Hybrid PET/MR Imaging and Brain Connectivity

Connectome-based predictive modeling of brain pathology and cognition in Autosomal Dominant Alzheimer's Disease

INTRODUCTION

Autosomal Dominant Alzheimer's Disease (ADAD) through genetic mutations can result in near complete expression of the disease. Tracking AD pathology development in an ADAD cohort of Presenilin-1 (PSEN1) E280A carriers' mutation has allowed us to observe incipient tau tangles accumulation as early as 6 years prior to symptom onset.

METHODS

Resting-state functional Magnetic Resonance Imaging (fMRI) and Positron-Emission Tomography (PET) scans were acquired in a group of PSEN1 carriers (n=32) and non-carrier family members (n=35). We applied Connectome-based Predictive Modeling (CPM) to examine the relationship between the participant's functional connectome and their respective tau/amyloid-β levels and cognitive scores (word list recall).

RESULTS

CPM models strongly predicted tau concentrations and cognitive scores within the carrier group. The connectivity patterns between the temporal cortex, default mode network, and other memory networks were the most informative of tau burden.

DISCUSSION

These results indicate that resting-state fMRI methods can complement PET methods in early detection and monitoring of disease progression in ADAD.

Evolving Radiological Approaches in the Diagnosis and Monitoring of Arachnoiditis Ossificans

Arachnoiditis ossificans (AO) is a rare and complex neurological condition characterized by pathological calcification or ossification of the arachnoid membrane. Arachnoiditis ranks as the third most frequent cause of failed back surgery syndrome (FBSS). This narrative review explores the evolving radiological approaches in its diagnosis and monitoring. The historical perspective traces the progression from plain radiographs to advanced imaging techniques. Current radiological modalities, including X-ray, computed tomography (CT), and magnetic resonance imaging (MRI), are discussed, highlighting their respective roles, advantages, and limitations. Emerging and advanced imaging modalities, such as high-resolution CT, 3T and 7T MRI, and PET/CT or PET/MRI, are examined for their potential to enhance diagnostic accuracy and monitoring capabilities. A comparative analysis of these imaging modalities considers their sensitivity, specificity, cost-effectiveness, and radiation exposure implications. The review also explores the crucial role of imaging in disease monitoring and treatment planning, including follow-up protocols, evaluation of disease progression, and guidance for interventional procedures. Future directions in the field are discussed, focusing on promising research areas, the potential of artificial intelligence and machine learning in image analysis, and identified gaps in current knowledge. The review emphasizes the importance of a multimodal imaging approach and the need for standardized protocols. It concludes that while significant advancements have been made, further research is necessary to fully understand the correlation between imaging findings and clinical outcomes. The continued evolution of radiological approaches is expected to significantly improve patient care and outcomes in AO.

The Prognostic Significance of Pontine-White Matter Score in Primary Central Nervous System Lymphoma Patients

BACKGROUND

Limited data exist on the significance of PET imaging and quantitative PET parameters in primary central nervous system (CNS) lymphoma due to its relative rarity. This study was conducted to investigate the prognostic value of a novel internal standardization indicator, the pontine-white matter (PW) score, in primary CNS lymphoma patients undergoing post-treatment 18F-FDG PET/CT and PET/MR imaging.

METHODS

From January 2014 to December 2022, eligible patients with primary CNS lymphoma who underwent post-treatment PET imaging were enrolled. Using the FDG uptake of the pons and white matter as an internal reference, the PW score was graded based on the metabolism of the post-therapeutic lesion for each patient, and its associations with patients' prognosis were investigated.

RESULTS

In total, 41 patients with post-treatment PET/CT and 49 patients with post-treatment PET/MR imaging were enrolled. ROC curve analysis indicated that the PW score possessed robust discriminative ability in distinguishing patients with worse outcomes. Furthermore, a higher PW score was significantly correlated with and identified as an independent prognostic indicator for, worse prognosis in both the PET/CT and PET/MR cohorts.

CONCLUSION

The study demonstrated that the PW score was an effective prognostic indicator for identifying post-treatment primary CNS lymphoma patients with worse outcomes.

MRI compatibility study of a prototype radiofrequency penetrable oval PET insert at 3 T

PURPOSE

To perform an MRI compatibility study of an RF field-penetrable oval-shaped PET insert that implements an MRI built-in body RF coil both as a transmitter and a receiver.

METHODS

Twelve electrically floating RF shielded PET detector modules were used to construct the prototype oval PET insert with a major axis of 440 mm, a minor axis of 350 mm, and an axial length of 225 mm. The electric floating of the PET detector modules was accomplished by isolating the cable shield from the detector shield using plastic tape. Studies were conducted on the transmit (B1) RF field, the image signal-to-noise ratio (SNR), and the RF pulse amplitude for a homogeneous cylindrical (diameter: 160 mm and length: 260 mm) phantom (NaCl + NiSO4 solution) in a 3 T clinical MRI system (Verio, Siemens, Erlangen, Germany).

RESULTS

The B1 maps for the oval insert were similar to the MRI-only field responses. Compared to the MRI-only values, SNR reductions of 51%, 45%, and 59% were seen, respectively, for the spin echo (SE), gradient echo (GE), and echo planar (EPI) images for the case of oval PET insert. Moreover, the required RF pulse amplitudes for the SE, GE, and EPI sequences were, respectively, 1.93, 1.85, and 1.36 times larger. However, a 30% reduction in the average RF reception sensitivity was observed for the oval insert.

CONCLUSIONS

The prototype floating PET insert was a safety concern for the clinical MRI system, and this compatibility study provided clearance for developing a large body size floating PET insert for the existing MRI system. Because of the RF shield of the insert, relatively large RF powers compared to the MRI-only case were required. Because of this and also due to low RF sensitivity of the body coil, the SNRs reduced largely.

A novel method for PET connectomics guided by fibre-tracking MRI: Application to Alzheimer's disease

This study introduces a novel brain connectome matrix, track-weighted PET connectivity (twPC) matrix, which combines positron emission tomography (PET) and diffusion magnetic resonance imaging data to compute a PET-weighted connectome at the individual subject level. The new method is applied to characterise connectivity changes in the Alzheimer's disease (AD) continuum. The proposed twPC samples PET tracer uptake guided by the underlying white matter fibre-tracking streamline point-to-point connectivity calculated from diffusion MRI (dMRI). Using tau-PET, dMRI and T1-weighted MRI from the Alzheimer's Disease Neuroimaging Initiative database, structural connectivity (SC) and twPC matrices were computed and analysed using the network-based statistic (NBS) technique to examine topological alterations in early mild cognitive impairment (MCI), late MCI and AD participants. Correlation analysis was also performed to explore the coupling between SC and twPC. The NBS analysis revealed progressive topological alterations in both SC and twPC as cognitive decline progressed along the continuum. Compared to healthy controls, networks with decreased SC were identified in late MCI and AD, and networks with increased twPC were identified in early MCI, late MCI and AD. The altered network topologies were mostly different between twPC and SC, although with several common edges largely involving the bilateral hippocampus, fusiform gyrus and entorhinal cortex. Negative correlations were observed between twPC and SC across all subject groups, although displaying an overall reduction in the strength of anti-correlation with disease progression. twPC provides a new means for analysing subject-specific PET and MRI-derived information within a hybrid connectome using established network analysis methods, providing valuable insights into the relationship between structural connections and molecular distributions. PRACTITIONER POINTS: New method is proposed to compute patient-specific PET connectome guided by MRI fibre-tracking. Track-weighted PET connectivity (twPC) matrix allows to leverage PET and structural connectivity information. twPC was applied to dementia, to characterise the PET nework abnormalities in Alzheimer's disease and mild cognitive impairment.

The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives

Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus-a discrete cortical area from which seizures originate-to a widespread epileptic network-spanning lobes and hemispheres-considerably advanced our understanding of epilepsy and continues to influence both research and clinical treatment of this multi-faceted high-impact neurological disorder. The epileptic network, however, is not static but evolves in time which requires novel approaches for an in-depth characterization. In this review, we discuss conceptual basics of network theory and critically examine state-of-the-art recording techniques and analysis tools used to assess and characterize a time-evolving human epileptic brain network. We give an account on current shortcomings and highlight potential developments towards an improved clinical management of epilepsy.

Depletion and activation of microglia impact metabolic connectivity of the mouse brain

AIM

We aimed to investigate the impact of microglial activity and microglial FDG uptake on metabolic connectivity, since microglial activation states determine FDG-PET alterations. Metabolic connectivity refers to a concept of interacting metabolic brain regions and receives growing interest in approaching complex cerebral metabolic networks in neurodegenerative diseases. However, underlying sources of metabolic connectivity remain to be elucidated.

MATERIALS AND METHODS

We analyzed metabolic networks measured by interregional correlation coefficients (ICCs) of FDG-PET scans in WT mice and in mice with mutations in progranulin (Grn) or triggering receptor expressed on myeloid cells 2 (Trem2) knockouts (^-/-) as well as in double mutant Grn^-/-/Trem2^-/- mice. We selected those rodent models as they represent opposite microglial signatures with disease associated microglia in Grn^-/- mice and microglia locked in a homeostatic state in Trem2^-/- mice; however, both resulting in lower glucose uptake of the brain. The direct influence of microglia on metabolic networks was further determined by microglia depletion using a CSF1R inhibitor in WT mice at two different ages. Within maps of global mean scaled regional FDG uptake, 24 pre-established volumes of interest were applied and assigned to either cortical or subcortical networks. ICCs of all region pairs were calculated and z-transformed prior to group comparisons. FDG uptake of neurons, microglia, and astrocytes was determined in Grn^-/- and WT mice via assessment of single cell tracer uptake (scRadiotracing).

RESULTS

Microglia depletion by CSF1R inhibition resulted in a strong decrease of metabolic connectivity defined by decrease of mean cortical ICCs in WT mice at both ages studied (6-7 m; p = 0.0148, 9-10 m; p = 0.0191), when compared to vehicle-treated age-matched WT mice. Grn^-/-, Trem2^-/- and Grn^-/-/Trem2^-/- mice all displayed reduced FDG-PET signals when compared to WT mice. However, when analyzing metabolic networks, a distinct increase of ICCs was observed in Grn^-/- mice when compared to WT mice in cortical (p < 0.0001) and hippocampal (p < 0.0001) networks. In contrast, Trem2^-/- mice did not show significant alterations in metabolic connectivity when compared to WT. Furthermore, the increased metabolic connectivity in Grn^-/- mice was completely suppressed in Grn^-/-/Trem2^-/- mice. Grn^-/- mice exhibited a severe loss of neuronal FDG uptake (- 61%, p < 0.0001) which shifted allocation of cellular brain FDG uptake to microglia (42% in Grn^-/- vs. 22% in WT).

CONCLUSIONS

Presence, absence, and activation of microglia have a strong impact on metabolic connectivity of the mouse brain. Enhanced metabolic connectivity is associated with increased microglial FDG allocation.

Relationships between serotonin availability and frontolimbic response to fearful and threatening faces

Serotonin is a critical neurotransmitter in the regulation of emotional behavior. Although emotion processing is known to engage a corticolimbic circuit, including the amygdala and prefrontal cortex, exactly how this brain system is modulated by serotonin remains unclear. Here, we hypothesized that serotonin modulates variability in excitability and functional connectivity within this circuit. We tested whether this modulation contributes to inter-individual differences in emotion processing. Using a multimodal neuroimaging approach with a simultaneous PET-3T fMRI scanner, we simultaneously acquired BOLD signal while participants viewed emotional faces depicting fear and anger, while also measuring serotonin transporter (SERT) levels, regulating serotonin functions. Individuals with higher activity of the medial amygdala BOLD in response to fearful or angry facial expressions, who were temperamentally more anxious, also exhibited lower SERT availability in the dorsal raphe nucleus (DRN). Moreover, higher connectivity of the medial amygdala with the left dorsolateral prefrontal and the anterior cingulate cortex was associated with lower levels of SERT availability in the DRN. These results demonstrate the association between the serotonin transporter level and emotion processing through changes in functional interactions between the amygdala and the prefrontal areas in healthy humans.

Simultaneous electroencephalography-functional magnetic resonance imaging for assessment of human brain function

Electroencephalography (EEG) and functional Magnetic Resonance Imaging (MRI) have long been used as tools to examine brain activity. Since both methods are very sensitive to changes of synaptic activity, simultaneous recording of EEG and fMRI can provide both high temporal and spatial resolution. Therefore, the two modalities are now integrated into a hybrid tool, EEG-fMRI, which encapsulates the useful properties of the two. Among other benefits, EEG-fMRI can contribute to a better understanding of brain connectivity and networks. This review lays its focus on the methodologies applied in performing EEG-fMRI studies, namely techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. We will investigate simultaneous resting-state and task-based EEG-fMRI studies and discuss their clinical and technological perspectives. Moreover, it is established that the brain regions affected by a task-based neural activity might not be limited to the regions in which they have been initiated. Advanced methods can help reveal the regions responsible for or affected by a developed neural network. Therefore, we have also looked into studies related to characterization of structure and dynamics of brain networks. The reviewed literature suggests that EEG-fMRI can provide valuable complementary information about brain neural networks and functions.

Hemodynamic and metabolic correspondence of resting-state voxel-based physiological metrics in healthy adults

Voxel-based physiological (VBP) variables derived from blood oxygen level dependent (BOLD) fMRI time-course variations include: amplitude of low frequency fluctuations (ALFF), fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity (ReHo). Although these BOLD-derived variables can detect between-group (e.g. disease vs control) spatial pattern differences, physiological interpretations are not well established. The primary objective of this study was to quantify spatial correspondences between BOLD VBP variables and PET measurements of cerebral metabolic rate and hemodynamics, being well-validated physiological standards. To this end, quantitative, whole-brain PET images of metabolic rate of glucose (MRGlu; 18FDG) and oxygen (MRO2; 15OO), blood flow (BF; H215O) and blood volume (BV; C15O) were obtained in 16 healthy controls. In the same subjects, BOLD time-courses were obtained for computation of ALFF, fALFF and ReHo images. PET variables were compared pair-wise with BOLD variables. In group-averaged, across-region analyses, ALFF corresponded significantly only with BV (R = 0.64; p < 0.0001). fALFF corresponded most strongly with MRGlu (R = 0.79; p < 0.0001), but also significantly (p < 0.0001) with MRO2 (R = 0.68), BF (R = 0.68) and BV (R=0.68). ReHo performed similarly to fALFF, with significant strong correspondence (p < 0.0001) with MRGlu (R = 0.78), MRO2 (R = 0.54), and, but less strongly with BF (R = 0.50) and BV (R=0.50). Mutual information analyses further clarified these physiological interpretations. When conditioned by BV, ALFF retained no significant MRGlu, MRO2 or BF information. When conditioned by MRGlu, fALFF and ReHo retained no significant MRO2, BF or BV information. Of concern, however, the strength of PET-BOLD correspondences varied markedly by brain region, which calls for future investigation on physiological interpretations at a regional and per-subject basis.

Structural Brain Network Reproducibility: Influence of Different Diffusion Acquisition and Tractography Reconstruction Schemes on Graph Metrics

Background: Graph metrics of structural brain networks demonstrate to be a powerful tool for investigating brain topology at a large scale. However, the variability of the results related to applying different magnetic resonance acquisition schemes and tractography reconstruction techniques is not fully characterized. Materials and Methods: The present work aims to evaluate the influence of different combinations of diffusion acquisition schemes (single and multishell), diffusion models (tensor and spherical deconvolution), and tractography reconstruction approaches (deterministic and probabilistic) on the reproducibility of graph metrics derived from structural connectome on test/retest (TRT) data released by the Human Connectome Project. From each implemented experimental setup, both global and local graph metrics were evaluated and their reproducibility was estimated by the intraclass correlation coefficient (ICC). Moreover, the percentage relative standard deviation (pRSD) from the ICC values of local graph metrics was calculated to quantify how much the reproducibility varied across nodes within each experimental setup. Results: The presented results show that different combinations of diffusion acquisition schemes, diffusion models, and tractography algorithms can strongly affect the reproducibility of global and local graph metrics. The combination of constrained spherical deconvolution (CSD) and deterministic tractography gave generally high reproducibility (ICCs >0.75) and lowest pRSD for the considered graph metrics, meanwhile probabilistic CSD with a high b-value returned the highest reproducibility. Notably, the introduction of streamline selection filters on CSD can substantially affect the reproducibility. Discussion: This work demonstrates that the TRT reproducibility of graph metrics is generally high but can vary substantially with different combinations of acquisition and reconstruction schemes. Impact statement This work demonstrates the influence of different diffusion acquisition schemes, diffusion models, and tractography reconstruction approaches on the reproducibility of graph metrics derived from structural connectome. The presented findings impact on the choice of both acquisition protocol and processing pipeline for topological analyses to produce reproducible measurements for brain network studies.

How does DICOM support big data management? Investigating its use in medical imaging community

The diagnostic imaging field is experiencing considerable growth, followed by increasing production of massive amounts of data. The lack of standardization and privacy concerns are considered the main barriers to big data capitalization. This work aims to verify whether the advanced features of the DICOM standard, beyond imaging data storage, are effectively used in research practice. This issue will be analyzed by investigating the publicly shared medical imaging databases and assessing how much the most common medical imaging software tools support DICOM in all its potential. Therefore, 100 public databases and ten medical imaging software tools were selected and examined using a systematic approach. In particular, the DICOM fields related to privacy, segmentation and reporting have been assessed in the selected database; software tools have been evaluated for reading and writing the same DICOM fields. From our analysis, less than a third of the databases examined use the DICOM format to record meaningful information to manage the images. Regarding software, the vast majority does not allow the management, reading and writing of some or all the DICOM fields. Surprisingly, if we observe chest computed tomography data sharing to address the COVID-19 emergency, there are only two datasets out of 12 released in DICOM format. Our work shows how the DICOM can potentially fully support big data management; however, further efforts are still needed from the scientific and technological community to promote the use of the existing standard, encouraging data sharing and interoperability for a concrete development of big data analytics.

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.

Altered coupling between resting-state glucose metabolism and functional activity in epilepsy

OBJECTIVE

Altered functional activities and hypometabolism have been found in medial temporal lobe epilepsy patients with hippocampal sclerosis (mTLE-HS). Hybrid PET/MR scanners provide opportunities to explore the relationship between resting-state energy consumption and functional activities, but whether repeated seizures disturb the bioenergetic coupling and its relationship with seizure outcomes remain unknown.

METHODS

¹⁸ F-FDG PET and resting-state functional MRI (rs-fMRI) scans were performed with hybrid PET/MR in 26 patients with mTLE-HS and in healthy controls. Energy consumption was quantified by ¹⁸ F-FDG standardized uptake value ratio(SUVR) relative to cerebellum. Spontaneous neural activities were estimated using regional homogeneity (ReHo), fractional amplitude of low frequency fluctuations (fALFF) from rs-fMRI. Between-group differences in SUVR and rs-fMRI derived metrics were evaluated by two-sample t test. Voxel-wise spatial correlations were explored between SUVR and ReHo, fALFF across gray matter and compared between groups. Furthermore, the relationships between altered fALFF/SUVR and ReHo/SUVR coupling and surgical outcomes were evaluated.

RESULTS

Both the patients and healthy controls showed significant positive correlations between SUVR and rs-fMRI metrics. Spatial correlations between SUVR and fMRI-derived metrics across gray matter were significantly higher in patients with mTLE-HS compared with healthy controls (fALFF/SUVR, P < 0.001; ReHo/SUVR, P = 0.022). Higher fALFF/SUVR couplings were found in patients who had Engel class IA after surgery than all other (P = 0.025), while altered ReHo/SUVR couplings (P = 0.097) were not.

CONCLUSION

These findings demonstrated altered bioenergetic coupling across gray matter and its relationship with seizure outcomes, which may provide novel insights into pathogenesis of mTLE-HS and potential biomarkers for epilepsy surgery planning.

Gliosis and Neurodegenerative Diseases: The Role of PET and MR Imaging

Glial activation characterizes most neurodegenerative and psychiatric diseases, often anticipating clinical manifestations and macroscopical brain alterations. Although imaging techniques have improved diagnostic accuracy in many neurological conditions, often supporting diagnosis, prognosis prediction and treatment outcome, very few molecular imaging probes, specifically focused on microglial and astrocytic activation, have been translated to a clinical setting. In this context, hybrid positron emission tomography (PET)/magnetic resonance (MR) scanners represent the most advanced tool for molecular imaging, combining the functional specificity of PET radiotracers (e.g., targeting metabolism, hypoxia, and inflammation) to both high-resolution and multiparametric information derived by MR in a single imaging acquisition session. This simultaneity of findings achievable by PET/MR, if useful for reciprocal technical adjustments regarding temporal and spatial cross-modal alignment/synchronization, opens still debated issues about its clinical value in neurological patients, possibly incompliant and highly variable from a clinical point of view. While several preclinical and clinical studies have investigated the sensitivity of PET tracers to track microglial (mainly TSPO ligands) and astrocytic (mainly MAOB ligands) activation, less studies have focused on MR specificity to this topic (e.g., through the assessment of diffusion properties and T2 relaxometry), and only few exploiting the integration of simultaneous hybrid acquisition. This review aims at summarizing and critically review the current state about PET and MR imaging for glial targets, as well as the potential added value of hybrid scanners for characterizing microglial and astrocytic activation.

Neuroimaging of Narcolepsy and Primary Hypersomnias

Advances in neuroimaging open up the possibility for new powerful tools to be developed that potentially can be applied to clinical populations to improve the diagnosis of neurological disorders, including sleep disorders. At present, the diagnosis of narcolepsy and primary hypersomnias is largely limited to subjective assessments and objective measurements of behavior and sleep physiology. In this review, we focus on recent neuroimaging findings that provide insight into the neural basis of narcolepsy and the primary hypersomnias Kleine-Levin syndrome and idiopathic hypersomnia. We describe the role of neuroimaging in confirming previous genetic, neurochemical, and neurophysiological findings and highlight studies that permit a greater understanding of the symptoms of these sleep disorders. We conclude by considering some of the remaining challenges to overcome, the existing knowledge gaps, and the potential role for neuroimaging in understanding the pathogenesis and clinical features of narcolepsy and primary hypersomnias.

Changes over the years in radiopharmaceutical design

Of the many uses of radiopharmaceuticals, developing radiotracers that contribute significantly to diagnosis and therapy of patients has been a major focus. This requires a broad spectrum of expertise including that of the attending physician who lends insight to an unmet clinical need neither addressed by other imaging techniques nor by analysis of tissue, blood, and urine for diagnostics and addressed by pharmaceuticals for therapeutic applications. The design criteria have depended on radiochemistry, on matching the radiopharmaceutical with the imaging devices, and basing the design on current pharmaceuticals. The chelates of technetium-99m were based on radiochemistry rather than clinical need yet are still used today in >70% of the clinical studies. Targeted radiotracers in neurologic and psychiatric disorders, inflammation, cardiovascular disease, and oncology have all been studied with the goal of determining the change in the density of a target protein as a function of disease or treatment or, especially in oncology, detection of the total extent of disease. In latter approach PET in university settings leads the way; however, the use of SPECT/CT has increased the specificity of SPECT imaging to complement the cost- effective generator and instant kits already available. Remarkable advances has been achieved in radionuclide therapy using theragnostic agents, with the exclusive domain of oncology For this application the design of radionuclide therapy follows that used for diagnostics. The increased impact of the discipline depends on the opportunity to continue the search for the most appropriate radiopharmaceutical for each individual patient.

Twenty years on: Myoclonus-dystonia and ε-sarcoglycan - neurodevelopment, channel, and signaling dysfunction

Myoclonus-dystonia is a clinical syndrome characterized by a typical childhood onset of myoclonic jerks and dystonia involving the neck, trunk, and upper limbs. Psychiatric symptomatology, namely, alcohol dependence and phobic and obsessive-compulsive disorder, is also part of the clinical picture. Zonisamide has demonstrated effectiveness at reducing both myoclonus and dystonia, and deep brain stimulation seems to be an effective and long-lasting therapeutic option for medication-refractory cases. In a subset of patients, myoclonus-dystonia is associated with pathogenic variants in the epsilon-sarcoglycan gene, located on chromosome 7q21, and up to now, more than 100 different pathogenic variants of the epsilon-sarcoglycan gene have been described. In a few families with a clinical phenotype resembling myoclonus-dystonia associated with distinct clinical features, variants have been identified in genes involved in novel pathways such as calcium channel regulation and neurodevelopment. Because of phenotypic similarities with epsilon-sarcoglycan gene-related myoclonus-dystonia, these conditions can be collectively classified as "myoclonus-dystonia syndromes." In the present article, we present myoclonus-dystonia caused by epsilon-sarcoglycan gene mutations, with a focus on genetics and underlying disease mechanisms. Second, we review those conditions falling within the spectrum of myoclonus-dystonia syndromes, highlighting their genetic background and involved pathways. Finally, we critically discuss the normal and pathological function of the epsilon-sarcoglycan gene and its product, suggesting a role in the stabilization of the dopaminergic membrane via regulation of calcium homeostasis and in the neurodevelopmental process involving the cerebello-thalamo-pallido-cortical network. © 2019 International Parkinson and Movement Disorder Society.

Simultaneous EEG-fMRI for Functional Neurological Assessment

The increasing incidence of neurodegenerative and psychiatric diseases requires increasingly sophisticated tools for their diagnosis and monitoring. Clinical assessment takes advantage of objective parameters extracted by electroencephalogram and magnetic resonance imaging (MRI) among others, to support clinical management of neurological diseases. The complementarity of these two tools can be now emphasized by the possibility of integrating the two technologies in a hybrid solution, allowing simultaneous acquisition of the two signals by the novel EEG-fMRI technology. This review will focus on simultaneous EEG-fMRI technology and related early studies, dealing about issues related to the acquisition and processing of simultaneous signals, and including critical discussion about clinical and technological perspectives.

MRI-Driven PET Image Optimization for Neurological Applications

Positron emission tomography (PET) and magnetic resonance imaging (MRI) are established imaging modalities for the study of neurological disorders, such as epilepsy, dementia, psychiatric disorders and so on. Since these two available modalities vary in imaging principle and physical performance, each technique has its own advantages and disadvantages over the other. To acquire the mutual complementary information and reinforce each other, there is a need for the fusion of PET and MRI. This combined dual-modality (either sequential or simultaneous) could generate preferable soft tissue contrast of brain tissue, flexible acquisition parameters, and minimized exposure to radiation. The most unique superiority of PET/MRI is mainly manifested in MRI-based improvement for the inherent limitations of PET, such as motion artifacts, partial volume effect (PVE) and invasive procedure in quantitative analysis. Head motion during scanning significantly deteriorates the effective resolution of PET image, especially for the dynamic scan with lengthy time. Hybrid PET/MRI device can offer motion correction (MC) for PET data through MRI information acquired simultaneously. Regarding the PVE associated with limited spatial resolution, the process and reconstruction of PET data can be further optimized by using acquired MRI either sequentially or simultaneously. The quantitative analysis of dynamic PET data mainly relies upon an invasive arterial blood sampling procedure to acquire arterial input function (AIF). An image-derived input function (IDIF) method without the need of arterial cannulization, can serve as a potential alternative estimation of AIF. Compared with using PET data only, combining anatomical or functional information from MRI for improving the accuracy in IDIF approach has been demonstrated. Yet, due to the interference and inherent disparity between the two modalities, these methods for optimizing PET image based on MRI still have many technical challenges. This review discussed upon the most recent progress, current challenges and future directions of MRI-driven PET data optimization for neurological applications, with either sequential or simultaneous acquisition approach.

Evaluation of Functional Connectivity in the Brain Using Positron Emission Tomography: A Mini-Review

Resting-state networks (RSNs) exhibit spontaneous functional connectivity in the resting state. Previous studies have evaluated RSNs mainly based on spontaneous fluctuations in blood oxygenation level-dependent (BOLD) signals during functional magnetic resonance imaging (fMRI). However, separation between regional increases in cerebral blood flow (CBF) and oxygen consumption is theoretically difficult using BOLD-fMRI. Such separation can be achieved using quantitative ¹⁵O-gas and water positron emission tomography (PET). In addition, ¹⁸F-FDG PET can be used to investigate functional connectivity based on changes in glucose metabolism, which reflects local brain activity. Previous studies have highlighted the feasibility and clinical usefulness of ¹⁸F-FDG-PET for the analysis of RSNs, and recent studies have utilized simultaneous PET/fMRI for such analyses. While PET provides seed information regarding the focus of the abnormalities (e.g., hypometabolism and reduced target binding), fMRI is used for the analysis of functional connectivity. Thus, as PET and fMRI provide different types of information, integrating these modalities may aid in elucidating the pathological mechanisms underlying certain diseases, and in characterizing individual patients.

The Challenges of Diagnostic Imaging in the Era of Big Data

The diagnostic imaging field has undergone considerable growth both in terms of technological development and market expansion; with the following increasing production of a considerable amount of data that potentially fully poses diagnostic imaging in the Big data in the context of healthcare. Nevertheless, the mere production of a large amount of data does not automatically permit the real exploitation of their intrinsic value. Therefore, it is necessary to develop digital platforms and applications that favor the correct and advantageous management of diagnostic images such as Big data. This work aims to frame the role of diagnostic imaging in this new scenario, emphasizing the open challenges in exploiting such intense data generation for decision making with Big data analytics.

A multi-parametric PET/MRI study of breast cancer: Evaluation of DCE-MRI pharmacokinetic models and correlation with diffusion and functional parameters

46 patients with histologically confirmed breast cancer were enrolled and imaged with a 3T hybrid PET/MRI system, at staging. Diffusion, functional and perfusion parameters (measured by Tofts and shutter speed models) were compared. Results showed a good correlation between pharmacokinetic parameters and the SUV.

Accurate hybrid template-based and MR-based attenuation correction using UTE images for simultaneous PET/MR brain imaging applications

Background

Attenuation correction is one of the most crucial correction factors for accurate PET data quantitation in hybrid PET/MR scanners, and computing accurate attenuation coefficient maps from MR brain acquisitions is challenging. Here, we develop a method for accurate bone and air segmentation using MR ultrashort echo time (UTE) images.

Methods

MR UTE images from simultaneous MR and PET imaging of five healthy volunteers was used to generate a whole head, bone and air template image for inclusion into an improved MR derived attenuation correction map, and applied to PET image data for quantitative analysis. Bone, air and soft tissue were segmented based on Gaussian Mixture Models with probabilistic tissue maps as a priori information. We present results for two approaches for bone attenuation coefficient assignments: one using a constant attenuation correction value; and another using an estimated continuous attenuation value based on a calibration fit. Quantitative comparisons were performed to evaluate the accuracy of the reconstructed PET images, with respect to a reference image reconstructed with manually segmented attenuation maps.

Results

The DICE coefficient analysis for the air and bone regions in the images demonstrated improvements compared to the UTE approach, and other state-of-the-art techniques. The most accurate whole brain and regional brain analyses were obtained using constant bone attenuation coefficient values.

Conclusions

A novel attenuation correction method for PET data reconstruction is proposed. Analyses show improvements in the quantitative accuracy of the reconstructed PET images compared to other state-of-the-art AC methods for simultaneous PET/MR scanners. Further evaluation is needed with radiopharmaceuticals other than FDG, and in larger cohorts of participants.

Neuroimaging in Fabry disease: current knowledge and future directions

Abstract

Fabry disease (FD) is a rare X-linked disorder characterised by abnormal progressive lysosomal deposition of globotriaosylceramide in a large variety of cell types. The central nervous system (CNS) is often involved in FD, with a wide spectrum of manifestations ranging from mild symptoms to more severe courses related to acute cerebrovascular events. In this review we present the current knowledge on brain imaging for this condition, with a comprehensive and critical description of its most common neuroradiological imaging findings. Moreover, we report results from studies that investigated brain physiopathology underlying this disorder by using advanced imaging techniques, suggesting possible future directions to further explore CNS involvement in FD patients.

Teaching Points

• Conventional neuroradiological findings in FD are aspecific.

• White matter hyperintensities represent the more consistent brain imaging feature of FD

• Abnormalities of the vasculature wall of posterior circulation are also consistent features.

• The pulvinar sign is not reliable as a finding pathognomonic for FD.

• Advanced imaging techniques have increased our knowledge about brain involvement in FD.

Multimodal Neuroimaging Approach to Variability of Functional Connectivity in Disorders of Consciousness: A PET/MRI Pilot Study

Behavioral assessments could not suffice to provide accurate diagnostic information in individuals with disorders of consciousness (DoC). Multimodal neuroimaging markers have been developed to support clinical assessments of these patients. Here we present findings obtained by hybrid fludeoxyglucose (FDG-)PET/MR imaging in three severely brain-injured patients, one in an unresponsive wakefulness syndrome (UWS), one in a minimally conscious state (MCS), and one patient emerged from MCS (EMCS). Repeated behavioral assessment by means of Coma Recovery Scale-Revised and neurophysiological evaluation were performed in the two weeks before and after neuroimaging acquisition, to ascertain that clinical diagnosis was stable. The three patients underwent one imaging session, during which two resting-state fMRI (rs-fMRI) blocks were run with a temporal gap of about 30 min. rs-fMRI data were analyzed with a graph theory approach applied to nine independent networks. We also analyzed the benefits of concatenating the two acquisitions for each patient or to select for each network the graph strength map with a higher ratio of fitness. Finally, as for clinical assessment, we considered the best functional connectivity pattern for each network and correlated graph strength maps to FDG uptake. Functional connectivity analysis showed several differences between the two rs-fMRI acquisitions, affecting in a different way each network and with a different variability for the three patients, as assessed by ratio of fitness. Moreover, combined PET/fMRI analysis demonstrated a higher functional/metabolic correlation for patients in EMCS and MCS compared to UWS. In conclusion, we observed for the first time, through a test-retest approach, a variability in the appearance and temporal/spatial patterns of resting-state networks in severely brain-injured patients, proposing a new method to select the most informative connectivity pattern.

Hybrid PET/MRI Methodology

The hybrid PET/MR scanner represents the first implementation of the effective integration of two modalities allowing truly synchronous/simultaneous acquisition of their imaging signals. This integration, resulting from the innovation and development of specific hardware components has paved the way for new approaches in the study of neurodegenerative diseases. This chapter will describe the hardware development that has led to the availability of different clinical solutions for PET/MR imaging as well as the still-open technological challenges and opportunities related to the processing and exploitation of the simultaneous acquisition in neurological studies.

Geometry optimization of electrically floating PET inserts for improved RF penetration for a 3 T MRI system

PURPOSE

An electrically floating radio frequency (RF) shielded PET insert with individual PET detectors shielded by separate Faraday cages enables the MRI built-in body RF coil to be used at least as an RF transmitter, in which the RF field penetrates the imaging region inside the PET ring through the narrow gaps between the shielded PET detector modules. Because the shielded PET ring blocks more than 90% of the imaging region for the transmit field from the body RF coil, it is very challenging to obtain the required RF field inside a full-ring floating PET insert. In this study, experiments were performed on the dependence of RF penetrability on different geometric aspects of the shielded PET modules and PET rings to optimize the design parameters to obtain the required RF field inside the PET ring.

METHODS

We developed several prototype cylindrical full-ring PET inserts using completely enclosed empty RF shield boxes (considered as dummy PET modules). Considering the RF shield box, we conducted studies for different axial lengths (240 and 120 mm) and heights (30 and 45 mm) of the shield boxes. On the other hand, considering the PET ring geometry, we also performed studies on three different categories of PET rings: a long-ring insert (longer than the MRI phantom), a short-ring insert (shorter than the MRI phantom), and a two-ring insert that combined two short-rings. In each ring category, two different inter-shield box gaps (1 and 3 mm) were considered. In the case of the two-ring insert, three different ring-gaps (5, 10, and 20 mm) were studied. In total, 21 PET inserts were studied with an inner diameter (i.d.) of 210 mm. To study the effect of ring diameter, another long-ring insert was studied for the 270 mm i.d. Experiments were conducted for the transmit RF (B₁ ) fields and signal-to-noise ratios of spin-echo and gradient-echo images using a homogeneous phantom in a 700 mm bore-diameter 3 T clinical MRI system. RF pulse amplitudes generated automatically by the MRI system were recorded for comparison.

RESULTS

A PET insert with a 3 mm inter-box gap was found to perform the best, at a level which is acceptable for PET imaging. In the case of an insert of multiple short-rings instead of one long-ring insert, the 5 and 10 mm ring-gaps provided higher RF field penetration. Increasing the inter-box gap improved the RF field penetration, whereas a ring-gap that was too wide concentrated the field near the ring-gap region. Relatively reduced RF power was required for wider inter-box gap or ring-gap or larger shield box height. Moreover, the rectangular shield box outperformed the trapezoidal shield box. On the other hand, when we changed the inner or outer diameter of the PET ring by keeping the same transaxial width of the shield boxes, we did not see any noticeable variation.

CONCLUSIONS

Our study results provide comprehensive guidance on the geometrical design aspects of RF-penetrable PET inserts for efficient RF penetration inside the PET ring. By choosing proper geometric design parameters, we could get the RF field that was similar to the MRI-only case.

Simultaneous resting-state FDG-PET/fMRI in Alzheimer Disease: Relationship between glucose metabolism and intrinsic activity

Simultaneously evaluating resting-state brain glucose metabolism and intrinsic functional activity has potential to impact the clinical neurosciences of Alzheimer Disease (AD). Indeed, integrating such combined information obtained in the same physiological setting may clarify how impairments in neuroenergetic and neuronal function interact and contribute to the mechanisms underlying AD. The present study used this multimodality approach to investigate, by means of a hybrid PET/MR scanner, the coupling between glucose consumption and intrinsic functional activity in 23 patients with AD-related cognitive impairment ranging from amnestic mild cognitive impairment (MCI) to mild-moderate AD (aMCI/AD), in comparison with a group of 23 healthy elderly controls. Between-group (Controls > Patients) comparisons were conducted on data from both imaging modalities using voxelwise 2-sample t-tests, corrected for partial-volume effects, head motion, age, gender and multiple tests. FDG-PET/fMRI relationships were assessed within and across subjects using Spearman partial correlations for three different resting-state fMRI (rs-fMRI) metrics sensitive to AD: fractional amplitude of low frequency fluctuations (fALFF), regional homogeneity (ReHo) and group independent component analysis with dual regression (gICA-DR). FDG and rs-fMRI metrics distinguished aMCI/AD from controls according to spatial patterns analogous to those found in stand-alone studies. Within-subject correlations were comparable across the three rs-fMRI metrics. Correlations were overall high in healthy controls (ρ = 0.80 ± 0.04), but showed a significant 17% reduction (p < 0.05) in aMCI/AD patients (ρ = 0.67 ± 0.05). Positive across-subject correlations were overall moderate (ρ = 0.33 ± 0.07) and consistent across rs-fMRI metrics. These were confined around AD-target posterior regions for metrics of functional connectivity (ReHo and gICA-DR). In contrast, FDG/fALFF correlations were distributed in the frontal gyrus, thalami and caudate nuclei. Taken together, these results support the presence of bioenergetic coupling between glucose utilization and rapid transmission of neural information in healthy ageing, which is substantially reduced in aMCI/AD, suggesting that abnormal glucose utilization is in some way linked to communication breakdown among brain regions impacted by the underlying pathological process.

Clinical Concepts Emerging from fMRI Functional Connectomics

Recent advances in connectomics have led to a synthesis of perspectives regarding the brain's functional organization that reconciles classical concepts of localized specialization with an appreciation for properties that emerge from interactions across distributed functional networks. This provides a more comprehensive framework for understanding neural mechanisms of normal cognition and disease. Although fMRI has not become a routine clinical tool, research has already had important influences on clinical concepts guiding diagnosis and patient management. Here we review illustrative examples. Studies demonstrating the network plasticity possible in adults and the global consequences of even focal brain injuries or disease both have had substantial impact on modern concepts of disease evolution and expression. Applications of functional connectomics in studies of clinical populations are challenging traditional disease classifications and helping to clarify biological relationships between clinical syndromes (and thus also ways of extending indications for, or "re-purposing," current treatments). Large datasets from prospective, longitudinal studies promise to enable the discovery and validation of functional connectomic biomarkers with the potential to identify people at high risk of disease before clinical onset, at a time when treatments may be most effective. Studies of pain and consciousness have catalyzed reconsiderations of approaches to clinical management, but also have stimulated debate about the clinical meaningfulness of differences in internal perceptual or cognitive states inferred from functional connectomics or other physiological correlates. By way of a closing summary, we offer a personal view of immediate challenges and potential opportunities for clinically relevant applications of fMRI-based functional connectomics.

Radiogenomic Analysis of Oncological Data: A Technical Survey

In the last few years, biomedical research has been boosted by the technological development of analytical instrumentation generating a large volume of data. Such information has increased in complexity from basic (i.e., blood samples) to extensive sets encompassing many aspects of a subject phenotype, and now rapidly extending into genetic and, more recently, radiomic information. Radiogenomics integrates both aspects, investigating the relationship between imaging features and gene expression. From a methodological point of view, radiogenomics takes advantage of non-conventional data analysis techniques that reveal meaningful information for decision-support in cancer diagnosis and treatment. This survey is aimed to review the state-of-the-art techniques employed in radiomics and genomics with special focus on analysis methods based on molecular and multimodal probes. The impact of single and combined techniques will be discussed in light of their suitability in correlation and predictive studies of specific oncologic diseases.

Functional reorganization in obstructive sleep apnoea and insomnia: A systematic review of the resting-state fMRI

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Resting state functional MRI studies is a promising non-invasive tool for better understanding of the pathophysiology of sleep disorders.

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The salience network is involved in hyperarousal and affective symptoms in insomnia.

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The posterior default mode network appears to underlie cognitive and depressive symptoms of obstructive sleep apnoea.

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Disruption of intrinsic networks have been demonstrated in major depression, which is a common co-morbidity of sleep disorders.

Functional neuroimaging techniques have accelerated progress in the study of sleep disorders. Considering the striking prevalence of these disorders in the general population, however, as well as their strong bidirectional relationship with major neuropsychiatric disorders, including major depressive disorder, their numbers are still surprisingly low. This review examines the contribution of resting state functional MRI to current understanding of two major sleep disorders, insomnia disorder and obstructive sleep apnoea. An attempt is made to learn from parallels of previous resting state functional neuroimaging findings in major depressive disorder. Moreover, shared connectivity biomarkers are suggested for each of the sleep disorders. Taken together, despite some inconsistencies, the synthesis of findings to date highlights the importance of the salience network in hyperarousal and affective symptoms in insomnia. Conversely, dysfunctional connectivity of the posterior default mode network appears to underlie cognitive and depressive symptoms of obstructive sleep apnoea.

Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry

A decade of research and development in resting-state functional MRI (RSfMRI) has opened new translational and clinical research frontiers. This review aims to bridge between technical and clinical researchers who seek reliable neuroimaging biomarkers for studying drug interactions with the brain. About 85 pharma-RSfMRI studies using BOLD signal (75% of all) or arterial spin labeling (ASL) were surveyed to investigate the acute effects of psychoactive drugs. Experimental designs and objectives include drug fingerprinting dose-response evaluation, biomarker validation and calibration, and translational studies. Common biomarkers in these studies include functional connectivity, graph metrics, cerebral blood flow and the amplitude and spectrum of BOLD fluctuations. Overall, RSfMRI-derived biomarkers seem to be sensitive to spatiotemporal dynamics of drug interactions with the brain. However, drugs cause both central and peripheral effects, thus exacerbate difficulties related to biological confounds, structured noise from motion and physiological confounds, as well as modeling and inference testing. Currently, these issues are not well explored, and heterogeneities in experimental design, data acquisition and preprocessing make comparative or meta-analysis of existing reports impossible. A unifying collaborative framework for data-sharing and data-mining is thus necessary for investigating the commonalities and differences in biomarker sensitivity and specificity, and establishing guidelines. Multimodal datasets including sham-placebo or active control sessions and repeated measurements of various psychometric, physiological, metabolic and neuroimaging phenotypes are essential for pharmacokinetic/pharmacodynamic modeling and interpretation of the findings. We provide a list of basic minimum and advanced options that can be considered in design and analyses of future pharma-RSfMRI studies. Hum Brain Mapp 38:2276-2325, 2017. © 2017 Wiley Periodicals, Inc.