82 research outputs found
Testâretest reliability of freesurfer measurements within and between sites: Effects of visual approval process
In the last decade, many studies have used automated processes to analyze magnetic resonance imaging (MRI) data such as cortical thickness, which is one indicator of neuronal health. Due to the convenience of image processing software (e.g., FreeSurfer), standard practice is to rely on automated results without performing visual inspection of intermediate processing. In this work, structural MRIs of 40 healthy controls who were scanned twice were used to determine the testâretest reliability of FreeSurferâderived cortical measures in four groups of subjectsâthose 25 that passed visual inspection (approved), those 15 that failed visual inspection (disapproved), a combined group, and a subset of 10 subjects (Travel) whose test and retest scans occurred at different sites. Testâretest correlation (TRC), intraclass correlation coefficient (ICC), and percent difference (PD) were used to measure the reliability in the Destrieux and DesikanâKilliany (DK) atlases. In the approved subjects, reliability of cortical thickness/surface area/volume (DK atlas only) were: TRC (0.82/0.88/0.88), ICC (0.81/0.87/0.88), PD (0.86/1.19/1.39), which represent a significant improvement over these measures when disapproved subjects are included. Travel subjectsâ results show that cortical thickness reliability is more sensitive to site differences than the cortical surface area and volume. To determine the effect of visual inspection on sample size required for studies of MRIâderived cortical thickness, the number of subjects required to show group differences was calculated. Significant differences observed across imaging sites, between visually approved/disapproved subjects, and across regions with different sizes suggest that these measures should be used with caution. Hum Brain Mapp 36:3472â3485, 2015. © 2015 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113142/1/hbm22856.pd
In vivo serotonin 1A receptor hippocampal binding potential in depression and reported childhood adversity
Abstract
Background
Reported childhood adversity (CA) is associated with development of depression in adulthood and predicts a more severe course of illness. Although elevated serotonin 1A receptor (5-HT1AR) binding potential, especially in the raphe nuclei, has been shown to be a trait associated with major depression, we did not replicate this finding in an independent sample using the partial agonist positron emission tomography tracer [11C]CUMI-101. Evidence suggests that CA can induce long-lasting changes in expression of 5-HT1AR, and thus, a history of CA may explain the disparate findings.
Methods
Following up on our initial report, 28 unmedicated participants in a current depressive episode (bipolar n = 16, unipolar n = 12) and 19 non-depressed healthy volunteers (HVs) underwent [11C]CUMI-101 imaging to quantify 5-HT1AR binding potential. Participants in a depressive episode were stratified into mild/moderate and severe CA groups via the Childhood Trauma Questionnaire. We hypothesized higher hippocampal and raphe nuclei 5-HT1AR with severe CA compared with mild/moderate CA and HVs.
Results
There was a group-by-region effect (p = 0.011) when considering HV, depressive episode mild/moderate CA, and depressive episode severe CA groups, driven by significantly higher hippocampal 5-HT1AR binding potential in participants in a depressive episode with severe CA relative to HVs (p = 0.019). Contrary to our hypothesis, no significant binding potential differences were detected in the raphe nuclei (p
-value
s > 0.05).
Conclusions
With replication in larger samples, elevated hippocampal 5-HT1AR binding potential may serve as a promising biomarker through which to investigate the neurobiological link between CA and depression
Recommended from our members
The Concise Health Risk Tracking-self Report: Psychometrics Within A Placebo-controlled Antidepressant Trial Among Depressed Outpatients
Background/aims: While substantial prior research has evaluated the psychometric properties of the 12-item Concise Health Risk Tracking-Self Report (CHRT-SR12), a measure of suicide propensity and suicidal thoughts, no prior research has investigated its factor structure, sensitivity to change over time, and other psychometric properties in a placebo-controlled trial of antidepressant medication, nor determined whether symptoms change throughout treatment. Methods: Participants in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study (n=278) provided data to evaluate the factor structure and sensitivity to change over time of the CHRT-SR12 through eight weeks of a clinical trial in which participants received either placebo or antidepressant medication (sertraline). Results/Outcomes: Factor analysis confirmed two factors: propensity (comprised of first-order factors including pessimism, helplessness, social support, and despair) and suicidal thoughts. Internal consistency (αâs ranged from 0.69â0.92) and external validity were both acceptable, with the total score and propensity factor scores significantly correlated with total scores and single-item suicidal-thoughts scores on the self-report Quick Inventory of Depressive Symptoms and the clinician-rated 17-item Hamilton Rating Scale for Depression. Through analyzing CHRT-SR12 changes over eight treatment weeks, the total score and both the factors decreased regardless of baseline suicidal thoughts. Change in clinician-rated suicidal thoughts was reflected by change in both the total score and propensity factor score. Conclusions/interpretation: These results confirm the reliability, validity, and applicability of the CHRT-SR12 to a placebo-controlled clinical trial of depressed outpatients receiving antidepressant medication
A Comprehensive Examination Of White Matter Tracts And Connectometry In Major Depressive Disorder
Background
Major depressive disorder (MDD) is a debilitating disorder characterized by widespread brain abnormalities. The literature is mixed as to whether or not white matter abnormalities are associated with MDD. This study sought to examine fractional anisotropy (FA) in white matter tracts in individuals with MDD using diffusion tensor imaging (DTI).
Methods
139 participants with MDD and 39 healthy controls (HC) in a multisite study were included. DTI scans were acquired in 64 directions and FA was determined in the brain using four methods: region of interest (ROI), tract-based spatial statistics (TBSS), and diffusion tractography. Diffusion connectometry was used to identify white matter pathways associated with MDD.
Results
There were no significant differences when comparing FA in MDD and HC groups using any method. In the MDD group, there was a significant relationship between depression severity and FA in the right medial orbitofrontal cortex, and between age of onset of MDD and FA in the right caudal anterior cingulate cortex using the ROI method. There was a significant relationship between age of onset and connectivity in the thalamocortical radiation, inferior longitudinal fasciculus, and cerebellar tracts using diffusion connectometry.
Conclusions
The lack of group differences in FA and connectometry analysis may result from the clinically heterogenous nature of MDD. However, the relationship between FA and depression severity may suggest a state biomarker of depression that should be investigated as a potential indicator of response. Age of onset may also be a significant clinical feature to pursue when studying white matter tracts
Recommended from our members
A Comparison Of Structural Connectivity In Anxious Depression Versus Non-anxious Depression
Background: Major depressive disorder (MDD) and anxiety disorders are highly co-morbid. Research has shown conïŹicting evidence for white matter alteration and amygdala volume reduction in mood and anxiety disorders. To date, no studies have examined differences in structural connectivity between anxious depressed and non-anxious depressed individuals. This study compared fractional anisotropy (FA) and density of selected white matter tracts and amygdala volume between anxious depressed and non-anxious depressed individuals. Methods: 64- direction DTI and T1 scans were collected from 110 unmedicated subjects with MDD, 39 of whom had a co-morbid anxiety disorder diagnosis. Region of interest (ROI) and tractography methods were performed to calculate amygdala volume and FA in the uncinate fasciculus, respectively. Diffusion connectometry was performed to identify whole brain group differences in white matter health. Correlations were computed between biological and clinical measures. Results: Tractography and ROI analyses showed no signiïŹcant differences between bilateral FA values or bilateral amygdala volumes when comparing the anxious depressed and non-anxious depressed groups. The diffusion connectometry analysis showed no signiïŹcant differences in anisotropy between the groups. Furthermore, there were no signiïŹcant relationships between MRI-based and clinical measures. Conclusion: The lack of group differences could indicate that structural connectivity and amygdalae volumes of those with anxious-depression are not signiïŹcantly altered by a co-morbid anxiety disorder. Improving understanding of anxiety co-morbid with MDD would facilitate development of treatments that more accurately target the underlying networks
Recommended from our members
Cerebral Blood Perfusion Predicts Response To Sertraline Versus Placebo For Major Depressive Disorder In The Embarc Trial
Background: Major Depressive Disorder (MDD) has been associated with brain-related changes. However, biomarkers have yet to be defined that could âaccuratelyâ identify antidepressant-responsive patterns and reduce the trial-and-error process in treatment selection. Cerebral blood perfusion, as measured by Arterial Spin Labeling (ASL), has been used to understand resting-state brain function, detect abnormalities in MDD, and could serve as a marker for treatment selection. As part of a larger trial to identify predictors of treatment outcome, the current investigation aimed to identify perfusion predictors of treatment response in MDD.
Methods: For this secondary analysis, participants include 231 individuals with MDD from the EMBARC study, a randomized, placebo-controlled trial investigating clincal, behavioral, and biological predictors of antidepressant response. Participants received sertraline (n=114) or placebo (n=117) and response was monitored for 8 weeks. Pre-treatment neuroimaging was completed, including ASL. A whole-brain, voxel-wise linear mixed-effects model was conducted to identify brain regions in which perfusion levels differentially predict (moderate) treatment response. Clinical effectiveness of perfusion moderators was investigated by composite moderator analysis and remission rates. Composite moderator analysis combined the effect of individual perfusion moderators and identified which contribute to sertraline or placebo as the âpreferredâ treatment. Remission rates were calculated for participants âaccuratelyâ treated based on the composite moderator (lucky) versus âinaccuratelyâ treated (unlucky).
Findings: Perfusion levels in multiple brain regions differentially predicted improvement with sertraline over placebo. Of these regions, perfusion in the putamen and anterior insula, inferior temporal gyrus, fusiform, parahippocampus, inferior parietal lobule, and orbital frontal gyrus contributed to sertraline response. Remission rates increased from 37% for all those who received sertraline to 53% for those who were lucky to have received it and sertraline was their perfusion-preferred treatment.
Interpretation: This large study showed that perfusion patterns in brain regions involved with reward, salience, affective, and default mode processing moderate treatment response favoring sertraline over placebo. Accurately matching patients with defined perfusion patterns could significantly increase remission rates.
Funding: National Institute of Mental Health, the Hersh Foundation, and the Center for Depression Research and Clinical Care, Peter OâDonnell Brain Institute at UT Southwestern Medical Cente
Recommended from our members
Characterizing Anxiety Subtypes And The Relationship To Behavioral Phenotyping In Major Depression: Results From The Embarc Study
The current study aimed to characterize the multifaceted nature of anxiety in patients with major depression by evaluating distinct anxiety factors. We then related these derived anxiety factors to performance on a Flanker Task of cognitive control, in order to further validate these factors. Data were collected from 195 patients with nonpsychotic chronic or recurrent major depression or dysthymic disorder. At baseline, participants completed self-report measures of anxiety, depression, and other related symptoms (mania, suicidality) and clinicians administered a structured diagnostic interview and the Hamilton Rating Scale for Depression, including anxiety/ somatization items. Four discrete factors (State Anxiety, Panic, Neuroticism/Worry, and Restlessness/Agitation) emerged, with high degrees of internal consistency. Discriminant and convergent validity analyses also yielded ïŹndings in the expected direction. Furthermore, the neuroticism/worry factor was associated with Flanker Task interference, such that individuals higher on neuroticism/worry responded more incorrectly (yet faster) to incongruent vs. congruent trials whereas individuals higher on the fear/panic factor responded more slowly, with no accuracy eïŹect, to the Flanker Task stimuli. These results parse anxiety into four distinct factors that encompass physiological, psychological, and cognitive components of anxiety. While state anxiety, panic and neuroticism/worry are related to existing measures of anxiety, the Restlessness/Agitation factor appears to be a unique measure of general anxious arousal. Furthermore, two factors were independently validated through the Flanker Task. These results suggest that these anxiety domains have distinct behavioral proïŹles and could have diïŹerential responses to distinct treatments
Recommended from our members
Development And Evaluation Of A Multimodal Marker Of Major Depressive Disorder
This study aimed to identify biomarkers of major depressive disorder (MDD), by relating neuroimage-derived measures to binary (MDD/control), ordinal (severe MDD/mild MDD/control), or continuous (depression severity) outcomes. To address MDD heterogeneity, factors (severity of psychic depression, motivation, anxiety, psychosis, and sleep disturbance) were also used as outcomes. A multisite, multimodal imaging (diffusion MRI [dMRI] and structural MRI [sMRI]) cohort (52 controls and 147 MDD patients) and several modeling techniquesâpenalized logistic regression, random forest, and support vector machine (SVM)âwere used. An additional cohort (25 controls and 83 MDD patients) was used for validation. The optimally performing classifier (SVM) had a 26.0% misclassification rate (binary), 52.2 ± 1.69% accuracy (ordinal) and r =â.36 correlation coefficient (p <â.001, continuous). Using SVM, R2 values for prediction of any MDD factors were <10%. Binary classification in the external data set resulted in 87.95% sensitivity and 32.00% specificity. Though observed classification rates are too low for clinical utility, four image-based features contributed to accuracy across all models and analysesâtwo dMRI-based measures (average fractional anisotropy in the right cuneus and left insula) and two sMRI-based measures (asymmetry in the volume of the pars triangularis and the cerebellum) and may serve as a priori regions for future analyses. The poor accuracy of classification and predictive results found here reflects current equivocal findings and sheds light on challenges of using these modalities for MDD biomarker identification. Further, this study suggests a paradigm (e.g., multiple classifier evaluation with external validation) for future studies to avoid nongeneralizable results
- âŠ