PET/MR Imaging: New Frontier in Alzheimer's Disease and Other Dementias

Mapping the knowledge landscape of the PET/MR domain: a multidimensional bibliometric analysis

OBJECTIVE

This study aims to conduct a bibliometric analysis to explore research trends, collaboration patterns, and emerging themes in the PET/MR field based on published literature from 2010 to 2024.

METHODS

A detailed literature search was performed using the Web of Science Core Collection (WoSCC) database with keywords related to PET/MR. A total of 4,349 publications were retrieved and analyzed using various bibliometric tools, including VOSviewer and CiteSpace.

RESULTS

The analysis revealed an initial increase in PET/MR publications, peaking at 495 in 2021, followed by a slight decline. The USA, Germany, and China were the most prolific countries, with the USA demonstrating strong collaborative networks. Key institutions included the Stanford University, Technical University of Munich and University of Duisburg-Essen. Prominent authors were primarily from Germany, with significant contributions from University Hospital Essen. Major journals in the field included the European Journal of Nuclear Medicine, Journal of Nuclear Medicine, and Physics in Medicine and Biology. Emerging research areas focused on oncology, neurological disorders, and cardiovascular diseases, with keywords such as "prostate cancer," "Alzheimer's disease," and "breast cancer" showing high research activity. Recent trends also highlight the growing integration of AI, particularly deep learning, to improve imaging reconstruction and diagnostic accuracy.

CONCLUSION

The findings emphasize the need for continuous investment, strategic planning, and technological innovations to expand PET/MR's clinical applications. Future research should focus on optimizing imaging techniques, fostering international collaborations, and integrating emerging technologies like artificial intelligence to enhance PET/MR's diagnostic and therapeutic potential in precision medicine.

Utilization of Neuroimaging Techniques in the Differential Diagnosis of Very Late-Onset Schizophrenia and Neurodegenerative Disorders

The emergence of psychiatric symptoms in late life presents a diagnostic challenge due to their overlap with neurodegenerative disorders. This case details a 66-year-old male with acute psychosis, initially raising concerns for an underlying neurodegenerative-related process. Comprehensive evaluation, including neuroimaging and laboratory studies, excluded neurodegeneration, leading to a diagnosis of very late-onset schizophrenia. The patient demonstrated clinical improvement with an atypical antipsychotic, while an acetylcholinesterase inhibitor was discontinued due to the absence of neurodegenerative pathology. This case highlights the critical role of thorough diagnostic assessment in differentiating primary psychiatric disorders from neurodegenerative conditions in older adults.

Advances in aggregation-induced emission luminogens for biomedicine: From luminescence mechanisms to diagnostic applications

Advancements in early detection have demonstrated the significance of biomarkers as indicators of health and disease. Traditional detection methods often face limitations, such as low sensitivity and time consumption. Fluorescence-based techniques are considered promising approaches because of their noninvasiveness and rapid response. However, these conventional methods have some drawbacks, such as low quantum yield, photobleaching, and aggregation-caused quenching. Recently, aggregation-induced emission (AIE) has emerged as a potential alternative, characterized by luminous emission upon aggregation, thus improving detection sensitivity and stability. This review explores the recent advancements in AIE luminogens (AIEgens) in biomedical engineering, with a particular focus on their application in biomarker detection. Here, we discuss the different types of AIE mechanisms and their advantages in disease diagnosis and imaging. In addition, we summarize the development of various AIEgen-based probes for the detection of diverse biomarkers. Finally, we address the remaining challenges and future directions for AIE materials in modern biomedical engineering, emphasizing the potential of AIEgens in biomarker detection and disease diagnosis strategies.

Mapping the evolution of PET/MR research: a bibliometric analysis of publication trends, leading contributors, and conceptual frameworks (2011-2023)

BACKGROUND

Positron emission tomography-magnetic resonance imaging (PET/MR) is a cutting-edge hybrid imaging technology with the potential to revolutionize medical diagnosis. This bibliometric study aims to map the research landscape of PET/MR by analyzing a curated set of Web of Science Core Collection documents from 2011 to 2023.

METHODS

We conducted a bibliometric analysis to map the research landscape of PET/MR, leveraging a curated dataset of 3,600 documents retrieved from the Web of Science Core Collection spanning the period from 2011 to 2023. We employed quantitative methods to assess the quantity and distribution of PET/MR studies, including patterns of change, research status, and directions. Additionally, we utilized VOSviewer software to conduct keyword co-occurrence analysis, explore collaborative networks among authors and institutions, and identify influential journals in the field.

RESULTS

Results: The analysis reveals several key insights: (1) a significant increase in the number of PET/MR publications over the past 12 years, highlighting the growing interest and activity in this field; (2) the United States and Germany as the leading countries in terms of research output and collaboration, with a growing presence of other countries such as China; (3) the Journal of Nuclear Medicine and the European Journal of Nuclear Medicine and Molecular Imaging as the most influential journals in the field; (4) a shift in research focus from imaging techniques to clinical applications, with an increasing emphasis on prostate cancer, PSMA, and FDG imaging.

CONCLUSIONS

This study provides a comprehensive overview of PET/MR research, identifying prominent trends, key researchers, and influential works. Based on these findings, we propose recommendations for future research directions in this rapidly evolving field.

FTIR Spectroscopy and Blood-Derived Extracellular Vesicles Duo in Alzheimer's Disease

Background

Alzheimer's disease (AD) diagnosis is difficult, and new accurate tools based on peripheral biofluids are urgently needed. Extracellular vesicles (EVs) emerged as a valuable source of biomarker profiles for AD, since their cargo is disease-specific and these can be easily isolated from easily accessible biofluids, as blood. Fourier Transform Infrared (FTIR) spectroscopy can be employed to analyze EVs and obtain the spectroscopic profiles from different regions of the spectra, simultaneously characterizing carbohydrates, nucleic acids, proteins, and lipids.

Objective

The aim of this study was to identify blood-derived EVs (bdEVs) spectroscopic signatures with AD discriminatory potential.

Methods

Herein, FTIR spectra of bdEVs from two biofluids (serum and plasma) and distinct sets of Controls and AD cases were acquired, and EVs' spectra analyzed.

Results

Analysis of bdEVs second derivative peaks area revealed differences between Controls and AD cases in distinct spectra regions, assigned to carbohydrates and nucleic acids, amides, and lipids.

Conclusions

EVs' spectroscopic profiles presented AD discriminatory value, supporting the use of bdEVs combined with FTIR as a screening or complementary tool for AD diagnosis.

Detection of Alzheimer's disease onset using MRI and PET neuroimaging: longitudinal data analysis and machine learning

The scientists are dedicated to studying the detection of Alzheimer's disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer's disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer's disease onset.

Conv-eRVFL: Convolutional Neural Network Based Ensemble RVFL Classifier for Alzheimer's Disease Diagnosis

As per the latest statistics, Alzheimer's disease (AD) has become a global burden over the following decades. Identifying AD at the intermediate stage became challenging, with mild cognitive impairment (MCI) utilizing credible biomarkers and robust learning approaches. Neuroimaging techniques like magnetic resonance imaging (MRI) and positron emission tomography (PET) are practical research approaches that provide structural atrophies and metabolic variations. With the help of MRI and PET scans, metabolic and structural changes in AD patients can be visible even ten years before the disease's onset. This paper proposes a novel wavelet packet transform-based structural and metabolic image fusion approach using MRI and PET scans. An eight-layer trained CNN extracts features from multiple layers and these features are fed to an ensemble of non-iterative random vector functional link (RVFL) models. The RVFL network incorporates the s-membership fuzzy function as an activation function that helps overcome outliers. Lastly, outputs of all the customized RVFL classifiers are averaged and fed to the RVFL classifier to make the final decision. Experiments are performed over Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and classification is made over CN vs. AD vs. MCI. The model performance obtained is decent enough to prove the effectiveness of the fusion-based ensemble approach.

Application and prospect for generative adversarial networks in cross-modality reconstruction of medical images

Cross-modality reconstruction of medical images refers to predicting the image from one modality to another so as to achieve more accurate personalized medicine. Generative adversarial networks is the most commonly used deep learning technique in cross-modality reconstruction. It can generate realistic images by learning features from implicit distributions that follow the distributions of real data and then reconstruct the image of another modality rapidly. With the sharp increase in clinical demand for multi-modality medical image, this technology has been widely used in the task of cross modal reconstruction between different medical image modalities, such as magnetic resonance imaging, computed tomography and positron emission computed tomography. It can achieve accurate and efficient cross-modality image reconstruction in different parts of the body, such as the brain, heart, etc. In addition, although GAN has achieved some success in cross-modality reconstruction, its stability, generalization ability, and accuracy still need further research and improvement.

Neuroimaging Modalities in Alzheimer's Disease: Diagnosis and Clinical Features

Alzheimer's disease (AD) is a neurodegenerative disease causing progressive cognitive decline until eventual death. AD affects millions of individuals worldwide in the absence of effective treatment options, and its clinical causes are still uncertain. The onset of dementia symptoms indicates severe neurodegeneration has already taken place. Therefore, AD diagnosis at an early stage is essential as it results in more effective therapy to slow its progression. The current clinical diagnosis of AD relies on mental examinations and brain imaging to determine whether patients meet diagnostic criteria, and biomedical research focuses on finding associated biomarkers by using neuroimaging techniques. Multiple clinical brain imaging modalities emerged as potential techniques to study AD, showing a range of capacity in their preciseness to identify the disease. This review presents the advantages and limitations of brain imaging modalities for AD diagnosis and discusses their clinical value.

BPGAN: Brain PET synthesis from MRI using generative adversarial network for multi-modal Alzheimer's disease diagnosis

BACKGROUND AND OBJECTIVE

Multi-modal medical images, such as magnetic resonance imaging (MRI) and positron emission tomography (PET), have been widely used for the diagnosis of brain disorder diseases like Alzheimer's disease (AD) since they can provide various information. PET scans can detect cellular changes in organs and tissues earlier than MRI. Unlike MRI, PET data is difficult to acquire due to cost, radiation, or other limitations. Moreover, PET data is missing for many subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. To solve this problem, a 3D end-to-end generative adversarial network (named BPGAN) is proposed to synthesize brain PET from MRI scans, which can be used as a potential data completion scheme for multi-modal medical image research.

METHODS

We propose BPGAN, which learns an end-to-end mapping function to transform the input MRI scans to their underlying PET scans. First, we design a 3D multiple convolution U-Net (MCU) generator architecture to improve the visual quality of synthetic results while preserving the diverse brain structures of different subjects. By further employing a 3D gradient profile (GP) loss and structural similarity index measure (SSIM) loss, the synthetic PET scans have higher-similarity to the ground truth. In this study, we explore alternative data partitioning ways to study their impact on the performance of the proposed method in different medical scenarios.

RESULTS

We conduct experiments on a publicly available ADNI database. The proposed BPGAN is evaluated by mean absolute error (MAE), peak-signal-to-noise-ratio (PSNR) and SSIM, superior to other compared models in these quantitative evaluation metrics. Qualitative evaluations also validate the effectiveness of our approach. Additionally, combined with MRI and our synthetic PET scans, the accuracies of multi-class AD diagnosis on dataset-A and dataset-B are 85.00% and 56.47%, which have been improved by about 1% and 1%, respectively, compared to the stand-alone MRI.

CONCLUSIONS

The experimental results of quantitative measures, qualitative displays, and classification evaluation demonstrate that the synthetic PET images by BPGAN are reasonable and high-quality, which provide complementary information to improve the performance of AD diagnosis. This work provides a valuable reference for multi-modal medical image analysis.

Cold Kit Labeling: The Future of 68Ga Radiopharmaceuticals?

Over the last couple of decades, gallium-68 (68Ga) has gained a formidable interest for PET molecular imaging of various conditions, from cancer to infection, through cardiac pathologies or neuropathies. It has gained routine use, with successful radiopharmaceuticals such as somatostatin analogs ([68Ga]Ga-DOTATOC and [68Ga]GaDOTATATE) for neuroendocrine tumors, and PSMA ligands for prostate cancer. It represents a major clinical impact, particularly in the context of theranostics, coupled with their 177Lu-labeled counterparts. Beside those, a bunch of new 68Ga-labeled molecules are in the preclinical and clinical pipelines, with some of them showing great promise for patient care. Increasing clinical demand and regulatory issues have led to the development of automated procedures for the production of 68Ga radiopharmaceuticals. However, the widespread use of these radiopharmaceuticals may rely on simple and efficient radiolabeling methods, undemanding in terms of equipment and infrastructure. To make them technically and economically accessible to the medical community and its patients, it appears mandatory to develop a procedure similar to the well-established kit-based 99mTc chemistry. Already available commercial kits for the production of 68Ga radiopharmaceuticals have demonstrated the feasibility of using such an approach, thus paving the way for more kit-based 68Ga radiopharmaceuticals to be developed. This article discusses the development of 68Ga cold kit radiopharmacy, including technical issues, and regulatory aspects.

PET/MR Technology: Advancement and Challenges

When this article was written, it coincided with the 11th anniversary of the installation of our PET/MR device in Munich. In fact, this was the first fully integrated device to be in clinical use. During this time, we have observed many interesting behaviors, to put it kindly. However, it is more critical that in this process, our understanding of the system also improved - including the advantages and limitations from a technical, logistical, and medical perspective. The last decade of PET/MRI research has certainly been characterized by most sites looking for a "key application." There were many ideas in this context and before and after the devices became available, some of which were based on the earlier work with integrating data from single devices. These involved validating classical PET methods with MRI (eg, perfusion or oncology diagnostics). More important, however, were the scenarios where intermodal synergies could be expected. In this review, we look back on this decade-long journey, at the challenges overcome and those still to come.

Advances in nonlinear optical microscopy techniques for in vivo and in vitro neuroimaging

Understanding the mechanism of the brain via optical microscopy is one of the challenges in neuroimaging, considering the complex structures. Advanced neuroimaging techniques provide a more comprehensive insight into patho-mechanisms of brain disorders, which is useful in the early diagnosis of the pathological and physiological changes associated with various neurodegenerative diseases. Recent advances in optical microscopy techniques have evolved powerful tools to overcome scattering of light and provide improved in vivo neuroimaging with sub-cellular resolution, endogenous contrast specificity, pinhole less optical sectioning capability, high penetration depth, and so on. The following article reviews the developments in various optical imaging techniques including two-photon and three-photon fluorescence, second-harmonic generation, third-harmonic generation, coherent anti-Stokes Raman scattering, and stimulated Raman scattering in neuroimaging. We have outlined the potentials and drawbacks of these techniques and their possible applications in the investigation of neurodegenerative diseases.

Systematic Review of Different Neuroimaging Correlates in Mild Cognitive Impairment and Alzheimer's Disease

Alzheimer's disease (AD) is a heterogeneous progressive neurocognitive disorder. Although different neuroimaging modalities have been used for the identification of early diagnostic and prognostic factors of AD, there is no consolidated view of the findings from the literature. Here, we aim to provide a comprehensive account of different neural correlates of cognitive dysfunction via magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI) (resting-state and task-related), positron emission tomography (PET) and magnetic resonance spectroscopy (MRS) modalities across the cognitive groups i.e., normal cognition, mild cognitive impairment (MCI), and AD. A total of 46 meta-analyses met the inclusion criteria, including relevance to MCI, and/or AD along with neuroimaging modality used with quantitative and/or functional data. Volumetric MRI identified early anatomical changes involving transentorhinal cortex, Brodmann area 28, followed by the hippocampus, which differentiated early AD from healthy subjects. A consistent pattern of disruption in the bilateral precuneus along with the medial temporal lobe and limbic system was observed in fMRI, while DTI substantiated the observed atrophic alterations in the corpus callosum among MCI and AD cases. Default mode network hypoconnectivity in bilateral precuneus (PCu)/posterior cingulate cortices (PCC) and hypometabolism/hypoperfusion in inferior parietal lobules and left PCC/PCu was evident. Molecular imaging revealed variable metabolite concentrations in PCC. In conclusion, the use of different neuroimaging modalities together may lead to identification of an early diagnostic and/or prognostic biomarker for AD.

Integrated Positron Emission Tomography/Magnetic Resonance Imaging in clinical diagnosis of Alzheimer's disease

Alzheimer's disease (AD), a progressive neurodegenerative disease which seriously endangers the health of the aged, is the most common etiology of senile dementia. With the increasing progress of neuroimaging technology, more and more imaging methods have been applied to study Alzheimer's disease. The emergence of integrated PET/MRI (Positron Emission Tomography/Magnetic Resonance Imaging) is a major advance in multimodal molecular imaging with many advantages on the structure of resolution and contrast of image over computed tomography (CT), PET and MRI. PET/MRI is now used stepwise in neurodegenerative diseases, and also has broad prospect of application in the early diagnosis of AD. In this review, we emphatically introduce the imaging advances of AD including functional imaging and molecular imaging, the advantages of PET/MRI over other imaging methods and prospects of PET/MRI in AD clinical diagnosis, especially in early diagnosis, clinical assessment and prediction on AD.

Bias-generating factors in biofluid amyloid-β measurements for Alzheimer's disease diagnosis

Alzheimer's disease (AD) is the most prevalent cause of dementia worldwide, yet the dearth of readily accessible diagnostic biomarkers is a substantial hindrance towards progressing to effective preventive and therapeutic approaches. Due to a long delay between cerebral amyloid-β (Aβ) accumulation and the onset of cognitive impairments, biomarkers that reflect Aβ pathology and enable routine screening for disease progression are of urgent need for application in the clinical diagnosis of AD. According to accumulating evidences, cerebrospinal fluid (CSF) and plasma offer windows to the brain as they allow monitoring of biochemical changes in the brain. Considering the high availability and accuracy in depicting Aβ deposition in the brain, Aβ levels in CSF and plasma are regarded as promising fluid biomarkers for the diagnosis of AD patients at an early stage. However, clinical data with intra- and interindividual variations in the concentrations of CSF and plasma Aβ implicate the need to reevaluate current Aβ detection methods and establish a standardized operating procedure. Therefore, this review introduces three bias-generating factors in biofluid Aβ measurement that may hamper the accurate Aβ quantification and how such complications can be overcome for the widespread implementation of fluid Aβ detection in clinical practice.

Motion estimation and correction for simultaneous PET/MR using SIRF and CIL

SIRF is a powerful PET/MR image reconstruction research tool for processing data and developing new algorithms. In this research, new developments to SIRF are presented, with focus on motion estimation and correction. SIRF's recent inclusion of the adjoint of the resampling operator allows gradient propagation through resampling, enabling the MCIR technique. Another enhancement enabled registering and resampling of complex images, suitable for MRI. Furthermore, SIRF's integration with the optimization library CIL enables the use of novel algorithms. Finally, SPM is now supported, in addition to NiftyReg, for registration. Results of MR and PET MCIR reconstructions are presented, using FISTA and PDHG, respectively. These demonstrate the advantages of incorporating motion correction and variational and structural priors. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Quantitative Assessment of Cortical Excitability in Alzheimer's Dementia and Its Association with Clinical Symptoms: A Systematic Review and Meta-Analyses

BACKGROUND

Alzheimer's disease (AD) is characterized by cognitive and neuropsychiatric symptoms (NPS) due to underlying neurodegenerative pathology. Some studies using electroencephalography (EEG) have shown increased epileptiform and epileptic activity in AD.

OBJECTIVE

This review and meta-analyses aims to synthesize the existing evidence for quantitative abnormalities of cortical excitability in AD and their relationship with clinical symptoms.

METHODS

We systematically searched and reviewed publications that quantitatively assessed cortical excitability, using transcranial magnetic stimulation (TMS) resting motor threshold (rMT), active motor threshold (aMT), motor evoked potential (MEP) or directly from the cortex using TMS-EEG via TMS-evoked potential (TEP). We meta-analyzed studies that assessed rMT and aMT using random effects model.

RESULTS

We identified 895 publications out of which 37 were included in the qualitative review and 30 studies using rMT or aMT were included in the meta-analyses. The AD group had reduced rMT (Hedges' g = -0.99, 95%CI [-1.29, -0.68], p <  0.00001) and aMT (Hedges' g = -0.87, 95%CI [-1.50, -0.24], p <  0.00001) as compared with control groups, indicative of higher cortical excitability. Qualitative review found some evidence of increased MEP amplitude, whereas findings related to TEP were inconsistent. There was some evidence supporting an inverse association between cortical excitability and global cognition. No publications reported on the relationship between cortical excitability and NPS.

CONCLUSION

There is strong evidence of increased motor cortex excitability in AD and some evidence of an inverse association between excitability and cognition. Future studies should assess cortical excitability from non-motor areas using TMS-EEG and examine its relationship with cognition and NPS.

Photoacoustic Neuroimaging - Perspectives on a Maturing Imaging Technique and its Applications in Neuroscience

A prominent goal of neuroscience is to improve our understanding of how brain structure and activity interact to produce perception, emotion, behavior, and cognition. The brain's network activity is inherently organized in distinct spatiotemporal patterns that span scales from nanometer-sized synapses to meter-long nerve fibers and millisecond intervals between electrical signals to decades of memory storage. There is currently no single imaging method that alone can provide all the relevant information, but intelligent combinations of complementary techniques can be effective. Here, we thus present the latest advances in biomedical and biological engineering on photoacoustic neuroimaging in the context of complementary imaging techniques. A particular focus is placed on recent advances in whole-brain photoacoustic imaging in rodent models and its influential role in bridging the gap between fluorescence microscopy and more non-invasive techniques such as magnetic resonance imaging (MRI). We consider current strategies to address persistent challenges, particularly in developing molecular contrast agents, and conclude with an overview of potential future directions for photoacoustic neuroimaging to provide deeper insights into healthy and pathological brain processes.

Pitfalls on PET/MRI

A decade of PET/MRI clinical imaging has passed and many of the pitfalls are similar to those on earlier studies. However, techniques to overcome them have emerged and continue to develop. Although clinically significant lung nodules are demonstrable, smaller nodules may be detected using ultrashort/zero echo-time (TE) lung MRI. Fast reconstruction ultrashort TE sequences have also been used to achieve high-resolution lung MRI even with free-breathing. The introduction and improvement of time-of-flight scanners and increasing the axial length of the PET detector arrays have more than doubled the sensitivity of the PET part of the system. MRI for attenuation correction has provided many potential pitfalls, including misclassification of tissue classes based on MRI information for attenuation correction. Although the use of short echo times have helped to address these pitfalls, one of the most exciting developments has been the use of deep learning algorithms and computational neural networks to rapidly provide soft tissue, fat, bone and air information for the attenuation correction as a supplement to the attenuation correction information from fat-water imaging. Challenges with motion correction, particularly respiratory and cardiac remain but are being addressed with respiratory monitors and using PET data. In order to address truncation artefacts, the system manufacturers have developed methods to extend the MR field-of-view for the purpose of the attenuation and scatter corrections. General pitfalls like stitching of body sections for individual studies, optimum delivery of images for viewing and reporting, and resource implications for the sheer volume of data generated remain Methods to overcome these pitfalls serve as a strong foundation for the future of PET/MRI. Advances in the underlying technology with significant evolution in hard-ware and software and the exiting developments in use of deep learning algorithms and computational neural networks will drive the next decade of PET/MRI imaging.

The application of multifunctional nanomaterials in Alzheimer's disease: A potential theranostics strategy

By virtue of their small size, nanomaterials can cross the blood-brain barrier and, when modified to target specific cells or regions, can achieve high bioavailability at the intended site of action. Modified nanomaterials are therefore promising agents for the diagnosis and treatment of neurodegenerative diseases such as Alzheimer's disease (AD). Here we review the roles and mechanisms of action of nanomaterials in AD. First, we discuss the general characteristics of nanomaterials and their application to nanomedicine. Then, we summarize recent studies on the diagnosis and treatment of AD using modified nanomaterials. These studies indicate that using nanomaterials is a potential strategy for AD treatment by slowing the progression of AD through enhanced therapeutic effects.

Molecular Imaging of a Zirconium-89 Labeled Antibody Targeting Plasmodium falciparum-Infected Human Erythrocytes

PURPOSE

Nuclear imaging is an important preclinical research tool to study infectious diseases in vivo and could be extended to investigate complex aspects of malaria infections. As such, we report for the first time successful radiolabeling of a novel antibody specific to Plasmodium-infected erythrocytes (IIIB6), its in vitro assessment and molecular imaging in nude mice.

PROCEDURES

In vitro confocal microscopy was used to determine the stage-specificity of Plasmodium-infected erythrocytes recognised by IIIB6. To enable micro-positron emission tomography (PET)/X-ray computed tomography (CT) imaging, IIIB6 was conjugated to Bz-DFO-NCS and subsequently radiolabeled with zirconium-89. Healthy nude mice were injected with [⁸⁹Zr]IIIB6, and pharmacokinetics and organ uptake were monitored over 24 h. This was followed by post-mortem animal dissection to determine the biodistribution of [⁸⁹Zr]IIIB6.

RESULTS

IIIB6 recognised all the relevant stages of Plasmodium falciparum-infected erythrocytes (trophozoites, schizonts and gametocytes) that are responsible for severe malaria pathology. [⁸⁹Zr]IIIB6-radiolabeling yields were efficient at 84-89 %. Blood pool imaging analysis indicated a pharmacological half-life of 9.6 ± 2.5 h for [⁸⁹Zr]IIIB6. The highest standard uptake values were determined at 2-6 h in the liver followed by the spleen, kidneys, heart, stomach and lung, respectively. Minimal activity was present in muscle and bone tissues.

CONCLUSION

In vitro characterization of IIIB6 and pharmacokinetic characterization of [⁸⁹Zr]IIIB6 revealed that this antibody has potential for future use in Plasmodium-infected mouse models to study malaria in a preclinical in vivo setting with PET/CT imaging.

Racial Differences in Alzheimer's Disease Specialist Encounters Are Associated with Usage of Molecular Imaging and Dementia Medications: An Enterprise-Wide Analysis Using i2b2

BACKGROUND

African Americans are at increased risk for Alzheimer's disease (AD) but barriers to optimal clinical care are unclear.

OBJECTIVE

To comprehensively evaluate potential racial differences in the diagnosis and treatment of AD in an academic medical center.

METHODS

We used the clinical informatics tool, i2b2, to analyze all patient encounters for AD or mild cognitive impairment (MCI) in the University of Alabama at Birmingham Health System over a three-year period, examining neuroimaging rates and dementia-related medication use by race and clinic site using ratio tests on contingency tables of stratified patient counts.

RESULTS

Enterprise-wide, African Americans were not underrepresented among outpatients seen for AD/MCI. However, there were differences in the clinic setting where visits occurred, with African Americans overrepresented in Geriatrics and primary care clinics and underrepresented in Memory Disorders specialty clinics. There were no racial differences in the rates at which any clinic ordered PET neuroimaging tests or dementia-related medications. However, unsurprisingly, specialty clinics ordered both PET neuroimaging and dementia-related medications at a higher rate than primary care clinics, and overall across the medical enterprise, African Americans were statistically less likely to have PET neuroimaging or dementia-related medications ordered.

CONCLUSION

African Americans with AD/MCI were not underrepresented at this academic medical center but were somewhat less likely to have PET neuroimaging or to be on dementia-related medications, potentially in part from underrepresentation in the specialty clinics where these orders are more likely. The reasons for this underrepresentation in specialty clinics are likely multifactorial and important to better understand.

Future Imaging in Dementia

Imaging has made an immense contribution toward supporting the diagnosis of dementias, detecting preclinical and prodromal pathology, and allowing disease progression to be objectively tracked. This has led to consensus guidelines for the use of imaging in dementias to be published and a future task will be to validate these guidelines. Additionally, there needs to be standardised approaches over the use of binary thresholds when assigning an abnormality status. Other medical unmet needs include the need for specific imaging markers of (1) linear tau tangles, TDP-43 and alpha synuclein aggregates; (2) microglial phenotypes that throw light on the activity of these inflammatory cells; (3) activity of intracellular processes which normally act to clear misfolded proteins; (4) epigenetic activity which regulates gene expression. Future imaging studies are predicted to be active in all these areas. Finally, as safer and more effective immunotherapy and other protective strategies against the pathologies of dementias are developed and trialed, imaging will play a major future role in determining the efficacy of neuroprotective treatments and their mechanism of action to be examined.

Zero Echo Time MRAC on FDG-PET/MR Maintains Diagnostic Accuracy for Alzheimer's Disease; A Simulation Study Combining ADNI-Data

Aim

Attenuation correction using zero-echo time (ZTE) - magnetic resonance imaging (MRI) (ZTE-MRAC) has become one of the standard methods for brain-positron emission tomography (PET) on commercial PET/MR scanners. Although the accuracy of the net tracer-uptake quantification based on ZTE-MRAC has been validated, that of the diagnosis for dementia has not yet been clarified, especially in terms of automated statistical analysis. The aim of this study was to clarify the impact of ZTE-MRAC on the diagnosis of Alzheimer's disease (AD) by performing simulation study.

Methods

We recruited 27 subjects, who underwent both PET/computed tomography (CT) and PET/MR (GE SIGNA) examinations. Additionally, we extracted 107 subjects from the Alzheimer Disease Neuroimaging Initiative (ADNI) dataset. From the PET raw data acquired on PET/MR, three FDG-PET series were generated, using two vendor-provided MRAC methods (ZTE and Atlas) and CT-based AC. Following spatial normalization to Montreal Neurological Institute (MNI) space, we calculated each patient's specific error maps, which correspond to the difference between the PET image corrected using the CTAC method and the PET images corrected using the MRAC methods. To simulate PET maps as if ADNI data had been corrected using MRAC methods, we multiplied each of these 27 error maps with each of the 107 ADNI cases in MNI space. To evaluate the probability of AD in each resulting image, we calculated a cumulative t-value using a fully automated method which had been validated not only in the original ADNI dataset but several multi-center studies. In the method, PET score = 1 is the 95% prediction limit of AD. PET score and diagnostic accuracy for the discrimination of AD were evaluated in simulated images using the original ADNI dataset as reference.

Results

Positron emission tomography score was slightly underestimated both in ZTE and Atlas group compared with reference CTAC (-0.0796 ± 0.0938 vs. -0.0784 ± 0.1724). The absolute error of PET score was lower in ZTE than Atlas group (0.098 ± 0.075 vs. 0.145 ± 0.122, p < 0.001). A higher correlation to the original PET score was observed in ZTE vs. Atlas group (R ²: 0.982 vs. 0.961). The accuracy for the discrimination of AD patients from normal control was maintained in ZTE and Atlas compared to CTAC (ZTE vs. Atlas. vs. original; 82.5% vs. 82.1% vs. 83.2% (CI 81.8-84.5%), respectively).

Conclusion

For FDG-PET images on PET/MR, attenuation correction using ZTE-MRI had superior accuracy to an atlas-based method in classification for dementia. ZTE maintains the diagnostic accuracy for AD.

Assessment of plaque morphology in Alzheimer's mouse cerebellum using three-dimensional X-ray phase-based virtual histology

Visualization and characterization of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β-amyloid deposits is a fundamental task in pre-clinical study of Alzheimer’s disease (AD) to assess its evolution and monitor the efficiency of new therapeutic strategies. While the cerebellum is one of the brain areas most underestimated in the context of AD, renewed interest in cerebellar lesions has recently arisen as they may link to motor and cognitive alterations. Thus, we quantitatively investigated three-dimensional plaque morphology in the cerebellum in APP/PS1 transgenic mouse, as a model of AD. In order to obtain a complete high-resolution three-dimensional view of the investigated tissue, we exploited synchrotron X-ray phase contrast tomography (XPCT), providing virtual slices with histology-matching resolution. We found the formation of plaques elongated in shape, and with a specific orientation in space depending on the investigated region of the cerebellar cortex. Remarkably, a similar shape is observed in human cerebellum from demented patients. Our findings demonstrate the capability of XPCT in volumetric quantification, supporting the current knowledge about plaque morphology in the cerebellum and the fundamental role of the surrounding tissue in driving their evolution. A good correlation with the human neuropathology is also reported.

Hollow core photonic crystal fiber-assisted Raman spectroscopy as a tool for the detection of Alzheimer's disease biomarkers

SIGNIFICANCE

Alzheimer's disease (AD) is an irreversible and progressive disorder that damages brain cells and impairs the cognitive abilities of the affected. Developing a sensitive and cost-effective method to detect Alzheimer's biomarkers appears vital in both a diagnostic and therapeutic perspective.

AIM

Our goal is to develop a sensitive and reliable tool for detection of amyloid β (1-42) peptide (Aβ42), a major AD biomarker, using fiber-enhanced Raman spectroscopy (FERS).

APPROACH

A hollow core photonic crystal fiber (HCPCF) was integrated with a conventional Raman spectroscopic setup to perform FERS measurements. FERS was then coupled with surface-enhanced Raman spectroscopy (SERS) to further amplify the Raman signal thanks to a combined FERS-SERS assay.

RESULTS

A minimum 20-fold enhancement of the Raman signal of Aβ42 as compared to a conventional Raman spectroscopy scheme was observed using the HCPCF-based light delivery system. The signal was further boosted by decorating the fiber core with gold bipyramids generating an additional SERS effect, resulting in an overall 200 times amplification.

CONCLUSIONS

The results demonstrate that the use of an HCPCF-based platform can provide sharp and intense Raman signals of Aβ42, in turn paving the way toward the development of a sensitive label-free detection tool for early diagnosis of AD.

The impact of atlas-based MR attenuation correction on the diagnosis of FDG-PET/MR for Alzheimer's diseases- A simulation study combining multi-center data and ADNI-data

Background

The purpose of this study was to assess the impact of vendor-provided atlas-based MRAC on FDG PET/MR for the evaluation of Alzheimer’s disease (AD) by using simulated images.

Methods

We recruited 47 patients, from two institutions, who underwent PET/CT and PET/MR (GE SIGNA) examination for oncological staging. From the PET raw data acquired on PET/MR, two FDG-PET series were generated, using vendor-provided MRAC (atlas-based) and CTAC. The following simulation steps were performed in MNI space: After spatial normalization and smoothing of the PET datasets, we calculated the error map for each patient, PET_MRAC/PET_CTAC. We multiplied each of these 47 error maps with each of the 203 Alzheimer’s Disease Neuroimaging Initiative (ADNI) cases after the identical normalization and smoothing. This resulted in 203*47 = 9541 datasets. To evaluate the probability of AD in each resulting image, a cumulative t-value was calculated automatically using commercially-available software (PMOD PALZ) which has been used in multiple large cohort studies. The diagnostic accuracy for the discrimination of AD and predicting progression from mild cognitive impairment (MCI) to AD were evaluated in simulated images compared with ADNI original images.

Results

The accuracy and specificity for the discrimination of AD-patients from normal controls were not substantially impaired, but sensitivity was slightly impaired in 5 out of 47 datasets (original vs. error; 83.2% [CI 75.0%-89.0%], 83.3% [CI 74.2%-89.8%] and 83.1% [CI 75.6%-88.3%] vs. 82.7% [range 80.4–85.0%], 78.5% [range 72.9–83.3%,] and 86.1% [range 81.4–89.8%]). The accuracy, sensitivity and specificity for predicting progression from MCI to AD during 2-year follow-up was not impaired (original vs. error; 62.5% [CI 53.3%-69.3%], 78.8% [CI 65.4%-88.6%] and 54.0% [CI 47.0%-69.1%] vs. 64.8% [range 61.5–66.7%], 75.7% [range 66.7–81.8%,] and 59.0% [range 50.8–63.5%]). The worst 3 error maps show a tendency towards underestimation of PET scores.

Conclusion

FDG-PET/MR based on atlas-based MR attenuation correction showed similar diagnostic accuracy to the CT-based method for the diagnosis of AD and the prediction of progression of MCI to AD using commercially-available software, although with a minor reduction in sensitivity.

Mass spectrometry imaging of free-floating brain sections detects pathological lipid distribution in a mouse model of Alzheimer's-like pathology

Mass spectrometry imaging (MSI) is a modern analytical technique capable of monitoring the spatial distribution of compounds within target tissues. Collection and storage are important steps in sample preparation. The recommended and most widely used preservation procedure for MSI is freezing samples in isopentane and storing them at temperatures below -80 °C. On the other hand, the most common and general method for preserving biological samples in clinical practice is fixation in paraformaldehyde. Special types of samples prepared from these fixed tissues that are used for histology and immunohistochemistry are free-floating sections. It would be very beneficial if the latter procedure could also be applicable for the samples intended for subsequent MSI analysis. In the present work, we optimized and evaluated paraformaldehyde-fixed free-floating sections for the analysis of lipids in mouse brains and used the sections for the study of lipid changes in double transgenic APP/PS1 mice, a model of Alzheimer's-like pathology. Moreover, we examined the neuroprotective properties of palm¹¹-PrRP31, an anorexigenic and glucose-lowering analog of prolactin-releasing peptide, and liraglutide, a type 2 diabetes drug. From the free-floating sections, we obtained lipid images without interference or delocalization, and we demonstrated that free-floating sections can be used for the MSI of lipids. In the APP/PS1 mice, we observed a changed distribution of various lipids compared to the controls. The most significant changes in lipids in the brains of APP/PS1 mice compared to wild-type controls were related to gangliosides (GM2 36:1, GM3 36:1) and phosphatidylinositols (PI 38:4, 36:4) in regions where the accumulation of senile plaques occurred. In APP/PS1 mice peripherally treated with palm¹¹-PrRP31 or liraglutide for 2 months, we found that both peptides reduced the amount and space occupied by lipids, which were linked to the senile plaques. These results indicate that palm¹¹-PrRP31 as well as liraglutide might be potentially useful in the treatment of neurodegenerative diseases.

Multimodal analysis using [11C]PiB-PET/MRI for functional evaluation of patients with Alzheimer's disease

BACKGROUND

Multimodal PET/MRI image data simultaneously obtained from patients with early-stage of Alzheimer's disease (eAD) were assessed in order to observe pathophysiologic and functional changes, as well as alterations of morphology and connectivity in the brain. Fifty-eight patients with mild cognitive impairment and early dementia (29 males, 69 ± 12 years) underwent [¹¹C]Pittsburgh compound-B (PiB) PET/MRI with 70-min PET and MRI scans. Sixteen age-matched healthy controls (CTL) (9 males, 68 ± 11 years) were also studied with the same scanning protocol. Cerebral blood flow (CBF) was calculated from the early phase PET images using the image-derived input function method. A standardized uptake value ratio (SUVr) was calculated from 50 to 70 min PET data with a reference region of the cerebellar cortex. MR images such as 3D-T1WI, resting-state functional MRI (RS-fMRI), diffusion tensor image (DTI), and perfusion MRI acquired during the dynamic PET scan were also analyzed to evaluate various brain functions on MRI.

RESULTS

Twenty-seven of the 58 patients were determined as eAD based on the results of PiB-PET and clinical findings, and a total of 43 subjects' data including CTL were analyzed in this study. PiB SUVr values in all cortical regions of eAD were significantly greater than those of CTL. The PiB accumulation intensity was negatively correlated with cognitive scores. The regional PET-CBF values of eAD were significantly lower in the bilateral parietal lobes and right temporal lobe compared with CTL, but not in MRI perfusion; however, SPM showed regional differences on both PET- and MRI-CBF. SPM analysis of RS-fMRI delineated regional differences between the groups in the anterior cingulate cortex and the left precuneus. VBM analysis showed atrophic changes in the AD group in a part of the bilateral hippocampus; however, analysis of fractional anisotropy calculated from DTI data did not show differences between the two groups.

CONCLUSION

Multimodal analysis conducted with various image data from PiB-PET/MRI scans showed differences in regional CBF, cortical volume, and neuronal networks in different regions, indicating that pathophysiologic and functional changes in the AD brain can be observed from various aspects of neurophysiologic parameters. Application of multimodal brain images using PET/MRI would be ideal for investigating pathophysiologic changes in patients with dementia and other neurodegenerative diseases.

PET image reconstruction using physical and mathematical modelling for time of flight PET-MR scanners in the STIR library

This work demonstrates how computational and physical modelling of the positron emission tomography (PET) image acquisition process for a state-of-the-art integrated PET and magnetic resonance imaging (PET-MR) system can produce images comparable to the manufacturer. The GE SIGNA PET/MR scanner is manufactured by General Electric and has time-of-flight (TOF) capabilities of about 390 ps. All software development took place in the Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) library, which is a widely used open source software to reconstruct data as exported from emission tomography scanners. The new software developments will be integrated into STIR, providing the opportunity for researchers worldwide to establish and expand their image reconstruction methods. Furthermore, this work is of particular significance as it provides the first validation of TOF PET image reconstruction for real scanner datasets using the STIR library. This paper presents the methodology, analysis, and critical issues encountered in implementing an independent reconstruction software package. Acquired PET data were processed via several appropriate algorithms which are necessary to produce an accurate and precise quantitative image. This included mathematical, physical and anatomical modelling of the patient and simulation of various aspects of the acquisition. These included modelling of random coincidences using 'singles' rates per crystals, detector efficiencies and geometric effects. Attenuation effects were calculated by using the STIR's attenuation correction model. Modelling all these effects within the system matrix allowed the reconstruction of PET images which demonstrates the metabolic uptake of the administered radiopharmaceutical. These implementations were validated using measured phantom and clinical datasets. The developments are tested using the ordered subset expectation maximisation (OSEM) and the more recently proposed kernelised expectation maximisation (KEM) algorithm which incorporates anatomical information from MR images into PET reconstruction.

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.

The accuracy of hippocampal volumetry and glucose metabolism for the diagnosis of patients with suspected Alzheimer's disease, using automatic quantitative clinical tools

The hippocampus is one of the earliest sites involved in the pathology of Alzheimer's disease (AD). Therefore, we specifically investigated the sensitivity and specificity of hippocampal volume and glucose metabolism in patients being evaluated for AD, using automated quantitative tools (NeuroQuant - magnetic resonance imaging [MRI] and Scenium - positron emission tomography [PET]) and clinical evaluation.This retrospective study included adult patients over the age of 45 years with suspected AD, who had undergone fluorodeoxyglucose positron emission tomography-computed tomography (FDG-PET-CT) and MRI. FDG-PET-CT images were analyzed both qualitatively and quantitatively. In quantitative volumetric MRI analysis, the percentage of the total intracranial volume of each brain region, as well as the total hippocampal volume, were considered in comparison to an age-adjusted percentile. The remaining brain regions were compared between groups according to the final diagnosis.Thirty-eight patients were included in this study. After a mean follow-up period of 23 ± 11 months, the final diagnosis for 16 patients was AD or high-risk mild cognitive impairment (MCI). Out of the 16 patients, 8 patients were women, and the average age of all patients was 69.38 ± 10.98 years. Among the remaining 22 patients enrolled in the study, 14 were women, and the average age was 67.50 ± 11.60 years; a diagnosis of AD was initially excluded, but the patients may have low-risk MCI. Qualitative FDG-PET-CT analysis showed greater accuracy (0.87), sensitivity (0.76), and negative predictive value (0.77), when compared to quantitative PET analysis, hippocampal MRI volumetry, and specificity. The positive predictive value of FDG-PET-CT was similar to the MRI value.The performance of FDG-PET-CT qualitative analysis was significantly more effective compared to MRI volumetry. At least in part, this observation could corroborate the sequential hypothesis of AD pathophysiology, which posits that functional changes (synaptic dysfunction) precede structural changes (atrophy).

Clinical 18F-FDG and amyloid brain positron emission tomography/CT in the investigation of cognitive impairment: where are we now?

The number of people living with dementia is increasing, but as yet there remains no cure or disease-modifying treatment. This review aims to help readers understand the role of 18F-FDG PET/CT imaging in the investigation of cognitive impairment and how the advent of amyloid PET/CT imaging may hold the key to radically changing management of the most common form of dementia - Alzheimer's disease. The indications for 18F-FDG PET/CT and amyloid PET/CT imaging in cognitive impairment are outlined. Additionally, the mechanisms of action, technique, patient preparation and acquisition parameters for both are detailed. We conclude by providing a framework for interpreting 18F-FDG PET/CT and amyloid PET/CT imaging in the more common conditions that lead to cognitive impairment conditions with tips on avoiding pitfalls in interpretation.

Mercury Involvement in Neuronal Damage and in Neurodegenerative Diseases

Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis are characterized by a chronic and selective process of neuronal cell death. Although the causes of neurodegenerative diseases remain still unknown, it is now a well-established idea that more factors, such as genetic, endogenous, and environmental, are involved. Among environmental causes, the accumulation of mercury, a heavy metal considered a toxic agent, was largely studied as a probable factor involved in neurodegenerative disease course. Mercury exists in three main forms: elemental mercury, inorganic mercury, and organic mercury (methylmercury and ethylmercury). Sources of elemental mercury can be natural (volcanic emission) or anthropogenic (coal-fired electric utilities, waste combustion, hazardous-waste incinerators, and gold extraction). Moreover, mercury is still used as an antiseptic, as a medical preservative, and as a fungicide. Dental amalgam can emit mercury vapor. Mercury vapor, being highly volatile and lipid soluble, can cross the blood-brain barrier and the lipid cell membranes and can be accumulated into the cells in its inorganic forms. Also, methylmercury can pass through blood-brain and placental barriers, causing serious damage in the central nervous system. This review describes the toxic effects of mercury in cell cultures, in animal models, and in patients with neurodegenerative diseases. In vitro experiments showed that mercury exposure was principally involved in oxidative stress and apoptotic processes. Moreover, motor and cognitive impairment and neural loss have been confirmed in various studies performed in animal models. Finally, observational studies on patients with neurodegenerative diseases showed discordant data about a possible mercury involvement.

Neuroimaging and Neurolaw: Drawing the Future of Aging

Human brain-aging is a complex, multidimensional phenomenon. Knowledge of the numerous aspects that revolve around it is therefore essential if not only the medical issues, but also the social, psychological, and legal issues related to this phenomenon are to be managed correctly. In the coming decades, it will be necessary to find solutions to the management of the progressive aging of the population so as to increase the number of individuals that achieve successful aging. The aim of this article is to provide a current overview of the physiopathology of brain aging and of the role and perspectives of neuroimaging in this context. The progressive development of neuroimaging has opened new perspectives in clinical and basic research and it has modified the concept of brain aging. Neuroimaging will play an increasingly important role in the definition of the individual's brain aging in every phase of the physiological and pathological process. However, when the process involved in age-related brain cognitive diseases is being investigated, factors that might affect this process on a clinical and behavioral level (genetic susceptibility, risks factors, endocrine changes) cannot be ignored but must, on the contrary, be integrated into a neuroimaging evaluation to ensure a correct and global management, and they are therefore discussed in this article. Neuroimaging appears important to the correct management of age-related brain cognitive diseases not only within a medical perspective, but also legal, according to a wider approach based on development of relationship between neuroscience and law. The term neurolaw, the neologism born from the relationship between these two disciplines, is an emerging field of study, that deals with various issues in the impact of neurosciences on individual rights. Neuroimaging, enhancing the detection of physiological and pathological brain aging, could give an important contribution to the field of neurolaw in elderly where the full control of cognitive and volitional functions is necessary to maintain a whole series of rights linked to legal capacity. For this reason, in order to provide the clinician and researcher with a broad view of the brain-aging process, the role of neurolaw will be introduced into the brain-aging context.

In vivo Brainstem Imaging in Alzheimer's Disease: Potential for Biomarker Development

The dearth of effective treatments for Alzheimer's disease (AD) is one of the largest public health issues worldwide, costing hundreds of billions of dollars per year. From a therapeutic standpoint, research efforts to date have met with strikingly little clinical success. One major issue is that trials begin after substantial pathological change has occurred, and it is increasingly clear that the most effective treatment regimens will need to be administered earlier in the disease process. In order to identify individuals within the long preclinical phase of AD who are likely to progress to dementia, improvements are required in biomarker development. One potential area of research that might prove fruitful in this regard is the in vivo detection of brainstem pathology. The brainstem is known to undergo pathological changes very early and progressively in AD. With an updated and harmonized AD research framework, and emerging advances in neuroimaging technology, the potential to leverage knowledge of brainstem pathology into biomarkers for AD will be discussed.

PET/MRI Hybrid Systems

Over the last decade, the combination of PET and MRI in one system has proven to be highly successful in basic preclinical research, as well as in clinical research. Nowadays, PET/MRI systems are well established in preclinical imaging and are progressing into clinical applications to provide further insights into specific diseases, therapeutic assessments, and biological pathways. Certain challenges in terms of hardware had to be resolved concurrently with the development of new techniques to be able to reach the full potential of both combined techniques. This review provides an overview of these challenges and describes the opportunities that simultaneous PET/MRI systems can exploit in comparison with stand-alone or other combined hybrid systems. New approaches were developed for simultaneous PET/MRI systems to correct for attenuation of 511 keV photons because MRI does not provide direct information on gamma photon attenuation properties. Furthermore, new algorithms to correct for motion were developed, because MRI can accurately detect motion with high temporal resolution. The additional information gained by the MRI can be employed to correct for partial volume effects as well. The development of new detector designs in combination with fast-decaying scintillator crystal materials enabled time-of-flight detection and incorporation in the reconstruction algorithms. Furthermore, this review lists the currently commercially available systems both for preclinical and clinical imaging and provides an overview of applications in both fields. In this regard, special emphasis has been placed on data analysis and the potential for both modalities to evolve with advanced image analysis tools, such as cluster analysis and machine learning.