Positron emission tomography imaging in neurological disorders. J Neurol. 2012;259:1769-1780. [PMID: 22297461 DOI: 10.1007/s00415-012-6428-3]

Common anesthetic used in preclinical PET imaging inhibits metabolism of the PET tracer [18F]3F4AP

Positron emission tomography (PET) imaging studies in laboratory animals are almost always performed under isoflurane anesthesia to ensure that the subject stays still during the image acquisition. Isoflurane is effective, safe, and easy to use, and it is generally assumed to not have an impact on the imaging results. Motivated by marked differences observed in the brain uptake and metabolism of the PET tracer 3-[18F]fluoro-4-aminopyridine [(18F]3F4AP) between human and nonhuman primate studies, this study investigates the possible effect of isoflurane on this process. Mice received [18F]3F4AP injection while awake or under anesthesia and the tracer brain uptake and metabolism was compared between groups. A separate group of mice received the known cytochrome P450 2E1 inhibitor disulfiram prior to tracer administration. Isoflurane was found to largely abolish tracer metabolism in mice (74.8 ± 1.6 vs. 17.7 ± 1.7% plasma parent fraction, % PF) resulting in a 4.0-fold higher brain uptake in anesthetized mice at 35 min post-radiotracer administration. Similar to anesthetized mice, animals that received disulfiram showed reduced metabolism (50.0 ± 6.9% PF) and a 2.2-fold higher brain signal than control mice. The higher brain uptake and lower metabolism of [18F]3F4AP observed in anesthetized mice compared to awake mice are attributed to isoflurane's interference in the CYP2E1-mediated breakdown of the tracer, which was confirmed by reproducing the effect upon treatment with the known CYP2E1 inhibitor disulfiram. These findings underscore the critical need to examine the effect of isoflurane in PET imaging studies before translating tracers to humans that will be scanned without anesthesia.

HNODThia: A Promising Chelator for the Development of 64Cu Radiopharmaceuticals

Herein, we present the synthesis and coordination chemistry of copper(II) and zinc(II) complexes of two novel heterocyclic triazacyclononane (tacn)-based chelators (HNODThia and NODThia-AcNHEt). The chelator HNODThia was further derivatized to obtain a novel PSMA-based bioconjugate (NODThia-PSMA) and a bifunctional photoactivatable azamacrocyclic analogue, NODThia-PEG3-ArN3, for the development of copper-64 radiopharmaceuticals. 64Cu radiolabeling experiments were performed on the different metal-binding chelates, whereby quantitative radiochemical conversion (RCC) was obtained in less than 10 min at room temperature. The in vitro stability of NODThia-PSMA in human plasma was assessed by ligand-challenge and copper-exchange experiments. Next, we investigated the viability of the photoactivatable analog (NODThia-PEG3-ArN3) for the light-induced photoradiosynthesis of radiolabeled proteins. One-pot photoconjugation reactions to human serum albumin (HSA) as a model protein and the clinically relevant monoclonal antibody formulation MetMAb were performed. [64Cu]Cu-7-azepin-HSA and [64Cu]Cu-7-azepin-onartuzumab were prepared in less than 15 min by irradiation at 395 nm, with radiochemical purities (RCP) of >95% and radiochemical yields (RCYs) of 42.7 ± 5.3 and 49.6%, respectively. Together, the results obtained here open the way for the development of highly stable 64Cu-radiopharmaceuticals by using aza-heterocyclic tacn-based chelators, and the method can easily be extended to the development of 67Cu radiopharmaceuticals for future applications in molecularly targeted radio(immuno)therapy.

Common anesthetic used in preclinical PET imaging inhibits metabolism of the PET tracer [ 18 F]3F4AP

PET imaging studies in laboratory animals are almost always performed under isoflurane anesthesia to ensure that the subject stays still during the image acquisition. Isoflurane is effective, safe, and easy to use, and it is generally assumed to not have an impact on the imaging results. Motivated by marked differences observed in [ 18 F]3F4AP brain uptake and metabolism between human and nonhuman primate studies, this study investigates the possible effect of isoflurane on [ 18 F]3F4AP metabolism and brain uptake. Isoflurane was found to largely abolish tracer metabolism in mice resulting in a 3.3-fold higher brain uptake in anesthetized mice at 35 min post radiotracer administration, which replicated the observed effect in unanesthetized humans and anesthetized monkeys. This effect is attributed to isoflurane's interference in the CYP2E1-mediated breakdown of [ 18 F]3F4AP, which was confirmed by reproducing a higher brain uptake and metabolic stability upon treatment with the known CYP2E1 inhibitor disulfiram. These findings underscore the critical need to examine the effect of isoflurane in PET imaging studies before translating tracers to humans that will be scanned without anesthesia.

Deep learning application for the classification of Alzheimer's disease using 18F-flortaucipir (AV-1451) tau positron emission tomography

The positron emission tomography (PET) with 18F-flortaucipir can distinguish individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively unimpaired (CU) individuals. This study aimed to evaluate the utility of 18F-flortaucipir-PET images and multimodal data integration in the differentiation of CU from MCI or AD through DL. We used cross-sectional data (18F-flortaucipir-PET images, demographic and neuropsychological score) from the ADNI. All data for subjects (138 CU, 75 MCI, 63 AD) were acquired at baseline. The 2D convolutional neural network (CNN)-long short-term memory (LSTM) and 3D CNN were conducted. Multimodal learning was conducted by adding the clinical data with imaging data. Transfer learning was performed for classification between CU and MCI. The AUC for AD classification from CU was 0.964 and 0.947 in 2D CNN-LSTM and multimodal learning. The AUC of 3D CNN showed 0.947, and 0.976 in multimodal learning. The AUC for MCI classification from CU had 0.840 and 0.923 in 2D CNN-LSTM and multimodal learning. The AUC of 3D CNN showed 0.845, and 0.850 in multimodal learning. The 18F-flortaucipir PET is effective for the classification of AD stage. Furthermore, the effect of combination images with clinical data increased the performance of AD classification.

A review on multiple sclerosis prognostic findings from imaging, inflammation, and mental health studies

Magnetic resonance imaging (MRI) of the brain is commonly used to detect where chronic and active lesions are in multiple sclerosis (MS). MRI is also extensively used as a tool to calculate and extrapolate brain health by way of volumetric analysis or advanced imaging techniques. In MS patients, psychiatric symptoms are common comorbidities, with depression being the main one. Even though these symptoms are a major determinant of quality of life in MS, they are often overlooked and undertreated. There has been evidence of bidirectional interactions between the course of MS and comorbid psychiatric symptoms. In order to mitigate disability progression in MS, treating psychiatric comorbidities should be investigated and optimized. New research for the prediction of disease states or phenotypes of disability have advanced, primarily due to new technologies and a better understanding of the aging brain.

Neuroimaging in Alzheimer's Disease for Early Diagnosis: A Comprehensive Review

Alzheimer's disease (AD) is the most common cause of dementia in the elderly, affecting roughly half of those over the age of 85. We briefly discussed the risk factors, epidemiology, and treatment options for AD. The development of therapeutic therapies operating very early in the disease cascade has been spurred by the realization that the disease process begins at least a decade or more before the manifestation of symptoms. Thus, the clinical significance of early diagnosis was emphasized. Using various keywords, a literature search was carried out using PubMed and other databases. For inclusion, pertinent articles were chosen and reviewed. This article has reviewed different neuroimaging techniques that are considered advanced tools to aid in establishing a diagnosis and highlighted the advantages as well as disadvantages of those techniques. Besides, the prevalence of several in vivo biomarkers aided in discriminating affected individuals from healthy controls in the early stages of the disease. Each imaging method has its advantages and disadvantages, hence no single imaging approach can be the optimum modality for diagnosis. This article also commented on a better approach to using these techniques to increase the likelihood of an early diagnosis.

Machine learning application for classification of Alzheimer's disease stages using 18F-flortaucipir positron emission tomography

BACKGROUND

The progression of Alzheimer's dementia (AD) can be classified into three stages: cognitive unimpairment (CU), mild cognitive impairment (MCI), and AD. The purpose of this study was to implement a machine learning (ML) framework for AD stage classification using the standard uptake value ratio (SUVR) extracted from ¹⁸F-flortaucipir positron emission tomography (PET) images. We demonstrate the utility of tau SUVR for AD stage classification. We used clinical variables (age, sex, education, mini-mental state examination scores) and SUVR extracted from PET images scanned at baseline. Four types of ML frameworks, such as logistic regression, support vector machine (SVM), extreme gradient boosting, and multilayer perceptron (MLP), were used and explained by Shapley Additive Explanations (SHAP) to classify the AD stage.

RESULTS

Of a total of 199 participants, 74, 69, and 56 patients were in the CU, MCI, and AD groups, respectively; their mean age was 71.5 years, and 106 (53.3%) were men. In the classification between CU and AD, the effect of clinical and tau SUVR was high in all classification tasks and all models had a mean area under the receiver operating characteristic curve (AUC) > 0.96. In the classification between MCI and AD, the independent effect of tau SUVR in SVM had an AUC of 0.88 (p < 0.05), which was the highest compared to other models. In the classification between MCI and CU, the AUC of each classification model was higher with tau SUVR variables than with clinical variables independently, which yielded an AUC of 0.75(p < 0.05) in MLP, which was the highest. As an explanation by SHAP for the classification between MCI and CU, and AD and CU, the amygdala and entorhinal cortex greatly affected the classification results. In the classification between MCI and AD, the para-hippocampal and temporal cortex affected model performance. Especially entorhinal cortex and amygdala showed a higher effect on model performance than all clinical variables in the classification between MCI and CU.

CONCLUSIONS

The independent effect of tau deposition indicates that it is an effective biomarker in classifying CU and MCI into clinical stages using MLP. It is also very effective in classifying AD stages using SVM with clinical information that can be easily obtained at clinical screening.

Functional Magnetic Resonance Spectroscopy of Lactate in Alzheimer Disease: A Comprehensive Review of Alzheimer Disease Pathology and the Role of Lactate

ABSTRACT

Functional 1H magnetic resonance spectroscopy (fMRS) is a derivative of dynamic MRS imaging. This modality links physiologic metabolic responses with available activity and measures absolute or relative concentrations of various metabolites. According to clinical evidence, the mitochondrial glycolysis pathway is disrupted in many nervous system disorders, especially Alzheimer disease, resulting in the activation of anaerobic glycolysis and an increased rate of lactate production. Our study evaluates fMRS with J-editing as a cutting-edge technique to detect lactate in Alzheimer disease. In this modality, functional activation is highlighted by signal subtractions of lipids and macromolecules, which yields a much higher signal-to-noise ratio and enables better detection of trace levels of lactate compared with other modalities. However, until now, clinical evidence is not conclusive regarding the widespread use of this diagnostic method. The complex machinery of cellular and noncellular modulators in lactate metabolism has obscured the potential roles fMRS imaging can have in dementia diagnosis. Recent developments in MRI imaging such as the advent of 7 Tesla machines and new image reconstruction methods, coupled with a renewed interest in the molecular and cellular basis of Alzheimer disease, have reinvigorated the drive to establish new clinical options for the early detection of Alzheimer disease. Based on the latter, lactate has the potential to be investigated as a novel diagnostic and prognostic marker for Alzheimer disease.

Feasibility of dose reduction for [18F]FDG-PET/MR imaging of patients with non-lesional epilepsy

The aim of the study was to evaluate the effect of reduced injected [18F]FDG activity levels on the quantitative and diagnostic accuracy of PET images of patients with non-lesional epilepsy (NLE).Nine healthy volunteers and nine patients with NLE underwent 60-min dynamic list-mode (LM) scans on a fully-integrated PET/MRI system. Injected FDG activity levels were reduced virtually by randomly removing counts from the last 10-min of the LM data, so as to simulate the following activity levels: 50 %, 35 %, 20 %, and 10 % of the original activity. Four image reconstructions were evaluated: standard OSEM, OSEM with resolution recovery (PSF), the A-MAP, and the Asymmetrical Bowsher (AsymBowsher) algorithms. For the A-MAP algorithms, two weights were selected (low and high). Image contrast and noise levels were evaluated for all subjects while the lesion-to-background ratio (L/B) was only evaluated for patients. Patient images were scored by a Nuclear Medicine physician on a 5-point scale to assess clinical impression associated with the various reconstruction algorithms.The image contrast and L/B ratio characterizing all four reconstruction algorithms were similar, except for reconstructions based on only 10 % of total counts. Based on clinical impression, images with diagnostic quality can be achieved with as low as 35 % of the standard injected activity. The selection of algorithms utilizing an anatomical prior did not provide a significant advantage for clinical readings, despite a small improvement in L/B (< 5 %) using the A-MAP and AsymBowsher reconstruction algorithms.In patients with NLE who are undergoing [18F]FDG-PET/MR imaging, the injected [18F]FDG activity can be reduced to 35 % of the original dose levels without compromising.

Pathogenesis of Huntington's Disease: An Emphasis on Molecular Pathways and Prevention by Natural Remedies

BACKGROUND

Huntington's disease is an inherited autosomal dominant trait neuro-degenerative disorder caused by changes (mutations) of a gene called huntingtin (htt) that is located on the short arm (p) of chromosome 4, CAG expansion mutation. It is characterized by unusual movements, cognitive and psychiatric disorders.

OBJECTIVE

This review was undertaken to apprehend biological pathways of Huntington's disease (HD) pathogenesis and its management by nature-derived products. Natural products can be lucrative for the management of HD as it shows protection against HD in pre-clinical trials. Advanced research is still required to assess the therapeutic effectiveness of the known organic products and their isolated compounds in HD experimental models.

SUMMARY

Degeneration of neurons in Huntington's disease is distinguished by progressive loss of motor coordination and muscle function. This is due to the expansion of CAG trinucleotide in the first exon of the htt gene responsible for neuronal death and neuronal network degeneration in the brain. It is believed that the factors such as molecular genetics, oxidative stress, excitotoxicity, mitochondrial dysfunction, neuroglia dysfunction, protein aggregation, and altered UPS leads to HD. The defensive effect of the natural product provides therapeutic efficacy against HD. Recent reports on natural drugs have enlightened the protective role against HD via antioxidant, anti-inflammatory, antiapoptotic, and neurofunctional regulation.

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.

Computational insights into missense mutations in HTT gene causing Huntington's disease and its interactome networks

BACKGROUND

Huntington's disease is a rare neurodegenerative illness of the central nervous system that is inherited in an autosomal dominant pattern. Mutant huntingtin protein is produced as a result of enlargement of CAG repeat in the N-terminal of the polyglutamine tract.

AIM OF THE STUDY

Herein, we aim to investigate the mutations and their effects on the HTT gene and its genetic variants. Additionally, the protein-protein interaction of HTT with other proteins and receptor-ligand interaction with the three-dimensional structure of huntingtin protein were identified.

METHODS

A comprehensive analysis of the HTT interactome and protein-ligand interaction has been carried out to provide a global picture of structure-function analysis of huntingtin protein. Mutations were analyzed and mutation verification tools were used to check the effect of mutation on protein function.

RESULTS

The results showed, mutations in a single gene are not only responsible for causing a particular disease but may also cause other hereditary disorders as well. Moreover, the modification at the nucleotide level also cause the change in the specific amino acid which may disrupt the function of HTT and its interacting proteins contributing in disease pathogenesis. Furthermore, the interaction between MECP2 and BDNF lowers the rate of transcriptional activity. Molecular docking further confirmed the strong interaction between MECP2 and BDNF with highest affinity. Amino acid residues of the HTT protein, involved in the interaction with tetrabenazine were N912, Y890, G2385, and V2320. These findings proved, tetrabenazine as one of the potential therapeutic agent for treatment of Huntington's disease.

CONCLUSION

These results give further insights into the genetics of Huntington's disease for a better understanding of disease models which will be beneficial for the future therapeutic studies.

Recent developments in the management of Huntington's disease

Huntington's disease (HD) is a rare, incurable, inheritedneurodegenerative disorder manifested by chorea, hyperkinetic, and hypokinetic movements. The FDA has approved only two drugs, viz. tetrabenazine, and deutetrabenazine, to manage the chorea associated with HD. However, several other drugs are used as an off-label to manage chorea and other symptoms such as depression, anxiety, muscle tremors, and cognitive dysfunction associated with HD. So far, there is no disease-modifying treatment available. Drug repurposing has been a primary drive to search for new anti-HD drugs. Numerous molecular targets along with a wide range of small molecules and gene therapies are currently under clinical investigation. More than 200 clinical studies are underway for HD, 75% are interventional, and 25% are observational studies. The present review discusses the small molecule clinical pipeline and molecular targets for HD. Furthermore, the biomarkers, diagnostic tests, gene therapies, behavioral and observational studies for HD were also deliberated.

Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement

High noise and low spatial resolution are two key confounding factors that limit the qualitative and quantitative accuracy of PET images. Artificial intelligence models for image denoising and deblurring are becoming increasingly popular for the postreconstruction enhancement of PET images. We present a detailed review of recent efforts for artificial intelligence-based PET image enhancement with a focus on network architectures, data types, loss functions, and evaluation metrics. We also highlight emerging areas in this field that are quickly gaining popularity, identify barriers to large-scale adoption of artificial intelligence models for PET image enhancement, and discuss future directions.

The Core of Medical Imaging: State of the Art and Perspectives on the Detectors

In this review, the roles of detectors in various medical imaging techniques were described. Ultrasound, optical (near-infrared spectroscopy and optical coherence tomography) and thermal imaging, magnetic resonance imaging, computed tomography, single-photon emission tomography, positron emission tomography were the imaging modalities considered. For each methodology, the state of the art of detectors mainly used in the systems was described, emphasizing new technologies applied.

Copper-mediated nucleophilic radiofluorination of [18 F]β-CFT for positron emission tomography imaging of dopamine transporter

[¹⁸ F]β-CFT is a positron emission tomography (PET) ligand for imaging of dopamine transporter. It was proved to be a sensitive PET marker to detect presynaptic dopaminergic hypofunction in Parkinson's disease. In recent years, copper-mediated ¹⁸ F-fluorination of aryl boronic esters has been successful in some molecules containing aromatic groups. In this study, we describe the novel synthetic strategy of [¹⁸ F]β-CFT by copper-mediated nucleophilic radiofluorination with pinacol-derived aryl boronic esters upon reaction with [¹⁸ F]KF/K₂₂₂ and Cu (OTf)₂ (py)₄ . The radiolabeling protocol was optimized with [¹⁸ F]fluoride elution method and amount of copper catalyst used. [¹⁸ F]β-CFT is obtained from boronic ester precursors in 2.2% to 10.6% non-isolated radiochemical yield (RCY). Purified [¹⁸ F]β-CFT with >99% radiochemical purity (RCP) and high molar activity was obtained in validation runs. The radiolabeling procedure is straightforward and can easily be adapted for clinical use.

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.

Dynamic PET image reconstruction utilizing intrinsic data-driven HYPR4D denoising kernel

PURPOSE

Reconstructed PET images are typically noisy, especially in dynamic imaging where the acquired data are divided into several short temporal frames. High noise in the reconstructed images translates to poor precision/reproducibility of image features. One important role of "denoising" is therefore to improve the precision of image features. However, typical denoising methods achieve noise reduction at the expense of accuracy. In this work, we present a novel four-dimensional (4D) denoised image reconstruction framework, which we validate using 4D simulations, experimental phantom, and clinical patient data, to achieve 4D noise reduction while preserving spatiotemporal patterns/minimizing error introduced by denoising.

METHODS

Our proposed 4D denoising operator/kernel is based on HighlY constrained backPRojection (HYPR), which is applied either after each update of OSEM reconstruction of dynamic 4D PET data or within the recently proposed kernelized reconstruction framework inspired by kernel methods in machine learning. Our HYPR4D kernel makes use of the spatiotemporal high frequency features extracted from a 4D composite, generated within the reconstruction, to preserve the spatiotemporal patterns and constrain the 4D noise increment of the image estimate.

RESULTS

Results from simulations, experimental phantom, and patient data showed that the HYPR4D kernel with our proposed 4D composite outperformed other denoising methods, such as the standard OSEM with spatial filter, OSEM with 4D filter, and HYPR kernel method with the conventional 3D composite in conjunction with recently proposed High Temporal Resolution kernel (HYPRC3D-HTR), in terms of 4D noise reduction while preserving the spatiotemporal patterns or 4D resolution within the 4D image estimate. Consequently, the error in outcome measures obtained from the HYPR4D method was less dependent on the region size, contrast, and uniformity/functional patterns within the target structures compared to the other methods. For outcome measures that depend on spatiotemporal tracer uptake patterns such as the nondisplaceable Binding Potential (BP_ND ), the root mean squared error in regional mean of voxel BP_ND values was reduced from ~8% (OSEM with spatial or 4D filter) to ~3% using HYPRC3D-HTR and was further reduced to ~2% using our proposed HYPR4D method for relatively small target structures (~10 mm in diameter). At the voxel level, HYPR4D produced two to four times lower mean absolute error in BP_ND relative to HYPRC3D-HTR.

CONCLUSION

As compared to conventional methods, our proposed HYPR4D method can produce more robust and accurate image features without requiring any prior information.

Cross-validation study between the HRRT and the PET component of the SIGNA PET/MRI system with focus on neuroimaging

Background

The Siemens high-resolution research tomograph (HRRT - a dedicated brain PET scanner) is to this day one of the highest resolution PET scanners; thus, it can serve as useful benchmark when evaluating performance of newer scanners. Here, we report results from a cross-validation study between the HRRT and the whole-body GE SIGNA PET/MR focusing on brain imaging.

Phantom data were acquired to determine recovery coefficients (RCs), % background variability (%BG), and image voxel noise (%). Cross-validation studies were performed with six healthy volunteers using [¹¹C]DTBZ, [¹¹C]raclopride, and [¹⁸F]FDG. Line profiles, regional time-activity curves, regional non-displaceable binding potentials (BP_ND) for [¹¹C]DTBZ and [¹¹C]raclopride scans, and radioactivity ratios for [¹⁸F]FDG scans were calculated and compared between the HRRT and the SIGNA PET/MR.

Results

Phantom data showed that the PET/MR images reconstructed with an ordered subset expectation maximization (OSEM) algorithm with time-of-flight (TOF) and TOF + point spread function (PSF) + filter revealed similar RCs for the hot spheres compared to those obtained on the HRRT reconstructed with an ordinary Poisson-OSEM algorithm with PSF and PSF + filter. The PET/MR TOF + PSF reconstruction revealed the highest RCs for all hot spheres. Image voxel noise of the PET/MR system was significantly lower. Line profiles revealed excellent spatial agreement between the two systems. BP_ND values revealed variability of less than 10% for the [¹¹C]DTBZ scans and 19% for [¹¹C]raclopride (based on one subject only). Mean [¹⁸F]FDG ratios to pons showed less than 12% differences.

Conclusions

These results demonstrated comparable performances of the two systems in terms of RCs with lower voxel-level noise (%) present in the PET/MR system. Comparison of in vivo human data confirmed the comparability of the two systems. The whole-body GE SIGNA PET/MR system is well suited for high-resolution brain imaging as no significant performance degradation was found compared to that of the reference standard HRRT.

18F-FDG PET Identifies Altered Brain Metabolism in Patients with Cri du Chat Syndrome

Cri du chat syndrome (CDCS) is a rare genetic disease that is caused by a deletion in the short arm of chromosome 5 (5p) and has a variable clinical spectrum. To our knowledge, no study in the literature has ever applied ¹⁸F-FDG PET/CT to investigate alterations in brain glucose metabolism in these subjects. The aims of this study were to detect differences in brain ¹⁸F-FDG metabolism in CDCS patients with different clinical presentations and identify possible brain metabolic phenotypes of this syndrome. Methods: Six patients (5 male and 1 female; age range, 10-27 y) with CDCS were assessed for the presence of cognitive and behavioral symptoms using a battery of neuropsychologic tests and then classified as having either a severe or a mild phenotype. The patients then underwent brain ¹⁸F-FDG PET/CT. The PET/CT findings were compared with an age- and sex-matched control group using statistical parametric mapping (SPM). Whether there was an association between different clinical phenotypes and ¹⁸F-FDG PET/CT findings was investigated. Results: Four patients had the severe phenotype, and 2 patients demonstrated the mild phenotype. SPM single-subject analysis, and a group analysis in comparison with the control cohort, revealed significant hypometabolism in the left temporal lobe (Brodmann areas [BAs] 20, 36, and 38), in the right frontal subcallosal gyrus (BA 34) and caudate body, and in the cerebellar tonsils (P < 0.001). Hypermetabolism (P = 0.001) was revealed in the right superior and precentral frontal gyrus (BA 6) in the patient group, compared with the control cohort. In SPM single-subject analysis, the hypermetabolic areas were detected only in patients with the severe phenotype. Conclusion: This study revealed different patterns of brain glucose metabolism in patients with the severe and mild phenotypes, compared with control subjects. In particular, abnormal hypermetabolism in the brain, as evaluated by¹⁸F-FDG PET/CT, seems to correlate with the severe CDCS phenotype.

Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods

The rapid expansion of machine learning is offering a new wave of opportunities for nuclear medicine. This paper reviews applications of machine learning for the study of attenuation correction (AC) and low-count image reconstruction in quantitative positron emission tomography (PET). Specifically, we present the developments of machine learning methodology, ranging from random forest and dictionary learning to the latest convolutional neural network-based architectures. For application in PET attenuation correction, two general strategies are reviewed: 1) generating synthetic CT from MR or non-AC PET for the purposes of PET AC, and 2) direct conversion from non-AC PET to AC PET. For low-count PET reconstruction, recent deep learning-based studies and the potential advantages over conventional machine learning-based methods are presented and discussed. In each application, the proposed methods, study designs and performance of published studies are listed and compared with a brief discussion. Finally, the overall contributions and remaining challenges are summarized.

Nanoparticle-Mediated Visualization and Control of Cellular Membrane Potential: Strategies, Progress, and Remaining Issues

The interfacing of nanoparticle (NP) materials with cells, tissues, and organisms for a range of applications including imaging, sensing, and drug delivery continues at a rampant pace. An emerging theme in this area is the use of NPs and nanostructured surfaces for the imaging and/or control of cellular membrane potential (MP). Given the important role that MP plays in cellular biology, both in normal physiology and in disease, new materials and methods are continually being developed to probe the activity of electrically excitable cells such as neurons and muscle cells. In this Review, we highlight the current state of the art for both the visualization and control of MP using traditional materials and techniques, discuss the advantageous features of NPs for performing these functions, and present recent examples from the literature of how NP materials have been implemented for the visualization and control of the activity of electrically excitable cells. We conclude with a forward-looking perspective of how we expect to see this field progress in the near term and further into the future.

Risk Factors and Metabolism of Different Brain Regions by Positron Emission Tomography in Parkinson Disease with Disabling Dyskinesia

Objective:

Dyskinesia is the most common motor complication in advanced Parkinson’s Disease (PD) and has a severe impact on daily life. But the mechanism of dyskinesia is still poorly understood. This study aims to explore risk factors for disabling dyskinesia in PD and further analyze the Vesicular Monoamine Transporter 2 (VMAT2) distribution (labeled with 18F-AV133) in the corpus striatum and the 18F-fluorodeoxyglucose (18F-FDG) metabolism of different brain regions by PET-CT.

Methods:

This is a cross-sectional study involving 135 PD patients. They were divided into disabling dyskinesia group (DD group, N=22) and non-dyskinesia group (ND group, N=113). All the patients were agreed to undergo PET-CT scans. Clinical data were analyzed between two groups by using multivariate logistic regression analysis, and risk factors for disabling dyskinesia were then determined. The standard uptake value ratios (SUVr) of 18F-AV133 in the corpus striatum and the 18F-FDG metabolism of different brain regions were identified and calculated by the software.

Results:

6.3% patients have disabling dyskinesia. DD group were more likely to have longer Disease Duration, higher Hoehn-Yahr degree, more severe clinic symptoms, more frequent sleep behavior disorder, and higher levodopa dose equivalency than ND group (P < 0.05). After adjusting confounding factors by multivariate logistic regression, DD group had longer PD duration and high levodopa dose equivalency compared with ND group (P < 0.05). There is no significant difference between the VMAT2 distribution (labeled with 18F- AV133) in the putamen and caudate between two groups. And the 18F-FDG metabolic changes in cortical and subcortical regions did not show a significant difference between the two groups either (P > 0.05).

Conclusion:

Long PD duration and high levodopa dose equivalency were two independent risk factors for disabling dyskinesia in PD patients. Compared to non-dyskinesia PD patients, there was no significant dopamine decline of the nigrostriatal system in disabling dyskinesia PD patients. Activities of different brain regions were not different between the two groups by 18F-FDG PETCT.

Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment

Alzheimer's disease (AD) is a devastating and progressive neurodegenerative disease for which there is no cure. Mild cognitive impairment (MCI) is considered a prodromal stage of the disease. Molecular imaging with positron emission tomography (PET) allows for the in vivo visualisation and tracking of pathophysiological changes in AD and MCI. PET is a very promising methodology for differential diagnosis and novel targets of PET imaging might also serve as biomarkers for disease-modifying therapeutic interventions. This review provides an overview of the current status and applications of in vivo molecular imaging of AD pathology, specifically amyloid, tau, and microglial activation. PET imaging studies were included and evaluated as potential biomarkers and for monitoring disease progression. Although the majority of radiotracers showed the ability to discriminate AD and MCI patients from healthy controls, they had various limitations that prevent the recommendation of a single technique or tracer as an optimal biomarker. Newer research examining amyloid, tau, and microglial PET imaging in combination suggest an alternative approach in studying the disease process.

Dementia spectrum disorders: lessons learnt from decades with PET research

The dementia spectrum encompasses a range of disorders with complex diagnosis, pathophysiology and limited treatment options. Positron emission tomography (PET) imaging provides insights into specific neurodegenerative processes underlying dementia disorders in vivo. Here we focus on some of the most common dementias: Alzheimer's disease, Parkinsonism dementias including Parkinson's disease with dementia, dementia with Lewy bodies, progressive supranuclear palsy and corticobasal syndrome, and frontotemporal lobe degeneration. PET tracers have been developed to target specific proteinopathies (amyloid, tau and α-synuclein), glucose metabolism, cholinergic system and neuroinflammation. Studies have shown distinct imaging abnormalities can be detected early, in some cases prior to symptom onset, allowing disease progression to be monitored and providing the potential to predict symptom onset. Furthermore, advances in PET imaging have identified potential therapeutic targets and novel methods to accurately discriminate between different types of dementias in vivo. There are promising imaging markers with a clinical application on the horizon, however, further studies are required before they can be implantation into clinical practice.

Convenient Entry to 18F-Labeled Amines through the Staudinger Reduction

Fluorine-18 possesses outstanding decay characteristics for positron emission tomography (PET) imaging. Therefore, it is ideally suited for clinical applications. As such, improved strategies to incorporate fluorine-18 into bioactive molecules are of utmost importance. Indirect 18F-labeling with amino-functionalized synthons is a convenient and versatile approach to synthesize a broad variety of PET tracers. Herein, we report a method to convert 18F-labeled azides to primary amines by means of the Staudinger reduction. Aliphatic and aromatic 18F-labeled azides were converted into the corresponding amines with high conversion yields. The method was easily automated. From a broader perspective, the applied strategy results in two useful synthons from a single precursor and thus increases the flexibility to label diverse chemical scaffolds with minimal synthetic effort.

Neuroimaging of Sleep Disturbances in Movement Disorders

Sleep dysfunction is recognized as a distinct clinical manifestation in movement disorders, often reported early on in the disease course. Excessive daytime sleepiness, rapid eye movement sleep behavior disorder and restless leg syndrome, amidst several others, are common sleep disturbances that often result in significant morbidity. In this article, we review the spectrum of sleep abnormalities across atypical Parkinsonian disorders including multiple system atrophy (MSA), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), as well as Parkinson's disease (PD) and Huntington's disease (HD). We also explore the current concepts on the neurobiological underpinnings of sleep disorders, including the role of dopaminergic and non-dopaminergic pathways, by evaluating the molecular, structural and functional neuroimaging evidence based on several novel techniques including magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), single-photon emission computed tomography (SPECT) and positron emission tomography (PET). Based on the current state of research, we suggest that neuroimaging is an invaluable tool for assessing structural and functional correlates of sleep disturbances, harboring the ability to shed light on the sleep problems attached to the limited treatment options available today. As our understanding of the pathophysiology of sleep and wake disruption heightens, novel therapeutic approaches are certain to transpire.

Magnetic resonance imaging in Alzheimer's disease and mild cognitive impairment

Research utilizing magnetic resonance imaging (MRI) has been crucial to the understanding of the neuropathological mechanisms behind and clinical identification of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). MRI modalities show patterns of brain damage that discriminate AD from other brain illnesses and brain abnormalities that are associated with risk of conversion to AD from MCI and other behavioural outcomes. This review discusses the application of various MRI techniques to and their clinical usefulness in AD and MCI. MRI modalities covered include structural MRI, diffusion tensor imaging (DTI), arterial spin labelling (ASL), magnetic resonance spectroscopy (MRS), and functional MRI (fMRI). There is much evidence supporting the validity of MRI as a biomarker for these disorders; however, only traditional structural imaging is currently recommended for routine use in clinical settings. Future research is needed to warrant the inclusion for more advanced MRI methodology in forthcoming revisions to diagnostic criteria for AD and MCI.

The Added Value of Dynamic 18F-Florbetapir PET in the Assessment of Dementia With Lewy Bodies

Dementia with Lewy bodies (DLB) is the most common cause of dementia after Alzheimer disease. It is often underdiagnosed because of the overlapping with Alzheimer disease symptoms. We report the F-FDG and F-florbetapir dynamic PET images (early and delay phases) of an 83-year-old woman with cognitive impairment associated with visual hallucinations and parkinsonism due to probable DLB. This image highlights that the early phases of F-florbetapir may reflect regional cerebral perfusion with a pattern very similar to that of regional glucose metabolism in DLB.

18F-VC701-PET and MRI in the in vivo neuroinflammation assessment of a mouse model of multiple sclerosis

Background

Positron emission tomography (PET) using translocator protein (TSPO) ligands has been used to detect neuroinflammatory processes in neurological disorders, including multiple sclerosis (MS). The aim of this study was to evaluate neuroinflammation in a mouse MS model (EAE) using TSPO-PET with ¹⁸F-VC701, in combination with magnetic resonance imaging (MRI).

Methods

MOG_35-55/CFA and pertussis toxin protocol was used to induce EAE in C57BL/6 mice. Disease progression was monitored daily, whereas MRI evaluation was performed at 1, 2, and 4 weeks post-induction. Microglia activation was assessed in vivo by ¹⁸F-VC701 PET at the time of maximum disease score and validated by radioligand ex vivo distribution and immunohistochemistry at 2 and 4 weeks post-immunization.

Results

In vivo and ex vivo analyses show that ¹⁸F-VC701 significantly accumulates within the central nervous system (CNS), particularly in the cortex, striatum, hippocampus, cerebellum, and cervical spinal cord of EAE compared to control mice, at 2 weeks post-immunization. MRI confirmed the presence of focal brain lesions at 2 weeks post-immunization in both T1-weighted and T2 images. Of note, MRI abnormalities attenuated in later post-immunization phase. Neuropathological analysis confirmed the presence of microglial activation in EAE mice, consistent with the in vivo increase of ¹⁸F-VC701 uptake.

Conclusion

Increase of ¹⁸F-VC701 uptake in EAE mice is strongly associated with the presence of microglia activation in the acute phase of the disease. The combined use of TSPO-PET and MRI provided complementary evidence on the ongoing disease process, thus representing an attractive new tool to investigate neuronal damage and neuroinflammation at preclinical levels.

Electronic supplementary material

The online version of this article (10.1186/s12974-017-1044-x) contains supplementary material, which is available to authorized users.

Development of a PET radioligand for potassium channels to image CNS demyelination

Central nervous system (CNS) demyelination represents the pathological hallmark of multiple sclerosis (MS) and contributes to other neurological conditions. Quantitative and specific imaging of demyelination would thus provide critical clinical insight. Here, we investigated the possibility of targeting axonal potassium channels to image demyelination by positron emission tomography (PET). These channels, which normally reside beneath the myelin sheath, become exposed upon demyelination and are the target of the MS drug, 4-aminopyridine (4-AP). We demonstrate using autoradiography that 4-AP has higher binding in non-myelinated and demyelinated versus well-myelinated CNS regions, and describe a fluorine-containing derivative, 3-F-4-AP, that has similar pharmacological properties and can be labeled with ¹⁸F for PET imaging. Additionally, we demonstrate that [¹⁸F]3-F-4-AP can be used to detect demyelination in rodents by PET. Further evaluation in Rhesus macaques shows higher binding in non-myelinated versus myelinated areas and excellent properties for brain imaging. Together, these data indicate that [¹⁸F]3-F-4-AP may be a valuable PET tracer for detecting CNS demyelination noninvasively.

The serotonergic system in Parkinson's patients with dyskinesia: evidence from imaging studies

The purpose of review is to review the current status of positron emission tomography (PET) molecular imaging of serotonergic system in Parkinson’s patients who experience levodopa-induced (LIDs) and graft-induced dyskinesias (GIDs). PET imaging studies have shown that Parkinson’s disease is characterized by progressive loss of dopaminergic and serotonergic neurons. Parkinson’s patients who experienced LIDs and GIDs have an aberrant spreading of serotonergic terminals, which lead to an increased serotonergic/dopaminergic terminals ratio within the putamen. Serotonergic terminals convert exogenous levodopa into dopamine in a non-physiological manner and release an abnormal amount of dopamine without an auto-regulatory feedback. This results in higher swings in synaptic levels of dopamine, which leads to the development of LIDs and GIDs. The modulation of serotonergic terminals with 5-HT_1A and 5-HT_1B receptors agonists partially reduced these motor complications. In vivo PET studies confirmed that abnormal spreading of serotonergic terminals within the putamen has a pivotal role in the development of LIDs and GIDs. However, glutamatergic, adenosinergic, opioid systems, and phosphodiesterases 10A may also play a role in the development of these motor complications. An integrative multimodal imaging approach combining PET and MRI imaging techniques is needed to fully understand the mechanisms underlying the development of LIDs and GIDs.

Illuminating Brain Activities with Fluorescent Protein-Based Biosensors

Fluorescent protein-based biosensors are indispensable molecular tools for life science research. The invention and development of high-fidelity biosensors for a particular molecule or molecular event often catalyze important scientific breakthroughs. Understanding the structural and functional organization of brain activities remain a subject for which optical sensors are in desperate need and of growing interest. Here, we review genetically encoded fluorescent sensors for imaging neuronal activities with a focus on the design principles and optimizations of various sensors. New bioluminescent sensors useful for deep-tissue imaging are also discussed. By highlighting the protein engineering efforts and experimental applications of these sensors, we can consequently analyze factors influencing their performance. Finally, we remark on how future developments can fill technological gaps and lead to new discoveries.

Discovery of PET radiopharmaceuticals at the academia-industry interface

Project-specific collaborations between academia and pharmaceutical partners are a growing phenomenon within molecular imaging and in particular in the positron emission tomography (PET) radiopharmaceutical community. This cultural shift can be attributed in part to decreased public funding in academia in conjunction with the increased reliance on outsourcing of chemistry, radiochemistry, pharmacology and molecular imaging studies by the pharmaceutical industry. This account highlights some of our personal experiences working with industrial partners to develop new PET radiochemistry methodologies for drug discovery and neuro-PET research studies. These symbiotic academic-industrial partnerships have not only led to novel radiotracers for new targets but also to the application of new carbon-11 and fluorine-18 labeling methodologies and technologies to label previously unprecedented compounds for in vivo evaluations.

PET Molecular Imaging Research of Levodopa-Induced Dyskinesias in Parkinson's Disease

Purpose of Review

To review the current status of positron emission tomography (PET) molecular imaging research of levodopa-induced dyskinesias (LIDs) in Parkinson’s disease (PD).

Recent Findings

Recent PET studies have provided robust evidence that LIDs in PD are associated with elevated and fluctuating striatal dopamine synaptic levels, which is a consequence of the imbalance between dopaminergic and serotonergic terminals, with the latter playing a key role in mishandling presynaptic dopamine release. Long-term exposure to levodopa is no longer believed to solely induce LIDs, as studies have highlighted that PD patients who go on to develop LIDs exhibit elevated putaminal dopamine release before the initiation of levodopa treatment, suggesting the involvement of other mechanisms, including altered neuronal firing and abnormal levels of phosphodiesterase 10A.

Summary

Dopaminergic, serotonergic, glutamatergic, adenosinergic and opioid systems and phosphodiesterase 10A levels have been shown to be implicated in the development of LIDs in PD. However, no system may be considered sufficient on its own for the development of LIDs, and the mechanisms underlying LIDs in PD may have a multisystem origin. In line with this notion, future studies should use multimodal PET molecular imaging in the same individuals to shed further light on the different mechanisms underlying the development of LIDs in PD.

Imaging the Nonmotor Symptoms in Parkinson's Disease

Parkinson's disease is acknowledged to be a multisystem syndrome, manifesting as a result of multineuropeptide dysfunction, including dopaminergic, cholinergic, serotonergic, and noradrenergic deficits. This multisystem disorder ultimately leads to the presentation of a range of nonmotor symptoms, now appreciated to be an integral part of the disease-specific spectrum of symptoms, often preceding the diagnosis of motor Parkinson's disease. In this chapter, we review the dopaminergic and nondopaminergic basis of these symptoms by exploring the neuroimaging evidence based on several techniques including positron emission tomography, single-photon emission computed tomography molecular imaging, magnetic resonance imaging, functional magnetic resonance imaging, and diffusion tensor imaging. We discuss the role of these neuroimaging techniques in elucidating the underlying pathophysiology of NMS in Parkinson's disease.

Molecular Imaging Markers to Track Huntington's Disease Pathology

Huntington's disease (HD) is a progressive, monogenic dominant neurodegenerative disorder caused by repeat expansion mutation in the huntingtin gene. The accumulation of mutant huntingtin protein, forming intranuclear inclusions, subsequently leads to degeneration of medium spiny neurons in the striatum and cortical areas. Genetic testing can identify HD gene carriers before individuals develop overt cognitive, psychiatric, and chorea symptoms. Thus, HD gene carriers can be studied in premanifest stages to understand and track the evolution of HD pathology. While advances have been made, the precise pathophysiological mechanisms underlying HD are unclear. Magnetic resonance imaging (MRI) and positron emission tomography (PET) have been employed to understand HD pathology in presymptomatic and symptomatic disease stages. PET imaging uses radioactive tracers to detect specific changes, at a molecular level, which could be used as markers of HD progression and to monitor response to therapeutic treatments for HD gene expansion carriers (HDGECs). This review focuses on available PET techniques, employed in cross-sectional and longitudinal human studies, as biomarkers for HD, and highlights future potential PET targets. PET studies have assessed changes in postsynaptic dopaminergic receptors, brain metabolism, microglial activation, and recently phosphodiesterase 10A (PDE10A) as markers to track HD progression. Alterations in PDE10A expression are the earliest biochemical change identified in HD gene carriers up to 43 years before predicted symptomatic onset. Thus, PDE10A expression could be a promising marker to track HD progression from early premanifest disease stages. Other PET targets which have been less well investigated as biomarkers include cannabinoid, adenosine, and GABA receptors. Future longitudinal studies are required to fully validate these PET biomarkers for use to track disease progression from far-onset premanifest to manifest HD stages. PET imaging is a crucial neuroimaging tool, with the potential to detect early changes and validate sensitivity of biomarkers for tracking HD pathology. Moreover, continued development of novel PET tracers provides exciting opportunities to investigate new molecular targets, such as histamine and serotonin receptors, to further understand the mechanisms underlying HD pathology.

Current status of PET imaging in Huntington's disease

Purpose

To review the developments of recent decades and the current status of PET molecular imaging in Huntington’s disease (HD).

Methods

A systematic review of PET studies in HD was performed. The MEDLINE, Web of Science, Cochrane and Scopus databases were searched for articles in all languages published up to 19 August 2015 using the major medical subject heading “Huntington Disease” combined with text and key words “Huntington Disease”, “Neuroimaging” and “PET”. Only peer-reviewed, primary research studies in HD patients and premanifest HD carriers, and studies in which clinical features were described in association with PET neuroimaging results, were included in this review. Reviews, case reports and nonhuman studies were excluded.

Results

A total of 54 PET studies were identified and analysed in this review. Brain metabolism ([¹⁸F]FDG and [¹⁵O]H₂O), presynaptic ([¹⁸F]fluorodopa, [¹¹C]β-CIT and [¹¹C]DTBZ) and postsynaptic ([¹¹C]SCH22390, [¹¹C]FLB457 and [¹¹C]raclopride) dopaminergic function, phosphodiesterases ([¹⁸F]JNJ42259152, [¹⁸F]MNI-659 and [¹¹C]IMA107), and adenosine ([¹⁸F]CPFPX), cannabinoid ([¹⁸F]MK-9470), opioid ([¹¹C]diprenorphine) and GABA ([¹¹C]flumazenil) receptors were evaluated as potential biomarkers for monitoring disease progression and for assessing the development and efficacy of novel disease-modifying drugs in premanifest HD carriers and HD patients. PET studies evaluating brain restoration and neuroprotection were also identified and described in detail.

Conclusion

Brain metabolism, postsynaptic dopaminergic function and phosphodiesterase 10A levels were proven to be powerful in assessing disease progression. However, no single technique may be currently considered an optimal biomarker and an integrative multimodal imaging approach combining different techniques should be developed for monitoring potential neuroprotective and preventive treatment in HD.

Considerations in the Development of Reversibly Binding PET Radioligands for Brain Imaging

The development of reversibly binding radioligands for imaging brain proteins in vivo, such as enzymes, neurotransmitter transporters, receptors and ion channels, with positron emission tomography (PET) is keenly sought for biomedical studies of neuropsychiatric disorders and for drug discovery and development, but is recognized as being highly challenging at the medicinal chemistry level. This article aims to compile and discuss the main considerations to be taken into account by chemists embarking on programs of radioligand development for PET imaging of brain protein targets.

Molecular imaging of levodopa-induced dyskinesias

Levodopa-induced dyskinesias (LIDs) occur in the majority of patients with Parkinson's disease (PD) following years of levodopa treatment. The pathophysiology underlying LIDs in PD is poorly understood, and current treatments generate only minor benefits for the patients. Studies with positron emission tomography (PET) molecular imaging have demonstrated that in advanced PD patients, levodopa administration induces sharp increases in striatal dopamine levels, which correlate with LIDs severity. Fluctuations in striatal dopamine levels could be the result of the attenuated buffering ability in the dopaminergically denervated striatum. Lines of evidence from PET studies indicate that serotonergic terminals could also be responsible for the development of LIDs in PD by aberrantly processing exogenous levodopa and by releasing dopamine in a dysregulated manner from the serotonergic terminals. Additionally, other downstream mechanisms involving glutamatergic, cannabinoid, opioid, cholinergic, adenosinergic, and noradrenergic systems may contribute in the development of LIDs. In this article, we review the findings from preclinical, clinical, and molecular imaging studies, which have contributed to our understanding the pathophysiology of LIDs in PD.

Improved synthesis and application of [(11) C]benzyl iodide in positron emission tomography radiotracer production

Positron emission tomography has increased the demand for new carbon-11 radiolabeled tracers and building blocks. A promising radiolabeling synthon is [(11) C]benzyl iodide ([(11) C]BnI), because the benzyl group is a widely present functionality in biologically active compounds. Unfortunately, synthesis of [(11) C]BnI has received little attention, resulting in limited application. Therefore, we investigated the synthesis in order to significantly improve, automate, and apply it for labeling of the dopamine D2 antagonist [(11) C]clebopride as a proof of concept. [(11) C]BnI was synthesized from [(11) C]CO2 via a Grignard reaction and purified prior the reaction with desbenzyl clebopride. According to a one-pot procedure, [(11) C]BnI was synthesized in 11 min from [(11) C]CO2 with high yield, purity, and specific activity, 52 ± 3% (end of the cyclotron bombardment), 95 ± 3%, and 123 ± 17 GBq/µmol (end of the synthesis), respectively. Changes in the [(11) C]BnI synthesis are reduced amounts of reagents, a lower temperature in the Grignard reaction, and the introduction of a solid-phase intermediate purification. [(11) C]Clebopride was synthesized within 28 min from [(11) C]CO2 in an isolated decay-corrected yield of 11 ± 3% (end of the cyclotron bombardment) with a purity of >98% and specific activity (SA) of 54 ± 4 GBq/µmol (n = 3) at the end of the synthesis. Conversion of [(11) C]BnI to product was 82 ± 11%. The reliable synthesis of [(11) C]BnI allows the broad application of this synthon in positron emission tomography radiopharmaceutical development.

Recent imaging advances in neurology

Over the recent years, the application of neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) has considerably advanced the understanding of complex neurological disorders. PET is a powerful molecular imaging tool, which investigates the distribution and binding of radiochemicals attached to biologically relevant molecules; as such, this technique is able to give information on biochemistry and metabolism of the brain in health and disease. MRI uses high intensity magnetic fields and radiofrequency pulses to provide structural and functional information on tissues and organs in intact or diseased individuals, including the evaluation of white matter integrity, grey matter thickness and brain perfusion. The aim of this article is to review the most recent advances in neuroimaging research in common neurological disorders such as movement disorders, dementia, epilepsy, traumatic brain injury and multiple sclerosis, and to evaluate their contribution in the diagnosis and management of patients.

Dopamine receptor mapping with PET imaging in Parkinson's disease

Parkinson's disease (PD) is a chronic neurodegenerative disorder characterised pathologically by the loss of dopaminergic neurons in the substantia nigra pars compacta. These neurons project to the striatum, and their loss leads to alterations in the activity of the neural circuits that regulate movement. The striatal output of the circuit related to the control of movement is mediated by two pathways: the direct striatal pathway, which is mediated through facilitation of D1 receptors, and the indirect striatal pathway, mediated through D2 receptors. Positron emission tomography (PET) molecular imaging is a powerful in vivo technique in which using selective dopaminergic radioligands has been employed to investigate the dopaminergic system in humans. In this article we aim to review the role of PET imaging in understanding the postsynaptic dopaminergic mechanisms in PD. PET studies have allowed us to gain important insights into the functions of the dopaminergic system, the mechanisms of drug-induced motor and non-motor complications, and the placebo effect in PD.