Diagnostic utility of brain MRI volumetry in comparing traumatic brain injury, Alzheimer disease and behavioral variant frontotemporal dementia.

BACKGROUND: Brain MRI with volumetric quantification, MRI volumetry, can improve diagnostic delineation of patients with neurocognitive disorders by identifying brain atrophy that may not be evident on visual assessments. OBJECTIVE: To investigate diagnostic utility of MRI volumetry in traumatic brain injury (TBI), early-onset Alzheimer disease (EOAD), late-onset Alzheimer disease, and behavioral variant frontotemporal dementia (bvFTD). METHOD: We utilized 137 participants of TBI (n = 40), EOAD (n = 45), LOAD (n = 32), and bvFTD (n = 20). Participants had 3D T1 brain MRI imaging amendable to MRI volumetry. Scan volumes were analyzed with Neuroreader. One-way ANOVA compared brain volumes across diagnostic groups. Discriminant analysis was done with leave-one-out cross validation on Neuroreader metrics to determine diagnostic delineation across groups. RESULT: LOAD was the oldest compared to other groups (F = 27.5, p < .001). There were no statistically significant differences in sex (p = .58) with women comprising 54.7% of the entire cohort. EOAD and LOAD had the lowest Mini-Mental State Exam (MMSE) scores compared to TBI (p = .04 for EOAD and p = .01 for LOAD). LOAD had lowest hippocampal volumes (Left Hippocampus F = 13.1, Right Hippocampus F = 7.3, p < .001), low white matter volume in TBI (F = 5.9, p < .001), lower left parietal lobe volume in EOAD (F = 9.4, p < .001), and lower total gray matter volume in bvFTD (F = 32.8, p < .001) and caudate atrophy (F = 1737.5, p < .001). Areas under the curve ranged from 92.3 to 100%, sensitivity between 82.2 and 100%, specificity of 78.1-100%. TBI was the most accurately delineated diagnosis. Predictive features included caudate, frontal, parietal, temporal lobar and total white matter volumes. CONCLUSION: We identified the diagnostic utility of regional volumetric differences across multiple neurocognitive disorders. Brain MRI volumetry is widely available and can be applied in distinguishing these disorders.

Exercise-Related Physical Activity Relates to Brain Volumes in 10,125 Individuals.

BACKGROUND: The potential neuroprotective effects of regular physical activity on brain structure are unclear, despite links between activity and reduced dementia risk. OBJECTIVE: To investigate the relationships between regular moderate to vigorous physical activity and quantified brain volumes on magnetic resonance neuroimaging. METHODS: A total of 10,125 healthy participants underwent whole-body MRI scans, with brain sequences including isotropic MP-RAGE. Three deep learning models analyzed axial, sagittal, and coronal views from the scans. Moderate to vigorous physical activity, defined by activities increasing respiration and pulse rate for at least 10 continuous minutes, was modeled with brain volumes via partial correlations. Analyses adjusted for age, sex, and total intracranial volume, and a 5% Benjamini-Hochberg False Discovery Rate addressed multiple comparisons. RESULTS: Participant average age was 52.98±13.04 years (range 18-97) and 52.3% were biologically male. Of these, 7,606 (75.1%) reported engaging in moderate or vigorous physical activity approximately 4.05±3.43 days per week. Those with vigorous activity were slightly younger (p < 0.00001), and fewer women compared to men engaged in such activities (p = 3.76e-15). Adjusting for age, sex, body mass index, and multiple comparisons, increased days of moderate to vigorous activity correlated with larger normalized brain volumes in multiple regions including: total gray matter (Partial R = 0.05, p = 1.22e-7), white matter (Partial R = 0.06, p = 9.34e-11), hippocampus (Partial R = 0.05, p = 5.96e-7), and frontal, parietal, and occipital lobes (Partial R = 0.04, p≤1.06e-5). CONCLUSIONS: Exercise-related physical activity is associated with increased brain volumes, indicating potential neuroprotective effects.

Visceral and Subcutaneous Abdominal Fat Predict Brain Volume Loss at Midlife in 10,001 Individuals.

Abdominal fat is increasingly linked to brain health. A total of 10,001 healthy participants were scanned on 1.5T MRI with a short whole-body MR imaging protocol. Deep learning with FastSurfer segmented 96 brain regions. Separate models segmented visceral and subcutaneous abdominal fat. Regression analyses of abdominal fat types and normalized brain volumes were evaluated, controlling for age and sex. Logistic regression models determined the risk of brain total gray and white matter volume loss from the highest quartile of visceral fat and lowest quartile of these brain volumes. This cohort had an average age of 52.9 ± 13.1 years with 52.8% men and 47.2% women. Segmented visceral abdominal fat predicted lower volumes in multiple regions including: total gray matter volume (r = -.44, p<.001), total white matter volume (r =-.41, p<.001), hippocampus (r = -.39, p< .001), frontal cortex (r = -.42, p<.001), temporal lobes (r = -.44, p<.001), parietal lobes (r = -.39, p<.001), occipital lobes (r =-.37, p<.001). Women showed lower brain volumes than men related to increased visceral fat. Visceral fat predicted increased risk for lower total gray matter (age 20-39: OR = 5.9; age 40-59, OR = 5.4; 60-80, OR = 5.1) and low white matter volume: (age 20-39: OR = 3.78; age 40-59, OR = 4.4; 60-80, OR = 5.1). Higher subcutaneous fat is related to brain volume loss. Elevated visceral and subcutaneous fat predicted lower brain volumes and may represent novel modifiable factors in determining brain health.

Neuroinflammation: A Modifiable Pathway Linking Obesity, Alzheimer's disease, and Depression.

Obesity, depression and Alzheimer's disease (AD) are three major interrelated modern health conditions with complex relationships. Early-life depression may serve as a risk factor for AD, while late-life depression may be a prodrome of AD. Depression affects approximately 23% of obese individuals, and depression itself raises the risk of obesity by 37%. Mid-life obesity independently increases AD risk, while late-life obesity, particularly metabolically healthy obesity, may offer protection against AD pathology. Chronic inflammation serves as a key mechanism linking obesity, AD, and depression, encompassing systemic inflammation from metabolic disturbances, immune dysregulation through the gut microbiome, and direct interactions with amyloid pathology and neuroinflammation. In this review, we explore the biological mechanisms of neuroinflammation in relation to obesity, AD, and depression. We assess the efficacy of therapeutic interventions targeting neuroinflammation and discuss current and future radiological imaging initiatives for studying neuroinflammation. By comprehending the intricate interplay among depression, obesity, and AD, especially the role of neuroinflammation, we can advance our understanding and develop innovative strategies for prevention and treatment.

Handgrip Strength Is Related to Hippocampal and Lobar Brain Volumes in a Cohort of Cognitively Impaired Older Adults with Confirmed Amyloid Burden.

BACKGROUND: Strength and mobility are essential for activities of daily living. With aging, weaker handgrip strength, mobility, and asymmetry predict poorer cognition. We therefore sought to quantify the relationship between handgrip metrics and volumes quantified on brain magnetic resonance imaging (MRI). OBJECTIVE: To model the relationships between handgrip strength, mobility, and MRI volumetry. METHODS: We selected 38 participants with Alzheimer's disease dementia: biomarker evidence of amyloidosis and impaired cognition. Handgrip strength on dominant and non-dominant hands was measured with a hand dynamometer. Handgrip asymmetry was calculated. Two-minute walk test (2MWT) mobility evaluation was combined with handgrip strength to identify non-frail versus frail persons. Brain MRI volumes were quantified with Neuroreader. Multiple regression adjusting for age, sex, education, handedness, body mass index, and head size modeled handgrip strength, asymmetry and 2MWT with brain volumes. We modeled non-frail versus frail status relationships with brain structures by analysis of covariance. RESULTS: Higher non-dominant handgrip strength was associated with larger volumes in the hippocampus (p = 0.02). Dominant handgrip strength was related to higher frontal lobe volumes (p = 0.02). Higher 2MWT scores were associated with larger hippocampal (p = 0.04), frontal (p = 0.01), temporal (p = 0.03), parietal (p = 0.009), and occipital lobe (p = 0.005) volumes. Frailty was associated with reduced frontal, temporal, and parietal lobe volumes. CONCLUSION: Greater handgrip strength and mobility were related to larger hippocampal and lobar brain volumes. Interventions focused on improving handgrip strength and mobility may seek to include quantified brain volumes on MR imaging as endpoints.

Differentiation of Subjective Cognitive Decline, Mild Cognitive Impairment, and Dementia Using qEEG/ERP-Based Cognitive Testing and Volumetric MRI in an Outpatient Specialty Memory Clinic.

BACKGROUND: Distinguishing between subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia in a scalable, accessible way is important to promote earlier detection and intervention. OBJECTIVE: We investigated diagnostic categorization using an FDA-cleared quantitative electroencephalographic/event-related potential (qEEG/ERP)-based cognitive testing system (eVox® by Evoke Neuroscience) combined with an automated volumetric magnetic resonance imaging (vMRI) tool (Neuroreader® by Brainreader). METHODS: Patients who self-presented with memory complaints were assigned to a diagnostic category by dementia specialists based on clinical history, neurologic exam, neuropsychological testing, and laboratory results. In addition, qEEG/ERP (n = 161) and quantitative vMRI (n = 111) data were obtained. A multinomial logistic regression model was used to determine significant predictors of cognitive diagnostic category (SCD, MCI, or dementia) using all available qEEG/ERP features and MRI volumes as the independent variables and controlling for demographic variables. Area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the diagnostic accuracy of the prediction models. RESULTS: The qEEG/ERP measures of Reaction Time, Commission Errors, and P300b Amplitude were significant predictors (AUC = 0.79) of cognitive category. Diagnostic accuracy increased when volumetric MRI measures, specifically left temporal lobe volume, were added to the model (AUC = 0.87). CONCLUSION: This study demonstrates the potential of a primarily physiological diagnostic model for differentiating SCD, MCI, and dementia using qEEG/ERP-based cognitive testing, especially when combined with volumetric brain MRI. The accessibility of qEEG/ERP and vMRI means that these tools can be used as adjuncts to clinical assessments to help increase the diagnostic certainty of SCD, MCI, and dementia.

Quantified Brain Magnetic Resonance Imaging Volumes Differentiate Behavioral Variant Frontotemporal Dementia from Early-Onset Alzheimer's Disease.

BACKGROUND: The differentiation of behavioral variant frontotemporal dementia (bvFTD) from early-onset Alzheimer's disease (EOAD) by clinical criteria can be inaccurate. The volumetric quantification of clinically available magnetic resonance (MR) brain scans may facilitate early diagnosis of these neurodegenerative dementias. OBJECTIVE: To determine if volumetric quantification of brain MR imaging can identify persons with bvFTD from EOAD. METHODS: 3D T1 MR brain scans of 20 persons with bvFTD and 45 with EOAD were compared using Neuroreader to measure subcortical, and lobar volumes, and Volbrain for hippocampal subfields. Analyses included: 1) discriminant analysis with leave one out cross-validation; 2) input of predicted probabilities from this process into a receiver operator characteristic (ROC) analysis; and 3) Automated linear regression to identify predictive regions. RESULTS: Both groups were comparable in age and sex with no statistically significant differences in symptom duration. bvFTD had lower volume percentiles in frontal lobes, thalamus, and putamen. EOAD had lower parietal lobe volumes. ROC analyses showed 99.3% accuracy with Neuroreader percentiles and 80.2% with subfields. The parietal lobe was the most predictive percentile. Although there were differences in hippocampal (particularly left CA2-CA3) subfields, it did not add to the discriminant analysis. CONCLUSION: Percentiles from an MR based volumetric quantification can help differentiate between bvFTD from EOAD in routine clinical care. Use of hippocampal subfield volumes does not enhance the diagnostic separation of these two early-onset dementias.

Quantitative MRI Differences Between Early versus Late Onset Alzheimer's Disease.

Investigators report greater parietal tau deposition and alternate frontoparietal network involvement in early onset Alzheimer's Disease (EOAD) with onset <65 years as compared with typical late onset AD (LOAD). To determine whether clinical brain MRI volumes reflect these differences in EOAD compared with LOAD. This study investigated the clinical MRI scans of 45 persons with Clinically Probable AD with onset <65 years, and compared them to 32 with Clinically Probable AD with onset ≥65 years. Brain volumes on their T1 MRI scans were quantified with a volumetric program. Receiver operating curve analyses were performed. Persons with EOAD had significantly smaller parietal lobes (volumetric percentiles) than LOAD. Late onset Alzheimer's Disease had a smaller left putamen and hippocampus. Area Under the Curve was 96.5% with brain region delineation of EOAD compared to LOAD. This study indicates parietal atrophy less than 30% of normal on clinical MRI scans is suggestive of EOAD compared to LOAD.

Brain Structure in Bilingual Compared to Monolingual Individuals with Alzheimer's Disease: Proof of Concept.

BACKGROUND: Bilingualism is increasingly recognized as protective in persons at risk for Alzheimer's disease (AD). OBJECTIVE: Compare MRI measured brain volumes in matched bilinguals versus monolinguals with AD. METHODS: This IRB approved study analyzed T1 volumetric brain MRIs of patients with criteria-supported Probable AD. We identified 17 sequential bilinguals (any native language) with Probable AD, matched to 28 (62%) monolinguals on age and MMSE. Brain volumes were quantified with Neuroreader. Regional volumes as fraction of total intracranial volume (TIV) were compared between both groups, and Cohen's D effect sizes were calculated for statistically significant structures. Partial correlations between bilingualism and brain volumes adjusted for age, gender, and TIV. RESULTS: Bilinguals had higher brain volumes in 37 structures. Statistical significance (p < 0.05) was observed in brainstem (t = 2.33, p = 0.02, Cohen's D = 0.71) and ventral diencephalon (t = 3.01, p = 0.004, Cohen's D = 0.91). Partial correlations showed statistical significance between bilingualism and larger volumes in brainstem (rp = 0 . 37, p = 0.01), thalamus (rp = 0.31, p = 0.04), ventral diencephalon (rp = 0.50, p = 0.001), and pallidum (rp = 0.38, p = 0.01). Bilingualism positively correlated with hippocampal volume, though not statistically significant (rp = 0.17, p = 0.26). No brain volumes were larger in monolinguals. CONCLUSION: Bilinguals demonstrated larger thalamic, ventral diencephalon, and brainstem volumes compared to matched monolinguals with AD. This may represent a neural substrate for increased cognitive reserve in bilingualism. Future studies should extrapolate this finding into cognitively normal persons at risk for AD.

Neurobiology of COVID-19.

Anosmia, stroke, paralysis, cranial nerve deficits, encephalopathy, delirium, meningitis, and seizures are some of the neurological complications in patients with coronavirus disease-19 (COVID-19) which is caused by acute respiratory syndrome coronavirus 2 (SARS-Cov2). There remains a challenge to determine the extent to which neurological abnormalities in COVID-19 are caused by SARS-Cov2 itself, the exaggerated cytokine response it triggers, and/or the resulting hypercoagulapathy and formation of blood clots in blood vessels throughout the body and the brain. In this article, we review the reports that address neurological manifestations in patients with COVID-19 who may present with acute neurological symptoms (e.g., stroke), even without typical respiratory symptoms such as fever, cough, or shortness of breath. Next, we discuss the different neurobiological processes and mechanisms that may underlie the link between SARS-Cov2 and COVID-19 in the brain, cranial nerves, peripheral nerves, and muscles. Finally, we propose a basic "NeuroCovid" classification scheme that integrates these concepts and highlights some of the short-term challenges for the practice of neurology today and the long-term sequalae of COVID-19 such as depression, OCD, insomnia, cognitive decline, accelerated aging, Parkinson's disease, or Alzheimer's disease in the future. In doing so, we intend to provide a basis from which to build on future hypotheses and investigations regarding SARS-Cov2 and the nervous system.

MRI Volumetric Quantification in Persons with a History of Traumatic Brain Injury and Cognitive Impairment.

BACKGROUND: While traumatic brain injury (TBI) is recognized as a risk factor for dementia, there is lack of clinical tools to identify brain changes that may confer such vulnerability. Brain MRI volumetric quantification can sensitively identify brain atrophy. OBJECTIVE: To characterize regional brain volume loss in persons with TBI presenting with cognitive impairment. METHODS: IRB approved review of medical records in patients with cognitive decline focused on those who had documented TBI histories and brain MRI scans after TBI (n = 40, 67.7±14.5 years) with volumetric quantification by applying an FDA cleared software program. TBI documentation included head trauma mechanism. Brain volumes were compared to a normative database to determine the extent of atrophy. Correlations between these regions and global tests of cognition (MMSE in n = 17, MoCA in n = 27, n = 14 in both) were performed. RESULTS: Multiple regions demonstrated volume loss in TBI, particularly ventral diencephalon, putamen, and pallidum with smaller magnitude of atrophy in temporal lobes and brainstem. Lobar structures showed strongest correlations between atrophy and lower scores on MMSE and MoCA. The hippocampus, while correlated to tests of cognitive function, was the least atrophic region as a function of TBI history. CONCLUSION: Persons with TBI history exhibit show regional brain atrophy. Several of these areas, such as thalamus and temporal lobes, also correlate with cognitive function. Alzheimer's disease atrophy was less likely given relative sparing of the hippocampi. Volumetric quantification of brain MRI in TBI warrants further investigation to further determine its clinical potential in TBI and differentiating causes of cognitive impairment.

Emerging advances of in vivo detection of chronic traumatic encephalopathy and traumatic brain injury.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disorder that is of epidemic proportions in contact sports athletes and is linked to subconcussive and concussive repetitive head impacts (RHI). Although postmortem analysis is currently the only confirmatory method to diagnose CTE, there has been progress in early detection techniques of fluid biomarkers as well as in advanced neuroimaging techniques. Specifically, promising new methods of diffusion MRI and radionucleotide PET scans could aid in the early detection of CTE.The authors examine early detection methods focusing on various neuroimaging techniques. Advances in structural and diffusion MRI have demonstrated the ability to measure volumetric and white matter abnormalities associated with CTE. Recent studies using radionucleotides such as flortaucipir and 18F-FDDNP have shown binding patterns that are consistent with the four stages of neurofibrillary tangle (NFT) distribution postmortem. Additional research undertakings focusing on fMRI, MR spectroscopy, susceptibility-weighted imaging, and singlephoton emission CT are also discussed as are advanced MRI methods such as diffusiontensor imaging and arterial spin labeled. Neuroimaging is fast becoming a key instrument in early detection and could prove essential for CTE quantification. This review explores a global approach to in vivo early detection.Limited data of in vivo CTE biomarkers with postmortem confirmation are available. While some data exist, they are limited by selection bias. It is unlikely that a single test will be sufficient to properly diagnosis and distinguish CTE from other neurodegenerative diseases such as Alzheimer disease or Frontotemporal Dementia. However, with a combination of fluid biomarkers, neuroimaging, and genetic testing, early detection may become possible.

Patterns of Regional Cerebral Blood Flow as a Function of Age Throughout the Lifespan.

BACKGROUND: Understanding the influence of aging on the brain remains a challenge in determining its role as a risk factor for Alzheimer's disease. OBJECTIVE: To identify patterns of aging in a large neuroimaging cohort. METHODS: A large psychiatric cohort of 31,227 individuals received brain SPECT at rest and during a concentration task for a total of 62,454 scans. ANOVA was done to identify the mean age trends over the course of the age range in this group, 0-105 years. A regression model in which brain SPECT regions of interest was used to predict chronological age (CA) was then utilized to derive brain estimated age (BEA). The difference between CA and BEA was calculated to determine increased brain aging in common disorders in our sample such as depression, dementia, substance use, and anxiety. RESULTS: Throughout the lifespan, variations in perfusion were observed in childhood, adolescence, and late life. Increased brain aging was seen in alcohol use, cannabis use, anxiety, bipolar, schizophrenia, attention-deficit/hyperactivity disorder, and in men. CONCLUSION: Brain SPECT can predict chronological age and this feature varies as a function of common psychiatric disorders.

Deficits in Regional Cerebral Blood Flow on Brain SPECT Predict Treatment Resistant Depression.

BACKGROUND: Depression remains an important risk factor for Alzheimer's disease, yet few neuroimaging biomarkers are available to identify treatment response in depression. OBJECTIVE: To analyze and compare functional perfusion neuroimaging in persons with treatment resistant depression (TRD) compared to those experiencing full remission. METHODS: A total of 951 subjects from a community psychiatry cohort were scanned with perfusion single photon emission computed tomography (SPECT) of the brain in both resting and task related settings. Of these, 78% experienced either full remission (n = 506) or partial remission (n = 237) and 11% were minimally responsive (n = 103) or non-responsive (11%. n = 106). Severity of depression symptoms were used to define these groups with changes in the Beck Depression Inventory prior to and following treatment. Voxel-based analyses of brain SPECT images from full remission compared to the worsening group was conducted with the statistical parametric mapping software, version 8 (SPM 8). Multiple comparisons were accounted for with a false discovery rate (p < 0.001). RESULTS: Persons with depression that worsened following treatment had reduced cerebral perfusion compared to full remission in the multiple regions including the bilateral frontal lobes, right hippocampus, left precuneus, and cerebellar vermis. Such differences were observed on both resting and concentration SPECT scans. CONCLUSION: Our findings identify imaging-based biomarkers in persons with depression related to treatment response. These findings have implications in understanding both depression to prognosis and its role as a risk factor for dementia.

Gender-Based Cerebral Perfusion Differences in 46,034 Functional Neuroimaging Scans.

BACKGROUND: Studies have reported that females have widespread increases in regional cerebral blood flow, but the studies were relatively small and inconsistent. OBJECTIVE: Here we analyzed a healthy and a very large clinical psychiatric population to determine the effect of gender, using single photon emission computed tomography (SPECT). METHODS: Whole brain and region of interest (ROI) gender differences were analyzed in a total of 46,034 SPECT scans at baseline and concentration. The sample included 119 healthy subjects and 26,683 patients (60.4% male, 39.6% female); a subset of 11,587 patients had complete diagnostic information. A total of 128 regions were analyzed according to the AAL Atlas, using ROI Extract and SPSS statistical software programs, controlling for age, diagnoses, and correcting for multiple comparisons. RESULTS: Compared to males, healthy females showed significant whole brain (p < 0.01) and ROI increases in 65 baseline and 48 concentration regions (p < 0.01 corrected). Healthy males showed non-significant increases in 9 and 22 regions, respectively. In the clinical group, there were widespread significant increases in females, especially in the prefrontal and limbic regions, and specific increases in males in the inferior occipital lobes, inferior temporal lobes, and lobule 7 and Crus 2 of the cerebellum. These findings were replicated in the subset of 11,587 patients with the effect of diagnoses removed. CONCLUSIONS: Our results demonstrated significant gender differences in a healthy and clinical population. Understanding these differences is crucial in evaluating functional neuroimaging and may be useful in understanding the epidemiological gender differences among psychiatric disorders.

Quantitative Erythrocyte Omega-3 EPA Plus DHA Levels are Related to Higher Regional Cerebral Blood Flow on Brain SPECT.

BACKGROUND: The interrelationships between omega-3 fatty acids status, brain perfusion, and cognition are not well understood. OBJECTIVE: To evaluate if SPECT brain imaging of cerebral perfusion and cognition varies as a function of omega-3 fatty acid levels. METHODS: A random sample of 166 study participants was drawn from a psychiatric referral clinical for which erythrocyte quantification of omega-3 eicosapentaenoic acid (EPA) plus docosahexaenoic acid (DHA) (the Omega-3 Index) was available. Quantitative brain SPECT was done on 128 regions based on a standard anatomical Atlas. Persons with erythrocyte EPA+DHA concentrations were dichotomized based on membership in top 50th percentile versus bottom 50th percentile categories. Two-sample t-tests were done to identify statistically significant differences in perfusion between the percentile groups. Partial correlations were modeled between EPA+DHA concentration and SPECT regions. Neurocognitive status was assessed using computerized testing (WebNeuro) and was separately correlated to cerebral perfusion on brain SPECT imaging and omega-3 EPA+DHA levels. RESULTS: Partial correlation analyses showed statistically significant relationships between higher omega-3 levels and cerebral perfusion were in the right parahippocampal gyrus (r = 0.20, p = 0.03), right precuneus (r = 0.20, p = 0.03), and vermis subregion 6 (p = 0.21, p = 0.03). Omega-3 Index levels separately correlated to the feeling subsection of the WebNeuro (r = 0.25, p = 0.01). CONCLUSION: Quantitative omega-3 EPA+DHA erythrocyte concentrations are independently correlated with brain perfusion on SPECT imaging and neurocognitive tests. These results have implications for the role of omega-3 fatty acids toward contributing to cognitive reserve.

Classification of Depression, Cognitive Disorders, and Co-Morbid Depression and Cognitive Disorders with Perfusion SPECT Neuroimaging.

BACKGROUND: Depression and cognitive disorders (CDs) are two common co-morbid afflictions that commonly present with overlapping symptoms. OBJECTIVE: To evaluate if perfusion neuroimaging with brain SPECT can distinguish persons with depression from those with CDs or both conditions. METHODS: Inclusion criteria were DSM-IV defined depression or CDs (Alzheimer's disease, vascular dementia, dementia not otherwise specified, and amnestic disorders not otherwise specified) including persons with both (total n = 4,541; 847 CDs, 3,269 depression, 425 with both). Perfusion differences between the groups were calculated using two-sampled t-tests corrected for multiple comparisons. Diagnostic separation was determined with discriminant analysis. Feature selection revealed predictive regions in delineating depression from CDs and comorbid cases. RESULTS: Persons with CDs had lower cerebral perfusion compared to depression. In co-morbid persons, cerebral hypoperfusion was additive, with regions showing lower regional cerebral blood flow compared to either diagnosis alone. Both baseline and concentration SPECT regions yielded correct classification of 86% and leave one out cross-validation of 83%. AUC analysis for SPECT regions showed 86% accuracy, 80% sensitivity and 75% specificity. Discriminant analysis separated depression and CDs from comorbid cases with correct classification of 90.8% and cross validated accuracy of 88.6%. Area under the curve was 83% with sensitivity of 80% and specificity of 70%. Feature selection identified the most predictive regions in left hippocampus, right insula, cerebellar, and frontal lobe regions. CONCLUSION: Quantitative perfusion SPECT neuroimaging distinguishes depression from dementia and those with both co-morbidities. Perfusion brain SPECT can be utilized clinically to delineate between these two disorders.

Discriminative Properties of Hippocampal Hypoperfusion in Marijuana Users Compared to Healthy Controls: Implications for Marijuana Administration in Alzheimer's Dementia.

BACKGROUND: Few studies have evaluated the impact of marijuana use on regional cerebral blood flow. OBJECTIVE: To determine whether perfusion in specific brain regions on functional neuroimaging, including those affected by Alzheimer's disease pathology, are abnormal in marijuana users compared to controls. METHOD: Persons with a diagnosis of cannabis use disorder by DSM-IV and DSM-V criteria (n = 982) were compared to controls (n = 92) with perfusion neuroimaging with SPECT at rest and at a concentration task. Perfusion estimates were quantified using a standard atlas. Cerebral perfusion differences were calculated using one-way ANOVA. Diagnostic separation was determined with discriminant analysis of all subjects. Feature selection with a minimum redundancy maximum relevancy (mRMR) identified predictive regions in a subset of marijuana users (n = 436) with reduced psychiatric co-morbidities. RESULTS: Marijuana users showed lower cerebral perfusion on average (p < 0.05). Discriminant analysis distinguished marijuana users from controls with correct classification of 96% and leave one out cross-validation of 92%. With concentration SPECT regions, there was correct classification of 95% with a leave-one-out cross validation of 90%. AUC analysis for concentration SPECT regions showed 95% accuracy, 90% sensitivity, and 83% specificity. The mRMR analysis showed right hippocampal hypoperfusion on concentration SPECT imaging was the most predictive in separating marijuana subjects from controls. CONCLUSION: Multiple brain regions show low perfusion on SPECT in marijuana users. The most predictive region distinguishing marijuana users from healthy controls, the hippocampus, is a key target of Alzheimer's disease pathology. This study raises the possibility of deleterious brain effects of marijuana use.

X-ray radiation and the risk of multiple sclerosis: Do the site and dose of exposure matter?

BACKGROUND: The sporadic cases of radiation-activated multiple sclerosis (MS) has been previously described, with a few studies focused on the relationship between radiation and the risk of MS. The aim of our study was to evaluate the association between history of X-ray radiation and MS. METHODS: This case-control study was conducted on 150 individuals including 65 MS patients and 85 age- and sex-matched healthy controls enrolled using non-probability convenient sampling. Any history of previous Xray radiation consisted of job-related X-ray exposure, radiotherapy, radiographic evaluations including chest Xray, lumbosacral X-ray, skull X-ray, paranasal sinuses (PNS) X-ray, gastrointestinal (GI) series, foot X-ray and brain CT scanning were recorded and compared between two groups. Statistical analysis was performed using independent t test, Chi square and receiver operating characteristics (ROC) curve methods through SPSS software. RESULTS: History of both diagnostic [OR=3.06 (95% CI: 1.32-7.06)] and therapeutic [OR=7.54 (95% CI: 1.5935.76) X-ray radiations were significantly higher among MS group. Mean number of skull X-rays [0.4 (SD=0.6) vs. 0.1 (SD=0.3), p=0.004] and brain CT scanning [0.9 (SD=0.8) vs. 0.5 (SD=0.7), p=0.005] was higher in MS group as well as mean of the cumulative X-ray radiation dosage [1.84 (SD=1.70) mSv vs. 1.11 (SD=1.54) mSv; p=0.008]. CONCLUSION: Our study was one of the first to show higher history of X-ray radiation in patients with MS compared to healthy controls. A possible association was also found between the dose and the site exposed to X-ray radiation and risk of developing MS.