Background Major depressive disorder (MDD) has been shown to be associated with a disrupted topological organization of functional brain networks. However, little is known regarding whether these ...changes have a structural basis. Diffusion tensor imaging (DTI) enables comprehensive whole-brain mapping of the white matter tracts that link regions distributed throughout the entire brain, the so-called human connectome. Methods We examined whole-brain structural networks in a cohort of 95 MDD outpatients and 102 matched control subjects. Structural networks were represented by an 84 × 84 connectivity matrix representing probabilistic white matter connections between 84 parcellated cortical and subcortical regions using DTI tractography. Network-based statistics were used to assess differences in the interregional connectivity matrix between the two groups, and graph theory was used to examine overall topological organization. Results Our network-based statistics analysis demonstrates lowered structural connectivity within two distinct brain networks that are present in depression: the first primarily involves the regions of the default mode network and the second comprises the frontal cortex, thalamus, and caudate regions that are central in emotional and cognitive processing. These two altered networks were observed in the context of an overall preservation of topology as reflected as no significant group differences for the graph-theory measures. Conclusions This is the first report to use DTI to show the structural connectomic alterations present in MDD. Our findings highlight that altered structural connectivity between nodes of the default mode network and the frontal-thalamo-caudate regions are core neurobiological features associated with MDD.
Wall shear stress (WSS) plays a governing role in vascular remodeling and a pathogenic role in vessel wall diseases. However, little is known of the normal WSS patterns in the aorta as there is ...currently no practical means to routinely measure WSS and no normal ranges derived from population data exist. WSS measurements were made on the aorta of 224 subjects with normal anatomy using four-dimensional flow MRI with multiple encoding velocities and an optimized postprocessing routine. The spatial and temporal variation in WSS and oscillatory shear index was analyzed using a flat map representation of the unfolded aorta. The influence of aortic shape and velocity on WSS was evaluated using regression analysis. WSS in the thoracic aorta is dominated by axial flow. Average peak systolic WSS was 1.79 ± 0.71 Pa in the aortic arch and was significantly higher at 2.23 ± 1.04 Pa in the descending aorta, with a strong negative correlation with advancing age. The spatial distribution of WSS is highly heterogeneous, with a localized region of elevated WSS along the length of the anterior wall seen across all individuals. Our data demonstrate that accurate four-dimensional flow-derived WSS measurement is feasible, and we further provide a standardized parametric approach for presentation and analysis. We present a normal range for WSS across the lifespan, demonstrating a decrease in WSS with advancing age as well as illustrating the high degree of spatial and temporal variation. NEW & NOTEWORTHY With the use of four-dimensional flow MRI and postprocessing, accurate direct measurement of wall shear stress (WSS) was performed in a population of normal thoracic aortas ( n = 224). WSS was higher in the descending aorta compared with the aortic arch and decreased with age. A heterogeneous pattern of elevated WSS along the length of the aorta anterior wall was consistent across the population. This work provides normal data across the adult age range, permitting comparison with pathology.
IMPORTANCE: Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, ...suggesting that a common neurobiological substrate may exist across mental illness. OBJECTIVE: To conduct a meta-analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large-scale healthy participant data sets to help interpret structural findings in the meta-analysis. DATA SOURCES: PubMed was searched to identify voxel-based morphometry studies through July 2012 comparing psychiatric patients to healthy control individuals for the meta-analysis. The 3 parallel healthy participant data sets included resting-state functional magnetic resonance imaging, a database of activation foci across thousands of neuroimaging experiments, and a data set with structural imaging and cognitive task performance data. DATA EXTRACTION AND SYNTHESIS: Studies were included in the meta-analysis if they reported voxel-based morphometry differences between patients with an Axis I diagnosis and control individuals in stereotactic coordinates across the whole brain, did not present predominantly in childhood, and had at least 10 studies contributing to that diagnosis (or across closely related diagnoses). The meta-analysis was conducted on peak voxel coordinates using an activation likelihood estimation approach. MAIN OUTCOMES AND MEASURES: We tested for areas of common gray matter volume increase or decrease across Axis I diagnoses, as well as areas differing between diagnoses. Follow-up analyses on other healthy participant data sets tested connectivity related to regions arising from the meta-analysis and the relationship of gray matter volume to cognition. RESULTS: Based on the voxel-based morphometry meta-analysis of 193 studies comprising 15 892 individuals across 6 diverse diagnostic groups (schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety), we found that gray matter loss converged across diagnoses in 3 regions: the dorsal anterior cingulate, right insula, and left insula. By contrast, there were few diagnosis-specific effects, distinguishing only schizophrenia and depression from other diagnoses. In the parallel follow-up analyses of the 3 independent healthy participant data sets, we found that the common gray matter loss regions formed a tightly interconnected network during tasks and at resting and that lower gray matter in this network was associated with poor executive functioning. CONCLUSIONS AND REVELANCE: We identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate–based network, which may relate to executive function deficits observed across diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates across psychopathology, despite likely diverse etiologies, which is currently not an explicit component of psychiatric nosology.
Functional neuroimaging studies implicate anterior cingulate and limbic dysfunction in major depressive disorder (MDD) and responsiveness to antidepressants. Diffusion tensor imaging (DTI) enables ...characterisation of white matter tracts that relate to these regions.
To examine whether DTI measures of anterior cingulate and limbic white matter are useful prognostic biomarkers for MDD.
Of the 102 MDD out-patients from the International Study to Predict Optimized Treatment for Depression (iSPOT-D) who provided baseline magnetic resonance imaging (MRI) data, 74 completed an 8-week course of antidepressant medication (randomised to escitalopram, sertraline or extended-release venlafaxine) and were included in the present analyses. Thirty-four matched controls also provided DTI data. Fractional anisotropy was measured for five anterior cingulate-limbic white matter tracts: cingulum cingulate and hippocampus bundle, fornix, stria terminalis and uncinate fasciculus. (Trial registered at ClinicalTrials.gov: NCT00693849.)
A cross-validated logistic regression model demonstrated that altered connectivity for the cingulum part of the cingulate and stria terminalis tracts significantly predicted remission independent of demographic and clinical measures with 62% accuracy. Prediction improved to 74% when age was added to this model.
Anterior cingulate-limbic white matter is a useful predictor of antidepressant treatment outcome in MDD.
The hippocampus is a key component of emotional and memory circuits and is broadly connected throughout the brain. We tracked the whole-brain connections of white matter fibres from the hippocampus ...using ultra-high angular resolution diffusion MRI in both a single 1150-direction dataset and a large normal cohort (n = 94; 391-directions). Using a connectomic approach, we identified six dominant pathways in terms of strength, length and anatomy, and characterised them by their age and gender variation. The strongest individual connection was to the ipsilateral thalamus. There was a strong age dependence of hippocampal connectivity to medial occipital regions. Overall, our results concur with preclinical and ex-vivo data, confirming that meaningful in vivo characterisation of hippocampal connections is possible in an individual. Our findings extend the collective knowledge of hippocampal anatomy, highlighting the importance of the spinal-limbic pathway and the striking lack of hippocampal connectivity with motor and sensory cortices.
Silent brain infarcts (SBIs) are frequently identified after transcatheter aortic valve implantation (TAVI), when patients are screened with diffusion-weighted magnetic resonance imaging (DW-MRI). ...Outside the cardiac literature, SBIs have been correlated with progressive cognitive dysfunction; however, their prognostic utility after TAVI remains uncertain. This study's main goals were to explore (i) the incidence of and potential risk factors for SBI after TAVI; and (ii) the effect of SBI on early post-procedural cognitive dysfunction (PCD).
A systematic literature review was performed to identify all publications reporting SBI incidence, as detected by DW-MRI after TAVI. Silent brain infarct incidence, baseline characteristics, and the incidence of early PCD were evaluated via meta-analysis and meta-regression models. We identified 39 relevant studies encapsulating 2408 patients. Out of 2171 patients who underwent post-procedural DW-MRI, 1601 were found to have at least one new SBI (pooled effect size 0.76, 95% CI: 0.72-0.81). The incidence of reported stroke with focal neurological deficits was 3%. Meta-regression noted that diabetes, chronic renal disease, 3-Tesla MRI, and pre-dilation were associated with increased SBI risk. The prevalence of early PCD increased during follow-up, from 16% at 10.0 ± 6.3 days to 26% at 6.1 ± 1.7 months and meta-regression suggested an association between the mean number of new SBI and incidence of PCD. The use of cerebral embolic protection devices (CEPDs) appeared to decrease the volume of SBI, but not their overall incidence.
Silent brain infarcts are common after TAVI; and diabetes, kidney disease, and pre-dilation increase overall SBI risk. While higher numbers of new SBIs appear to adversely affect early neurocognitive outcomes, long-term follow-up studies remain necessary as TAVI expands to low-risk patient populations. The use of CEPD did not result in a significant decrease in the occurrence of SBI.
Background Silent brain infarcts ( SBI ) are increasingly being recognized as an important complication of cardiac procedures as well as a potential surrogate marker for studies on brain injury. The ...extent of subclinical brain injury is poorly defined. Methods and Results We conducted a systematic review and meta-analysis utilizing studies of SBI s and focal neurologic deficits following cardiac procedures. Our final analysis included 42 studies with 49 separate intervention groups for a total of 2632 patients. The prevalence of SBI s following transcatheter aortic valve implantation was 0.71 (95% CI 0.64-0.77); following aortic valve replacement 0.44 (95% CI 0.31-0.57); in a mixed cardiothoracic surgery group 0.39 (95% CI 0.28-0.49); coronary artery bypass graft 0.25 (95% CI 0.15-0.35); percutaneous coronary intervention 0.14 (95% CI 0.10-0.19); and off-pump coronary artery bypass 0.14 (0.00-0.58). The risk ratio of focal neurologic deficits to SBI in aortic valve replacement was 0.22 (95% CI 0.15-0.32); in off-pump coronary artery bypass 0.21 (95% CI 0.02-2.04); with mixed cardiothoracic surgery 0.15 (95% CI 0.07-0.33); coronary artery bypass graft 0.10 (95% CI 0.05-0.18); transcatheter aortic valve implantation 0.10 (95% CI 0.07-0.14); and percutaneous coronary intervention 0.06 (95% CI 0.03-0.14). The mean number of SBI s per patient was significantly higher in the transcatheter aortic valve implantation group (4.58 ± 2.09) compared with both the aortic valve replacement group (2.16 ± 1.62, P=0.03) and the percutaneous coronary intervention group (1.88 ± 1.02, P=0.03). Conclusions SBI s are a very common complication following cardiac procedures, particularly those involving the aortic valve. The high frequency of SBI s compared with strokes highlights the importance of recording this surrogate measure in cardiac interventional studies. We suggest that further work is required to standardize reporting in order to facilitate the use of SBI s as a routine outcome measure.
Executive function (EF) is a set of cognitive capabilities considered essential for successful daily living, and is negatively affected by ageing and neurodegenerative conditions. Underpinning EF ...performance are functional nodes in the executive control network (ECN), while the structural connectivity underlying this network is not well understood. In this paper, we evaluated the structural white matter tracts that interconnect the ECN and investigated their relationship to the EF performance. Using high‐angular resolution diffusion MRI data, we performed tractography analysis of structural connectivity in a cognitively normal cohort (n = 140), specifically targeting the connectivity between ECN nodes. Our data revealed the presence of a strongly‐connected “structural core” of the ECN comprising three components: interhemispheric frontal connections, a fronto‐parietal subnetwork and fronto‐striatal connections between right dorsolateral prefrontal cortex and right caudate. These pathways were strongly correlated with EF performance (p = .003). Post‐hoc analysis of subregions within the significant ECN connections showed that these effects were driven by a highly specific subset of interconnected cortical regions. The structural core subnetwork of the functional ECN may be an important feature crucial to a better future understanding of human cognition and behaviour.
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