Fluorodeoxyglucose PET in Neurology and Psychiatry

Improving 18F-FDG PET Quantification Through a Spatial Normalization Method

Quantification of 18F-FDG PET images is useful for accurate diagnosis and evaluation of various brain diseases, including brain tumors, epilepsy, dementia, and Parkinson disease. However, accurate quantification of 18F-FDG PET images requires matched 3-dimensional T1 MRI scans of the same individuals to provide detailed information on brain anatomy. In this paper, we propose a transfer learning approach to adapt a pretrained deep neural network model from amyloid PET to spatially normalize 18F-FDG PET images without the need for 3-dimensional MRI. Methods: The proposed method is based on a deep learning model for automatic spatial normalization of 18F-FDG brain PET images, which was developed by fine-tuning a pretrained model for amyloid PET using only 103 18F-FDG PET and MR images. After training, the algorithm was tested on 65 internal and 78 external test sets. All T1 MR images with a 1-mm isotropic voxel size were processed with FreeSurfer software to provide cortical segmentation maps used to extract a ground-truth regional SUV ratio using cerebellar gray matter as a reference region. These values were compared with those from spatial normalization-based quantification methods using the proposed method and statistical parametric mapping software. Results: The proposed method showed superior spatial normalization compared with statistical parametric mapping, as evidenced by increased normalized mutual information and better size and shape matching in PET images. Quantitative evaluation revealed a consistently higher SUV ratio correlation and intraclass correlation coefficients for the proposed method across various brain regions in both internal and external datasets. The remarkably good correlation and intraclass correlation coefficient values of the proposed method for the external dataset are noteworthy, considering the dataset's different ethnic distribution and the use of different PET scanners and image reconstruction algorithms. Conclusion: This study successfully applied transfer learning to a deep neural network for 18F-FDG PET spatial normalization, demonstrating its resource efficiency and improved performance. This highlights the efficacy of transfer learning, which requires a smaller number of datasets than does the original network training, thus increasing the potential for broader use of deep learning-based brain PET spatial normalization techniques for various clinical and research radiotracers.

PET-MRI Applications and Future Prospects in Psychiatry

This article reviews the synergistic application of positron emission tomography-magnetic resonance imaging (PET-MRI) in neuroscience with relevance for psychiatry, particularly examining neurotransmission, epigenetics, and dynamic imaging methodologies. We begin by discussing the complementary insights that PET and MRI modalities provide into neuroreceptor systems, with a focus on dopamine, opioids, and serotonin receptors, and their implications for understanding and treating psychiatric disorders. We further highlight recent PET-MRI studies using a radioligand that enables the quantification of epigenetic enzymes, specifically histone deacetylases, in the brain in vivo. Imaging epigenetics is used to exemplify the impact the quantification of novel molecular targets may have, including new treatment approaches for psychiatric disorders. Finally, we discuss innovative designs involving functional PET using [18F]FDG (fPET-FDG), which provides detailed information regarding dynamic changes in glucose metabolism. Concurrent acquisitions of fPET-FDG and functional MRI provide a time-resolved approach to studying brain function, yielding simultaneous metabolic and hemodynamic information and thereby opening new avenues for psychiatric research. Collectively, the review underscores the potential of a multimodal PET-MRI approach to advance our understanding of brain structure and function in health and disease, which could improve clinical care based on objective neurobiological features and treatment response monitoring. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Depth-encoding using optical photon TOF in a prism-PET detector with tapered crystals

BACKGROUND

High-resolution brain positron emission tomography (PET) scanner is emerging as a significant and transformative non-invasive neuroimaging tool to advance neuroscience research as well as improve diagnosis and treatment in neurology and psychiatry. Time-of-flight (TOF) and depth-of-interaction (DOI) information provide markedly higher PET imaging performance by increasing image signal-to-noise ratio and mitigating spatial resolution degradation due to parallax error, respectively. PET detector modules that utilize light sharing can inherently carry DOI information from the multiple timestamps that are generated per gamma event. The difference between two timestamps that are triggered by scintillation photons traveling in opposite directions signifies the event's depth-dependent optical photon TOF (oTOF). However, light leak at the crystal-readout interface substantially degrades the resolution of this oTOF-based depth encoding.

PURPOSE

We demonstrate the feasibility of oTOF-based depth encoding by mitigating light leak in single-ended-readout Prism-PET detector modules using tapered crystals. Minimizing light leak also improved both energy-based DOI and coincidence timing resolutions.

METHODS

The tapered Prism-PET module consists of a 16  × $\times$  16 array of 1.5  × $\times$  1.5  × $\times$  20 mm 3 ${\rm {mm}}^3$ lutetium yttrium oxyorthosillicate (LYSO) crystals, which are tapered down to 1.2  × $\times$  1.2 mm 2 ${\rm {mm}}^2$ at the crystal-readout interface. The LYSO array couples 4-to-1 to an 8  × $\times$  8 array of 3  × $\times$  3 mm 2 ${\rm {mm}}^2$ silicon photomultiplier (SiPM) pixels on the tapered end and to a segmented prismatoid light guide array on the opposite end. Performance of tapered and non-tapered Prism-PET detectors was experimentally characterized and evaluated by measuring flood histogram, energy resolution, energy-, and oTOF-based DOI resolutions, and coincidence timing resolution. Sensitivities of scanners using different Prism-PET detector designs were simulated using Geant4 application for tomographic emission (GATE).

RESULTS

For the tapered (non-tapered) Prism-PET module, the measured full width at half maximum (FWHM) energy, timing, energy-based DOI, and oTOF-based DOI resolutions were 8.88 (11.18)%, 243 (286) ps, 2.35 (3.18) mm, and 5.42 (13.87) mm, respectively. The scanner sensitivities using non-tapered and tapered crystals, and 10 rings of detector modules, were simulated to be 30.9 and 29.5 kcps/MBq, respectively.

CONCLUSIONS

The tapered Prism-PET module with minimized light leak enabled the first experimental report of oTOF-based depth encoding at the detector module level. It also enabled the utilization of thinner (i.e., 0.1 mm) inter-crystal spacing with barium sulfate as the reflector while also improving energy-based DOI and timing resolutions.

Quasi-supervised learning for super-resolution PET

Low resolution of positron emission tomography (PET) limits its diagnostic performance. Deep learning has been successfully applied to achieve super-resolution PET. However, commonly used supervised learning methods in this context require many pairs of low- and high-resolution (LR and HR) PET images. Although unsupervised learning utilizes unpaired images, the results are not as good as that obtained with supervised deep learning. In this paper, we propose a quasi-supervised learning method, which is a new type of weakly-supervised learning methods, to recover HR PET images from LR counterparts by leveraging similarity between unpaired LR and HR image patches. Specifically, LR image patches are taken from a patient as inputs, while the most similar HR patches from other patients are found as labels. The similarity between the matched HR and LR patches serves as a prior for network construction. Our proposed method can be implemented by designing a new network or modifying an existing network. As an example in this study, we have modified the cycle-consistent generative adversarial network (CycleGAN) for super-resolution PET. Our numerical and experimental results qualitatively and quantitatively show the merits of our method relative to the state-of-the-art methods. The code is publicly available at https://github.com/PigYang-ops/CycleGAN-QSDL.

OIF-Net: An Optical Flow Registration-Based PET/MR Cross-Modal Interactive Fusion Network for Low-Count Brain PET Image Denoising

The short frames of low-count positron emission tomography (PET) images generally cause high levels of statistical noise. Thus, improving the quality of low-count images by using image postprocessing algorithms to achieve better clinical diagnoses has attracted widespread attention in the medical imaging community. Most existing deep learning-based low-count PET image enhancement methods have achieved satisfying results, however, few of them focus on denoising low-count PET images with the magnetic resonance (MR) image modality as guidance. The prior context features contained in MR images can provide abundant and complementary information for single low-count PET image denoising, especially in ultralow-count (2.5%) cases. To this end, we propose a novel two-stream dual PET/MR cross-modal interactive fusion network with an optical flow pre-alignment module, namely, OIF-Net. Specifically, the learnable optical flow registration module enables the spatial manipulation of MR imaging inputs within the network without any extra training supervision. Registered MR images fundamentally solve the problem of feature misalignment in the multimodal fusion stage, which greatly benefits the subsequent denoising process. In addition, we design a spatial-channel feature enhancement module (SC-FEM) that considers the interactive impacts of multiple modalities and provides additional information flexibility in both the spatial and channel dimensions. Furthermore, instead of simply concatenating two extracted features from these two modalities as an intermediate fusion method, the proposed cross-modal feature fusion module (CM-FFM) adopts cross-attention at multiple feature levels and greatly improves the two modalities' feature fusion procedure. Extensive experimental assessments conducted on real clinical datasets, as well as an independent clinical testing dataset, demonstrate that the proposed OIF-Net outperforms the state-of-the-art methods.

Simultaneous estimation of a model-derived input function for quantifying cerebral glucose metabolism with [18F]FDG PET

BACKGROUND

Quantification of the cerebral metabolic rate of glucose (CMRGlu) by dynamic [18F]FDG PET requires invasive arterial sampling. Alternatives to using an arterial input function (AIF) include the simultaneous estimation (SIME) approach, which models the image-derived input function (IDIF) by a series of exponentials with coefficients obtained by fitting time activity curves (TACs) from multiple volumes-of-interest. A limitation of SIME is the assumption that the input function can be modelled accurately by a series of exponentials. Alternatively, we propose a SIME approach based on the two-tissue compartment model to extract a high signal-to-noise ratio (SNR) model-derived input function (MDIF) from the whole-brain TAC. The purpose of this study is to present the MDIF approach and its implementation in the analysis of animal and human data.

METHODS

Simulations were performed to assess the accuracy of the MDIF approach. Animal experiments were conducted to compare derived MDIFs to measured AIFs (n = 5). Using dynamic [18F]FDG PET data from neurologically healthy volunteers (n = 18), the MDIF method was compared to the original SIME-IDIF. Lastly, the feasibility of extracting parametric images was investigated by implementing a variational Bayesian parameter estimation approach.

RESULTS

Simulations demonstrated that the MDIF can be accurately extracted from a whole-brain TAC. Good agreement between MDIFs and measured AIFs was found in the animal experiments. Similarly, the MDIF-to-IDIF area-under-the-curve ratio from the human data was 1.02 ± 0.08, resulting in good agreement in grey matter CMRGlu: 24.5 ± 3.6 and 23.9 ± 3.2 mL/100 g/min for MDIF and IDIF, respectively. The MDIF method proved superior in characterizing the first pass of [18F]FDG. Groupwise parametric images obtained with the MDIF showed the expected spatial patterns.

CONCLUSIONS

A model-driven SIME method was proposed to derive high SNR input functions. Its potential was demonstrated by the good agreement between MDIFs and AIFs in animal experiments. In addition, CMRGlu estimates obtained in the human study agreed to literature values. The MDIF approach requires fewer fitting parameters than the original SIME method and has the advantage that it can model the shape of any input function. In turn, the high SNR of the MDIFs has the potential to facilitate the extraction of voxelwise parameters when combined with robust parameter estimation methods such as the variational Bayesian approach.

Transforming Neurology and Psychiatry: Organ-specific PET Instrumentation and Clinical Applications

PET technology has immense potential for furthering understanding of the brain and associated disorders, including advancements in high-resolution tomographs and hybrid imaging modalities. Novel radiotracers targeting specific neurotransmitter systems and molecular markers provide opportunities to unveil intricate mechanisms underlying neurologic and psychiatric conditions. As PET imaging techniques and analysis methods continue to be refined, the field is poised to make significant contributions to personalized medicine for more targeted and effective interventions. PET instrumentation has advanced the fields of neurology and psychiatry, providing insights into pathophysiology and development of effective treatments.

Semiquantitative analysis of cerebral [18F]FDG-PET uptake in pediatric patients

BACKGROUND

Glycolytic metabolism in the brain of pediatric patients, imaged with [18F]  fluorodeoxyglucose-positron emission tomography (FDG-PET) is incompletely characterized.

OBJECTIVE

The purpose of the current study was to characterize [18F]FDG-PET brain uptake in a large sample of pediatric patients with non-central nervous system diseases as an alternative to healthy subjects to evaluate changes at different pediatric ages.

MATERIALS AND METHODS

Seven hundred ninety-five [18F]FDG-PET examinations from children < 18 years of age without central nervous system diseases were included. Each brain image was spatially normalized, and the standardized uptake value (SUV) was obtained. The SUV and the SUV relative to different pseudo-references were explored as a function of age.

RESULTS

At all evaluated ages, the occipital lobe showed the highest [18F]FDG uptake (0.27 ± 0.04 SUV/year), while the parietal lobe and brainstem had the lowest uptake (0.17 ± 0.02 SUV/year, for both regions). An increase [18F]FDG uptake was found for all brain regions until 12 years old, while no significant uptake differences were found between ages 13 (SUV = 5.39) to 17 years old (SUV = 5.52) (P < 0.0001 for the whole brain). A sex dependence was found in the SUVmean for the whole brain during adolescence (SUV 5.04-5.25 for males, 5.68-5.74 for females, P = 0.0264). Asymmetries in [18F]FDG uptake were found in the temporal and central regions during infancy.

CONCLUSIONS

Brain glycolytic metabolism of [18F]FDG, measured through the SUVmean, increased with age until early adolescence (< 13 years old), showing differences across brain regions. Age, sex, and brain region influence [18F]FDG uptake, with significant hemispheric asymmetries for temporal and central regions.

Single subanesthetic dose of ketamine produces delayed impact on brain [18F]FDG PET imaging and metabolic connectivity in rats

Introduction

Ketamine, a glutamate NMDA receptor antagonist, is suggested to act very rapidly and durably on the depressive symptoms including treatment-resistant patients but its mechanisms of action remain unclear. There is a requirement for non-invasive biomarkers, such as imaging techniques, which hold promise in monitoring and elucidating its therapeutic impact.

Methods

We explored the glucose metabolism with [¹⁸F]FDG positron emission tomography (PET) in ten male rats in a longitudinal study designed to compare imaging patterns immediately after acute subanaesthetic ketamine injection (i.p. 10 mg/kg) with its sustained effects, 5 days later. Changes in [¹⁸F]FDG uptake following ketamine administration were estimated using a voxel-based analysis with SPM12 software, and a region of interest (ROI) analysis. A metabolic connectivity analysis was also conducted to estimate the immediate and delayed effects of ketamine on the inter-individual metabolic covariance between the ROIs.

Results

No significant difference was observed in brain glucose metabolism immediately following acute subanaesthetic ketamine injection. However, a significant decrease of glucose uptake appeared 5 days later, reflecting a sustained and delayed effect of ketamine in the frontal and the cingulate cortex. An increase in the raphe, caudate and cerebellum was also measured. Moreover, metabolic connectivity analyses revealed a significant decrease between the hippocampus and the thalamus at day 5 compared to the baseline.

Discussion

This study showed that the differences in metabolic profiles appeared belatedly, 5 days after ketamine administration, particularly in the cortical regions. Finally, this methodology will help to characterize the effects of future molecules for the treatment of treatment resistant depression.

Prediction of voluntary movements of the upper extremities by resting state-brain regional glucose metabolism in patients with chronic severe brain injury: A pilot study

Confirmation of the exact voluntary movements of patients with disorder of consciousness following severe traumatic brain injury (TBI) is difficult because of the associated communication disturbances. In this pilot study, we investigated whether regional brain glucose metabolism assessed by ¹⁸ F-fluorodeoxyglucose positron emission tomography (FDG-PET) at rest could predict voluntary movement in severe TBI patients, particularly those with sufficient upper limb capacity to use communication devices. We visually and verbally instructed patients to clasp or open their hands. After video capture, three independent rehabilitation therapists determined whether the patients' movements were voluntary or involuntary. The results were compared with the standardized uptake value in the primary motor cortex, referring to the Penfield's homunculus, by resting state by FDG-PET imaged 1 year prior. Results showed that glucose uptake in the left (p = 0.0015) and right (p = 0.0121) proximal limb of the primary motor cortex, based on Penfield's homunculus on cerebral cartography, may reflect contralateral voluntary movement. Receiver operating characteristic curve analysis showed that a mean cutoff standardized uptake value of 5.47 ± 0.08 provided the best sensitivity and specificity for differentiating between voluntary and involuntary movements in each area. FDG-PET may be a useful and robust biomarker for predicting long-term recovery of motor function in severe TBI patients with disorders of consciousness.

Evaluation of advanced, pathophysiologic new targets for imaging of CNS

The inadequate information about the in vivo pathological, physiological, and neurological impairments, as well as the absence of in vivo tools for assessing brain penetrance and the efficiency of newly designed drugs, has hampered the development of new techniques for the treatment for variety of new central nervous system (CNS) diseases. The searching sites such as Science Direct and PubMed were used to find out the numerous distinct tracers across 16 CNS targets including tau, synaptic vesicle glycoprotein, the adenosine 2A receptor, the phosphodiesterase enzyme PDE10A, and the purinoceptor, among others. Among the most encouraging are [¹⁸ F]FIMX for mGluR imaging, [¹¹ C]Martinostat for Histone deacetylase, [¹⁸ F]MNI-444 for adenosine 2A imaging, [¹¹ C]ER176 for translocator protein, and [¹⁸ F]MK-6240 for tau imaging. We also reviewed the findings for each tracer's features and potential for application in CNS pathophysiology and therapeutic evaluation investigations, including target specificity, binding efficacy, and pharmacokinetic factors. This review aims to present a current evaluation of modern positron emission tomography tracers for CNS targets, with a focus on recent advances for targets that have newly emerged for imaging in humans.

Diagnosis of Alzheimer’s disease: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology

ABSTRACT This paper presents the consensus of the Scientific Department of Cognitive Neurology and Aging from the Brazilian Academy of Neurology on the diagnostic criteria for Alzheimer’s disease (AD) in Brazil. The authors conducted a literature review regarding clinical and research criteria for AD diagnosis and proposed protocols for use at primary, secondary, and tertiary care levels. Within this clinical scenario, the diagnostic criteria for typical and atypical AD are presented as well as clinical, cognitive, and functional assessment tools and complementary propaedeutics with laboratory and neuroimaging tests. The use of biomarkers is also discussed for both clinical diagnosis (in specific conditions) and research.

Virtual high-count PET image generation using a deep learning method

PURPOSE

Recently, deep learning-based methods have been established to denoise the low-count positron emission tomography (PET) images and predict their standard-count image counterparts, which could achieve reduction of injected dosage and scan time, and improve image quality for equivalent lesion detectability and clinical diagnosis. In clinical settings, the majority scans are still acquired using standard injection dose with standard scan time. In this work, we applied a 3D U-Net network to reduce the noise of standard-count PET images to obtain the virtual-high-count (VHC) PET images for identifying the potential benefits of the obtained VHC PET images.

METHODS

The training datasets, including down-sampled standard-count PET images as the network input and high-count images as the desired network output, were derived from 27 whole-body PET datasets, which were acquired using 90-min dynamic scan. The down-sampled standard-count PET images were rebinned with matched noise level of 195 clinical static PET datasets, by matching the normalized standard derivation (NSTD) inside 3D liver region of interests (ROIs). Cross-validation was performed on 27 PET datasets. Normalized mean square error (NMSE), peak signal to noise ratio (PSNR), structural similarity index (SSIM), and standard uptake value (SUV) bias of lesions were used for evaluation on standard-count and VHC PET images, with real-high-count PET image of 90 min as the gold standard. In addition, the network trained with 27 dynamic PET datasets was applied to 195 clinical static datasets to obtain VHC PET images. The NSTD and mean/max SUV of hypermetabolic lesions in standard-count and VHC PET images were evaluated. Three experienced nuclear medicine physicians evaluated the overall image quality of randomly selected 50 out of 195 patients' standard-count and VHC images and conducted 5-score ranking. A Wilcoxon signed-rank test was used to compare differences in the grading of standard-count and VHC images.

RESULTS

The cross-validation results showed that VHC PET images had improved quantitative metrics scores than the standard-count PET images. The mean/max SUVs of 35 lesions in the standard-count and true-high-count PET images did not show significantly statistical difference. Similarly, the mean/max SUVs of VHC and true-high-count PET images did not show significantly statistical difference. For the 195 clinical data, the VHC PET images had a significantly lower NSTD than the standard-count images. The mean/max SUVs of 215 hypermetabolic lesions in the VHC and standard-count images showed no statistically significant difference. In the image quality evaluation by three experienced nuclear medicine physicians, standard-count images and VHC images received scores with mean and standard deviation of 3.34±0.80 and 4.26 ± 0.72 from Physician 1, 3.02 ± 0.87 and 3.96 ± 0.73 from Physician 2, and 3.74 ± 1.10 and 4.58 ± 0.57 from Physician 3, respectively. The VHC images were consistently ranked higher than the standard-count images. The Wilcoxon signed-rank test also indicated that the image quality evaluation between standard-count and VHC images had significant difference.

CONCLUSIONS

A DL method was proposed to convert the standard-count images to the VHC images. The VHC images had reduced noise level. No significant difference in mean/max SUV to the standard-count images was observed. VHC images improved image quality for better lesion detectability and clinical diagnosis.

Diagnosis of Alzheimer's disease: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology

This paper presents the consensus of the Scientific Department of Cognitive Neurology and Aging from the Brazilian Academy of Neurology on the diagnostic criteria for Alzheimer's disease (AD) in Brazil. The authors conducted a literature review regarding clinical and research criteria for AD diagnosis and proposed protocols for use at primary, secondary, and tertiary care levels. Within this clinical scenario, the diagnostic criteria for typical and atypical AD are presented as well as clinical, cognitive, and functional assessment tools and complementary propaedeutics with laboratory and neuroimaging tests. The use of biomarkers is also discussed for both clinical diagnosis (in specific conditions) and research.

[18 F]FDG brain uptake of C57Bl/6 male mice is affected by locomotor activity after cocaine use: A small animal positron emission tomography study

We verified if cocaine-induced peripheral activation might disrupt [¹⁸ F]FDG brain uptake after a cocaine challenge and suggested an optimal protocol to measure cocaine-induced brain metabolic alterations in mice. C57Bl/6 male mice were injected with [¹⁸ F]FDG and randomly separated into three groups. Groups 1 and 2 were kept conscious after [¹⁸ F]FDG administration and after 5 min received saline or cocaine (20 mg/kg). The animals in group 1 (n = 5) were then evaluated in the open field for 30 min and those from group 2 (n = 6) were kept alone in a home cage for the same period. Forty-five minutes after [¹⁸ F]FDG administration, images were acquired for 30 min. Group 3 (n = 6) was kept anesthetized and image acquisition started immediately after tracer injection, for 75 min. Saline (Day 1) or cocaine (Day 2) was injected 5 min after starting acquisition. Another set of animals (n = 5) were treated with cocaine every other day for 10 days or saline (n = 6) and were scanned with the dynamic protocol to verify its efficacy. [¹⁸ F]FDG uptake increased after cocaine administration when compared to baseline only in animals kept under anesthesia. No brain effect of cocaine was observed in animals submitted to the open field or kept in the home cage. The use of anesthesia is essential to visualize cocaine-induced changes in brain metabolism by [¹⁸ F]FDG PET, providing an interesting preclinical approach to investigate naïve subjects and enabling a bidirectional translational science approach for better understanding of cocaine use disorder.

Connectivity and Patterns of Regional Cerebral Blood Flow, Cerebral Glucose Uptake, and Aβ-Amyloid Deposition in Alzheimer's Disease (Early and Late-Onset) Compared to Normal Ageing

PURPOSE

The aim of this study was to investigate the differences in early (EOAD) and late (LOAD) onset of Alzheimer´s disease, as well as glucose uptake, regional cerebral blood flow (R1), amyloid depositions, and functional brain connectivity between normal young (YC) and Old Controls (OC).

METHODOLOGY

The study included 22 YC (37 ± 5 y), 22 OC (73 ± 5.9 y), 18 patients with EOAD (63 ± 9.5 y), and 18 with LOAD (70.6 ± 7.1 y). Patients underwent FDG and PIB PET/CT. R1 images were obtained from the compartmental analysis of the dynamic PIB acquisitions. Images were analyzed by a voxel-wise and a VOI-based approach. Functional connectivity was studied from the R1 and glucose uptake images.

RESULTS

OC had a significant reduction of R1 and glucose uptake compared to YC, predominantly at the dorsolateral and mesial frontal cortex. EOAD and LOAD vs. OC showed a decreased R1 and glucose uptake at the posterior parietal cortex, precuneus, and posterior cingulum. EOAD vs. LOAD showed a reduction in glucose uptake and R1 at the occipital and parietal cortex and an increased at the mesial frontal and temporal cortex. There was a mild increase in an amyloid deposition at the frontal cortex in LOAD vs. EOAD. YC presented higher connectivity than OC in R1 but lower connectivity considering glucose uptake. Moreover, EOAD and LOAD showed a decreased connectivity compared to controls that were more pronounced in glucose uptake than R1.

CONCLUSION

Our results demonstrated differences in amyloid deposition and functional imaging between groups and a differential pattern of functional connectivity in R1 and glucose uptake in each clinical condition. These findings provide new insights into the pathophysiological processes of AD and may have an impact on patient diagnostic evaluation.

Voxel-Based Analysis of [18F]-FDG Brain PET in Rats Using Data-Driven Normalization

Introduction: [18F]-FDG PET is a widely used imaging modality that visualizes cellular glucose uptake and provides functional information on the metabolic state of different tissues in vivo. Various quantification methods can be used to evaluate glucose metabolism in the brain, including the cerebral metabolic rate of glucose (CMR_glc) and standard uptake values (SUVs). Especially in the brain, these (semi-)quantitative measures can be affected by several physiological factors, such as blood glucose level, age, gender, and stress. Next to this inter- and intra-subject variability, the use of different PET acquisition protocols across studies has created a need for the standardization and harmonization of brain PET evaluation. In this study we present a framework for statistical voxel-based analysis of glucose uptake in the rat brain using histogram-based intensity normalization.

Methods: [18F]-FDG PET images of 28 normal rat brains were coregistered and voxel-wisely averaged. Ratio images were generated by voxel-wisely dividing each of these images with the group average. The most prevalent value in the ratio image was used as normalization factor. The normalized PET images were voxel-wisely averaged to generate a normal rat brain atlas. The variability of voxel intensities across the normalized PET images was compared to images that were either normalized by whole brain normalization, or not normalized.

To illustrate the added value of this normal rat brain atlas, 9 animals with a striatal hemorrhagic lesion and 9 control animals were intravenously injected with [18F]-FDG and the PET images of these animals were voxel-wisely compared to the normal atlas by group- and individual analyses.

Results: The average coefficient of variation of the voxel intensities in the brain across normal [18F]-FDG PET images was 6.7% for the histogram-based normalized images, 11.6% for whole brain normalized images, and 31.2% when no normalization was applied. Statistical voxel-based analysis, using the normal template, indicated regions of significantly decreased glucose uptake at the site of the ICH lesion in the ICH animals, but not in control animals.

Conclusion: In summary, histogram-based intensity normalization of [18F]-FDG uptake in the brain is a suitable data-driven approach for standardized voxel-based comparison of brain PET images.

Crossed cerebellar diaschisis on 18F-FDG PET: Frequency across neurodegenerative syndromes and association with 11C-PIB and 18F-Flortaucipir

We used 18F-FDG-PET to investigate the frequency of crossed cerebellar diaschisis (CCD) in 197 patients with various syndromes associated with neurodegenerative diseases. In a subset of 117 patients, we studied relationships between CCD and cortical asymmetry of Alzheimer's pathology (β-amyloid (11C-PIB) and tau (18F-Flortaucipir)). PET images were processed using MRIs to derive parametric SUVR images and define regions of interest. Indices of asymmetry were calculated in the cerebral cortex, basal ganglia and cerebellar cortex. Across all patients, cerebellar 18F-FDG asymmetry was associated with reverse asymmetry of 18F-FDG in the cerebral cortex (especially frontal and parietal areas) and basal ganglia. Based on our operational definition (cerebellar asymmetry >3% with contralateral supratentorial hypometabolism), significant CCD was present in 47/197 (24%) patients and was most frequent in corticobasal syndrome and semantic and logopenic variants of primary progressive aphasia. In β-amyloid-positive patients, mediation analyses showed that 18F-Flortaucipir cortical asymmetry was associated with cerebellar 18F-FDG asymmetry, but that cortical 18F-FDG asymmetry mediated this relationship. Analysis of 18F-FDG-SUVR values suggested that CCD might also occur in the absence of frank cerebellar 18F-FDG asymmetry due to symmetrical supratentorial degeneration resulting in a bilateral diaschisis process.

Cortical metabolic and structural differences in patients with chronic migraine. An exploratory 18FDG-PET and MRI study

Background

To describe interictal brain structural and metabolic differences between patients with episodic migraine (EM), chronic migraine (CM) and healthy controls (HC).

Methods

This is an exploratory study including right-handed age-matched women with EM, CM and HC. On the same day, a sequential interictal scan was performed with ¹⁸FDG-PET and MRI. 3D T1-weighted images were segmented with FreeSurfer, normalized to a reference atlas and the mean values of metabolism, cortical thickness (CTh) and local gyrification index (IGI) were determined. Groups were compared using age-adjusted linear models, corrected for multiple comparisons. ¹⁸FDG-PET measurements between groups were also analysed adjusting by patient’s age, CTh and lGI. The variables independently associated with diagnosis were obtained using a logistic regression analysis.

Results

Fifteen patients (8 EM, 7 CM) and 11 HC were included. Morphometric data showed an increased CTh in 6 frontal areas (L/R-Caudal Middle Frontal, L/R-Rostral Middle Frontal, L-Medial Orbitofrontal and L-Superior Frontal) in CM patients compared to HC without differences for IGI. The structural adjusted analysis in CM showed a statistically significantly hypometabolism in 9 frontal areas (L-Lateral Orbitofrontal, L/R-Medial Orbitofrontal, L-Frontal Superior, R-Frontal pole, R-Parts Triangularis, L/R-Paracentral and R-Precentral) and 7 temporal areas (L/R-Insula, L/R-Inferior temporal, L/R-Temporal pole and R-Banks superior temporal sulcus) compared to HC. EM patients presented intermediate metabolic values ​​between EM and HC (non-significant).

Conclusions

CM patients showed frontotemporal hypometabolism and increased frontal cortical thickness when compared to HC that may explain some cognitive and behavioural pain-processing and sensory integration alterations in CM patients. Combined information from sequential or simultaneous PET and MRI could optimize the study of complex functional neurological disorders such as migraine.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10194-021-01289-5.

Brain SPECT as a Biomarker of Neurodegeneration in Dementia in the Era of Molecular Imaging: Still a Valid Option?

Biomarkers are playing a progressively leading role in both clinical practice and scientific research in dementia. Although amyloid and tau biomarkers have gained ground in the clinical community in recent years, neurodegeneration biomarkers continue to play a key role due to their ability to identify different patterns of brain involvement that sign the transition between asymptomatic and symptomatic stages of the disease with high sensitivity and specificity. Both ¹⁸F-FDG positron emission tomography (PET) and perfusion single photon emission computed tomography (SPECT) have proved useful to reveal the functional alterations underlying various neurodegenerative diseases. Although the focus of nuclear neuroimaging has shifted to PET, the lower cost and wider availability of SPECT make it a still valid alternative for the study of patients with dementia. This review discusses the principles of both techniques, compares their diagnostic performance for the diagnosis of neurodegenerative diseases and highlights the role of SPECT to characterize patients from low- and middle-income countries, where special care of additional costs is particularly needed to meet the new recommendations for the diagnosis and characterization of patients with dementia.

Clinical Impact of PET With 18F-FDG and 11C-PIB in Patients With Dementia in a Developing Country

Introduction: The objective of this study was to evaluate the clinical impact PET with ¹⁸F-FDG and ¹¹C-PIB in patients with dementia in a developing country.

Methodology: Retrospective study of the patients referred for the evaluation of dementia to the only PET center in Uruguay. A total of 248 patients were identified, from which 70 patients were included based on the availability of medical history and clinical follow-up. Main outcomes included change in diagnosis, diagnostic dilemma and AD treatment. We evaluated the association of clinical outcomes with PET concordance with baseline diagnosis, diagnostic dilemma, level of education, AD pathology/Non-AD pathology (AD/Non-AD), baseline diagnosis and ¹¹C-PIB PET result.

Results: Baseline clinical diagnosis was concordant with ¹⁸F-FDG and ¹¹C-PIB PET results in 64.7 and 77.1% of the patients, respectively. Change in diagnosis after PET was identified in 30.0% of the patients and was associated with discordant ¹⁸F-FDG (p = 0.002) and ¹¹C-PIB (p < 0.001) PET results, previous diagnostic dilemma (p = 0.005), low education (p = 0.027), Non-AD baseline diagnosis (p = 0.027), and negative ¹¹C-PIB PET result (p < 0.001). Only the last variable remained significant in the multivariate analysis (adjusted p = 0.038). Diagnostic dilemma decreased after PET from 15.7 to 7.1% (p = 0.11) and was associated with Non-AD diagnosis (p = 0.002) and negative ¹¹C-PIB PET result (p = 0.003). Change in AD treatment after PET occurred in 45.7% of the patients.

Conclusion:¹⁸F-FDG and ¹¹C-PIB PET had a significant clinical impact in terms of change in diagnosis and treatment in patients with dementia in a developing country, similar to that reported in high-income countries.

Cerebral glucose metabolism in bipolar disorder: A voxel-based meta-analysis of positron emission tomography studies

BACKGROUND

Previous positron emission tomography studies have reported the changes of cerebral glucose metabolism in bipolar disorder. However, the findings across studies remain controversial, containing differing results.

METHODS

A systematic literature search of the PubMed, Embase, Cochrane Library, and Web of Science databases was conducted. We conducted a voxel-wide meta-analysis of cerebral glucose metabolism studies, using the seed-based mapping approach, in patients with bipolar disorder (BD).

RESULTS

We identified 7 studies suitable for inclusion, which included a total of 126 individuals with BD and 160 healthy controls. The most consistent and robust findings were an increase in cerebral glucose metabolism in the right precentral gyrus and a decrease in the left superior temporal gyrus, left middle temporal gyrus, and cerebellum. Additionally, the sex distribution and illness duration had significant moderating effects on cerebral glucose metabolism alterations.

CONCLUSIONS

Cerebral glucose metabolism alterations in these brain regions are likely to reflect the disease-related functional abnormalities such as emotion and cognition. These findings contribute to a better understanding of the neurobiological underpinnings of bipolar disorder.

LIMITATIONS

This study was done at a study level and cannot be addressed at the patient level. Subgroup analysis of BD I and BD II is not possible due to limited literature data.

SimPET-An open online platform for the Monte Carlo simulation of realistic brain PET data. Validation for 18 F-FDG scans

Purpose

SimPET (www.sim‐pet.org) is a free cloud‐based platform for the generation of realistic brain positron emission tomography (PET) data. In this work, we introduce the key features of the platform. In addition, we validate the platform by performing a comparison between simulated healthy brain FDG‐PET images and real healthy subject data for three commercial scanners (GE Advance NXi, GE Discovery ST, and Siemens Biograph mCT).

Methods

The platform provides a graphical user interface to a set of automatic scripts taking care of the code execution for the phantom generation, simulation (SimSET), and tomographic image reconstruction (STIR). We characterize the performance using activity and attenuation maps derived from PET/CT and MRI data of 25 healthy subjects acquired with a GE Discovery ST. We then use the created maps to generate synthetic data for the GE Discovery ST, the GE Advance NXi, and the Siemens Biograph mCT. The validation was carried out by evaluating Bland‐Altman differences between real and simulated images for each scanner. In addition, SPM voxel‐wise comparison was performed to highlight regional differences. Examples for amyloid PET and for the generation of ground‐truth pathological patients are included.

Results

The platform can be efficiently used for generating realistic simulated FDG‐PET images in a reasonable amount of time. The validation showed small differences between SimPET and acquired FDG‐PET images, with errors below 10% for 98.09% (GE Discovery ST), 95.09% (GE Advance NXi), and 91.35% (Siemens Biograph mCT) of the voxels. Nevertheless, our SPM analysis showed significant regional differences between the simulated images and real healthy patients, and thus, the use of the platform for converting control subject databases between different scanners requires further investigation.

Conclusions

The presented platform can potentially allow scientists in clinical and research settings to perform MC simulation experiments without the need for high‐end hardware or advanced computing knowledge and in a reasonable amount of time.

Brain activity and transcriptional profiling in mice under chronic jet lag

Shift work is known to be associated with an increased risk of neurological and psychiatric diseases, but how it contributes to the development of these diseases remains unclear. Chronic jet lag (CJL) induced by shifting light-dark cycles repeatedly is a commonly used protocol to mimic the environmental light/dark changes encountered by shift workers. Here we subjected wildtype mice to CJL and performed positron emission tomography imaging of glucose metabolism to monitor brain activities. We also conducted RNA sequencing using prefrontal cortex and nucleus accumbens tissues from these animals, which are brain regions strongly implicated in the pathology of various neurological and psychiatric conditions. Our results reveal the alterations of brain activities and systematic reprogramming of gene expression in brain tissues under CJL, building hypothesis for how CJL increases the susceptibility to neurological and psychiatric diseases.

Fluid Biomarkers for Synaptic Dysfunction and Loss

Synapses are the site for brain communication where information is transmitted between neurons and stored for memory formation. Synaptic degeneration is a global and early pathogenic event in neurodegenerative disorders with reduced levels of pre- and postsynaptic proteins being recognized as a core feature of Alzheimer's disease (AD) pathophysiology. Together with AD, other neurodegenerative and neurodevelopmental disorders show altered synaptic homeostasis as an important pathogenic event, and due to that, they are commonly referred to as synaptopathies. The exact mechanisms of synapse dysfunction in the different diseases are not well understood and their study would help understanding the pathogenic role of synaptic degeneration, as well as differences and commonalities among them and highlight candidate synaptic biomarkers for specific disorders. The assessment of synaptic proteins in cerebrospinal fluid (CSF), which can reflect synaptic dysfunction in patients with cognitive disorders, is a keen area of interest. Substantial research efforts are now directed toward the investigation of CSF synaptic pathology to improve the diagnosis of neurodegenerative disorders at an early stage as well as to monitor clinical progression. In this review, we will first summarize the pathological events that lead to synapse loss and then discuss the available data on established (eg, neurogranin, SNAP-25, synaptotagmin-1, GAP-43, and α-syn) and emerging (eg, synaptic vesicle glycoprotein 2A and neuronal pentraxins) CSF biomarkers for synapse dysfunction, while highlighting possible utilities, disease specificity, and technical challenges for their detection.

Intensity normalization methods in brain FDG-PET quantification

BACKGROUND

The lack of standardization of intensity normalization methods and its unknown effect on the quantification output is recognized as a major drawback for the harmonization of brain FDG-PET quantification protocols. The aim of this work is the ground truth-based evaluation of different intensity normalization methods on brain FDG-PET quantification output.

METHODS

Realistic FDG-PET images were generated using Monte Carlo simulation from activity and attenuation maps directly derived from 25 healthy subjects (adding theoretical relative hypometabolisms on 6 regions of interest and for 5 hypometabolism levels). Single-subject statistical parametric mapping (SPM) was applied to compare each simulated FDG-PET image with a healthy database after intensity normalization based on reference regions methods such as the brain stem (RRBS), cerebellum (RRC) and the temporal lobe contralateral to the lesion (RRTL), and data-driven methods, such as proportional scaling (PS), histogram-based method (HN) and iterative versions of both methods (iPS and iHN). The performance of these methods was evaluated in terms of the recovery of the introduced theoretical hypometabolic pattern and the appearance of unspecific hypometabolic and hypermetabolic findings.

RESULTS

Detected hypometabolic patterns had significantly lower volumes than the introduced hypometabolisms for all intensity normalization methods particularly for slighter reductions in metabolism . Among the intensity normalization methods, RRC and HN provided the largest recovered hypometabolic volumes, while the RRBS showed the smallest recovery. In general, data-driven methods overcame reference regions and among them, the iterative methods overcame the non-iterative ones. Unspecific hypermetabolic volumes were similar for all methods, with the exception of PS, where it became a major limitation (up to 250 cm³) for extended and intense hypometabolism. On the other hand, unspecific hypometabolism was similar far all methods, and usually solved with appropriate clustering.

CONCLUSIONS

Our findings showed that the inappropriate use of intensity normalization methods can provide remarkable bias in the detected hypometabolism and it represents a serious concern in terms of false positives. Based on our findings, we recommend the use of histogram-based intensity normalization methods. Reference region methods performance was equivalent to data-driven methods only when the selected reference region is large and stable.

Advances in CNS PET: the state-of-the-art for new imaging targets for pathophysiology and drug development

PURPOSE

A limit on developing new treatments for a number of central nervous system (CNS) disorders has been the inadequate understanding of the in vivo pathophysiology underlying neurological and psychiatric disorders and the lack of in vivo tools to determine brain penetrance, target engagement, and relevant molecular activity of novel drugs. Molecular neuroimaging provides the tools to address this. This article aims to provide a state-of-the-art review of new PET tracers for CNS targets, focusing on developments in the last 5 years for targets recently available for in-human imaging.

METHODS

We provide an overview of the criteria used to evaluate PET tracers. We then used the National Institute of Mental Health Research Priorities list to identify the key CNS targets. We conducted a PubMed search (search period 1st of January 2013 to 31st of December 2018), which yielded 40 new PET tracers across 16 CNS targets which met our selectivity criteria. For each tracer, we summarised the evidence of its properties and potential for use in studies of CNS pathophysiology and drug evaluation, including its target selectivity and affinity, inter and intra-subject variability, and pharmacokinetic parameters. We also consider its potential limitations and missing characterisation data, but not specific applications in drug development. Where multiple tracers were present for a target, we provide a comparison of their properties.

RESULTS AND CONCLUSIONS

Our review shows that multiple new tracers have been developed for proteinopathy targets, particularly tau, as well as the purinoceptor P2X7, phosphodiesterase enzyme PDE10A, and synaptic vesicle glycoprotein 2A (SV2A), amongst others. Some of the most promising of these include 18F-MK-6240 for tau imaging, 11C-UCB-J for imaging SV2A, 11C-CURB and 11C-MK-3168 for characterisation of fatty acid amide hydrolase, 18F-FIMX for metabotropic glutamate receptor 1, and 18F-MNI-444 for imaging adenosine 2A. Our review also identifies recurrent issues within the field. Many of the tracers discussed lack in vivo blocking data, reducing confidence in selectivity. Additionally, late-stage identification of substantial off-target sites for multiple tracers highlights incomplete pre-clinical characterisation prior to translation, as well as human disease state studies carried out without confirmation of test-retest reproducibility.

The basis of clinicopathological heterogeneity in TDP-43 proteinopathy

Transactive response DNA-binding protein 43 kDa (TDP-43) was identified as a major disease-associated component in the brain of patients with amyotrophic lateral sclerosis (ALS), as well as the largest subset of patients with frontotemporal lobar degeneration with ubiquitinated inclusions (FTLD-U), which characteristically exhibits cytoplasmic inclusions that are positive for ubiquitin but negative for tau and α-synuclein. TDP-43 pathology occurs in distinct brain regions, involves disparate brain networks, and features accumulation of misfolded proteins in various cell types and in different neuroanatomical regions. The clinical phenotypes of ALS and FTLD-TDP (FTLD with abnormal intracellular accumulations of TDP-43) correlate with characteristic distribution patterns of the underlying pathology across specific brain regions with disease progression. Recent studies support the idea that pathological protein spreads from neuron to neuron via axonal transport in a hierarchical manner. However, little is known to date about the basis of the selective cellular and regional vulnerability, although the information would have important implications for the development of targeted and personalized therapies. Here, we aim to summarize recent advances in the neuropathology, genetics and animal models of TDP-43 proteinopathy, and their relationship to clinical phenotypes for the underlying selective neuronal and regional susceptibilities. Finally, we attempt to integrate these findings into the emerging picture of TDP-43 proteinopathy, and to highlight key issues for future therapy and research.

Early Detection and Treatment of Patients with Alzheimer's Disease: Future Perspectives

Alzheimer's disease affects approximately 6% of people over the age of 65 years. It is characterized as chronic degeneration of cortical neurons, with loss of memory, cognition and executive functions. As the disease progresses, it is accompanied by accumulation of amyloid plaques and neurofibrillary tangles in key areas of the brain, leading to a loss of neurogenesis and synaptic plasticity in the hippocampus, along with changes in the levels of essential neurotransmitters such as acetylcholine and glutamate. Individuals with concomitant diseases such as depression, diabetes and cardiovascular disorders have a higher risk of developing Alzheimer's disease, and those who have a healthier diet and partake in regular exercise and intellectual stimulation have a lower risk of developing the disorder. This chapter describes the advances made in early diagnosis of Alzheimer's disease as this could help to improve outcomes for the patients by facilitating earlier treatment.

Brain cytochrome-c-oxidase as a marker of mitochondrial function: A pilot study in major depression using NIRS

BACKGROUND

Brain mitochondrial dysfunction is implicated in the pathophysiology of mood disorders. Brain cytochrome-c-oxidase (COX) activity is associated with the mitochondrial function. Near-infrared spectroscopy (NIRS) noninvasively measures oxidized COX (oxCOX) and tissue oxygenation index (TOI) reflecting cerebral blood flow and oxygenation.

METHODS

oxCOX and TOI were assessed in prefrontal cortex (Fp1/2, Brodmann area 10) in patients in a major depressive episode (N = 13) with major depressive disorder (MDD; N = 7) and bipolar disorder (BD; N = 6) compared with the controls (N = 10). One patient with MDD and all the patients with BD were taking medications. Computational modeling estimated oxCOX and TOI related indices of mitochondrial function and cerebral blood flow, respectively.

RESULTS

oxCOX was lower in patients than controls (p = .014) correlating inversely with depression severity (r = -.72; p = .006), driven primarily by lower oxCOX in BD compared with the controls. Computationally modeled mitochondrial parameters of the electron transport chain, such as the nicotinamide adenine dinucleotide ratio (NAD⁺ /NADH; p = .001) and the proton leak rate across the inner mitochondrial membrane (k_lk2 ; p = .008), were also lower in patients and correlated inversely with depression severity. No such effects were found for TOI.

CONCLUSIONS

In this pilot study, oxCOX and related mitochondrial parameters assessed by NIRS indicate an abnormal cerebral metabolic state in mood disorders proportional to depression severity, potentially providing a biomarker of antidepressant effect. Because the effect was driven by the medicated BD group, findings need to be evaluated in a larger, medication-free population.

Consequences of Metabolic Disruption in Alzheimer's Disease Pathology

Alzheimer's disease (AD) is an irreversible, progressive disease that slowly destroys cognitive function, such as thinking, remembering, and reasoning, to a level that one cannot carry out a daily living. As people live longer, the risk of developing AD has increased to 1 in 10 among people who are older than 65 and to almost 1 in 2 among those who are older than 85 according to a 2019 Alzheimer's Association report. As a most common cause of dementia, AD accounts for 60-80% of all dementia cases. AD is characterized by amyloid plaques and neurofibrillary tangles, composed of extracellular aggregates of amyloid-β peptides and intracellular aggregates of hyperphosphorylated tau, respectively. Besides plaques and tangles, AD pathology includes synaptic dysfunction including loss of synapses, inflammation, brain atrophy, and brain hypometabolism, all of which contribute to progressive cognitive decline. Recent genetic studies of sporadic cases of AD have identified a score of risk factors, as reported by Hollingworth et al. (Nat Genet 43:429-435, 2001) and Lambert et al. (Nat Genet 45:1452-1458, 2013). Of all these genes, apolipoprotein E4 (APOE4) still presents the biggest risk factor for sporadic cases of AD, as stated in Saunders et al. (Neurology 43:1467-1472, 1993): depending on whether you have 1 or 2 copies of APOE4 allele, the risk increases from 3- to 12-fold, respectively, in line with Genin et al. (Mol Psychiatry 16:903-907, 2011). Besides these genetic risk factors, having type 2 diabetes (T2D), a chronic metabolic disease, is known to increase the AD risk by at least 2-fold when these individuals age, conforming to Sims-Robinson et al. (Nat Rev Neurol 6:551-559, 2010). Diabetes is reaching a pandemic scale with over 422 million people diagnosed worldwide in 2014 according to World Health Organization. Although what proportion of these diabetic patients develop AD is not known, even if 10% of diabetic patients develop AD later in their life, it would double the number of AD patients in the world. Better understanding between T2D and AD is of paramount of importance for the future. The goal of this review is to examine our current understanding on metabolic dysfunction in AD, so that a potential target can be identified in the near future.

Effects of Amisulpride Adjunctive Therapy on Working Memory and Brain Metabolism in the Frontal Cortex of Patients with Schizophrenia: A Preliminary Positron Emission Tomography/Computerized Tomography Investigation

Objective

Dopamine plays a significant role in working memory by acting as a key neuromodulator between brain networks. Additionally, treatment of patients with schizophrenia using amisulpride, a pure dopamine class 2/3 receptor antagonist, improves their clinical symptoms with fewer side effects. We hypothesized that patients with schizophrenia treated with amisulpride and aripiprazole show increased working memory and glucose metabolism compared with those treated with cognitive behavioral therapy (CBT) and aripiprazole instead.

Methods

Sixteen patients with schizophrenia (eight in the amisulpride group [aripiprazole+amisulpride] and eight in the CBT group [aripiprazole+CBT]) and 15 age- and sex-matched healthy control subjects were recruited for a 12-week-long prospective trial. An [18F]-fluorodeoxyglucose-positron emission tomography/computerized tomography scanner was used to acquire the images.

Results

After 12 weeks of treatment, the amisulpride group showed greater improvement in the Letter-Number Span scores than the CBT group. Additionally, although brain metabolism in the left middle frontal gyrus, left occipital lingual gyrus, and right inferior parietal lobe was increased in all patients with schizophrenia, the amisulpride group exhibited a greater increase in metabolism in both the right superior frontal gyrus and right frontal precentral gyrus than the CBT group.

Conclusion

This study suggests that a small dose of amisulpride improves the general psychopathology, working memory performance, and brain glucose metabolism of patients with schizophrenia treated with aripiprazole.

Effect and cerebral mechanism of acupuncture treatment for functional constipation: study protocol for a randomized controlled clinical trial

Background

Acupuncture is effective in functional constipation (FC) treatment, but the central mechanism has not been well investigated. This trial will combine functional magnetic resonance imaging (fMRI) and positron emission tomography-computed tomography (PET-CT) to investigate the potential central mechanism of acupuncture treatment for FC.

Methods

This is a multimodal neuroimaging randomized controlled trial. In total, 140 FC patients will be randomly allocated into four groups: the verum acupuncture group; the sham acupuncture group; the PEG 4000 group; and the waiting-list group. This trial will include a two-week baseline period and a two-week treatment period. Patients will receive 10 sessions of acupuncture, sham acupuncture, PEG 4000, or no intervention during the treatment period. The stool diary, Cleveland Constipation Score (CCS), Patient Assessment of Constipation Symptom (PAC-SYM), and Patient Assessment of Constipation Quality of Life Questionnaire (PAC-QoL) will be used to assess the clinical efficacy of different interventions. The MRI and PET-CT scans will be performed to detect cerebral functional changes in 15 patients in each group at baseline and at the end of treatment/waiting. Multimodal imaging data will be associated with clinical data to investigate possible correlation between brain activity changes elicited by different interventions and symptoms improvement.

Discussion

We hypothesize that acupuncture can treat FC through normalizing the pathological alteration of the cerebral activity. The results of this trial will allow us to re-testify the therapeutic effects of acupuncture treating for FC and to investigate the potential central mechanism of acupuncture treatment for FC from direct (cerebral glucose metabolism) and indirect (contrast of oxyhemoglobin and deoxyhemoglobin) approaches.

Trial registration

Chinese Clinical Trial Registry, ChiCTR1800016658. Registered on 14 June 2018.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3410-8) contains supplementary material, which is available to authorized users.

Streptozotocin causes acute responses on hippocampal S100B and BDNF proteins linked to glucose metabolism alterations

Streptozotocin (STZ) is a glucosamine-nitrosourea commonly used to induce long-lasting models of diabetes mellitus and Alzheimer's disease. Direct toxicity of STZ on the pancreas and kidneys has been well characterized, but the acute effect of this compound on brain tissue has received less attention. Herein, we investigated the acute and direct toxicity of STZ on fresh hippocampal slices, measuring changes in BDNF and S100B secretion (two widely-used peripheral markers of brain injury), as well as glucose metabolism. Moreover, we investigated in vivo changes of these proteins in the hippocampus, 48 h after intracerebroventricular STZ administration. Transverse hippocampal slices (0.3 mm thick) were obtained using a McIlwain tissue chopper and target proteins were measured in the incubation medium by ELISA. STZ decreased S100B secretion, but increased BDNF secretion as well as causing impairment in glucose uptake in hippocampal slices, measured using [³H] deoxy-glucose. Glucose levels and glucose metabolism differentially modulated S100B secretion in astrocytes and BDNF secretion in neurons, when evaluated under specific conditions (high-potassium medium, presence of tetrodotoxin or fluorocitrate). Moreover, at 48 h after intracerebroventricular STZ, hippocampal BDNF content, but not S100B, was reduced. Our results indicate that BDNF and S100B are useful and sensitive markers of glucose metabolism disturbance and reinforce these proteins as general acute markers of brain disorders.

Diagnostic manifestations of total hemispheric glucose metabolism ratio in neuronal network diaschisis: diagnostic implications in Alzheimer's disease and mild cognitive impairment

PURPOSE

We tested the hypothesis that lateralized hemispheric glucose metabolism may have diagnostic implications in Alzheimer's disease (AD) and mild cognitive impairment (MCI).

METHODS

We performed FDG-PET/CT in 23 patients (mean age 63.7 years, range 50-78, 17 females) diagnosed with AD (n = 15) or MCI (n = 8) during a six-month period in 2014. Ten neurologically healthy individuals (HIs) (mean age 62.5 years, range 43-75, 5 females) served as controls. A neuroimaging expert provided visual assessment of diaschisis. The total hemispheric glucose metabolism ratio (THGr) was calculated, and with area-under the curve of receiver operating characteristics (AUC-ROC) we generated a "Network Diaschisis Test (NDT)".

RESULTS

The qualitative detection of cerebral (Ce) and cerebellar (Cb) diaschisis was 7/15 (47%), 0/8 (0%), and 0/10 (0%) in AD, MCI, and HI groups, respectively. Median cerebral THGr was 0.68 (range 0.43-0.99), 0.86 (range 0.64-0.98), and 0.95 (range 0.65-1.00) for AD, MCI, and HI groups, respectively (p = 0.04). Median cerebellar THGr was, respectively, 0.70 (range 0.18-0.98), 0.70 (range 0.48-0.81), and 0.84 (range 0.75-0.96) (p = 0.0138). A positive NDT yielded a positive predictive value of 100% for the presence of AD or MCI and a 86% negative predictive value for healthy brain. Moreover, the diagnostic manifestation of THGr between MCI and AD led to a positive predictive value of 100% for AD, but a negative predictive value of 42.9% for MCI.

CONCLUSION

Patients with AD or MCI had more pronounced diaschisis, lateralized hemispheric glucose metabolism and lower THGr compared to healthy controls. The NDT distinguished AD and MCI patients from HIs, and AD from MCI patients with a high positive predictive value and moderate and low negative predictive values. THGr can be a straightforward source of investigating neuronal network diaschisis in AD and MCI and in other cerebral diseases, across institutions.

Mitochondrial Involvement in Mental Disorders; Energy Metabolism, Genetic, and Environmental Factors

Mental disorders such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) are generally characterized by a combination of abnormal thoughts, perceptions, emotions, behavior, and relationships with others. Multiple risk factors incorporating genetic and environmental susceptibility are associated with development of these disorders. Mitochondria have a central role in the energy metabolism, and the literature suggests energy metabolism abnormalities are widespread in the brains of subjects with MDD, BD, and SZ. Numerous studies have shown altered expressions of mitochondria-related genes in these mental disorders. In addition, environmental factors for these disorders, such as stresses, have been suggested to induce mitochondrial abnormalities. Moreover, animal studies have suggested that interactions of altered expression of mitochondria-related genes and environmental factors might be involved in mental disorders. Further investigations into interactions of mitochondrial abnormalities with environmental factors are required to elucidate of the pathogenesis of these mental disorders.

Biomarkers for diseases with TDP-43 pathology

The discovery that aggregated transactive response DNA-binding protein 43 kDa (TDP-43) is the major component of pathological ubiquitinated inclusions in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) caused seminal progress in the unveiling of the genetic bases and molecular characteristics of these now so-called TDP-43 proteinopathies. Substantial increase in the knowledge of clinic-pathological coherencies, especially for FTLD variants, could be made in the last decade, but also revealed a considerable complexity of TDP-43 pathology and often a poor correlation of clinical and molecular disease characteristics. To date, an underlying TDP-43 pathology can be predicted only for patients with mutations in the genes C9orf72 and GRN, but is dependent on neuropathological verification in patients without family history, which represent the majority of cases. As etiology-specific therapies for neurodegenerative proteinopathies are emerging, methods to forecast TDP-43 pathology at patients' lifetime are highly required. Here, we review the current status of research pursued to identify specific indicators to predict or exclude TDP-43 pathology in the ALS-FTLD spectrum disorders and findings on candidates for prognosis and monitoring of disease progression in TDP-43 proteinopathies with a focus on TDP-43 with its pathological forms, neurochemical and imaging biomarkers.

Construction of a novel Chinese normal brain database using 18F-FDG PET images and MIMneuro software, the initial application in epilepsy

PURPOSE

To create a standard Western Chinese normal functional brain database for quantitative analysis using 2-deoxy-2-[18F] fluoro-d-glucose (¹⁸F-FDG) positron emission tomography (PET) images and MIMneuro software.

METHODS

78 healthy right-handed Chinese volunteers from Tangdu Hospital were scanned using ¹⁸F-FDG PET to evaluate brain metabolism between March and October 2016. All PET images were processed using MIMneuro software to create a normal database platform. The platform included anatomical optimization to facilitate spatial localization of abnormalities and a statistical comparison with normal cases utilizing the Z-scores, which represent the number of standard deviations from the mean of the normal controls in the database.

RESULTS

The novel Chinese brain metabolism database platform including 78 healthy volunteers (male: female 40:38; age 3-78 years, mean age, 45 years) was constructed based on the MIMneuro software, which increased the diagnostic confidence in the test patient by quantifying and emphasizing the abnormality. The BrainAlign^TM deformation algorithm of MIMneuro matched the size, shape, and orientation of the patient's brain scan to a template brain for comparison against a database of normal controls. The quantitative analysis performed on a voxel and regional level was useful in assessing the areas of abnormalities.

CONCLUSIONS

A novel Chinese ¹⁸F-FDG PET-based normal brain function database was created to highlight the local regions of abnormal metabolic activity through quantitative comparisons against the normal database. The Z-scores obtained by MIMneuro potentially aid in visualizing and quantifying the subtle lesions on ¹⁸FDG-PET scan images as observed in a patient diagnosed with epilepsy.

Characteristic patterns of inter- and intra-hemispheric metabolic connectivity in patients with stable and progressive mild cognitive impairment and Alzheimer's disease

The change in hypometabolism affects the regional links in the brain network. Here, to understand the underlying brain metabolic network deficits during the early stage and disease evolution of AD (Alzheimer disease), we applied correlation analysis to identify the metabolic connectivity patterns using ¹⁸F-FDG PET data for NC (normal control), sMCI (stable MCI), pMCI (progressive MCI) and AD, and explore the inter- and intra-hemispheric connectivity between anatomically-defined brain regions. Regions extracted from 90 anatomical structures were used to construct the matrix for measuring the inter- and intra-hemispheric connectivity. The brain connectivity patterns from the metabolic network show a decreasing trend of inter- and intra-hemispheric connections for NC, sMCI, pMCI and AD. Connection of temporal to the frontal or occipital regions is a characteristic pattern for conversion of NC to MCI, and the density of links in the parietal-occipital network is a differential pattern between sMCI and pMCI. The reduction pattern of inter and intra-hemispheric brain connectivity in the metabolic network depends on the disease stages, and is with a decreasing trend with respect to disease severity. Both frontal-occipital and parietal-occipital connectivity patterns in the metabolic network using ¹⁸F-FDG PET are the key feature for differentiating disease groups in AD.

Positron emission tomography assessment of cerebral glucose metabolic rates in autism spectrum disorder and schizophrenia

Several models have been proposed to account for observed overlaps in clinical features and genetic predisposition between schizophrenia and autism spectrum disorder. This study assessed similarities and differences in topological patterns and vectors of glucose metabolism in both disorders in reference to these models. Co-registered 18fluorodeoxyglucose PET and MRI scans were obtained in 41 schizophrenia, 25 ASD, and 55 healthy control subjects. AFNI was used to map cortical and subcortical regions of interest. Metabolic rates were compared between three diagnostic groups using univariate and multivariate repeated-measures ANOVA. Compared to controls, metabolic rates in schizophrenia subjects were decreased in the frontal lobe, anterior cingulate, superior temporal gyrus, amygdala and medial thalamic nuclei; rates were increased in the occipital cortex, hippocampus, basal ganglia and lateral thalamic nuclei. In ASD subjects metabolic rates were decreased in the parietal lobe, frontal premotor and eye-fields areas, and amygdala; rates were increased in the posterior cingulate, occipital cortex, hippocampus and basal ganglia. In relation to controls, subjects with ASD and schizophrenia showed opposite changes in metabolic rates in the primary motor and somatosensory cortex, anterior cingulate and hypothalamus; similar changes were found in prefrontal and occipital cortices, inferior parietal lobule, amygdala, hippocampus, and basal ganglia. Schizophrenia and ASD appear to be associated with a similar pattern of metabolic abnormalities in the social brain. Divergent maladaptive trade-offs, as postulated by the diametrical hypothesis of their evolutionary relationship, may involve a more circumscribed set of anterior cingulate, motor and somatosensory regions and the specific cognitive functions they subserve.

Reconceptualization of translocator protein as a biomarker of neuroinflammation in psychiatry

A great deal of interest in psychiatric research is currently centered upon the pathogenic role of inflammatory processes. Positron emission tomography (PET) using radiolabeled ligands selective for the 18 kDa translocator protein (TSPO) has become the most widely used technique to assess putative neuroimmune abnormalities in vivo. Originally used to detect discrete neurotoxic damages, TSPO has generally turned into a biomarker of 'neuroinflammation' or 'microglial activation'. Psychiatric research has mostly accepted these denotations of TSPO, even if they may be inadequate and misleading under many pathological conditions. A reliable and neurobiologically meaningful diagnosis of 'neuroinflammation' or 'microglial activation' is unlikely to be achieved by the sole use of TSPO PET imaging. It is also very likely that the pathological meanings of altered TSPO binding or expression are disease-specific, and therefore, not easily generalizable across different neuropathologies or inflammatory conditions. This difficulty is intricately linked to the varying (and still ill-defined) physiological functions and cellular expression patterns of TSPO in health and disease. While altered TSPO binding or expression may indeed mirror ongoing neuroinflammatory processes in some cases, it may reflect other pathophysiological processes such as abnormalities in cell metabolism, energy production and oxidative stress in others. Hence, the increasing popularity of TSPO PET imaging has paradoxically introduced substantial uncertainty regarding the nature and meaning of neuroinflammatory processes and microglial activation in psychiatry, and likely in other neuropathological conditions as well. The ambiguity of conceiving TSPO simply as a biomarker of 'neuroinflammation' or 'microglial activation' calls for alternative interpretations and complimentary approaches. Without the latter, the ongoing scientific efforts and excitement surrounding the role of the neuroimmune system in psychiatry may not turn into therapeutic hope for affected individuals.

Cellular Origin of [18F]FDG-PET Imaging Signals During Ceftriaxone-Stimulated Glutamate Uptake: Astrocytes and Neurons

Ceftriaxone stimulates astrocytic uptake of the excitatory neurotransmitter glutamate, and it is used to treat glutamatergic excitotoxicity that becomes manifest during many brain diseases. Ceftriaxone-stimulated glutamate transport was reported to drive signals underlying [¹⁸F]fluorodeoxyglucose-positron emission tomographic ([¹⁸F]FDG-PET) metabolic images of brain glucose utilization and interpreted as supportive of the notion of lactate shuttling from astrocytes to neurons. This study draws attention to critical roles of astrocytes in the energetics and imaging of brain activity, but the results are provocative because (1) the method does not have cellular resolution or provide information about downstream pathways of glucose metabolism, (2) neuronal and astrocytic [¹⁸F]FDG uptake were not separately measured, and (3) strong evidence against lactate shuttling was not discussed. Evaluation of potential metabolic responses to ceftriaxone suggests lack of astrocytic specificity and significant contributions by pre- and postsynaptic neuronal compartments. Indeed, astrocytic glycolysis may not make a strong contribution to the [¹⁸F]FDG-PET signal because partial or complete oxidation of one glutamate molecule on its uptake generates enough ATP to fuel uptake of 3 to 10 more glutamate molecules, diminishing reliance on glycolysis. The influence of ceftriaxone on energetics of glutamate-glutamine cycling must be determined in astrocytes and neurons to elucidate its roles in excitotoxicity treatment.

Overview of neuroradiology

Neuroradiology with computed tomography (CT) and magnetic resonance imaging (MRI) is essential for the initial evaluation of patients with a clinical suspicion of brain and spine disorders. Morphologic imaging is required to obtain a probable diagnosis to support the treatment decisions in pre- and perinatal disorders, vascular diseases, traumatic injuries, metabolic disorders, epilepsy, infection/inflammation, neurodegenerative disorders, degenerative spinal disease, and tumors of the central nervous system. Different postprocessing tools are increasingly used for three-dimensional visualization and quantification of lesions. Additional information is provided by angiographic methods and physiologic CT and MRI techniques, such as diffusion MRI, perfusion CT/MRI, MR spectroscopy, functional MRI, tractography, and nuclear medicine imaging methods. Positron emission tomography (PET) is now integrated with CT (PET/CT), and PET/MR scanners have recently also been introduced. These hybrid techniques facilitate the co-registration of lesions with different modalities, and give new possibilites for functional imaging. Repeated imaging is increasingly performed for treatment monitoring. The improved imaging techniques together with the neuropathologic diagnosis after biopsy or surgery allow more personalized treatment of the patient. Neuroradiology also includes endovascular treatment of aneurysms and arteriovenous malformations as well as thrombectomy in acute stroke. This catheter-based treatment has replaced invasive neurosurgery in many cases.

Quantitative positron emission tomography in brain research

The application of positron emission tomography (PET) in brain research has increased substantially during the past 20years, and is still growing. PET provides a unique insight into physiological and pathological processes in vivo. In this article we introduce the fundamentals of PET, and the methods available for acquiring quantitative estimates of the parameters of interest. A short introduction to different areas of application is also given, including basic research of brain function and in neurology, psychiatry, drug receptor occupancy studies, and its application in diagnostics of neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Our aim is to inform the unfamiliar reader of the underlying basics and potential applications of PET, hoping to inspire the reader into considering how the technique could be of benefit for his or her own research.

Traumatic brain injuries

Traumatic brain injuries (TBIs) are clinically grouped by severity: mild, moderate and severe. Mild TBI (the least severe form) is synonymous with concussion and is typically caused by blunt non-penetrating head trauma. The trauma causes stretching and tearing of axons, which leads to diffuse axonal injury - the best-studied pathogenetic mechanism of this disorder. However, mild TBI is defined on clinical grounds and no well-validated imaging or fluid biomarkers to determine the presence of neuronal damage in patients with mild TBI is available. Most patients with mild TBI will recover quickly, but others report persistent symptoms, called post-concussive syndrome, the underlying pathophysiology of which is largely unknown. Repeated concussive and subconcussive head injuries have been linked to the neurodegenerative condition chronic traumatic encephalopathy (CTE), which has been reported post-mortem in contact sports athletes and soldiers exposed to blasts. Insights from severe injuries and CTE plausibly shed light on the underlying cellular and molecular processes involved in mild TBI. MRI techniques and blood tests for axonal proteins to identify and grade axonal injury, in addition to PET for tau pathology, show promise as tools to explore CTE pathophysiology in longitudinal clinical studies, and might be developed into diagnostic tools for CTE. Given that CTE is attributed to repeated head trauma, prevention might be possible through rule changes by sports organizations and legislators.

Applications of global quantitative 18F-FDG-PET analysis in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is a prevalent neurodegenerative disease associated with various neuropsychiatric disorders and decreased quality of life. Much has been said about the use of fluorine-18 fluorodeoxyglucose positron emission tomography (18F-FDG-PET), magnetic resonance imaging (MRI), and computed tomography in the qualitative assessment of TLE. However, research into the applications of quantitative measurements to treat and diagnose TLE is severely lacking in the literature. Global quantitative analysis using 18F-FDG-PET is a powerful tool in the metabolic assessment of TLE, and can more accurately identify seizure lateralization and the potential effects of treatment as compared with visual assessments and traditional biopsy region-of-interest quantification. Therefore, there is a pressing need to introduce these novel methods to the treatment of TLE. Although 18F-FDG-PET is most commonly used for visual assessments, qualitative analysis is associated with high levels of interobserver and intraobserver variability. Semiquantitative analysis using standardized uptake value is a more consistently accurate measure of the hypometabolic patterns seen in TLE patients. Novel methods of global quantitative analysis developed in our laboratory have the potential to improve TLE assessment by limiting variability and correcting for the partial volume effect. It is of great importance to adopt these techniques into the mainstream diagnosis and treatment of TLE in order to improve patient care worldwide.