references of retrieved literature were also included.

FINDINGS

A total of 73 article abstracts were assessed, yielding 26 papers that were directly relevant to the topic of FDG PET-CT in NPSLE. Results suggest that FDG PET-CT is a sensitive imaging test for NPSLE diagnosis and may play a role in assessing treatment response. It is complementary to routine anatomical imaging, particularly in diffuse manifestations of the disease. Newer quantitative analyses are commonly used for interpretation and can detect even subtle abnormalities, missed on visual inspection. Findings of group-wise analyses of FDG PET-CT scans in NPSLE patients are important in furthering our understanding of the complicated pathophysiological mechanisms involved. Limitations of FDG PET-CT include its lack of specificity, high cost and poor access.

CONCLUSION

FDG PET-CT is a sensitive test for NPSLE diagnosis but is hampered by lack of specificity. It is a valuable tool for clinicians managing SLE patients, particularly when anatomical imaging is negative. Its exact application will depend on the local context and clinical scenario.

Non-invasive assessment of stimulation-specific changes in cerebral glucose metabolism with functional PET

PURPOSE

Functional positron emission tomography (fPET) with [18F]FDG allows quantification of stimulation-induced changes in glucose metabolism independent of neurovascular coupling. However, the gold standard for quantification requires invasive arterial blood sampling, limiting its widespread use. Here, we introduce a novel fPET method without the need for an input function.

METHODS

We validated the approach using two datasets (DS). For DS1, 52 volunteers (23.2 ± 3.3 years, 24 females) performed Tetris® during a [18F]FDG fPET scan (bolus + constant infusion). For DS2, 18 participants (24.2 ± 4.3 years, 8 females) performed an eyes-open/finger tapping task (constant infusion). Task-specific changes in metabolism were assessed with the general linear model (GLM) and cerebral metabolic rate of glucose (CMRGlu) was quantified with the Patlak plot as reference. We then estimated simplified outcome parameters, including GLM beta values and percent signal change (%SC), and compared them, region and whole-brain-wise.

RESULTS

We observed higher agreement with the reference for DS1 than DS2. Both DS resulted in strong correlations between regional task-specific beta estimates and CMRGlu (r = 0.763…0.912). %SC of beta values exhibited strong agreement with %SC of CMRGlu (r = 0.909…0.999). Average activation maps showed a high spatial similarity between CMRGlu and beta estimates (Dice = 0.870…0.979) as well as %SC (Dice = 0.932…0.997), respectively.

CONCLUSION

The non-invasive method reliably estimates task-specific changes in glucose metabolism without blood sampling. This streamlines fPET, albeit with the trade-off of being unable to quantify baseline metabolism. The simplification enhances its applicability in research and clinical settings.

Exploratory Tau PET/CT with [11C]PBB3 in Patients with Suspected Alzheimer's Disease and Frontotemporal Lobar Degeneration: A Pilot Study on Correlation with PET Imaging and Cerebrospinal Fluid Biomarkers

Accurately diagnosing Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) is challenging due to overlapping symptoms and limitations of current imaging methods. This study investigates the use of [11C]PBB3 PET/CT imaging to visualize tau pathology and improve diagnostic accuracy. Given diagnostic challenges with symptoms and conventional imaging, [11C]PBB3 PET/CT's potential to enhance accuracy was investigated by correlating tau pathology with cerebrospinal fluid (CSF) biomarkers, positron emission tomography (PET), computed tomography (CT), amyloid-beta, and Mini-Mental State Examination (MMSE). We conducted [11C]PBB3 PET/CT imaging on 24 patients with suspected AD or FTLD, alongside [11C]PiB PET/CT (13 patients) and [18F]FDG PET/CT (15 patients). Visual and quantitative assessments of [11C]PBB3 uptake using standardized uptake value ratios (SUV-Rs) and correlation analyses with clinical assessments were performed. The scans revealed distinct tau accumulation patterns; 13 patients had no or faint uptake (PBB3-negative) and 11 had moderate to pronounced uptake (PBB3-positive). Significant inverse correlations were found between [11C]PBB3 SUV-Rs and MMSE scores, but not with CSF-tau or CSF-amyloid-beta levels. Here, we show that [11C]PBB3 PET/CT imaging can reveal distinct tau accumulation patterns and correlate these with cognitive impairment in neurodegenerative diseases. Our study demonstrates the potential of [11C]PBB3-PET imaging for visualizing tau pathology and assessing disease severity, offering a promising tool for enhancing diagnostic accuracy in AD and FTLD. Further research is essential to validate these findings and refine the use of tau-specific PET imaging in clinical practice, ultimately improving patient care and treatment outcomes.

Diagnostic Reference Levels in PET Imaging at Chulabhorn Hospital, Thailand

Diagnostic reference levels (DRLs) are an important tool for controlling radiation exposure and ensuring safety in medical applications. In Thailand, DRL data have been gathered and established for nuclear medicine diagnostics since 2021. However, there is a lack of information on PET imaging examinations. At the National Cyclotron and PET Scan Centre, Chulabhorn Hospital, radiopharmaceuticals are produced for medical imaging and research, and a wide range of PET/CT and PET/MRI examinations are performed. Our objective was to investigate the administered activity of radiopharmaceuticals in patients undergoing PET imaging, especially the existing data on DRLs in medical diagnostic imaging. Methods: This was a retrospective study on nuclear medicine patients at the National Cyclotron and PET Scan Centre in 2023. Statistical analysis, including the mean and the 75th percentile values, was conducted to determine DRLs according to the International Commission on Radiological Protection guidelines. Results: The center performed 8,711 PET/CT and PET/MRI studies with 13 protocols in 2023. The most commonly administered activity was 18F-FDG in oncology and neurology examinations, with DRLs of 186.11 and 136.16 MBq, respectively. These values were notably almost twice lower than several reports in other countries. Conclusion: There is a lack of comprehensive data on most DRLs for PET imaging at this center because of the nonwidespread use of several radiopharmaceuticals. However, the lower DRLs for 18F-FDG can highlight the need for ongoing investigation toward the establishment of local DRLs, as well as assurance on the safety and efficiency of radiation used in nuclear medicine.

A deep learning model for generating [18F]FDG PET Images from early-phase [18F]Florbetapir and [18F]Flutemetamol PET images

INTRODUCTION

Amyloid-β (Aβ) plaques is a significant hallmark of Alzheimer's disease (AD), detectable via amyloid-PET imaging. The Fluorine-18-Fluorodeoxyglucose ([18F]FDG) PET scan tracks cerebral glucose metabolism, correlated with synaptic dysfunction and disease progression and is complementary for AD diagnosis. Dual-scan acquisitions of amyloid PET allows the possibility to use early-phase amyloid-PET as a biomarker for neurodegeneration, proven to have a good correlation to [18F]FDG PET. The aim of this study was to evaluate the added value of synthesizing the later from the former through deep learning (DL), aiming at reducing the number of PET scans, radiation dose, and discomfort to patients.

METHODS

A total of 166 subjects including cognitively unimpaired individuals (N = 72), subjects with mild cognitive impairment (N = 73) and dementia (N = 21) were included in this study. All underwent T1-weighted MRI, dual-phase amyloid PET scans using either Fluorine-18 Florbetapir ([18F]FBP) or Fluorine-18 Flutemetamol ([18F]FMM), and an [18F]FDG PET scan. Two transformer-based DL models called SwinUNETR were trained separately to synthesize the [18F]FDG from early phase [18F]FBP and [18F]FMM (eFBP/eFMM). A clinical similarity score (1: no similarity to 3: similar) was assessed to compare the imaging information obtained by synthesized [18F]FDG as well as eFBP/eFMM to actual [18F]FDG. Quantitative evaluations include region wise correlation and single-subject voxel-wise analyses in comparison with a reference [18F]FDG PET healthy control database. Dice coefficients were calculated to quantify the whole-brain spatial overlap between hypometabolic ([18F]FDG PET) and hypoperfused (eFBP/eFMM) binary maps at the single-subject level as well as between [18F]FDG PET and synthetic [18F]FDG PET hypometabolic binary maps.

RESULTS

The clinical evaluation showed that, in comparison to eFBP/eFMM (average of clinical similarity score (CSS) = 1.53), the synthetic [18F]FDG images are quite similar to the actual [18F]FDG images (average of CSS = 2.7) in terms of preserving clinically relevant uptake patterns. The single-subject voxel-wise analyses showed that at the group level, the Dice scores improved by around 13% and 5% when using the DL approach for eFBP and eFMM, respectively. The correlation analysis results indicated a relatively strong correlation between eFBP/eFMM and [18F]FDG (eFBP: slope = 0.77, R2 = 0.61, P-value < 0.0001); eFMM: slope = 0.77, R2 = 0.61, P-value < 0.0001). This correlation improved for synthetic [18F]FDG (synthetic [18F]FDG generated from eFBP (slope = 1.00, R2 = 0.68, P-value < 0.0001), eFMM (slope = 0.93, R2 = 0.72, P-value < 0.0001)).

CONCLUSION

We proposed a DL model for generating the [18F]FDG from eFBP/eFMM PET images. This method may be used as an alternative for multiple radiotracer scanning in research and clinical settings allowing to adopt the currently validated [18F]FDG PET normal reference databases for data analysis.

Recent Update on PET/CT Radiotracers for Imaging Cerebral Glioma

Positron emission tomography/computed tomography (PET/CT) has dramatically altered the landscape of noninvasive glioma evaluation, offering complementary insights to those gained through magnetic resonance imaging (MRI). PET/CT scans enable a multifaceted analysis of glioma biology, supporting clinical applications from grading and differential diagnosis to mapping the full extent of tumors and planning subsequent treatments and evaluations. With a broad array of specialized radiotracers, researchers and clinicians can now probe various biological characteristics of gliomas, such as glucose utilization, cellular proliferation, oxygen deficiency, amino acid trafficking, and reactive astrogliosis. This review aims to provide a recent update on the application of versatile PET/CT radiotracers in glioma research and clinical practice.

EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy

Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy surgery is a treatment option depending on the localisation of the seizure focus for seizure relief or seizure freedom with consecutive improvement in quality of life. Beside examinations such as scalp video/electroencephalography (EEG) telemetry, structural, and functional magnetic resonance imaging (MRI), which are primary standard tools for the diagnostic work-up and therapy management of epilepsy patients, molecular neuroimaging using different radiopharmaceuticals with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) influences and impacts on therapy decisions. To date, there are no literature-based praxis recommendations for the use of Nuclear Medicine (NM) imaging procedures in epilepsy. The aims of these guidelines are to assist in understanding the role and challenges of radiotracer imaging for epilepsy; to provide practical information for performing different molecular imaging procedures for epilepsy; and to provide an algorithm for selecting the most appropriate imaging procedures in specific clinical situations based on current literature. These guidelines are written and authorized by the European Association of Nuclear Medicine (EANM) to promote optimal epilepsy imaging, especially in the presurgical setting in children, adolescents, and adults with focal epilepsy. They will assist NM healthcare professionals and also specialists such as Neurologists, Neurophysiologists, Neurosurgeons, Psychiatrists, Psychologists, and others involved in epilepsy management in the detection and interpretation of epileptic seizure onset zone (SOZ) for further treatment decision. The information provided should be applied according to local laws and regulations as well as the availability of various radiopharmaceuticals and imaging modalities.

Glial Activity Load on PET Reveals Persistent "Smoldering" Inflammation in MS Despite Disease-Modifying Treatment: 18 F-PBR06 Study

PURPOSE OF THE REPORT

18 F-PBR06-PET targeting 18-kDa translocator protein can detect abnormal microglial activation (MA) in multiple sclerosis (MS). The objectives of this study are to develop individualized mapping of MA using 18 F-PBR06, to determine the effect of disease-modifying treatment (DMT) efficacy on reducing MA, and to determine its clinical, radiological, and serological correlates in MS patients.

PATIENTS AND METHODS

Thirty 18 F-PBR06-PET scans were performed in 22 MS patients (mean age, 46 ± 13 years; 16 females) and 8 healthy controls (HCs). Logarithmically transformed "glial activity load on PET" scores (calculated as the sum of voxel-by-voxel z -scores ≥4), "lnGALP," were compared between MS and HC and between MS subjects on high-efficacy DMTs (H-DMT, n = 13) and those on no or lower-efficacy treatment, and correlated with clinical measures, serum biomarkers, and cortical thickness.

RESULTS

Cortical gray matter (CoGM) and white matter (WM) lnGALP scores were higher in MS versus HC (+33% and +48%, P < 0.001). In H-DMT group, CoGM and WM lnGALP scores were significantly lower than lower-efficacy treatment ( P < 0.01) but remained abnormally higher than in HC group ( P = 0.006). Within H-DMT patients, CoGM lnGALP scores correlated positively with physical disability, fatigue and serum glial fibrillary acid protein levels ( r = 0.65-0.79, all P 's < 0.05), and inversely with cortical thickness ( r = -0.66, P < 0.05).

CONCLUSIONS

High-efficacy DMTs decrease, but do not normalize, CoGM and WM MA in MS patients. Such "residual" MA in CoGM is associated with clinical disability, serum biomarkers, and cortical degeneration. Individualized mapping of translocator protein PET using 18 F-PBR06 is clinically feasible and can potentially serve as an imaging biomarker for evaluating "smoldering" inflammation in MS patients.

Enhancing the Diagnostic Utility of ASL Imaging in Temporal Lobe Epilepsy through FlowGAN: An ASL to PET Image Translation Framework

Background and Significance

Positron Emission Tomography (PET) using fluorodeoxyglucose (FDG-PET) is a standard imaging modality for detecting areas of hypometabolism associated with the seizure onset zone (SOZ) in temporal lobe epilepsy (TLE). However, FDG-PET is costly and involves the use of a radioactive tracer. Arterial Spin Labeling (ASL) offers an MRI-based quantification of cerebral blood flow (CBF) that could also help localize the SOZ, but its performance in doing so, relative to FDG-PET, is limited. In this study, we seek to improve ASL's diagnostic performance by developing a deep learning framework for synthesizing FDG-PET-like images from ASL and structural MRI inputs.

Methods

We included 68 epilepsy patients, out of which 36 had well lateralized TLE. We compared the coupling between FDG-PET and ASL CBF values in different brain regions, as well as the asymmetry of these values across the brain. We additionally assessed each modality's ability to lateralize the SOZ across brain regions. Using our paired PET-ASL data, we developed FlowGAN, a generative adversarial neural network (GAN) that synthesizes PET-like images from ASL and T1-weighted MRI inputs. We tested our synthetic PET images against the actual PET images of subjects to assess their ability to reproduce clinically meaningful hypometabolism and asymmetries in TLE.

Results

We found variable coupling between PET and ASL CBF values across brain regions. PET and ASL had high coupling in neocortical temporal and frontal brain regions (Spearman's r > 0.30, p < 0.05) but low coupling in mesial temporal structures (Spearman's r < 0.30, p > 0.05). Both whole brain PET and ASL CBF asymmetry values provided good separability between left and right TLE subjects, but PET (AUC = 0.96, 95% CI: [0.88, 1.00]) outperformed ASL (AUC = 0.81; 95% CI: [0.65, 0.96]). FlowGAN-generated images demonstrated high structural similarity to actual PET images (SSIM = 0.85). Globally, asymmetry values were better correlated between synthetic PET and original PET than between ASL CBF and original PET, with a mean correlation increase of 0.15 (95% CI: [0.07, 0.24], p<0.001, Cohen's d = 0.91). Furthermore, regions that had poor ASL-PET correlation (e.g. mesial temporal structures) showed the greatest improvement with synthetic PET images.

Conclusions

FlowGAN improves ASL's diagnostic performance, generating synthetic PET images that closely mimic actual FDG-PET in depicting hypometabolism associated with TLE. This approach could improve non-invasive SOZ localization, offering a promising tool for epilepsy presurgical assessment. It potentially broadens the applicability of ASL in clinical practice and could reduce reliance on FDG-PET for epilepsy and other neurological disorders.

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.

Quantitative brain 18F-FDG PET/CT analysis in seronegative autoimmune encephalitis

OBJECTIVE

Brain 18F-FDG PET/CT is a useful diagnostic in evaluating patients with suspected autoimmune encephalitis (AE). Specific patterns of brain dysmetabolism have been reported in anti-NMDAR and anti-LGI1 AE, and the degree of dysmetabolism may correlate with clinical functional status.18FDG-PET/CT abnormalities have not yet been described in seronegative AE.

METHODS

We conducted a cross-sectional analysis of brain18FDG-PET/CT data in people with seronegative AE treated at the Johns Hopkins Hospital. Utilizing NeuroQ™ software, the Z-scores of 47 brain regions were calculated relative to healthy controls, then visually and statistically compared for probable and possible AE per clinical consensus diagnostic criteria to previous data from anti-NMDAR and anti-LGI1 cohorts.

RESULTS

Eight probable seronegative AE and nine possible seronegative AE were identified. The group only differed in frequency of abnormal brain MRI, which was seen in all of the probable seronegative AE patients. Both seronegative groups had similar overall patterns of brain dysmetabolism. A common pattern of frontal lobe hypometabolism and medial temporal lobe hypermetabolism was observed in patients with probable and possible seronegative AE, as well as anti-NMDAR and anti-LGI1 AE as part of their respective characteristic patterns of dysmetabolism. Four patients had multiple brain18FDG-PET/CT scans, with changes in number and severity of abnormal brain regions mirroring clinical status.

CONCLUSIONS

A18FDG-PET/CT pattern of frontal lobe hypometabolism and medial temporal lobe hypermetabolism could represent a common potential biomarker of AE, which along with additional clinical data may facilitate earlier diagnosis and treatment.

[18F]SynVesT-1 and [18F]FDG quantitative PET imaging in the presurgical evaluation of MRI-negative children with focal cortical dysplasia type II

PURPOSE

MRI-negative children with focal cortical dysplasia type II (FCD II) are one of the most challenging cases in surgical epilepsy management. We aimed to utilize quantitative positron emission tomography (QPET) analysis to complement [18F]SynVesT-1 and [18F]FDG PET imaging and facilitate the localization of epileptogenic foci in pediatric MRI-negative FCD II patients.

METHODS

We prospectively enrolled 17 MRI-negative children with FCD II who underwent [18F]SynVesT-1 and [18F]FDG PET before surgical resection. The QPET scans were analyzed using statistical parametric mapping (SPM) with respect to healthy controls. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of [18F]SynVesT-1 PET, [18F]FDG PET, [18F]SynVesT-1 QPET, and [18F]FDG QPET in the localization of epileptogenic foci were assessed. Additionally, we developed a multivariate prediction model based on dual trace PET/QPET assessment.

RESULTS

The AUC values of [18F]FDG PET and [18F]SynVesT-1 PET were 0.861 (sensitivity = 94.1%, specificity = 78.2%, PPV = 38.1%, NPV = 98.9%) and 0.908 (sensitivity = 82.4%, specificity = 99.2%, PPV = 93.3%, NPV = 97.5%), respectively. [18F]FDG QPET showed lower sensitivity (76.5%) and NPV (96.6%) but higher specificity (95.0%) and PPV (68.4%) than visual assessment, while [18F]SynVesT-1 QPET exhibited higher sensitivity (94.1%) and NPV (99.1%) but lower specificity (97.5%) and PPV (84.2%). The multivariate prediction model had the highest AUC value (AUC = 0.996, sensitivity = 100.0%, specificity = 96.6%, PPV = 81.0%, NPV = 100%).

CONCLUSIONS

The multivariate prediction model based on [18F]SynVesT-1 and [18F]FDG PET/QPET assessments holds promise in noninvasively identifying epileptogenic regions in MRI-negative children with FCD II. Furthermore, the combination of visual assessment and QPET may improve the sensitivity and specificity of diagnostic tests in localizing epileptogenic foci and achieving a preferable surgical outcome in MRI-negative FCD II.

The cingulate island sign in a mixed memory clinical cohort: Prevalence and diagnostic accuracy

INTRODUCTION

Visual rating of the cingulate island sign (CIS) on [18F]fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) has a high specificity for dementia with Lewy bodies (DLB) in selected cohorts such as DLB versus Alzheimer's disease (AD). In a mixed memory clinical population this study aimed to uncover the prevalence of CIS, the diagnostic accuracy for DLB, and the relationship between CIS and disease severity.

METHODS

CIS on [18F]FDG-PET was retrospectively assessed with the visual CIS rating scale (CISRs) in 1000 patients with a syndrome diagnosis of mild cognitive impairment (MCI) or dementia with no restrictions in etiological diagnosis.

RESULTS

In this cohort 24.3 % had a CISRs score ≥1 and 3.5 % had a CISRs score = 4. The prevalence of a CISRs score ≥1 was highest in DLB (74.0 %, n = 57). A CISRs score ≥1 was present in at least 9 % in other diagnostic groups. The prevalence of CIS across disease severities showed no statistically significant difference (p = 0.23). To differentiate DLB from non-DLB the optimal cut-off was a CISRs score ≥1 (balanced accuracy = 77.1 %) in MCI/mild dementia and a CISRs score ≥2 (balanced accuracy = 80.6 %) in moderate/severe dementia. The positive predictive value of a CISRs score = 4 for DLB was 57.7 % in MCI/mild dementia and 33.3 % in moderate/severe dementia.

CONCLUSION

The CISRs is useful in differentiating DLB from other etiologies in a mixed memory clinical population. Balanced accuracy and positive predictive value may vary across disease severities in the population studied.

High-temporal resolution functional PET/MRI reveals coupling between human metabolic and hemodynamic brain response

PURPOSE

Positron emission tomography (PET) provides precise molecular information on physiological processes, but its low temporal resolution is a major obstacle. Consequently, we characterized the metabolic response of the human brain to working memory performance using an optimized functional PET (fPET) framework at a temporal resolution of 3 s.

METHODS

Thirty-five healthy volunteers underwent fPET with [18F]FDG bolus plus constant infusion, 19 of those at a hybrid PET/MRI scanner. During the scan, an n-back working memory paradigm was completed. fPET data were reconstructed to 3 s temporal resolution and processed with a novel sliding window filter to increase signal to noise ratio. BOLD fMRI signals were acquired at 2 s.

RESULTS

Consistent with simulated kinetic modeling, we observed a constant increase in the [18F]FDG signal during task execution, followed by a rapid return to baseline after stimulation ceased. These task-specific changes were robustly observed in brain regions involved in working memory processing. The simultaneous acquisition of BOLD fMRI revealed that the temporal coupling between hemodynamic and metabolic signals in the primary motor cortex was related to individual behavioral performance during working memory. Furthermore, task-induced BOLD deactivations in the posteromedial default mode network were accompanied by distinct temporal patterns in glucose metabolism, which were dependent on the metabolic demands of the corresponding task-positive networks.

CONCLUSIONS

In sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing. This allows to capture unique information in the temporal domain, which is not accessible to conventional PET imaging.

Evidence of brain metabolism redistribution from neocortex to primitive brain structures in early acute COVID-19 respiratory syndrome

BACKGROUND

Neuropsychiatric sequelae of COVID-19 have been widely documented in patients with severe neurological symptoms during the chronic or subacute phase of the disease. However, it remains unclear whether subclinical changes in brain metabolism can occur early in the acute phase of the disease. The aim of this study was to identify and quantify changes in brain metabolism in patients hospitalized for acute respiratory syndrome due to COVID-19 with no or mild neurological symptoms.

RESULTS

Twenty-three non-intubated patients (13 women; mean age 55.5 ± 12.1 years) hospitalized with positive nasopharyngeal swab test (RT-PCR) for COVID-19, requiring supplemental oxygen and no or mild neurological symptoms were studied. Serum C-reactive protein measured at admission ranged from 6.43 to 189.0 mg/L (mean: 96.9 ± 54.2 mg/L). The mean supplemental oxygen demand was 2.9 ± 1.4 L/min. [18F]FDG PET/CT images were acquired with a median of 12 (4-20) days of symptoms. After visual interpretation of the images, semiquantitative analysis of [18F]FDG uptake in multiple brain regions was evaluated using dedicated software and the standard deviation (SD) of brain uptake in each region was automatically calculated in comparison with reference values of a normal database. Evolutionarily ancient structures showed positive SD mean values of [18F]FDG uptake. Lenticular nuclei were bilaterally hypermetabolic (> 2 SD) in 21/23 (91.3%) patients, and thalamus in 16/23 (69.6%), bilaterally in 11/23 (47.8%). About half of patients showed hypermetabolism in brainstems, 40% in hippocampi, and 30% in cerebellums. In contrast, neocortical regions (frontal, parietal, temporal and occipital lobes) presented negative SD mean values of [18F]FDG uptake and hypometabolism (< 2 SD) was observed in up to a third of patients. Associations were found between hypoxia, inflammation, coagulation markers, and [18F]FDG uptake in various brain structures.

CONCLUSIONS

Brain metabolism is clearly affected during the acute phase of COVID-19 respiratory syndrome in neurologically asymptomatic or oligosymptomatic patients. The most frequent finding is marked hypermetabolism in evolutionary ancient structures such as lenticular nucleus and thalami. Neocortical metabolism was reduced in up to one third of patients, suggesting a redistribution of brain metabolism from the neocortex to evolutionary ancient brain structures in these patients.

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.

Tracking the progression of Alzheimer's disease: Insights from metabolic patterns of SOMI stages

BACKGROUND

SOMI (Stages of Objective Memory Impairment) is a novel classification that identifies six stages of memory decline in Alzheimer's Disease (AD) using the Free and Cued Selective Reminding Test (FCSRT). However, the relationship between SOMI stages and brain metabolism remains unexplored. This study aims to investigate the metabolic correlates of SOMI stages using FDG-PET in Mild Cognitive Impairment due to AD (MCI-AD) and early AD patients.

METHODS

One hundred twenty-nine-patients (99 aMCI-AD and 30 AD), and 42 healthy controls (HCs) (MMSE = 29.2 ± .8; age:69.1 ± 8.6 years; education:10.7 ± 3.8 years) who underwent an extensive neuropsychological battery including FCSRT and brain FDG-PET were enrolled. According to their clinical relevance and available sample sizes, SOMI-4 (N = 24 subjects; MMSE score:26.6 ± 2.6: age:75.4 ± 3.2; education:9.9 ± 4.5) and SOMI-5 groups (N = 97; MMSE:25.3 ± 2.6; age:73.9 ± 5.8; education:9.4 ± 4.1) were investigated.

RESULTS

Compared to HCs, SOMI-4 showed hypometabolism in the precuneus, medial temporal gyrus bilaterally, right pecuneus and angular gyrus. SOMI-5 exhibited broader hypometabolism, extending to the left posterior cingulate and medial frontal gyrus bilaterally. The conjunction analysis revealed overlapping areas in the precuneus, medial temporal gyrus bilaterally, and in the right angular gyrus and cuneus. The disjunction analysis identified SOMI-5 specific hypometabolism encompassing left inferior temporal gyrus, uncus and parahippocampal gyrus, and medial frontal gyrus bilaterally (p < .001, p-value (FWE) < .05).

DISCUSSION

SOMI-4 relates to posterior hypometabolism, while SOMI-5 to more extensive hypometabolism further encompassing frontal cortices, suggesting SOMI as a biologically relevant classification system of memory decline.

CONCLUSION

Memory decline staged with SOMI is associated with hypometabolism spreading in amnesic MCI-AD/AD, suggesting its usefulness as a clinical marker of increasing neurodegeneration.

Early cerebral amyloid-β accumulation and hypermetabolism are associated with subtle cognitive deficits before accelerated cerebral atrophy

AIMS

Alzheimer's disease (AD) is characterized by the accumulation of amyloid beta (Aβ) in the brain. The deposition of Aβ is believed to initiate a detrimental cascade, including cerebral hypometabolism, accelerated brain atrophy, and cognitive problems-ultimately resulting in AD. However, the timing and causality of the cascade resulting in AD are not yet fully established. Therefore, we examined whether early Aβ accumulation affects cerebral glucose metabolism, atrophy rate, and age-related cognitive decline before the onset of neurodegenerative disease.

METHODS

Participants from the Metropolit 1953 Danish Male Birth Cohort underwent brain positron emission tomography (PET) imaging using the radiotracers [11C]Pittsburgh Compound-B (PiB) (N = 70) and [18F]Fluorodeoxyglucose (FDG) (N = 76) to assess cerebral Aβ accumulation and glucose metabolism, respectively. The atrophy rate was calculated from anatomical magnetic resonance imaging (MRI) scans conducted presently and 10 years ago. Cognitive decline was examined from neurophysiological tests conducted presently and ten or 5 years ago.

RESULTS

Higher Aβ accumulation in AD-critical brain regions correlated with greater visual memory decline (p = 0.023). Aβ accumulation did not correlate with brain atrophy rates. Increased cerebral glucose metabolism in AD-susceptible regions correlated with worse verbal memory performance (p = 0.040).

CONCLUSIONS

Aβ accumulation in known AD-related areas was associated with subtle cognitive deficits. The association was observed before hypometabolism or accelerated brain atrophy, suggesting that Aβ accumulation is involved early in age-related cognitive dysfunction. The association between hypermetabolism and worse memory performance may be due to early compensatory mechanisms adapting for malfunctioning neurons by increasing metabolism.

A ROI-based quantitative pipeline for 18F-FDG PET metabolism and pCASL perfusion joint analysis: Validation of the 18F-FDG PET line

In Mild Cognitive Impairment (MCI), the study of brain metabolism, provided by 18F-FluoroDeoxyGlucose Positron Emission Tomography (18F-FDG PET) can be integrated with brain perfusion through pseudo-Continuous Arterial Spin Labeling Magnetic Resonance sequences (MR pCASL). Cortical hypometabolism identification generally relies on wide control group datasets; pCASL control groups are instead not publicly available yet, due to lack of standardization in the acquisition parameters. This study presents a quantitative pipeline to be applied to PET and pCASL data to coherently analyze metabolism and perfusion inside 16 matching cortical regions of interest (ROIs) derived from the AAL3 atlas. The PET line is tuned on 36 MCI patients and 107 healthy control subjects, to agree in identifying hypometabolic regions with clinical reference methods (visual analysis supported by a vendor tool and Statistical Parametric Mapping, SPM, with two parametrizations here identified as SPM-A and SPM-B). The analysis was conducted for each ROI separately. The proposed PET analysis pipeline obtained accuracy 78 % and Cohen's к 60 % vs visual analysis, accuracy 79 % and Cohen's к 58 % vs SPM-A, accuracy 77 % and Cohen's к 54 % vs SPM-B. Cohen's к resulted not significantly different from SPM-A and SPM-B Cohen's к when assuming visual analysis as reference method (p-value 0.61 and 0.31 respectively). Considering SPM-A as reference method, Cohen's к is not significantly different from SPM-B Cohen's к as well (p-value = 1.00). The complete PET-pCASL pipeline was then preliminarily applied on 5 MCI patients and metabolism-perfusion regional correlations were assessed. The proposed approach can be considered as a promising tool for PET-pCASL joint analyses in MCI, even in the absence of a pCASL control group, to perform metabolism-perfusion regional correlation studies, and to assess and compare perfusion in hypometabolic or normo-metabolic areas.

The pathogenesis of blepharospasm

Blepharospasm is a focal dystonia characterized by involuntary tetanic contractions of the orbicularis oculi muscle, which can lead to functional blindness and loss of independent living ability in severe cases. It usually occurs in adults, with a higher incidence rate in women than in men. The etiology and pathogenesis of this disease have not been elucidated to date, but it is traditionally believed to be related to the basal ganglia. Studies have also shown that this is related to the decreased activity of inhibitory neurons in the cerebral cortex caused by environmental factors and genetic predisposition. Increasingly, studies have focused on the imbalance in the regulation of neurotransmitters, including dopamine, serotonin, and acetylcholine, in blepharospasm. The onset of the disease is insidious, and the misdiagnosis rate is high based on history and clinical manifestations. This article reviews the etiology, epidemiological features, and pathogenesis of blepharospasm, to improve understanding of the disease by neurologists and ophthalmologists.

Asymmetry of thalamic hypometabolism on FDG-PET/CT in neurofibromatosis type 1: Association with peripheral tumor burden

BACKGROUND AND PURPOSE

Thalamic hypometabolism is a consistent finding in brain PET with F-18 fluorodeoxyglucose (FDG) in patients with neurofibromatosis type 1 (NF1). However, the pathophysiology of this metabolic alteration is unknown. We hypothesized that it might be secondary to disturbance of peripheral input to the thalamus by NF1-characteristic peripheral nerve sheath tumors (PNSTs). To test this hypothesis, we investigated the relationship between thalamic FDG uptake and the number, volume, and localization of PNSTs.

METHODS

This retrospective study included 22 adult NF1 patients (41% women, 36.2 ± 13.0 years) referred to whole-body FDG-PET/contrast-enhanced CT for suspected malignant transformation of PNSTs and 22 sex- and age-matched controls. Brain FDG uptake was scaled voxelwise to the individual median uptake in cerebellar gray matter. Bilateral mean and left-right asymmetry of thalamic FDG uptake were determined using a left-right symmetric anatomical thalamus mask. PNSTs were manually segmented in contrast-enhanced CT.

RESULTS

Thalamic FDG uptake was reduced in NF1 patients by 2.0 standard deviations (p < .0005) compared to controls. Left-right asymmetry was increased by 1.3 standard deviations (p = .013). Thalamic hypometabolism was higher in NF1 patients with ≥3 PNSTs than in patients with ≤2 PNSTs (2.6 vs. 1.6 standard deviations, p = .032). The impact of the occurrence of paraspinal/paravertebral PNSTs and of the mean PNST volume on thalamic FDG uptake did not reach statistical significance (p = .098 and p = .189). Left-right asymmetry of thalamic FDG uptake was not associated with left-right asymmetry of PNST burden (p = .658).

CONCLUSIONS

This study provides first evidence of left-right asymmetry of thalamic hypometabolism in NF1 and that it might be mediated by NF1-associated peripheral tumors.

An overview: Radiotracers and nano-radiopharmaceuticals for diagnosis of Parkinson's disease

Parkinson's disease (PD) is a widespread progressive neurodegenerative disease. Clinical diagnosis approaches are insufficient to provide an early and accurate diagnosis before a substantial of loss of dopaminergic neurons. PET and SPECT can be used for accurate and early diagnosis of PD by using target-specific radiotracers. Additionally, the importance of BBB penetrating targeted nanosystems has increased in recent years. This article reviews targeted radiopharmaceuticals used in clinics and novel nanocarriers for research purposes of PD imaging.

Thai national guideline for nuclear medicine investigation in movement disorders: Nuclear medicine society of Thailand, the neurological society of Thailand, and Thai medical physicist society collaboration

Movement disorders are chronic neurological syndromes with both treatable and non-treatable causes. The top causes of movement disorders are Parkinson's disease and related disorders. Functional imaging investigations with Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) images play vital roles in diagnosis and differential diagnosis to guide disease management. Since there have been new advanced imaging technologies and radiopharmaceuticals development, there is a need for up-to-date consensus guidelines. Thus, the Nuclear Medicine Society of Thailand, the Neurological Society of Thailand, and the Thai Medical Physicist Society collaborated to establish the guideline for Nuclear Medicine investigations in movement disorder for practical use in patient care. We have extensively reviewed the current practice guidelines from other related societies and good quality papers as well as our own experience in Nuclear Medicine practice in movement disorders. We also adjust for the most suitability for application in Thailand and other developing countries.

Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group

 Neuroimaging is increasingly being included in clinical trials of Huntington's disease (HD) for a wide range of purposes from participant selection and safety monitoring, through to demonstration of disease modification. Selection of the appropriate modality and associated analysis tools requires careful consideration. On behalf of the EHDN Imaging Working Group, we present current opinion on the utility and future prospects for inclusion of neuroimaging in HD trials. Covering the key imaging modalities of structural-, functional- and diffusion- MRI, perfusion imaging, positron emission tomography, magnetic resonance spectroscopy, and magnetoencephalography, we address how neuroimaging can be used in HD trials to: 1) Aid patient selection, enrichment, stratification, and safety monitoring; 2) Demonstrate biodistribution, target engagement, and pharmacodynamics; 3) Provide evidence for disease modification; and 4) Understand brain re-organization following therapy. We also present the challenges of translating research methodology into clinical trial settings, including equipment requirements and cost, standardization of acquisition and analysis, patient burden and invasiveness, and interpretation of results. We conclude, that with appropriate consideration of modality, study design and analysis, imaging has huge potential to facilitate effective clinical trials in HD.

Deep-learning predicted PET can be subtracted from the true clinical fluorodeoxyglucose PET co-registered to MRI to identify the epileptogenic zone in focal epilepsy

OBJECTIVE

Normal interictal [18 F]FDG-PET can be predicted from the corresponding T1w MRI with Generative Adversarial Networks (GANs). A technique we call SIPCOM (Subtraction Interictal PET Co-registered to MRI) can then be used to compare epilepsy patients' predicted and clinical PET. We assessed the ability of SIPCOM to identify the Resection Zone (RZ) in patients with drug-resistant epilepsy (DRE) with reference to visual and statistical parametric mapping (SPM) analysis.

METHODS

Patients with complete presurgical work-up and subsequent SEEG and cortectomy were included. RZ localisation, the reference region, was assigned to one of eighteen anatomical brain regions. SIPCOM was implemented using healthy controls to train a GAN. To compare, the clinical PET coregistered to MRI was visually assessed by two trained readers, and a standard SPM analysis was performed.

RESULTS

Twenty patients aged 17-50 (32 ± 7.8) years were included, 14 (70%) with temporal lobe epilepsy (TLE). Eight (40%) were MRI-negative. After surgery, 14 patients (70%) had a good outcome (Engel I-II). RZ localisation rate was 60% with SIPCOM vs 35% using SPM (P = 0.015) and vs 85% using visual analysis (P = 0.54). Results were similar for Engel I-II patients, the RZ localisation rate was 64% with SIPCOM vs 36% with SPM. With SIPCOM localisation was correct in 67% in MRI-positive vs 50% in MRI-negative patients, and 64% in TLE vs 43% in extra-TLE. The average number of false-positive clusters was 2.2 ± 1.3 using SIPCOM vs 2.3 ± 3.1 using SPM. All RZs localized with SPM were correctly localized with SIPCOM. In one case, PET and MRI were visually reported as negative, but both SIPCOM and SPM localized the RZ.

SIGNIFICANCE

SIPCOM performed better than the reference computer-assisted method (SPM) for RZ detection in a group of operated DRE patients. SIPCOM's impact on epilepsy management needs to be prospectively validated.

MSCs overexpressing GDNF restores brain structure and neurological function in rats with intracerebral hemorrhage

Mesenchymal stem cells (MSCs) have been applied in transplantation to treat intracerebral hemorrhage (ICH) but with limited efficacy. Accumulated evidence has shown that glial cell-derived neurotrophic factor (GDNF) plays a crucial part in neuronal protection and functional recovery of the brain after ICH; however, GDNF has difficulty crossing the blood-brain barrier, which limits its application. In this study, we investigated the influences of MSCs overexpressing GDNF (MSCs/GDNF) on the brain structure as well as gait of rats after ICH and explored the possible mechanisms. We found that cell transplantation could reverse the neurological dysfunction and brain damage caused by ICH to a certain extent, and MSCs/GDNF transplantation was superior to MSCs transplantation. Moreover, Transplantation of MSCs overexpressing GDNF effectively reduced the volume of bleeding foci and increased the level of glucose uptake in rats with ICH, which could be related to improving mitochondrial quality. Furthermore, GDNF produced by transplanted MSCs/GDNF further inhibited neuroinflammation, improved mitochondrial quality and function, promoted angiogenesis and the survival of neurons and oligodendrocytes, and enhanced synaptic plasticity in ICH rats when compared with simple MSC transplantation. Overall, our data indicate that GDNF overexpression heightens the curative effect of MSC implantation in treating rats following ICH.

Clinical Value of Hybrid PET/MR Imaging: Brain Imaging Using PET/MR Imaging

Hybrid PET/MR imaging offers a unique opportunity to acquire MR imaging and PET information during a single imaging session. PET/MR imaging has numerous advantages, including enhanced diagnostic accuracy, improved disease characterization, and better treatment planning and monitoring. It enables the immediate integration of anatomic, functional, and metabolic imaging information, allowing for personalized characterization and monitoring of neurologic diseases. This review presents recent advances in PET/MR imaging and highlights advantages in clinical practice for neuro-oncology, epilepsy, and neurodegenerative disorders. PET/MR imaging provides valuable information about brain tumor metabolism, perfusion, and anatomic features, aiding in accurate delineation, treatment response assessment, and prognostication.

Combined 18F-FDG PET-CT markers in dementia with Lewy bodies

INTRODUCTION

18F-Fluoro-deoxyglucose-positron emission tomography (FDG-PET) is a supportive biomarker in dementia with Lewy bodies (DLB) diagnosis and its advanced analysis methods, including radiomics and machine learning (ML), were developed recently. The aim of this study was to evaluate the FDG-PET diagnostic performance in predicting a DLB versus Alzheimer's disease (AD) diagnosis.

METHODS

FDG-PET scans were visually and semi-quantitatively analyzed in 61 patients. Radiomics and ML analyses were performed, building five ML models: (1) clinical features; (2) visual and semi-quantitative PET features; (3) radiomic features; (4) all PET features; and (5) overall features.

RESULTS

At follow-up, 34 patients had DLB and 27 had AD. At visual analysis, DLB PET signs were significantly more frequent in DLB, having the highest diagnostic accuracy (86.9%). At semi-quantitative analysis, the right precuneus, superior parietal, lateral occipital, and primary visual cortices showed significantly reduced uptake in DLB. The ML model 2 had the highest diagnostic accuracy (84.3%).

DISCUSSION

FDG-PET is a valuable tool in DLB diagnosis, having visual and semi-quantitative analyses with the highest diagnostic accuracy at ML analyses.

Automatic covariance pattern analysis outperforms visual reading of 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) in variant progressive supranuclear palsy

BACKGROUND

To date, studies on positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP-RS).

OBJECTIVES

To evaluate FDG-PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice.

METHODS

This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non-RS variants of PSP (vPSP), and 46 age-matched healthy controls. Two state-of-the art methods for the interpretation of FDG-PET were compared: visual analysis supported by voxel-based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP-related pattern.

RESULTS

Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false-negative cases was 10% in the PSP-RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false-negative cases was 0% in the PSP-RS subsample and 15% in the vPSP subsample.

CONCLUSIONS

Visual interpretation of FDG-PET supported by voxel-based testing provides good accuracy for the detection of PSP-RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP-RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false-positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel-based testing of FDG-PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A review of PET attenuation correction methods for PET-MR

Despite being thirteen years since the installation of the first PET-MR system, the scanners constitute a very small proportion of the total hybrid PET systems installed. This is in stark contrast to the rapid expansion of the PET-CT scanner, which quickly established its importance in patient diagnosis within a similar timeframe. One of the main hurdles is the development of an accurate, reproducible and easy-to-use method for attenuation correction. Quantitative discrepancies in PET images between the manufacturer-provided MR methods and the more established CT- or transmission-based attenuation correction methods have led the scientific community in a continuous effort to develop a robust and accurate alternative. These can be divided into four broad categories: (i) MR-based, (ii) emission-based, (iii) atlas-based and the (iv) machine learning-based attenuation correction, which is rapidly gaining momentum. The first is based on segmenting the MR images in various tissues and allocating a predefined attenuation coefficient for each tissue. Emission-based attenuation correction methods aim in utilising the PET emission data by simultaneously reconstructing the radioactivity distribution and the attenuation image. Atlas-based attenuation correction methods aim to predict a CT or transmission image given an MR image of a new patient, by using databases containing CT or transmission images from the general population. Finally, in machine learning methods, a model that could predict the required image given the acquired MR or non-attenuation-corrected PET image is developed by exploiting the underlying features of the images. Deep learning methods are the dominant approach in this category. Compared to the more traditional machine learning, which uses structured data for building a model, deep learning makes direct use of the acquired images to identify underlying features. This up-to-date review goes through the literature of attenuation correction approaches in PET-MR after categorising them. The various approaches in each category are described and discussed. After exploring each category separately, a general overview is given of the current status and potential future approaches along with a comparison of the four outlined categories.

Brain FDG-PET findings in chimeric antigen receptor T-cell therapy neurotoxicity for diffuse large B-cell lymphoma

BACKGROUND AND PURPOSE

Chimeric antigen receptor (CAR) T-cell therapy is potentially associated with treatment-related toxicities mainly consisting of cytokine release syndrome (CRS) and immune-effector cell-associated neurotoxicity syndrome (ICANS). We evaluated brain metabolic correlates of CRS with and without ICANS in diffuse large B-cell lymphoma patients treated with CAR-T.

METHODS

Twenty-one refractory DLCBLs underwent whole-body and brain [18 F]-fluorodeoxyglucose (FDG) PET before and 30 days after treatment with CAR-T. Five patients did not develop inflammatory-related side effects, 11 patients developed CRS, while in 5 patients CRS evolved in ICANS. Baseline and post-CAR-T brain FDG-PET were compared with a local controls dataset to identify hypometabolic patterns both at single-patient and group levels (p < .05 after correction for family-wise error [FWE). Metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were computed on baseline FDG-PET and compared between patients' subgroups (t-test).

RESULTS

ICANS showed an extended and bilateral hypometabolic pattern mainly involving the orbitofrontal cortex, frontal dorsolateral cortex, and anterior cingulate (p < .003 FWE-corrected). CRS without ICANS showed significant hypometabolism in less extended clusters mainly involving bilateral medial and lateral temporal lobes, posterior parietal lobes, anterior cingulate, and cerebellum (p < .002 FWE-corrected). When compared, ICANS showed a more prominent hypometabolism in the orbitofrontal and frontal dorsolateral cortex in both hemispheres than CRS (p < .002 FWE-corrected). Mean baseline MTV and TLG were significantly higher in ICANS than CRS (p < .02).

CONCLUSIONS

Patients with ICANS are characterized by a frontolateral hypometabolic signature coherently with the hypothesis of ICANS as a predominant frontal syndrome and with the more prominent susceptibility of frontal lobes to cytokine-induced inflammation.

Different associations between amyloid-βeta 42, amyloid-βeta 40, and amyloid-βeta 42/40 with soluble phosphorylated-tau and disease burden in Alzheimer's disease: a cerebrospinal fluid and fluorodeoxyglucose-positron emission tomography study

BACKGROUND

Despite the high sensitivity of cerebrospinal fluid (CSF) amyloid beta (Aβ)42 to detect amyloid pathology, the Aβ42/Aβ40 ratio (amyR) better estimates amyloid load, with higher specificity for Alzheimer's disease (AD). However, whether Aβ42 and amyR have different meanings and whether Aβ40 represents more than an Aβ42-corrective factor remain to be clarified. Our study aimed to compare the ability of Aβ42 and amyR to detect AD pathology in terms of p-tau/Aβ42 ratio and brain glucose metabolic patterns using fluorodeoxyglucose-positron emission tomography (FDG-PET).

METHODS

CSF biomarkers were analyzed with EUROIMMUN ELISA. We included 163 patients showing pathological CSF Aβ42 and normal p-tau (A + T -  = 98) or pathological p-tau levels (A + T +  = 65) and 36 control subjects (A - T -). A + T - patients were further stratified into those with normal (CSFAβ42 + /amyR -  = 46) and pathological amyR (CSFAβ42 + /amyR +  = 52). We used two distinct cut-offs to determine pathological values of p-tau/Aβ42: (1) ≥ 0.086 and (2) ≥ 0.122. FDG-PET patterns were evaluated in a subsample of patients (n = 46) and compared to 24 controls.

RESULTS

CSF Aβ40 levels were the lowest in A - T - and in CSFAβ42 + /amyR - , higher in CSFAβ42 + /amyR + and highest in A + T + (F = 50.75; p < 0.001), resembling CSF levels of p-tau (F = 192; p < 0.001). We found a positive association between Aβ40 and p-tau in A - T - (β = 0.58; p < 0.001), CSFAβ42 + /amyR - (β = 0.47; p < 0.001), and CSFAβ42 + /amyR + patients (β = 0.48; p < 0.001) but not in A + T + . Investigating biomarker changes as a function of amyR, we observed a weak variation in CSF p-tau (+ 2 z-scores) and Aβ40 (+ 0.8 z-scores) in the normal amyR range, becoming steeper over the pathological threshold of amyR (p-tau: + 5 z-scores, Aβ40: + 4.5 z-score). CSFAβ42 + /amyR + patients showed a significantly higher probability of having pathological p-tau/Aβ42 than CSFAβ42 + /amyR - (cut-off ≥ 0.086: OR 23.3; cut-off ≥ 0.122: OR 8.8), which however still showed pathological values of p-tau/Aβ42 in some cases (cut-off ≥ 0.086: 35.7%; cut-off ≥ 0.122: 17.3%) unlike A - T - . Accordingly, we found reduced FDG metabolism in the temporoparietal regions of CSFAβ42 + /amyR - compared to controls, and further reduction in frontal areas in CSFAβ42 + /amyR + , like in A + T + .

CONCLUSIONS

Pathological p-tau/Aβ42 and FDG hypometabolism typical of AD can be found in patients with decreased CSF Aβ42 levels alone. AmyR positivity, associated with higher Aβ40 levels, is accompanied by higher CSF p-tau and widespread FDG hypometabolism.

Cerebral electrometabolic coupling in disordered and normal states of consciousness

We assess cerebral integrity with cortical and subcortical FDG-PET and cortical electroencephalography (EEG) within the mesocircuit model framework in patients with disorders of consciousness (DoCs). The mesocircuit hypothesis proposes that subcortical activation facilitates cortical function. We find that the metabolic balance of subcortical mesocircuit areas is informative for diagnosis and is associated with four EEG-based power spectral density patterns, cortical metabolism, and α power in healthy controls and patients with a DoC. Last, regional electrometabolic coupling at the cortical level can be identified in the θ and α ranges, showing positive and negative relations with glucose uptake, respectively. This relation is inverted in patients with a DoC, potentially related to altered orchestration of neural activity, and may underlie suboptimal excitability states in patients with a DoC. By understanding the neurobiological basis of the pathophysiology underlying DoCs, we foresee translational value for diagnosis and treatment of patients with a DoC.

Metabolic Brain Changes Can Predict the Underlying Pathology in Neurodegenerative Brain Disorders: A Case Report of Sporadic Creutzfeldt-Jakob Disease with Concomitant Parkinson's Disease

The co-occurrence of multiple proteinopathies is being increasingly recognized in neurodegenerative disorders and poses a challenge in differential diagnosis and patient selection for clinical trials. Changes in brain metabolism captured by positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) allow us to differentiate between different neurodegenerative disorders either by visual exploration or by studying disease-specific metabolic networks in individual patients. However, the impact of multiple proteinopathies on brain metabolism and metabolic networks remains unknown due to the absence of pathological studies. In this case study, we present a 67-year-old patient with rapidly progressing dementia clinically diagnosed with probable sporadic Creutzfeldt-Jakob disease (sCJD). However, in addition to the expected pronounced cortical and subcortical hypometabolism characteristic of sCJD, the brain FDG PET revealed an intriguing finding of unexpected relative hypermetabolism in the bilateral putamina, raising suspicions of coexisting Parkinson's disease (PD). Additional investigation of disease-specific metabolic brain networks revealed elevated expression of both CJD-related pattern (CJDRP) and PD-related pattern (PDRP) networks. The patient eventually developed akinetic mutism and passed away seven weeks after symptom onset. Neuropathological examination confirmed neuropathological changes consistent with sCJD and the presence of Lewy bodies confirming PD pathology. Additionally, hyperphosphorylated tau and TDP-43 pathology were observed, a combination of four proteinopathies that had not been previously reported. Overall, this case provides valuable insights into the complex interplay of neurodegenerative pathologies and their impact on metabolic brain changes, emphasizing the role of metabolic brain imaging in evaluating potential presence of multiple proteinopathies.

Imaging Correlates between Headache and Breast Cancer: An [18F]FDG PET Study

This study aimed to examine brain metabolic patterns on [18F]Fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) in breast cancer (BC), comparing patients with tension-type headache (TTH), migraine (MiG), and those without headache. Further association with BC response to neoadjuvant chemotherapy (NAC) was explored. In this prospective study, BC patients eligible for NAC performed total-body [18F]FDG PET/CT with a dedicated brain scan. A voxel-wise analysis (two-sample t-test) and a multiple regression model were used to compare brain metabolic patterns among TTH, MiG, and no-headache patients and to correlate them with clinical covariates. A single-subject analysis compared each patient's brain uptake before and after NAC with a healthy control group. Primary headache was diagnosed in 39/46 of BC patients (39% TTH and 46% MiG). TTH patients exhibited hypometabolism in specific brain regions before NAC. TTH patients with a pathological complete response (pCR) to NAC showed hypermetabolic brain regions in the anterior medial frontal cortex. The correlation between tumor uptake and brain metabolism varied before and after NAC, suggesting an inverse relationship. Additionally, the single-subject analysis revealed that hypometabolic brain regions were not present after NAC. Primary headache, especially MiG, was associated with a better response to NAC. These findings suggest complex interactions between BC, headache, and hormonal status, warranting further investigation in larger prospective cohorts.

Diagnostic accuracy of cerebral [18F]FDG PET in atypical parkinsonism

BACKGROUND

Atypical parkinsonism (AP) often presents with Parkinson's symptoms but has a much worse long-term prognosis. The diagnosis is presently based on clinical criteria, but a cerebral positron emission tomography (PET) scan with [18F]fluoro-2-deoxy-2-D-glucose ([18F]FDG) may assist in the diagnosis of AP such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), and Lewy body dementia (DLB). Only few studies have evaluated the sensitivity and specificity of [18F]FDG PET for separating the diseases in a mixed patient population, which we aim to assess in a retrospective material.

RESULTS

We identified 156 patients referred for a cerebral [18F]FDG PET for suspicion of AP during 2017-2019. The [18F]FDG PET was analysed by a nuclear medicine specialist blinded to clinical information but with access to dopamine transporter imaging. The reference standard was the follow-up clinical diagnosis (follow-up: 6-72 months). The overall accuracy for correct classification was 74%. Classification sensitivity (95% confidence interval, CI) and specificity (95% CI) for MSA (n = 20) were 1.00 (0.83-1.00) and 0.91 (0.85-0.95), for DLB/Parkinson with dementia (PDD) (n = 26) were 0.81 (0.61-0.93) and 0.97 (0.92-0.99) and for CBD/PSP (n = 68) were 0.62 (0.49-0.73) and 0.97 (0.90-0.99).

CONCLUSIONS

Our results support the additional use of [18F]FDG PET for the clinical diagnosis of AP with moderate to high sensitivity and specificity. Use of [18F]FDG PET may be beneficial for prognosis and supportive treatment of the patients and useful for future clinical treatment trials.

A Systematic Review of Clinical Practice Guidelines for Alzheimer's Disease and Strategies for Future Advancements

INTRODUCTION

Alzheimer's disease (AD) is a disease continuum from pathophysiologic, biomarker and clinical perspectives. With the advent of advanced technologies, diagnosing and managing patients is evolving.

METHODS

A systematic literature review (SLR) of practice guidelines for mild cognitive impairment (MCI) and AD dementia was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This systematic literature review (SLR) aimed to summarize current clinical practice guidelines for screening, testing, diagnosis, treatment and monitoring in the AD continuum. The results of this SLR were used to propose a way forward for practice guidelines given the possible introduction of biomarker-guided technology using blood- or plasma-based assays and disease-modifying treatments (DMTs) targeted for early disease.

RESULTS

53 clinical practice guidelines were identified, 15 of which were published since 2018. Screening for asymptomatic populations was not recommended. Biomarker testing was not included in routine diagnostic practice. There was no consensus on which neurocognitive tests to use to diagnose and monitor MCI or AD dementia. Pharmacologic therapies were not recommended for MCI, while cholinesterase inhibitors and memantine were recommended for AD treatment.

DISCUSSION

The pre-2018 and post-2018 practice guidelines share similar recommendations for screening, diagnosis and treatment. However, once DMTs are approved, clinicians will require guidance on the appropriate use of DMTs in a clinical setting. This guidance should include strategies for identifying eligible patients and evaluating the DMT benefit-to-risk profile to facilitate shared decision-making among physicians, patients and care partners.

CONCLUSION

Regular evidence-based updates of existing guidelines for the AD continuum are required over the coming decades to integrate rapidly evolving technologic and medical scientific advances and bring emerging approaches for management of early disease into clinical practice. This will pave the way toward biomarker-guided identification and targeted treatment and the realization of precision medicine for AD.

Clinical validation of the cingulate island sign visual rating scale in dementia with Lewy bodies

INTRODUCTION

The cingulate island sign (CIS) is a metabolic pattern on [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography (PET) associated with dementia with Lewy bodies (DLB). The aim of this study was to validate the visual CIS rating scale (CISRs) for the diagnosis of DLB and to explore the clinical correlates.

METHODS

This single-center study included 166 DLB patients and 161 patients with Alzheimer's disease (AD). The CIS on [¹⁸F]FDG-PET scans was rated using the CISRs independently by three blinded raters.

RESULTS

The optimal cut-off to differentiate DLB from AD was a CISRs score ≥ 1 (sensitivity = 66%, specificity = 84%) whereas a CISRs score ≥ 2 (sensitivity = 58%, specificity = 92%) was optimal to differentiate amyloid positive DLB (n = 43 (82.7%)) and AD. To identify DLB with abnormal (n = 53 (72.6%)) versus normal (n = 20 (27.4%)) dopamine transporter imaging, a CISRs cut-off of 4 had a specificity of 95%. DLB with a CISRs score of 4 performed significantly better in tests on free verbal recall and picture based cued recall, but worse on processing speed compared to DLB with a CISRs score of 0.

CONCLUSION

This study confirms the CISRs as a valid marker for the diagnosis of DLB with a high specificity and a lower, but acceptable, sensitivity. Concomitant AD pathology does not influence diagnostic accuracy of the CISRs. In DLB patients, presence of CIS is associated with relative preserved memory function and impaired processing speed.

Metabolic patterns in brain 18F-fluorodeoxyglucose PET relate to aetiology in paediatric dystonia

There is a lack of imaging markers revealing the functional characteristics of different brain regions in paediatric dystonia. In this observational study, we assessed the utility of [18F]2-fluoro-2-deoxy-D-glucose (FDG)-PET in understanding dystonia pathophysiology by revealing specific resting awake brain glucose metabolism patterns in different childhood dystonia subgroups. PET scans from 267 children with dystonia being evaluated for possible deep brain stimulation surgery between September 2007 and February 2018 at Evelina London Children's Hospital (ELCH), UK, were examined. Scans without gross anatomical abnormality (e.g. large cysts, significant ventriculomegaly; n = 240) were analysed with Statistical Parametric Mapping (SPM12). Glucose metabolism patterns were examined in the 144/240 (60%) cases with the 10 commonest childhood-onset dystonias, focusing on nine anatomical regions. A group of 39 adult controls was used for comparisons. The genetic dystonias were associated with the following genes: TOR1A, THAP1, SGCE, KMT2B, HPRT1 (Lesch Nyhan disease), PANK2 and GCDH (Glutaric Aciduria type 1). The acquired cerebral palsy (CP) cases were divided into those related to prematurity (CP-Preterm), neonatal jaundice/kernicterus (CP-Kernicterus) and hypoxic-ischaemic encephalopathy (CP-Term). Each dystonia subgroup had distinct patterns of altered FDG-PET uptake. Focal glucose hypometabolism of the pallidi, putamina or both, was the commonest finding, except in PANK2, where basal ganglia metabolism appeared normal. HPRT1 uniquely showed glucose hypometabolism across all nine cerebral regions. Temporal lobe glucose hypometabolism was found in KMT2B, HPRT1 and CP-Kernicterus. Frontal lobe hypometabolism was found in SGCE, HPRT1 and PANK2. Thalamic and brainstem hypometabolism were seen only in HPRT1, CP-Preterm and CP-term dystonia cases. The combination of frontal and parietal lobe hypermetabolism was uniquely found in CP-term cases. PANK2 cases showed a distinct combination of parietal hypermetabolism with cerebellar hypometabolism but intact putaminal-pallidal glucose metabolism. HPRT1, PANK2, CP-kernicterus and CP-preterm cases had cerebellar and insula glucose hypometabolism as well as parietal glucose hypermetabolism. The study findings offer insights into the pathophysiology of dystonia and support the network theory for dystonia pathogenesis. 'Signature' patterns for each dystonia subgroup could be a useful biomarker to guide differential diagnosis and inform personalized management strategies.

Prognosis of consciousness disorders in the intensive care unit

Assessments of consciousness are a critical part of prognostic algorithms for critically ill patients suffering from severe brain injuries. There have been significant advances in the field of coma science over the past two decades, providing clinicians with more advanced and precise tools for diagnosing and prognosticating disorders of consciousness (DoC). Advanced neuroimaging and electrophysiological techniques have vastly expanded our understanding of the biological mechanisms underlying consciousness, and have helped identify new states of consciousness. One of these, termed cognitive motor dissociation, can predict functional recovery at 1 year post brain injury, and is present in up to 15-20% of patients with DoC. In this chapter, we review several tools that are used to predict DoC, describing their strengths and limitations, from the neurological examination to advanced imaging and electrophysiologic techniques. We also describe multimodal assessment paradigms that can be used to identify covert consciousness and thus help recognize patients with the potential for future recovery and improve our prognostication practices.