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Objective: To examine the utility of single-photon emission computed tomography (SPECT) to predict conversion from mild cognitive impairment (MCI) to Alzheimer disease (AD).Design: Longitudinal, prospective study.Setting: University-based memory disorders clinic.Participants: One hundred twenty seven patients with MCI and 59 healthy comparison subjects followed up for 1-9 years.Measurements: Diagnostic evaluation, neuropsychological tests, social/cognitive function, olfactory identification, apolipoprotein E genotype, magnetic resonance imaging, and brain Tc hexamethyl-propylene-aminoxime SPECT scan with visual ratings, and region of interest (ROI) analyses were done.Results: Visual ratings of SPECT temporal and parietal blood flow did not distinguish eventual MCI converters to AD (N = 31) from nonconverters (N = 96), but the global rating predicted conversion (41.9% sensitivity and 82.3% specificity, Fisher's exact test p = 0.013). Blood flow in each ROI was not predictive, but when dichotomized at the median value of the patients with MCI, low flow increased the hazard of conversion to AD for parietal (hazard ratio: 2.96, 95% confidence interval: 1.16-7.53, p = 0.023) and medial temporal regions (hazard ratio: 3.12, 95% confidence interval: 1.14-8.56, p = 0.027). In the 3-year follow-up sample, low parietal (p <0.05) and medial temporal (p <0.01) flow predicted conversion to AD, with or without controlling for age, Mini-Mental State Examination, and apolipoprotein E ε4 genotype. These measures lost significance when other strong predictors were included in logistic regression analyses: verbal memory, social/cognitive functioning, olfactory identification deficits, hippocampal, and entorhinal cortex volumes.Conclusions: SPECT visual ratings showed limited utility in predicting MCI conversion to AD. The modest predictive utility of quantified low parietal and medial temporal flow using SPECT may decrease when other stronger predictors are available. [ABSTRACT FROM AUTHOR]

We have used the nystatin perforated patch technique to study ionic currents in rat pancreatic beta-cells. The access resistance (Ra) between the pipette and the cell cytoplasm, measured by analyzing capacitive currents, decreased with a slow exponential time course (tau = 5.4 +/- 2.7 min) after seal formation. As Ra decreased, the magnitude of voltage-dependent K and Ca currents increased with a similar time course, and their activation kinetics became faster. After Ra stabilized, the macroscopic currents remained stable for up to an hour or more. When the final Ra was sufficiently low, Ca tail currents could be resolved which had properties similar to those recorded with the classical whole-cell technique. Two types of K channels could be characterized with perforated patch recordings of macroscopic K currents: (i) ATP-blockable K (KATP) channels which generate a time and voltage independent current that is blocked by glyburide and enhanced by pinacidil and (ii) voltage-dependent K (Kv) channels. Whole-cell recordings of KATP currents in the absence of ATP in the pipette showed that the maximum KATP conductance of the beta-cell was 83.8 +/- 40 nS. Perforated patch recordings show that the resting KATP conductance is 3.57 +/- 2.09 nS, which corresponds to about 4% of the channels being open in the intact beta-cell. In classical whole-cell recordings. Kv activation kinetics become faster during the first 10-15 min of recording, probably due to a dissipating Donnan potential. In perforated patch recordings where the Donnan potential is very small, Kv activation kinetics were nearly identical to the steady-state whole cell measurements. [ABSTRACT FROM AUTHOR]

The vesicular acetylcholine transporter (VAChT) in the brain is an important presynaptic cholinergic biomarker, and neuroimaging studies of VAChT may provide in vivo information about psychiatric and neurologic conditions including Alzheimer's disease that are not accessible by other methods. The 18 F-labeled radiotracer, ((-)-(1-(-8-(2-[ 18 F]fluoroethoxy)-3-hydroxy-1,2,3,4-tetrahydronaphthalen-2-yl)piperidin-4-yl)(4-fluorophenyl)-methanone ([ 18 F]VAT, 1), was reported as a selective and high affinity ligand for the in vivo imaging of VAChT. The synthesis of [ 18 F]VAT has been reported in a two-step procedure with total 140 min, which includes preparation of 2-[ 18 F]fluoroethyltosylate and alkylation of benzovesamicol (-)-5 precursor with this radiosynthon using two different automated production modules consecutively. A multiple step synthetic route was employed for the synthesis of stereospecific precursor benzovesamicol (-)-5, which is difficult to be adapted for scale-up. To make the production of this tracer more amenable for clinical imaging, we present an improved total synthesis protocol to attain [ 18 F]VAT: (1) a tosylethoxy group being pre-installed tosylate precursor (-)-8 is synthesized to render a simple one-step radiofluorination under mild conditions; (2) The key optically active intermediate benzovesamicol (-)-5 was obtained via the regio- and enantio-enriched ring-opening amination of meso-epoxide 3 with 4-phenylpiperidine derivative 2 under catalysis of a chiral salenCo(III) catalyst 4b, which dramatically simplifies the synthetic route of the tosylate precursor (-)-8. [ 18 F]VAT 1 was prepared within ~65 min with desired chemical and radiochemical purities, via a fully automated procedure, using a commercial PET tracer production module. The final drug product was obtained as a sterile, pyrogen-free solution that conforms United States Pharmacopeia (USP) <823> requirements., (© 2023 John Wiley & Sons Ltd.)

Background: Treatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner., Methods: In the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16., Results: Greater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline., Conclusion: These exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.

Substance use disorder (SUD) comorbidity in mood disorders increases suicide risk. Suicide attempters with active SUD appear to have distinct characteristics but little is known whether these characteristics persist during remission and if they are related to different aspects of suicidal behavior. In this study, suicide attempters with a DSM mood disorder and remitted SUD (AT+SUD) (N = 135) were compared to those without lifetime SUD (AT-SUD) (N = 219) in terms of demographic, clinical and suicidal behavioral characteristics. Factor analyses were conducted to generate subjective distress and impulsivity/aggression factors - previously identified by our group to predict suicide risk in mood disorders. Associations between these traits and SUD history and suicidal behavior characteristics were then tested. Compared with AT-SUD, AT+SUD were more likely to be male, less educated and to have a Cluster B personality disorder. AT+SUD individuals had greater impulsivity/aggression factor scores, but comparable subjective distress scores. AT+SUD made a greater number of suicide attempts, with higher lethality, despite comparable suicide intent and degree of planning with AT-SUD. Impulsivity/aggression was higher in multiple versus single attempters, but did not correlate with suicide attempt lethality. Among suicide attempters with mood disorders, a history of lifetime SUD was associated with more frequent and more lethal suicide attempts. Among other correlates of lifetime SUD in this sample, impulsive/aggressive traits may explain greater frequency of suicide attempts. The results underscore that persons with mood disorders and lifetime SUD are at particularly high risk of frequent and lethal suicide attempts where more intensive prevention efforts are warranted., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Many studies have shown volumetric differences in the hippocampus between COMT gene polymorphisms and other studies have shown differences between depressed patients and controls; yet, few studies have been completed to identify the volumetric differences when taking both factors into consideration. Using voxel-based morphology (VBM) we investigated, in major depressive disorder (MDD) patients and healthy controls, the relationship between COMT gene polymorphism and volumetric abnormalities. Data from 60 MDD patients and 25 healthy controls were included in this study. Volumetric measurements and genotyping of COMTval158met polymorphism were conducted to determine its impact on gray matter volume (GMV) in the hippocampus and amygdala using a Met dominant model (Val/Val vs Met/Val & Met/Met). In the analysis, a significant difference in the right hippocampus (p = 0.015), right amygdala (p = 0.003) and entire amygdala (p = 0.019) was found between the interaction of diagnosis and genotype after MRI scanner, age and sex correction. Healthy controls (HC) with the Met dominant genotype exhibited a larger right hippocampal, right amygdalar and entire amydgalar volume than MDD patients with the Met dominant genotype. Conversely, HC with the Val/Val genotype displayed a lower right hippocampal, right amygdalar and entire amygdalar volume than their MDD counterparts. This study shows that COMT polymorphism and depression may have a confounding effect on neuroimaging studies.

Background: Standard guidelines recommend selective serotonin reuptake inhibitors as first-line antidepressants for adults with major depressive disorder, but success is limited and patients who fail to benefit are often switched to non-selective serotonin reuptake inhibitor agents. This study investigated whether brain- and behavior-based markers of reward processing might be associated with response to bupropion after sertraline nonresponse., Methods: In a two-stage, double-blinded clinical trial, 296 participants were randomized to receive 8 weeks of sertraline or placebo in stage 1. Individuals who responded continued on another 8-week course of the same intervention in stage 2, while sertraline and placebo nonresponders crossed over to bupropion and sertraline, respectively. Data from 241 participants were analyzed. The stage 2 sample comprised 87 patients with major depressive disorder who switched medication and 38 healthy control subjects. A total of 116 participants with major depressive disorder treated with sertraline in stage 1 served as an independent replication sample. The probabilistic reward task and resting-state functional magnetic resonance imaging were administered at baseline., Results: Greater pretreatment reward sensitivity and higher resting-state functional connectivity between bilateral nucleus accumbens and rostral anterior cingulate cortex were associated with positive response to bupropion but not sertraline. Null findings for sertraline were replicated in the stage 1 sample., Conclusions: Pretreatment reward sensitivity and frontostriatal connectivity may identify patients likely to benefit from bupropion following selective serotonin reuptake inhibitor failures. Results call for a prospective replication based on these biomarkers to advance clinical care., (Copyright © 2020 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.

Medications to treat major depressive disorder (MDD) are not equally effective across patients. Given that neural response to rewards is altered in MDD and given that reward-related circuitry is modulated by dopamine and serotonin, we examined, for the first time, whether reward-related neural activity moderated response to sertraline, an antidepressant medication that targets these neurotransmitters. A total of 222 unmedicated adults with MDD randomized to receive sertraline (n = 110) or placebo (n = 112) in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study completed demographic and clinical assessments, and pretreatment functional magnetic resonance imaging while performing a reward task. We tested whether an index of reward system function in the ventral striatum (VS), a key reward circuitry region, moderated differential response to sertraline versus placebo, assessed with the Hamilton Rating Scale for Depression (HSRD) over 8 weeks. We observed a significant moderation effect of the reward index, reflecting the temporal dynamics of VS activity, on week-8 depression levels (Fs ≥ 9.67, ps ≤ 0.002). Specifically, VS responses that were abnormal with respect to predictions from reinforcement learning theory were associated with lower week-8 depression symptoms in the sertraline versus placebo arms. Thus, a more abnormal pattern of pretreatment VS dynamic response to reward expectancy (expected outcome value) and prediction error (difference between expected and actual outcome), likely reflecting serotonergic and dopaminergic deficits, was associated with better response to sertraline than placebo. Pretreatment measures of reward-related VS activity may serve as objective neural markers to advance efforts to personalize interventions by guiding individual-level choice of antidepressant treatment.

Background: Baseline rostral anterior cingulate cortex (rACC) activity is a well-replicated nonspecific predictor of depression improvement. The rACC is a key hub of the default mode network, which prior studies indicate is hyperactive in major depressive disorder. Because default mode network downregulation is reliant on input from the salience network and frontoparietal network, an important question is whether rACC connectivity with these systems contributes to depression improvement., Methods: Our study evaluated this hypothesis in outpatients (N = 238; 151 female) enrolled in the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) 8-week randomized clinical trial of sertraline versus placebo for major depressive disorder. Depression severity was measured using the Hamilton Rating Scale for Depression, and electroencephalography was recorded at baseline and week 1. Exact low-resolution electromagnetic tomography was used to compute activity from the rACC, and key regions within the default mode network (posterior cingulate cortex), frontoparietal network (left dorsolateral prefrontal cortex), and salience network (right anterior insula [rAI]). Connectivity in the theta band (4.5-7 Hz) and beta band (12.5-21 Hz) was computed using lagged phase synchronization., Results: Stronger baseline theta-band rACC-rAI (salience network hub) connectivity predicted greater depression improvement across 8 weeks of treatment for both treatment arms (B = -0.57, 95% confidence interval = -1.07, -0.08, p = .03). Early increases in theta-band rACC-rAI connectivity predicted greater likelihood of achieving remission at week 8 (odds ratio = 2.90, p = .03)., Conclusions: Among patients undergoing treatment, theta-band rACC-rAI connectivity is a prognostic, albeit treatment-nonspecific, indicator of depression improvement, and early connectivity changes may predict clinically meaningful outcomes., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits., Methods: Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics., Results: Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58)., Conclusions: A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.

Attenuation correction is a notable challenge associated with simultaneous PET/MRI, particularly in neuroimaging, where sharp boundaries between air and bone volumes exist. This challenge leads to concerns about the visual and, more specifically, quantitative accuracy of PET reconstructions for data obtained with PET/MRI. Recently developed techniques can synthesize attenuation maps using only MRI data and are likely adequate for clinical use; however, little work has been conducted to assess their suitability for the dynamic PET studies frequently used in research to derive physiologic information such as the binding potential of neuroreceptors in a region. At the same time, existing PET/MRI attenuation correction methods are predicated on synthesizing CT data, which is not ideal, as CT data are acquired with much lower-energy photons than PET data and thus do not optimally reflect the PET attenuation map. Methods: We trained a convolutional neural network to generate patient-specific transmission data from T1-weighted MRI. Using the trained network, we generated transmission data for a testing set comprising 11 subjects scanned with 11 C-labeled N -[2-]4-(2-methoxyphenyl)-1-piperazinyl]ethyl]- N -(2-pyridinyl)cyclohexanecarboxamide) ( 11 C-WAY-100635) and 10 subjects scanned with 11 C-labeled 3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl)benzonitrile ( 11 C-DASB). We assessed both static and dynamic reconstructions. For dynamic PET data, we report differences in both the nondisplaceable and the free binding potential for 11 C-WAY-100635 and distribution volume for 11 C-DASB. Results: The mean bias for generated transmission data was -1.06% ± 0.81%. Global biases in static PET uptake were -0.49% ± 1.7%, and -1.52% ± 0.73% for 11 C-WAY-100635 and 11 C-DASB, respectively. Conclusion: Our neural network approach is capable of synthesizing patient-specific transmission data with sufficient accuracy for both static and dynamic PET studies., (© 2019 by the Society of Nuclear Medicine and Molecular Imaging.)

Importance: Major depressive disorder (MDD) remains challenging to treat. Although several clinical and demographic variables have been found to predict poor antidepressant response, these markers have not been robustly replicated to warrant implementation in clinical care. Increased pretreatment rostral anterior cingulate cortex (rACC) theta activity has been linked to better antidepressant outcomes. However, no prior study has evaluated whether this marker has incremental predictive validity over clinical and demographic measures., Objective: To determine whether increased pretreatment rACC theta activity would predict symptom improvement regardless of randomization arm., Design, Setting, and Participants: A multicenter randomized clinical trial enrolled outpatients without psychosis and with chronic or recurrent MDD between July 29, 2011, and December 15, 2015 (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care [EMBARC]). Patients were consecutively recruited from 4 university hospitals: 634 patients were screened, 296 were randomized to receive sertraline hydrochloride or placebo, 266 had electroencephalographic (EEG) recordings, and 248 had usable EEG data. Resting EEG data were recorded at baseline and 1 week after trial onset, and rACC theta activity was extracted using source localization. Intent-to-treat analysis was conducted. Data analysis was performed from October 7, 2016, to January 19, 2018., Interventions: An 8-week course of sertraline or placebo., Main Outcomes and Measures: The 17-item Hamilton Rating Scale for Depression score (assessed at baseline and weeks 1, 2, 3, 4, 6, and 8)., Results: The 248 participants (160 [64.5%] women, 88 [35.5%] men) with usable EEG data had a mean (SD) age of 36.75 (13.15) years. Higher rACC theta activity at both baseline (b = -1.05; 95% CI, -1.77 to -0.34; P = .004) and week 1 (b = -0.83; 95% CI, -1.60 to -0.06; P < .04) predicted greater depressive symptom improvement, even when controlling for clinical and demographic variables previously linked with treatment outcome. These effects were not moderated by treatment arm. The rACC theta marker, in combination with clinical and demographic variables, accounted for an estimated 39.6% of the variance in symptom change (with 8.5% of the variance uniquely attributable to the rACC theta marker)., Conclusions and Relevance: Increased pretreatment rACC theta activity represents a nonspecific prognostic marker of treatment outcome. This is the first study to date to demonstrate that rACC theta activity has incremental predictive validity., Trial Registration: clinicaltrials.gov Identifier: NCT01407094.

The mechanisms of action of the rapid antidepressant effects of ketamine, an N-methyl-D-aspartate glutamate receptor antagonist, have not been fully elucidated. This study examined the effects of ketamine on ligand binding to a metabotropic glutamatergic receptor (mGluR5) in individuals with major depressive disorder (MDD) and healthy controls. Thirteen healthy and 13 MDD nonsmokers participated in two [ 11 C]ABP688 positron emission tomography (PET) scans on the same day-before and during intravenous ketamine administration-and a third scan 1 day later. At baseline, significantly lower [ 11 C]ABP688 binding was detected in the MDD as compared with the control group. We observed a significant ketamine-induced reduction in mGluR5 availability (that is, [ 11 C]ABP688 binding) in both MDD and control subjects (average of 14±9% and 19±22%, respectively; P<0.01 for both), which persisted 24 h later. There were no differences in ketamine-induced changes between MDD and control groups at either time point (P=0.8). A significant reduction in depressive symptoms was observed following ketamine administration in the MDD group (P<0.001), which was associated with the change in binding (P<0.04) immediately after ketamine. We hypothesize that glutamate released after ketamine administration moderates mGluR5 availability; this change appears to be related to antidepressant efficacy. The sustained decrease in binding may reflect prolonged mGluR5 internalization in response to the glutamate surge.

Despite much research, bipolar depression remains poorly understood, with no clinically useful biomarkers for its diagnosis. The paralimbic system has become a target for biomarker research, with paralimbic structural connectivity commonly reported to distinguish bipolar patients from controls in tractography-based diffusion MRI studies, despite inconsistent findings in voxel-based studies. The purpose of this analysis was to validate existing findings with traditional diffusion MRI metrics and investigate the utility of a novel diffusion MRI metric, entropy of diffusion, in the search for bipolar depression biomarkers. We performed group-level analysis on 9 un-medicated (6 medication-naïve; 3 medication-free for at least 33 days) bipolar patients in a major depressive episode and 9 matched healthy controls to compare: (1) average mean diffusivity (MD) and fractional anisotropy (FA) and; (2) MD and FA histogram entropy-a statistical measure of distribution homogeneity-in the amygdala, hippocampus, orbitofrontal cortex and temporal pole. We also conducted classification analyses with leave-one-out and separate testing dataset (N = 11) approaches. We did not observe statistically significant differences in average MD or FA between the groups in any region. However, in the temporal pole, we observed significantly lower MD entropy in bipolar patients; this finding suggests a regional difference in MD distributions in the absence of an average difference. This metric allowed us to accurately characterize bipolar patients from controls in leave-one-out (accuracy = 83%) and prediction (accuracy = 73%) analyses. This novel application of diffusion MRI yielded not only an interesting separation between bipolar patients and healthy controls, but also accurately classified bipolar patients from controls., (© 2017 Wiley Periodicals, Inc.)

Purpose: To fully quantify PET imaging outcome measures, a blood sampling pump is often used during the PET acquisition. With simultaneous PET/MR studies, a structural magnetization-prepared rapid gradient-echo (MP-RAGE) may also be acquired while the pump is generating electromagnetic noise. This study investigated whether this noise contamination would be detrimental to the quantification of volume and cortical thickness measures obtained from automated segmentation of the MP-RAGE image., Methods: MP-RAGE T1w structural images were acquired for a phantom and 10 healthy volunteers (five female, 27.2 ± 5.1 y old) with the blood sampling pump and without. The white matter signal-to-noise ratio (SNR) was computed for all images. Region-wise cortical thickness and volume were extracted with Freesurfer 5.3.0., Results: The phantom SNR and the white matter human subject SNR was degraded in the MP-RAGE images acquired with the pump (P = 0.005; white matter SNR: 43.9 and 50.8 with the pump and without). Intrasession, region-wise volume and cortical thickness estimates were significantly overestimated with the pump (percent difference: 1.14 ± 2.67% for volume (P = 0.0003) and 0.34 ± 1.59% (P = 0.02) for cortical thickness). Regions with percent differences greater than 5% between pump conditions were those close to tissue-air interfaces: entorhinal, frontal pole, parsorbitalis, temporal pole, and medial orbitofrontal. Synthetically adding Gaussian noise to the without pump MP-RAGE images yielded similar, significant detriments to cortical morphometry compared to without the pump., Conclusions: This study provides evidence that the use of PET blood sampling pumps may generate unstructured, Gaussian-distributed noise in MP-RAGE images that significantly alters the accuracy of Freesurfer-derived volume and cortical thickness estimates. While many cortical regions showed a percent difference of less than 1% with the pump, regions close to tissue-air interfaces, subject to larger susceptibility artifacts, were significantly affected. This potential for decreased accuracy should be considered in PET/MR research studies utilizing blood sampling pumps, as well as any MRI study utilizing radiofrequency noise producing devices such as functional MRI task equipment and physiologic monitoring devices., (© 2017 American Association of Physicists in Medicine.)

Introduction: Previous investigations of test-retest reliability of cerebral blood flow (CBF) at rest measured with pseudo-continuous Arterial Spin Labeling (pCASL) demonstrated good reliability, but are limited by the use of similar scanner platforms. In the present study we examined test-retest reliability of CBF in regions implicated in emotion and the default mode network., Material and Methods: We measured absolute and relative CBF at rest in thirty-one healthy subjects in two scan sessions, one week apart, at four different sites and three different scan platforms. We derived CBF from pCASL images with an automated algorithm and calculated intra-class correlation coefficients (ICCs) across sessions for regions of interest. In addition, we investigated site effects., Results: For both absolute and relative CBF measures, ICCs were good to excellent (i.e. >0.6) in most brain regions, with highest values observed for the subgenual anterior cingulate cortex and ventral striatum. A leave-one-site-out cross validation analysis did not show a significant effect for site on whole brain CBF and there was no proportional bias across sites. However, a significant site effect was present in the repeated measures ANOVA., Conclusions: The high test-retest reliability of CBF measured with pCASL in a range of brain regions implicated in emotion and salience processing, emotion regulation, and the default mode network, which have been previously linked to depression symptomatology supports its use in studies that aim to identify neuroimaging biomarkers of treatment response., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: One in three clinical trial patients with major depressive disorder report symptomatic improvement with placebo. Strategies to mitigate the effect of placebo responses have focused on modifying study design with variable success. Identifying and excluding or controlling for individuals with a high likelihood of responding to placebo may improve clinical trial efficiency and avoid unnecessary medication trials., Methods: Participants included those assigned to the placebo arm (n = 141) of the Establishing Moderators and Biosignatures for Antidepressant Response in Clinical Care (EMBARC) trial. The elastic net was used to evaluate 283 baseline clinical, behavioral, imaging, and electrophysiological variables to identify the most robust yet parsimonious features that predicted depression severity at the end of the double-blind 8-week trial. Variables retained in at least 50% of the 100 imputed data sets were used in a Bayesian multiple linear regression model to simultaneously predict the probabilities of response and remission., Results: Lower baseline depression severity, younger age, absence of melancholic features or history of physical abuse, less anxious arousal, less anhedonia, less neuroticism, and higher average theta current density in the rostral anterior cingulate predicted a higher likelihood of improvement with placebo. The Bayesian model predicted remission and response with an actionable degree of accuracy (both AUC > 0.73). An interactive calculator was developed predicting the likelihood of placebo response at the individual level., Conclusion: Easy-to-measure clinical, behavioral, and electrophysiological assessments can be used to identify placebo responders with a high degree of accuracy. Development of this calculator based on these findings can be used to identify potential placebo responders., (© 2018 S. Karger AG, Basel.)