Functional Positron Emission Tomography Research Articles

3-[18F]Fluoro-para-hydroxyphenethylguanidine (3-[18F]pHPG) PET-A Novel Imaging Modality for Paraganglioma.

Functional positron emission tomography (PET) imaging for the characterization of pheochromocytoma and paraganglioma (PCC/PGL) and for detection of metastases in malignant disease, offers valuable clinical insights that can significantly guide patient treatment. This work aimed to evaluate a novel PET radiotracer, 3-[18F]fluoro-para-hydroxyphenethylguanidine (3-[18F]pHPG), a norepinephrine analogue, for its ability to localize PCC/PGL. 3-[18F]pHPG PET/CT whole-body scans were performed on 16 patients (8 male:8 female; mean age 47.6 ± 17.6 years; range, 19-74 years) with pathologically confirmed or clinically diagnosed PCC/PGL. After intravenous administration of 304 to 475 MBq (8.2-12.8 mCi) of 3-[18F]pHPG, whole-body PET scans were performed at 90 minutes in all patients. 3-[18F]pHPG PET was interpreted for abnormal findings consistent with primary tumor or metastasis, and biodistribution in normal organs recorded. Standardized uptake value (SUV) measurements were obtained for target lesions and physiological organ distributions. 3-[18F]pHPG PET showed high radiotracer uptake and trapping in primary tumors, and metastatic tumor lesions that included bone, lymph nodes, and other solid organ sites. Physiological biodistribution was universally present in salivary glands (parotid, submandibular, sublingual), thyroid, heart, liver, adrenals, kidneys, and bladder. Comparison [68Ga]DOTATATE PET/CT was available in 10 patients and in all cases showed concordant distribution. Comparison [123I]meta-iodobenzylguanidine [123I]mIBG planar scintigraphy and SPECT/CT scans were available for 4 patients, with 3-[18F]pHPG showing a greater number of metastatic lesions. We found the kinetic profile of 3-[18F]pHPG PET affords high activity retention within benign and metastatic PCC/PGL. Therefore, 3-[18F]pHPG PET imaging provides a novel modality for functional imaging and staging of malignant paraganglioma with advantages of high lesion affinity, whole-body coregistered computed tomography, and rapid same-day imaging.

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

Functional positron emission tomography (fPET) with [18F]FDG allows quantification of stimulation-induced changes in glucose metabolism independent of neurovascular coupling. However, the gold standard for quantification requires invasive arterial blood sampling, limiting its widespread use. Here, we introduce a novel fPET method without the need for an input function. We validated the approach using two datasets (DS). For DS1, 52 volunteers (23.2 ± 3.3years, 24 females) performed Tetris® during a [18F]FDG fPET scan (bolus + constant infusion). For DS2, 18 participants (24.2 ± 4.3years, 8 females) performed an eyes-open/finger tapping task (constant infusion). Task-specific changes in metabolism were assessed with the general linear model (GLM) and cerebral metabolic rate of glucose (CMRGlu) was quantified with the Patlak plot as reference. We then estimated simplified outcome parameters, including GLM beta values and percent signal change (%SC), and compared them, region and whole-brain-wise. We observed higher agreement with the reference for DS1 than DS2. Both DS resulted in strong correlations between regional task-specific beta estimates and CMRGlu (r = 0.763…0.912). %SC of beta values exhibited strong agreement with %SC of CMRGlu (r = 0.909…0.999). Average activation maps showed a high spatial similarity between CMRGlu and beta estimates (Dice = 0.870…0.979) as well as %SC (Dice = 0.932…0.997), respectively. The non-invasive method reliably estimates task-specific changes in glucose metabolism without blood sampling. This streamlines fPET, albeit with the trade-off of being unable to quantify baseline metabolism. The simplification enhances its applicability in research and clinical settings.

Current Trends and Applications of PET/MRI Hybrid Imaging in Neurodegenerative Diseases and Normal Aging.

Dementia is a significant global health issue that is exacerbated by an aging population. Imaging plays an established role in the evaluation of patients with neurocognitive disorders such as dementia. In current clinical practice, magnetic resonance imaging (MRI) and positron emission tomography (PET) are primary imaging modalities used separately but in concert to help diagnose and classify dementia. The clinical applications of PET/MRI hybrid imaging in dementia are an active area of research, particularly given the continued emergence of functional MRI (fMRI) and amyloid PET tracers. This narrative review provides a comprehensive overview of the rationale and current evidence for PET/MRI hybrid dementia imaging from 2018 to 2023. Hybrid imaging offers advantages in the accuracy of characterizing neurodegenerative disorders, and future research will need to address the cost of integrated PET/MRI systems compared to stand-alone scanners, the development of new biomarkers, and image correction techniques.

The parallax: The possible errors in the quantification of human decision-making behavior in the experiment of neuroeconomics-A perspective from psychoanalysis.

With the development of neuroscience and technology, economics, which focuses on the selection and decision-making of human behavior, has also entered the field of neuroeconomics. Based on rational biological humans, neuroeconomics assumes that humans are rational biological individuals and behaviors of biological humans can be monitored and quantified in the nervous system through brain imaging technologies such as functional MRI and positron emission tomography. As an emerging discipline, neuroeconomics inevitably encounters obstacles in methodology and epistemology, showing excessive constraints in its understanding of rationality and facing basic conceptual disputes on the theoretical basis of "clear uncertainty monism." In neuroeconomics experiments, measurability will inevitably be traced back to quantification, but when faced with a complex and ever-changing social field, what can be predicted is only probability rather than behavior. Not all human behaviors and decisions can be quantified. Therefore, such research may be biased. Psychoanalysis, a major branch of psychology that is quite similar to neuroeconomics research in subject and object, can greatly correct these basic concepts. Seen from the perspective of psychoanalysis, the existence of these unquantifiable things conversely plays a decisive role and cannot be ignored. This article analyzes the core rational behavior detection of neuroeconomics from the perspective of psychoanalysis and proposes suggestions from the epistemology and methodology of experimental design as well as basic concept discrimination and so forth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Partial volume correction of PET image data using geometric transfer matrices based on uniform B-splines

Objective. Most methods for partial volume correction (PVC) of positron emission tomography (PET) data employ anatomical segmentation of images into regions of interest. This approach is not optimal for exploratory functional imaging beyond regional hypotheses. Here, we describe a novel method for unbiased voxel-wise PVC. Approach. B-spline basis functions were combined with geometric transfer matrices to enable a method (bsGTM) that provides PVC or alternatively provides smoothing with minimal regional crosstalk. The efficacy of the proposed method was evaluated using Monte Carlo simulations, human PET data, and murine functional PET data. Main results. In simulations, bsGTM provided recovery of partial volume signal loss comparable to iterative deconvolution, while demonstrating superior resilience to noise. In a real murine PET dataset, bsGTM yielded much higher sensitivity for detecting amphetamine-induced reduction of [11C]raclopride binding potential. In human PET data, bsGTM smoothing enabled increased signal-to-noise ratios with less degradation of binding potentials relative to Gaussian convolution or non-local means. Significance. bsGTM offers improved performance for PVC relative to iterative deconvolution, the current method of choice for voxel-wise PVC, especially in the common PET regime of low signal-to-noise ratio. The new method provides an anatomically unbiased way to compensate partial volume errors in cases where anatomical segmentation is unavailable or of questionable relevance or accuracy.

Deep learning-based multimodality classification of chronic mild traumatic brain injury using resting-state functional MRI and PET imaging.

Mild traumatic brain injury (mTBI) is a public health concern. The present study aimed to develop an automatic classifier to distinguish between patients with chronic mTBI (n = 83) and healthy controls (HCs) (n = 40). Resting-state functional MRI (rs-fMRI) and positron emission tomography (PET) imaging were acquired from the subjects. We proposed a novel deep-learning-based framework, including an autoencoder (AE), to extract high-level latent and rectified linear unit (ReLU) and sigmoid activation functions. Single and multimodality algorithms integrating multiple rs-fMRI metrics and PET data were developed. We hypothesized that combining different imaging modalities provides complementary information and improves classification performance. Additionally, a novel data interpretation approach was utilized to identify top-performing features learned by the AEs. Our method delivered a classification accuracy within the range of 79-91.67% for single neuroimaging modalities. However, the performance of classification improved to 95.83%, thereby employing the multimodality model. The models have identified several brain regions located in the default mode network, sensorimotor network, visual cortex, cerebellum, and limbic system as the most discriminative features. We suggest that this approach could be extended to the objective biomarkers predicting mTBI in clinical settings.

Resting-State Functional MRI and PET Imaging as Noninvasive Tools to Study (Ab)Normal Neurodevelopment in Humans and Rodents.

Neurodevelopmental disorders (NDDs) are a group of complex neurologic and psychiatric disorders. Functional and molecular imaging techniques, such as resting-state functional magnetic resonance imaging (rs-fMRI) and positron emission tomography (PET), can be used to measure network activity noninvasively and longitudinally during maturation in both humans and rodent models. Here, we review the current knowledge on rs-fMRI and PET biomarkers in the study of normal and abnormal neurodevelopment, including intellectual disability (ID; with/without epilepsy), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), in humans and rodent models from birth until adulthood, and evaluate the cross-species translational value of the imaging biomarkers. To date, only a few isolated studies have used rs-fMRI or PET to study (abnormal) neurodevelopment in rodents during infancy, the critical period of neurodevelopment. Further work to explore the feasibility of performing functional imaging studies in infant rodent models is essential, as rs-fMRI and PET imaging in transgenic rodent models of NDDs are powerful techniques for studying disease pathogenesis, developing noninvasive preclinical imaging biomarkers of neurodevelopmental dysfunction, and evaluating treatment-response in disease-specific models.

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

Positron emission tomography (PET) provides precise molecular information on physiological processes, but its low temporal resolution is a major obstacle. Consequently, we characterized the metabolic response of the human brain to working memory performance using an optimized functional PET (fPET) framework at a temporal resolution of 3s. Thirty-five healthy volunteers underwent fPET with [18F]FDG bolus plus constant infusion, 19 of those at a hybrid PET/MRI scanner. During the scan, an n-back working memory paradigm was completed. fPET data were reconstructed to 3s temporal resolution and processed with a novel sliding window filter to increase signal to noise ratio. BOLD fMRI signals were acquired at 2s. Consistent with simulated kinetic modeling, we observed a constant increase in the [18F]FDG signal during task execution, followed by a rapid return to baseline after stimulation ceased. These task-specific changes were robustly observed in brain regions involved in working memory processing. The simultaneous acquisition of BOLD fMRI revealed that the temporal coupling between hemodynamic and metabolic signals in the primary motor cortex was related to individual behavioral performance during working memory. Furthermore, task-induced BOLD deactivations in the posteromedial default mode network were accompanied by distinct temporal patterns in glucose metabolism, which were dependent on the metabolic demands of the corresponding task-positive networks. In sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing. This allows to capture unique information in the temporal domain, which is not accessible to conventional PET imaging.

Functional connectivity moderates the impact of synaptic loss on behaviour in frontotemporal lobar degeneration syndromes

AbstractBackgroundThere is growing evidence for early and extensive synaptic loss in frontotemporal lobar degeneration syndromes from in vivo and post‐mortem studies. We proposed that synaptic loss would affect behaviour, in relation to changes in functional connectivity.MethodWe recruited 29 participants with progressive supranuclear palsy, 16 participants with amyloid‐negative corticobasal syndrome, 8 participants with behavioural variant frontotemporal dementia and 24 similarly‐aged healthy volunteers. All participants underwent resting‐state functional 3T MRI and positron emission tomography with [11C]UCB‐J, that binds synaptic vesicle 2A. We compared the connectivity metrics of nodal weighted degree and voxelwise regional homogeneity with [11C]UCB‐J non‐displaceable binding potential (BPND), in associative and commonality analyses. We then used independent component analysis to extract [11C]UCB‐J BPND signal variance across participants, followed by derivation of participant‐specific scores of functional spatial covariance with the [11C]UCB‐J components. We applied model selection to assess whether connectivity scores would improve prediction of and moderate the effect of synaptic loss on clinical severity.ResultReduced [11C]UCB‐J BPND was associated with reduced connectivity, with synaptic density predicting both measures of connectivity over and above grey matter volume (Figure 1). The anatomical distribution of synaptic loss partially overlapped in PSP, bvFTD and CBS, but there were also disease‐specific effects (Figure 2). The effect of synaptic loss on functional connectivity was expressed local to the regions of severe synaptic loss, and in remote regions. Moreover, functional connectivity explained additional variance and moderated the relationship between synaptic density and clinical severity (Figure 3).ConclusionIn vivo synaptic loss is associated with reduced connectivity, and changes in behaviour, with implications for modelling disease pathogenesis and translational studies.

Positron emission tomography (PET) imaging of neuroinflammation in healthy and Alzheimer disease participants using TSPO tracers

AbstractBackgroundAlzheimer’s disease (AD) is the most common type of dementia. In addition to the widely recognized accumulation of amyloid and tau protein being the core pathology of AD, neuroinflammation is another cause of brain dysfunction and structural change. Expression of translocator protein (TSPO) on the outer mitochondrial membrane of activated microglia is strongly associated with neuroinflammation. With the development of TSPO positron emission tomography (PET) tracer, we were able to evaluate neuroinflammation non‐invasively in a clinical cohort of AD spectrum.MethodCognitively impaired patients (including AD and mild cognitive impairment (MCI)) and cognitively normal controls (CN) were recruited from single dementia clinic. [18F]FEPPA, the second‐generation PET ligand specifically binds TSPO was synthesized fully automated. Structural brain MRI and functional PET imaging were performed simultaneously with a PET/MR scanner (SIGNA, GE Company, USA). Kinetic analyses were performed using PMOD 4.2 modeling software. Total distribution volume (VT) in each ROI, including frontal, temporal, inferiolateral parietal, occipital, hippocampus and cerebellum, were derived from a two‐tissue compartment model (2‐TCM). In addition, APOE and rs6971 polymorphism genotyping were conducted in all subjects. Mann‐Whitney U Tet, Kruskal‐Wallis Test and linear correlation were performed.ResultA total of 39 participants (23 males and 16 females) participated, including 13 cognitively normal, 9 with MCI and 17 with Alzheimer’s disease. The rs6971 genotype had no significant effect on [18F]FEPPA binding to TSPO. The amount of TSPO expression was independent of age, gender, and APOE ε4 carrier status. The VT of each ROI did not differ significantly between cognitive groups. VT of frontal, temporal, inferiolateral parietal and occipital lobe were all negatively correlated with MMSE, Boston Naming Test and Trial Making A performance. However, such association was not observed between VT of hippocampus and cognitive tests.ConclusionAlthough there was no difference between TSPO expression in each ROI among cognitive groups, we still observed that higher TSPO expression in the cortex was associated with worse performance in certain cognitive tests. This implied that the increase in neuroinflammation was related to the decline of cognitive performance regardless of cognitive diagnosis.

Joint learning framework of cross-modal synthesis and diagnosis for Alzheimer’s disease by mining underlying shared modality information

Alzheimer’s disease (AD) is one of the most common neurodegenerative disorders presenting irreversible progression of cognitive impairment. How to identify AD as early as possible is critical for intervention with potential preventive measures. Among various neuroimaging modalities used to diagnose AD, functional positron emission tomography (PET) has higher sensitivity than structural magnetic resonance imaging (MRI), but it is also costlier and often not available in many hospitals. How to leverage massive unpaired unlabeled PET to improve the diagnosis performance of AD from MRI becomes rather important. To address this challenge, this paper proposes a novel joint learning framework of unsupervised cross-modal synthesis and AD diagnosis by mining underlying shared modality information, improving the AD diagnosis from MRI while synthesizing more discriminative PET images. We mine underlying shared modality information in two aspects: diversifying modality information through the cross-modal synthesis network and locating critical diagnosis-related patterns through the AD diagnosis network. First, to diversify the modality information, we propose a novel unsupervised cross-modal synthesis network, which implements the inter-conversion between 3D PET and MRI in a single model modulated by the AdaIN module. Second, to locate shared critical diagnosis-related patterns, we propose an interpretable diagnosis network based on fully 2D convolutions, which takes either 3D synthesized PET or original MRI as input. Extensive experimental results on the ADNI dataset show that our framework can synthesize more realistic images, outperform the state-of-the-art AD diagnosis methods, and have better generalization on external AIBL and NACC datasets.

＜Editors' Choice＞ Pattern of THK 5351 retention in normal aging involves core regions of resting state networks associated with higher cognitive function.

We aimed to elucidate the distribution pattern of the positron emission tomography probe [18F]THK 5351, a marker for astrogliosis and tau accumulation, in healthy aging. We also assessed the relationship between THK5351 retention and resting state networks. We enrolled 62 healthy participants in this study. All participants underwent magnetic resonance imaging/positron emission tomography scanning consisting of T1-weighted images, resting state functional magnetic resonance imaging, Pittsburgh Compound-B and THK positron emission tomography. The preprocessed THK images were entered into a scaled subprofile modeling/principal component analysis to extract THK distribution patterns. Using the most significant THK pattern, we generated regions of interest, and performed seed-based functional connectivity analyses. We also evaluated the functional connectivity overlap ratio to identify regions with high between-network connectivity. The most significant THK distributions were observed in the medial prefrontal cortex and bilateral putamen. The seed regions of interest in the medial prefrontal cortex had a functional connectivity map that significantly overlapped with regions of the dorsal default mode network. The seed regions of interest in the putamen showed strong overlap with the basal ganglia and anterior salience networks. The functional connectivity overlap ratio also showed that three peak regions had the characteristics of connector hubs. We have identified an age-related spatial distribution of THK in the medial prefrontal cortex and basal ganglia in normal aging. Interestingly, the distribution's peaks are located in regions of connector hubs that are strongly connected to large-scale resting state networks associated with higher cognitive function.

Correlation between cerebral hemodynamic functional near-infrared spectroscopy and positron emission tomography for assessing mild cognitive impairment and Alzheimer's disease: An exploratory study.

This study was performed to investigate the usefulness of functional near-infrared spectroscopy (fNIRS) by conducting a comparative analysis of hemodynamic activation detected by fNIRS and positron emission tomography (PET) and magnetic resonance imaging (MRI) in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Participants were divided into four groups: the subjective memory impairment (SMI), amnestic MCI (aMCI), non-amnestic MCI (naMCI), and AD groups. We recorded the hemodynamic response during the semantic verbal fluency task (SVFT) using a commercial wireless continuous-wave NIRS system. The correlation between the parameters of the neuroimaging assessments among the groups was analyzed. Region of interest-based comparisons showed that the four groups had significantly different hemodynamic responses during SVFT in the bilateral dorsolateral prefrontal cortex (DLPFC). The linear mixed effect model result indicates that the mean ΔHbO2 from the bilateral DLPFC regions showed a significant positive correlation to the overall FDG-PET after controlling for age and group differences in the fNIRS signals. Amyloid PET signals tended to better differentiate the AD group from other groups, and fNIRS signals tended to better differentiate the SMI group from other groups. In addition, a comparison between the group pairs revealed a mirrored pattern between the hippocampal volume and hemodynamic response in the DLPFC. The hemodynamic response detected by fNIRS showed a significant correlation with metabolic and anatomical changes associated with disease progression. Therefore, fNIRS may be considered as a screening tool to predict the hemodynamic and metabolic statuses of the brain in patients with MCI and AD.

Psychedelic therapy in the treatment of addiction: the past, present and future.

Psychedelic therapy has witnessed a resurgence in interest in the last decade from the scientific and medical communities with evidence now building for its safety and efficacy in treating a range of psychiatric disorders including addiction. In this review we will chart the research investigating the role of these interventions in individuals with addiction beginning with an overview of the current socioeconomic impact of addiction, treatment options, and outcomes. We will start by examining historical studies from the first psychedelic research era of the mid-late 1900s, followed by an overview of the available real-world evidence gathered from naturalistic, observational, and survey-based studies. We will then cover modern-day clinical trials of psychedelic therapies in addiction from first-in-human to phase II clinical trials. Finally, we will provide an overview of the different translational human neuropsychopharmacology techniques, including functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), that can be applied to foster a mechanistic understanding of therapeutic mechanisms. A more granular understanding of the treatment effects of psychedelics will facilitate the optimisation of the psychedelic therapy drug development landscape, and ultimately improve patient outcomes.

Whole-body metabolic connectivity framework with functional PET

The nervous and circulatory system interconnects the various organs of the human body, building hierarchically organized subsystems, enabling fine-tuned, metabolically expensive brain-body and inter-organ crosstalk to appropriately adapt to internal and external demands. A deviation or failure in the function of a single organ or subsystem could trigger unforeseen biases or dysfunctions of the entire network, leading to maladaptive physiological or psychological responses. Therefore, quantifying these networks in healthy individuals and patients may help further our understanding of complex disorders involving body-brain crosstalk.Here we present a generalized framework to automatically estimate metabolic inter-organ connectivity utilizing whole-body functional positron emission tomography (fPET). The developed framework was applied to 16 healthy subjects (mean age ± SD, 25 ± 6 years; 13 female) that underwent one dynamic 18F-FDG PET/CT scan. Multiple procedures of organ segmentation (manual, automatic, circular volumes) and connectivity estimation (polynomial fitting, spatiotemporal filtering, covariance matrices) were compared to provide an optimized thorough overview of the workflow.The proposed approach was able to estimate the metabolic connectivity patterns within brain regions and organs as well as their interactions. Automated organ delineation, but not simplified circular volumes, showed high agreement with manual delineation. Polynomial fitting yielded similar connectivity as spatiotemporal filtering at the individual subject level. Furthermore, connectivity measures and group-level covariance matrices did not match. The strongest brain-body connectivity was observed for the liver and kidneys.The proposed framework offers novel opportunities towards analyzing metabolic function from a systemic, hierarchical perspective in a multitude of physiological pathological states.

Widespread fMRI BOLD Signal Overactivations during Cognitive Control in Older Adults Are Not Matched by Corresponding Increases in fPET Glucose Metabolism.

A common observation in fMRI studies using the BOLD signal is that older adults, compared with young adults, show overactivations, particularly during less demanding tasks. The neuronal underpinnings of such overactivations are not known, but a dominant view is that they are compensatory in nature and involve recruitment of additional neural resources. We scanned 23 young (20-37 years) and 34 older (65-86 years) healthy human adults of both sexes with hybrid positron emission tomography/MRI. The radioligand [18F]fluoro-deoxyglucose was used to assess dynamic changes in glucose metabolism as a marker of task-dependent synaptic activity, along with simultaneous fMRI BOLD imaging. Participants performed two verbal working memory (WM) tasks: one involving maintenance (easy) and one requiring manipulation (difficult) of information in WM. Converging activations to the WM tasks versus rest were observed for both imaging modalities and age groups in attentional, control, and sensorimotor networks. Upregulation of activity to WM-demand, comparing the more difficult to the easier task, also converged between both modalities and age groups. For regions in which older adults showed task-dependent BOLD overactivations compared with the young adults, no corresponding increases in glucose metabolism were found. To conclude, findings from the current study show that task-induced changes in the BOLD signal and synaptic activity as measured by glucose metabolism generally converge, but overactivations observed with fMRI in older adults are not coupled with increased synaptic activity, which suggests that these overactivations are not neuronal in origin.SIGNIFICANCE STATEMENT Findings of increased fMRI activations in older compared with younger adults have been suggested to reflect increased use of neuronal resources to cope with reduced brain function. The physiological underpinnings of such compensatory processes are poorly understood, however, and rest on the assumption that vascular signals accurately reflect neuronal activity. Comparing fMRI and simultaneously acquired functional positron emission tomography as an alternative index of synaptic activity, we show that age-related overactivations do not appear to be neuronal in origin. This result is important because mechanisms underlying compensatory processes in aging are potential targets for interventions aiming to prevent age-related cognitive decline.

Examination of common and unique brain regions for atypical reading and math: a meta-analysis.

The purpose of this study is to identify consistencies across functional neuroimaging studies regarding common and unique brain regions/networks for individuals with reading difficulties (RD) and math difficulties (MD) compared to typically developing (TD) individuals. A systematic search of the literature, utilizing multiple databases, yielded 116 functional magnetic resonance imaging and positron emission tomography studies that met the criteria. Coordinates that directly compared TD with either RD or MD were entered into GingerALE (Brainmap.org). An activation likelihood estimate (ALE) meta-analysis was conducted to examine common and unique brain regions for RD and MD. Overall, more studies examined RD (n = 96) than MD (n = 20). Across studies, overactivation for reading and math occurred in the right insula and inferior frontal gyrus for atypically developing (AD) > TD comparisons, albeit in slightly different areas of these regions; however, inherent threshold variability across imaging studies could diminish overlying regions. For TD > AD comparisons, there were no similar or overlapping brain regions. Results indicate there were domain-specific differences for RD and MD; however, there were some similarities in the ancillary recruitment of executive functioning skills. Theoretical and practical implications for researchers and educators are discussed.

Magnetic resonance imaging for characterization of hepatocellular carcinoma metabolism.

With a better understanding of the pathophysiological and metabolic changes in hepatocellular carcinoma (HCC), multiparametric and novel functional magnetic resonance (MR) and positron emission tomography (PET) techniques have received wide interest and are increasingly being applied in preclinical and clinical research. These techniques not only allow for non-invasive detection of structural, functional, and metabolic changes in malignant tumor cells but also characterize the tumor microenvironment (TME) and the interactions of malignant tumor cells with the TME, which has hypoxia and low pH, resulting from the Warburg effect and accumulation of metabolites produced by tumor cells and other cellular components. The heterogeneity and complexity of the TME require a combination of images with various parameters and modalities to characterize tumors and guide therapy. This review focuses on the value of multiparametric magnetic resonance imaging and PET/MR in evaluating the structural and functional changes of HCC and in detecting metabolites formed owing to HCC and the TME.

Deep brain stimulation of the nucleus basalis of Meynert modulates hippocampal–frontoparietal networks in patients with advanced Alzheimer’s disease

BackgroundDeep brain stimulation (DBS) of the nucleus basalis of Meynert (NBM) has shown potential for the treatment of mild-to-moderate Alzheimer’s disease (AD). However, there is little evidence of whether NBM-DBS can improve cognitive functioning in patients with advanced AD. In addition, the mechanisms underlying the modulation of brain networks remain unclear. This study was aimed to assess the cognitive function and the resting-state connectivity following NBM-DBS in patients with advanced AD.MethodsEight patients with advanced AD underwent bilateral NBM-DBS and were followed up for 12 months. Clinical outcomes were assessed by neuropsychological examinations using the Mini-Mental State Examination (MMSE) and Alzheimer’s Disease Assessment Scale. Resting-state functional magnetic resonance imaging and positron emission tomography data were also collected.ResultsThe cognitive functioning of AD patients did not change from baseline to the 12-month follow-up. Interestingly, the MMSE score indicated clinical efficacy at 1 month of follow-up. At this time point, the connectivity between the hippocampal network and frontoparietal network tended to increase in the DBS-on state compared to the DBS-off state. Additionally, the increased functional connectivity between the parahippocampal gyrus (PHG) and the parietal cortex was associated with cognitive improvement. Further dynamic functional network analysis showed that NBM-DBS increased the proportion of the PHG-related connections, which was related to improved cognitive performance.ConclusionThe results indicated that NBM-DBS improves short-term cognitive performance in patients with advanced AD, which may be related to the modulation of multi-network connectivity patterns, and the hippocampus plays an important role within these networks.Trial registrationChiCTR, ChiCTR1900022324. Registered 5 April 2019—Prospective registration. https://www.chictr.org.cn/showproj.aspx?proj=37712

Can Swallowing Cerebral Neurophysiology Be Evaluated during Ecological Food Intake Conditions? A Systematic Literature Review.

Swallowing is a complex function that relies on both brainstem and cerebral control. Cerebral neurofunctional evaluations are mostly based on functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), performed with the individual laying down; which is a non-ecological/non-natural position for swallowing. According to the PRISMA guidelines, a review of the non-invasive non-radiating neurofunctional tools, other than fMRI and PET, was conducted to explore the cerebral activity in swallowing during natural food intake, in accordance with the PRISMA guidelines. Using Embase and PubMed, we included human studies focusing on neurofunctional imaging during an ecologic swallowing task. From 5948 unique records, we retained 43 original articles, reporting on three different techniques: electroencephalography (EEG), magnetoencephalography (MEG) and functional near infra-red spectroscopy (fNIRS). During swallowing, all three techniques showed activity of the pericentral cortex. Variations were associated with the modality of the swallowing process (volitional or non-volitional) and the substance used (mostly water and saliva). All techniques have been used in both healthy and pathological conditions to explore the precise time course, localization or network structure of the swallowing cerebral activity, sometimes even more precisely than fMRI. EEG and MEG are the most advanced and mastered techniques but fNIRS is the most ready-to-use and the most therapeutically promising. Ongoing development of these techniques will support and improve our future understanding of the cerebral control of swallowing.