Treatment effects of N-acetyl cysteine on resting-state functional MRI and cognitive performance in patients with chronic mild traumatic brain injury: a longitudinal study.

Mild traumatic brain injury (mTBI) is a significant public health concern, specially characterized by a complex pattern of abnormal neural activity and functional connectivity. It is often associated with a broad spectrum of short-term and long-term cognitive and behavioral symptoms including memory dysfunction, headache, and balance difficulties. Furthermore, there is evidence that oxidative stress significantly contributes to these symptoms and neurophysiological changes. The purpose of this study was to assess the effect of N-acetylcysteine (NAC) on brain function and chronic symptoms in mTBI patients. Fifty patients diagnosed with chronic mTBI participated in this study. They were categorized into two groups including controls (CN, n = 25), and patients receiving treatment with N-acetyl cysteine (NAC, n = 25). NAC group received 50 mg/kg intravenous (IV) medication once a day per week. In the rest of the week, they took one 500 mg NAC tablet twice per day. Each patient underwent rs-fMRI scanning at two timepoints including the baseline and 3 months later at follow-up, while the NAC group received a combination of oral and IV NAC over that time. Three rs-fMRI metrics were measured including fractional amplitude of low frequency fluctuations (fALFF), degree centrality (DC), and functional connectivity strength (FCS). Neuropsychological tests were also assessed at the same day of scanning for each patient. The alteration of rs-fMRI metrics and cognitive scores were measured over 3 months treatment with NAC. Then, the correlation analysis was executed to estimate the association of rs-fMRI measurements and cognitive performance over 3 months (p < 0.05). Two significant group-by-time effects demonstrated the changes of rs-fMRI metrics particularly in the regions located in the default mode network (DMN), sensorimotor network, and emotional circuits that were significantly correlated with cognitive function recovery over 3 months treatment with NAC (p < 0.05). NAC appears to modulate neural activity and functional connectivity in specific brain networks, and these changes could account for clinical improvement. This study confirmed the short-term therapeutic efficacy of NAC in chronic mTBI patients that may contribute to understanding of neurophysiological effects of NAC in mTBI. These findings encourage further research on long-term neurobehavioral assessment of NAC assisting development of therapeutic plans in mTBI.

Machine learning-based classification of chronic traumatic brain injury using hybrid diffusion imaging.

Background and purpose: Traumatic brain injury (TBI) can cause progressive neuropathology that leads to chronic impairments, creating a need for biomarkers to detect and monitor this condition to improve outcomes. This study aimed to analyze the ability of data-driven analysis of diffusion tensor imaging (DTI) and neurite orientation dispersion imaging (NODDI) to develop biomarkers to infer symptom severity and determine whether they outperform conventional T1-weighted imaging. Materials and methods: A machine learning-based model was developed using a dataset of hybrid diffusion imaging of patients with chronic traumatic brain injury. We first extracted the useful features from the hybrid diffusion imaging (HYDI) data and then used supervised learning algorithms to classify the outcome of TBI. We developed three models based on DTI, NODDI, and T1-weighted imaging, and we compared the accuracy results across different models. Results: Compared with the conventional T1-weighted imaging-based classification with an accuracy of 51.7-56.8%, our machine learning-based models achieved significantly better results with DTI-based models at 58.7-73.0% accuracy and NODDI with an accuracy of 64.0-72.3%. Conclusion: The machine learning-based feature selection and classification algorithm based on hybrid diffusion features significantly outperform conventional T1-weighted imaging. The results suggest that advanced algorithms can be developed for inferring symptoms of chronic brain injury using feature selection and diffusion-weighted imaging.

Neuropsychological Comparison of Guilt and Grief: A Review of Guilt Aspects in Prolonged Grief Disorder.

Taking an integrative approach toward developmental psychology and neurophysiology, this review selects findings from the psychological and medical literature on guilt and bereavement that are relevant to considering whether and how guilt contributes to the development of prolonged grief disorder (PGD) in bereaved persons. Mention of guilt is ubiquitous in literature on general grief and PGD, including 54 articles related to the neuropsychological development and manifestations of guilt and grief, as well as their neuroimaging correlates, that met scoping review criteria. However, mechanisms connecting guilt to development of PGD are scarce. Aspects of guilt are conceptually connected to many PGD criteria, opening avenues to explore treatment of PGD by targeting guilt. Positive and prosocial aspects of guilt are especially neglected in the treatment of psychiatric disorders, and consideration of these aspects may improve interventions for PGD such as complicated grief treatment.

"Visualization" of pain using cerebral 18F-FDG PET/CT following surgical treatment of lumbar disc herniation.

PURPOSE: We hypothesized that unilateral leg pain following surgical treatment of lumbar disc herniation (LDH) is associated with an increase in the glucose metabolism of the contralateral thalamus. METHODS: Patients scheduled for surgery due to LDH underwent 18F-fluorodeoxyglucose positron emission tomography/computed tomography less than two weeks prior to surgery. Their thalamic FDG uptake was measured and expressed as the mean and partial volume corrected mean standardized uptake values (SUVmean and cSUVmean). These measures were compared with patient-related outcome measures collected pre- and 1-year post-operatively: back and leg pain on a 0-100 VAS scale and health-related quality of life as measured by the EuroQol-5D (EQ-5D). RESULTS: Twenty-six patients (ten females) aged 49.7 ± 7.4 (mean ± SD) years were included. There was a significant correlation between painful body side and increased contralateral thalamic uptake of FDG, with regard to cSUVmean values. Correlation analyses including clinical parameters and cSUVmean indicated some association with 1-year change in EQ-5D. CONCLUSION: These preliminary data sustain the hypothesis that unilateral pain in patients with LDH is associated with increased glucose metabolism in the contralateral thalamus, suggesting a central role of thalamus in chronic pain perception.

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.

Continuous glucose monitoring metrics for earlier identification of pre-diabetes: protocol for a systematic review and meta-analysis.

INTRODUCTION: Glycaemic variability and other metrics are not well characterised in subjects without diabetes. More comprehensive sampling as obtained with continuous glucose monitoring (CGM) may improve diagnostic accuracy of the transition from health to pre-diabetes. Our goal is to investigate the glycaemic system as it shifts from health to pre-disease in adult patients without diabetes using CGM metrics. New insights may offer therapeutic promise for reversing dysglycaemia more successfully with dietary, nutritional and lifestyle change before progression occurs to pre-diabetes and diabetes. METHODS AND ANALYSIS: This systematic review will include comprehensive searches of the PubMed, Scopus, Cochrane Library and ClinicalTrials.gov databases, with restrictions set to studies published in the last 10 years in English and planned search date 10 March 2022. Reference lists of studies that meet eligibility criteria in the screening process will subsequently be screened for the potential inclusion of additional studies. We will include studies that examine CGM use and report diagnostic criteria such as fasting glucose and/or haemoglobin A1c such that we can assess correlation between CGM metrics and established diagnostic criteria and describe how CGM metrics are altered in the transition from health to pre-diabetes. The screening and data extraction will be conducted by two independent reviewers using Covidence. All included papers will also be evaluated for quality and publication bias using Cochrane Collaboration risk of bias tools. If there are two or more studies with quantitative estimates that can be combined, we will conduct a meta-analysis after assessing heterogeneity. ETHICS AND DISSEMINATION: The systematic review methodology does not require formal ethical review due to the nature of the study design. Study findings will be publicly available and published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42022308222.

Correction: A Telehealth-Delivered Tai Chi Intervention (TaiChi4Joint) for Managing Aromatase Inhibitor-Induced Arthralgia in Patients With Breast Cancer During COVID-19: Longitudinal Pilot Study.

[This corrects the article DOI: 10.2196/34995.].

Positron Emission Tomography-Based Assessment of Cognitive Impairment and Dementias, Critical Role of Fluorodeoxyglucose in such Settings.

Positron emission tomography (PET) has been a key component in the diagnostic armamentarium for assessing neurodegenerative diseases such as Alzheimer or Parkinson disease. PET imaging has been useful for diagnosing these disorders, identifying their pathophysiology, and following their treatment. Further, PET imaging has been extensively used for both clinical and research purposes, particularly for helping with potential therapeutic approaches for managing neurodegenerative diseases. This article will review the current literature regarding PET imaging in patients with neurodegenerative disorders. This includes an evaluation of the most commonly used tracer fluorodeoxyglucose that measures cerebral glucose metabolism, tracers that assess neurotransmitter systems, and tracers designed to reveal disease-specific pathophysiological processes. With the continuing development of an expanding variety of radiopharmaceuticals, PET imaging will likely play a prominent role in future research and clinical applications for neurodegenerative diseases.

A Telehealth-Delivered Tai Chi Intervention (TaiChi4Joint) for Managing Aromatase Inhibitor-Induced Arthralgia in Patients With Breast Cancer During COVID-19: Longitudinal Pilot Study.

BACKGROUND: Estrogen receptor-positive breast cancer is the most common type of breast cancer in postmenopausal women. Aromatase inhibitors (AIs) are the endocrine therapy of choice recommended for these patients. Up to 50% of those treated with an AI develop arthralgia, often resulting in poor adherence and decreased quality of life. OBJECTIVE: The study is a single-arm longitudinal pilot study aiming to evaluate the safety, feasibility, acceptability, and potential efficacy of TaiChi4Joint, a remotely delivered 12-week tai chi intervention designed to relieve AI-induced joint pain. METHODS: Women diagnosed with stage 0-III breast cancer who received an AI for at least 2 months and reported arthralgia with a ≥4 score on a 0 to 10 scale for joint pain were eligible for study enrollment. Participants were encouraged to join tai chi classes delivered over Zoom three times a week for 12 weeks. Program engagement strategies included using a private Facebook study group and a Box cloud for archiving live class recordings. The program uses SMS text messaging and emails with periodic positive quotes and evidence-based information on tai chi for facilitating community bonding and class attendance. Participants were invited to complete the following assessments at baseline and at 1-, 2-, and 3-month intervals from study enrollment: Brief Pain Inventory, Western Ontario and McMaster University Osteoarthritis Index (WOMAC), The Australian Canadian Osteoarthritis Hand Index (AUSCAN), Fatigue Symptom Inventory, Hot Flash Related Daily Interference Scale (HFRDIS), Pittsburgh Sleep Quality Index (PSQI), and Center for Epidemiological Studies-Depression (CES-D). RESULTS: A total of 55 eligible patients were invited to participate, and 39 (71%) consented and completed the baseline assessments. Participants attended 61% (median) of the suggested classes, with no tai chi-related adverse events reported. Of the 39 participants, 22 completed the 3-month follow-up assessment with a 56% retention rate. Study participants reported improvement from baseline compared to 3 months as follows (paired t test): Brief Pain Inventory (P<.001), AUSCAN pain subscale (P=.007), AUSCAN function subscale (P=.004), Fatigue Symptom Inventory (P=.004) and PSQI (P<.001), and HFRDIS (P=.02) and CES-D (P<.001). In particular, for our primary end point of interest, improvements in hip and knee symptoms, measured by WOMAC's three subscales, were clinically meaningful and statistically significant when adjusted for multiple comparisons from baseline to 3 months post intervention. CONCLUSIONS: The COVID-19 global pandemic has resulted in the need to rethink how mind-body therapies can be delivered. This study demonstrated the feasibility, acceptability, and potential efficacy of a telehealth-based tai chi intervention for reducing AI-induced arthralgia. The intervention decreased patient-reported pain and stiffness, and improved sleep quality and depressive symptoms. Fully powered, large, telehealth-based tai chi trials for AI-associated arthralgia are needed considering our promising findings. TRIAL REGISTRATION: ClinicalTrials.gov NCT04716920; https://www.clinicaltrials.gov/ct2/show/NCT04716920.

Systematic review of yoga for symptom management during conventional treatment of breast cancer patients.

INTRODUCTION: Breast cancer is one of the most commonly diagnosed cancers in women in the US, and its treatments have significant physical and psychological side effects and long-term complications causing significant morbidity and decreased quality of life. Integrative medicine modalities, such as Yoga, have been found to reduce side effects of conventional treatments without interfering with the treatment itself and improve quality of life. In this systematic review, we specifically explored Yoga as a potential option for symptomatic management in patients undergoing conventional breast cancer treatments. METHODS: We performed a literature search that was conducted to include the databases PubMed, PsychINFO, Cochrane Library, Scopus, and CINAHL, resulting in 28 randomized controlled trial (RCT) articles. We review the results of these trials regarding the impact of Yoga in this patient population. RESULTS: Overall, the majority of the RCT articles showed significant benefits of Yoga intervention in various aspects of quality of life, fatigue, nausea/vomiting, sleep quality, anxiety, depression, and distress. There are several studies that have explored the physiological mechanism behind the effects of Yoga and found that Yoga affects both the immune response and inflammation. DISCUSSION: These studies revealed that Yoga has a potential therapeutic role in the symptomatic management of breast cancer patients, enhancing quality of life during treatment as well as improving adherence to treatment. Future studies with more defined and consistent methodologies are necessary to fully understand the potential use of Yoga therapy in patients with breast cancer.

Cerebral Blood Flow and Brain Functional Connectivity Changes in Older Adults Participating in a Mindfulness-Based Stress Reduction Program.

There is a growing interest in the potential beneficial effects of mindfulness meditation training in protecting against age-related physical, emotional, and cognitive decline. The current prospective, single-center, single-arm study investigated if functional magnetic resonance imaging-based changes in cerebral blood flow and brain functional connectivity could be observed in 11 elderly adults (mean age 79) after participation in a Mindfulness-Based Stress Reduction (MBSR) program. The results showed significantly (p < 0.05) altered cerebral blood flow and functional connectivity in the cingulate gyrus, limbic structures, and subregions of the temporal and frontal lobes, similar to findings of other meditation-related studies in younger populations. Furthermore, these changes were also associated with significant improvements in depression symptoms. This study suggests that the MBSR program can potentially modify cerebral blood flow and connectivity in this population.

An updated classification of meditation methods using principles of taxonomy and systematics.

This paper revisits the proposal for the classification of meditation methods which we introduced in our initial 2013 publication, "Toward a Universal Taxonomy and Definition of Meditation". At that time, we advanced the thesis that meditation methods could be effectively segregated into three orthogonal categories by integrating the taxonomic principle of functional essentialism and the paradigm of Affect and Cognition; and we presented relevant research findings which supported that assertion. This iteration expands upon those theoretical and methodological elements by articulating a more comprehensive Three Tier Classification System which accounts for the full range of meditation methods; and demonstrates how recent neuroscience research continues to validate and support our thesis. This paper also introduces a novel criterion-based protocol for formulating classification systems of meditation methods, and demonstrates how this model can be used to compare and evaluate various other taxonomy proposals that have been published over the past 15 years.

Identification of chronic mild traumatic brain injury using resting state functional MRI and machine learning techniques.

Mild traumatic brain injury (mTBI) is a major public health concern that can result in a broad spectrum of short-term and long-term symptoms. Recently, machine learning (ML) algorithms have been used in neuroscience research for diagnostics and prognostic assessment of brain disorders. The present study aimed to develop an automatic classifier to distinguish patients suffering from chronic mTBI from healthy controls (HCs) utilizing multilevel metrics of resting-state functional magnetic resonance imaging (rs-fMRI). Sixty mTBI patients and forty HCs were enrolled and allocated to training and testing datasets with a ratio of 80:20. Several rs-fMRI metrics including fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), degree centrality (DC), voxel-mirrored homotopic connectivity (VMHC), functional connectivity strength (FCS), and seed-based FC were generated from two main analytical categories: local measures and network measures. Statistical two-sample t-test was employed comparing between mTBI and HCs groups. Then, for each rs-fMRI metric the features were selected extracting the mean values from the clusters showing significant differences. Finally, the support vector machine (SVM) models based on separate and multilevel metrics were built and the performance of the classifiers were assessed using five-fold cross-validation and via the area under the receiver operating characteristic curve (AUC). Feature importance was estimated using Shapley additive explanation (SHAP) values. Among local measures, the range of AUC was 86.67-100% and the optimal SVM model was obtained based on combined multilevel rs-fMRI metrics and DC as a separate model with AUC of 100%. Among network measures, the range of AUC was 80.42-93.33% and the optimal SVM model was obtained based on the combined multilevel seed-based FC metrics. The SHAP analysis revealed the DC value in the left postcentral and seed-based FC value between the motor ventral network and right superior temporal as the most important local and network features with the greatest contribution to the classification models. Our findings demonstrated that different rs-fMRI metrics can provide complementary information for classifying patients suffering from chronic mTBI. Moreover, we showed that ML approach is a promising tool for detecting patients with mTBI and might serve as potential imaging biomarker to identify patients at individual level. Clinical trial registration: [clinicaltrials.gov], identifier [NCT03241732].

SPECT Functional Neuroimaging Distinguishes Adult Attention Deficit Hyperactivity Disorder From Healthy Controls in Big Data Imaging Cohorts.

Background: The diagnosis of attention deficit hyperactivity disorder (ADHD) relies on history and observation, as no reliable biomarkers have been identified. In this study, we compared a large single diagnosis group of patients with ADHD (combined, inattentive, and hyperactive) to healthy controls using brain perfusion single-photon emission computed tomography (SPECT) imaging to determine specific brain regions which could serve as potential biomarkers to reliably distinguish ADHD. Methods: In a retrospective analysis, subjects (n = 1,135) were obtained from a large multisite psychiatric database, where resting state (baseline) and on-task SPECT scans were obtained. Only baseline scans were analyzed in the present study. Subjects were separated into two groups - Group 1 (n = 1,006) was composed of patients who only met criteria for ADHD with no comorbid diagnoses, while a control group (n = 129) composed of individuals who did not meet criteria for any psychiatric diagnosis, brain injury, or substance use served as a non-matched control. SPECT regions of interests (ROIs) and visual readings were analyzed using binary logistic regression. Predicted probabilities from this analysis were inputted into a Receiver Operating Characteristic analysis to identify sensitivity, specificity, and accuracy. Results: The baseline ROIs and visual readings show significant separations from healthy controls. Sensitivity of the visual reads was 100% while specificity was >97%. The sensitivity and specificity of the post-hoc ROI analysis were both 100%. Decreased perfusion was primarily seen in the orbitofrontal cortices, anterior cingulate gyri, areas of the prefrontal cortices, basal ganglia, and temporal lobes. In addition, ROI analysis revealed some unexpected areas with predictive value in distinguishing ADHD, such as cerebellar subregions and portions of the temporal lobes. Conclusions: Brain perfusion SPECT distinguishes adult ADHD patients without comorbidities from healthy controls. Areas which were highly significantly different from control and thus may serve as biomarkers in baseline SPECT scans included: medial anterior prefrontal cortex, left anterior temporal lobe, and right insular cortex. Future studies of these potential biomarkers in ADHD patients with comorbidities are warranted.

Alterations in Functional Connectivity Measured by Functional Magnetic Resonance Imaging and the Relationship With Heart Rate Variability in Subjects After Performing Orgasmic Meditation: An Exploratory Study.

Background: We measured changes in resting brain functional connectivity, with blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI), associated with a creative meditation practice that is augmented by clitoral stimulation and is designed to not only achieve a spiritual experience but to help individuals manage their most intimate personal relationships. Briefly, the meditative state is attained by both the male and female participants while the male stimulates the woman's clitoris. The goal of this practice, called orgasmic meditation (OM), according to the practitioners is not sexual, but to use the focus on clitoral stimulation to facilitate a meditative state of connectedness and calm alertness between the two participants. Methods: fMRI was acquired on 20 pairs of subjects shortly following one of two states that were randomized in their order - during the OM practice or during a neutral condition. The practice is performed while the female is lying down on pillows with the clitoris exposed. During the practice, the male performs digital stimulation of the clitoris for 15 min. Resting BOLD image acquisition was performed at completion of the practice to assess changes in functional connectivity associated with the performance of the practice. Results: The results demonstrated significant changes (p < 0.05) in functional connectivity associated with the OM compared to the neutral condition. For the entire group there was altered connectivity following the OM practice involving the left superior temporal lobe, the frontal lobe, anterior cingulate, and insula. In female subjects, there was altered connectivity involving the cerebellum, thalamus, inferior frontal lobe posterior parietal lobe, angular gyrus, amygdala and middle temporal gyrus, and prefrontal cortex. In males, functional connectivity changes involved the supramarginal gyrus, cerebellum, and orbitofrontal gyrus, cerebellum, parahippocampus, inferior temporal gyrus, and anterior cingulate. Conclusion: Overall, these findings suggest a complex pattern of functional connectivity changes occurring in both members of the couple pair that result from this unique meditation practice. The changes represent a hybrid of functional connectivity findings with some similarities to meditation based practices and some with sexual stimulation and orgasm. This study has broader implications for understanding the dynamic relationship between sexuality and spirituality.

N-acetyl cysteine administration affects cerebral blood flow as measured by arterial spin labeling MRI in patients with multiple sclerosis.

BACKGROUND: The purpose of this study was to explore if administration of N-acetyl-cysteine (NAC) in patients with multiple sclerosis (MS) resulted in altered cerebral blood flow (CBF) based on Arterial Spin Labeling (ASL) magnetic resonance imaging (MRI). METHODS: Twenty-three patients with mild to moderate MS, (17 relapsing remitting and 6 primary progressive) were randomized to either NAC plus standard of care (N = 11), or standard of care only (N = 12). The experimental group received NAC intravenously (50 mg/kg) once per week and orally (500mg 2x/day) the other six days. Patients in both groups were evaluated initially and after 2 months (of receiving the NAC or waitlist control) with ASL MRI to measure CBF. Clinical symptom questionnaires were also completed at both time points. RESULTS: The CBF data showed significant differences in several brain regions including the pons, midbrain, left temporal and frontal lobe, left thalamus, right middle frontal lobe and right temporal/hippocampus (p < 0.001) in the MS group after treatment with NAC, when compared to the control group. Self-reported scores related to cognition and attention were also significantly improved in the NAC group as compared to the control group. CONCLUSIONS: The results of this study suggest that NAC administration alters resting CBF in MS patients, and this is associated with qualitative improvements in cognition and attention. Given these findings, large scale efficacy studies will be of value to determine the potential clinical impact of NAC over the course of illness in patients with MS, as well as the most effective dosages and differential effects across subpopulations.

Hybrid diffusion imaging reveals altered white matter tract integrity and associations with symptoms and cognitive dysfunction in chronic traumatic brain injury.

The detection and association of in vivo biomarkers in white matter (WM) pathology after acute and chronic mild traumatic brain injury (mTBI) are needed to improve care and develop therapies. In this study, we used the diffusion MRI method of hybrid diffusion imaging (HYDI)to detect white matter alterations in patients with chronic TBI (cTBI). 40 patients with cTBI presenting symptoms at least three months post injury, and 17 healthy controls underwent magnetic resonance HYDI. cTBI patients were assessed with a battery of neuropsychological tests. A voxel-wise statistical analysis within the white matter skeleton was performed to study between group differences in the diffusion models. In addition, a partial correlation analysis controlling for age, sex, and time after injury was performed within the cTBI cohort, to test for associations between diffusion metrics and clinical outcomes. The advanced diffusion modeling technique of neurite orientation dispersion and density imaging (NODDI) showed large clusters of between-group differences resulting in lower values in the cTBI across the brain, where the single compartment diffusion tensor model failed to show any significant results. However, the diffusion tensor model appeared to be just as sensitive in detecting self-reported symptoms in the cTBI population using a within-group correlation. To the best of our knowledge this study provides the first application of HYDI in evaluation of cTBI using combined DTI and NODDI, significantly enhancing our understanding of the effects of concussion on white matter microstructure and emphasizing the utility of full characterization of complex diffusion to diagnose, monitor, and treat brain injury.

Alterations in cerebral glucose metabolism as measured by 18F-fluorodeoxyglucose-PET in patients with persistent postconcussion syndrome.

BACKGROUND: Many patients who have traumatic brain injury experience a wide range of psychiatric and neurological symptoms (including impairment in functional status, cognition, and mood), and if persistent are referred to as persistent postconcussion syndrome (PCS). To our knowledge, this is the first study to broadly evaluate metabolic dysregulation in a heterogenous patient population meeting the criteria for PCS. METHODS: A total of 64 PCS patients and 37 healthy controls underwent 18F-fluorodeoxyglucose-PET (18F-FDG-PET) scanning, and 70 brain structures (including left and right structures where appropriate) were analyzed in each subject. RESULTS: Compared to the brains of healthy controls, those of PCS patients demonstrated 15 hypermetabolic and 23 hypometabolic regions. Metabolic changes in the brains of PCS patients were subsequently correlated with various indices of symptom severity, mood, and physical/cognitive function. Among PCS patients, increased metabolism in the right cingulate gyrus correlated with the severity of postconcussion symptoms. Conversely, increased metabolism in the left temporal lobe was associated with both improved mood and measures of adaptability/rehabilitation. Furthermore, increased metabolism in the bilateral orbitofrontal regions correlated with improved working memory. CONCLUSIONS: Overall, these findings suggest a complex pattern of cerebral metabolism in PCS patients, with a mixture of hypometabolic and hypermetabolic regions that correlate with various symptoms, highlighting both potential pathological and compensatory mechanisms in PCS. The findings also suggest that FDG PET is useful for providing neurophysiological information in the evaluation of patients with PCS and may help guide future targeted therapies.

Tau Imaging in Head Injury.

Tau proteins play a significant role in a variety of degenerative neurologic conditions. Postmortem neuropathology studies of victims of repeat and severe head trauma have defined a unique spatial expression of neurologic tauopathies in these individuals, known as chronic traumatic encephalopathy. Established and newly developed radiotracers are now being applied to head injury populations with the intent of diagnosis and disease monitoring. This review assesses the role of tau in head injury, the state of tau radiotracer development, and the potential clinical value of tau-PET as derived from head injury studies.

Spiritual Fitness: A New Dimension in Alzheimer's Disease Prevention.

BACKGROUND: Religious and spiritual interventions may have an effect on Alzheimer's disease prevention. Kirtan Kriya meditation has been shown to mitigate the deleterious effects of chronic stress on cognition, reverse memory loss, and create psychological and spiritual wellbeing, which may reduce multiple drivers of Alzheimer's disease risk. OBJECTIVE: To detail a new concept in medicine called Spiritual Fitness, a merging of stress reduction, basic wellbeing, and psycho/spiritual wellbeing to prevent Alzheimer's disease. METHODS: The literature on the topics mentioned above is described, including an in-depth discussion on why and how each are critical to advancing the future of Alzheimer's disease prevention. The many negative effects of chronic stress, and the benefits of Kirtan Kriya, are reviewed. The four pillars of basic wellbeing, six practical aspects of psychological wellbeing, and the four new non-sectarian features of spiritual fitness are then disclosed. Moreover, instructions on practicing Kirtan Kriya are offered in the Supplementary Material. CONCLUSION: Religious and spiritual practices, including Kirtan Kriya, are crucial components in the development of enhanced cognition and well-being, which may help prevent and, in some cases, reverse cognitive decline. The key point of this review is that making a commitment to live a brain longevity lifestyle including spiritual fitness is a critically important way for aging Alzheimer's disease free. We hope that this article will inspire scientists, clinicians, and patients to embrace this new concept of spiritual fitness and make it a part of every multidomain program for the prevention of cognitive disability.