Baseline brain perfusion and brain structure in patients with major depression: a multimodal magnetic resonance imaging study

Vasić, Nenad; Wolf, Nadine D.; Grön, Georg; Sosic-Vasic, Zrinka; Connemann, Bernhard J.; Sambataro, Fabio; Strombeck, Anna von; Lang, D.; Otte, Stefanie; Dudek, Manuela; Wolf, Robert Christian

doi:10.1503/jpn.140246

Cited by 61 publications

(45 citation statements)

References 84 publications

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“…However, in the present study, cerebral blood hyper-perfusion tended to be located in the right brain hemisphere, which is inconsistent with certain previous studies (7,25). Our current findings and the findings of previous studies indicate a sophisticated phenomenon; however, this is not surprising, as the results of the different studies may have been influenced by various confounding factors, such as differences in clinical characteristics of the participants, effects of antidepressants on the participants, and the technical characteristics of image acquisition and analysis.…”

Section: Discussioncontrasting

confidence: 99%

Pseudo-continuous arterial spin labeling imaging of cerebral blood perfusion asymmetry in drug-naïve patients with first-episode major depression

et al. 2016

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Many previous studies have reported that regional cerebral blood flow (rCBF) aberrations may be one of the pathological characteristics of depression and rCBF has demonstrated a certain degree of asymmetry. However, studies investigating the cerebral blood perfusion asymmetry changes of drug-naïve patients experiencing their first episode of major depression using pseudo-continuous arterial spin labeling (pCASL) are rare. Ten drug-naïve patients experiencing their first major depression episode and 15 healthy volunteers were enrolled in the current study. A novel pCASL method was applied to whole brain MRI scans of all of the samples. The Statistics Parameter Mapping and Relative Expression Software Tool software packages were used for the pre-processing and statistical analysis of the two sets of images, and the differences in the cerebral blood perfusion at the whole brain level were compared between the two groups. Compared with the healthy control group, the cerebral perfusion of the depression patients showed an asymmetric pattern. Decreased cerebral blood perfusion regions were primarily located in the left hemisphere, specifically in the left temporal lobe, frontal lobe and cingulate cortex [P<0.05 and cluster size ≥30 with false discovery rate (FDR) correction]. Simultaneously, increased perfusion regions were predominantly located in the right hemisphere, specifically in the right cerebellum, thalamus, frontal lobe and anterior cingulate cortex (P<0.05 and cluster size ≥30, with FDR correction). Thus, pCASL may characterize the alterations in cerebral blood perfusion of patients with depression.

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Section: Discussioncontrasting

confidence: 99%

Pseudo-continuous arterial spin labeling imaging of cerebral blood perfusion asymmetry in drug-naïve patients with first-episode major depression

et al. 2016

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“…Our findings of GM and δrCBV are not symmetric. This is similar to the lateralized effects in brain structural changes (24) and those in cerebral blood volume changes (22) related to breeding of depressive-like behavior.…”

Section: Biological Implicationssupporting

confidence: 72%

“…in limbic and prefrontal cortex structures. Another study showed changes of cerebral blood flow and brain volume co‐occurring in patients with major depressive disorder . Short‐term effects of rCBV alterations are caused by swelling of capillaries, whereas long‐term effects occur due to changes in the capillary bed, like angiogenesis.…”

Section: Introductionmentioning

confidence: 99%

Influence of regional cerebral blood volume on voxel-based morphometry

et al. 2016

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The investigation of structural brain alterations is one focus in research of brain diseases like depression. Voxel-based morphometry (VBM) based on high-resolution 3D MRI images is a widely used non-invasive tool for such investigations. However, the result of VBM might be sensitive to local physiological parameters such as regional cerebral blood volume (rCBV) changes. In order to investigate whether rCBV changes may contribute to variation in VBM, we performed analyses in a study with the congenital learned helplessness (cLH) model for long-term findings. The 3D structural and rCBV data were acquired with T2 -weighted rapid acquisition with relaxation enhancement (RARE) pulse sequences. The group effects were determined by standard statistical parametric mapping (SPM) and biological parametric mapping (BPM) and examined further using atlas-based regions. In our genetic animal model of depression, we found co-occurrence of differences in gray matter volume and rCBV, while there was no evidence of significant interaction between both. However, the multimodal analysis showed similar gray matter differences compared with the standard VBM approach. Our data corroborate the idea that two group VBM differences might not be influenced by rCBV differences in genetically different strains. Copyright © 2016 John Wiley & Sons, Ltd.

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“…In major depression disorder (MDD), Vasic N. et al(88) suggest that while changes of cerebral blood flow (brain perfusion) and GM volume co-occur in MDD patients, they appear to reflect distinct levels of neuropathology. Dutt A et al(89) reported P300 latency, a measure of the speed of neural transmission, appeared to relate to the size of left hippocampus in schizophrenia, but not in psychotic bipolar disorder.…”

Section: Review Of Fusion Studies Focused On Psychopathologymentioning

confidence: 99%

Multimodal Fusion of Brain Imaging Data: A Key to Finding the Missing Link(s) in Complex Mental Illness

Calhoun

Sui

2016

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

316

283

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It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

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Baseline brain perfusion and brain structure in patients with major depression: a multimodal magnetic resonance imaging study

Cited by 61 publications

References 84 publications

Pseudo-continuous arterial spin labeling imaging of cerebral blood perfusion asymmetry in drug-naïve patients with first-episode major depression

Pseudo-continuous arterial spin labeling imaging of cerebral blood perfusion asymmetry in drug-naïve patients with first-episode major depression

Influence of regional cerebral blood volume on voxel-based morphometry

Multimodal Fusion of Brain Imaging Data: A Key to Finding the Missing Link(s) in Complex Mental Illness

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