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Table of Contents
REVIEW ARTICLE
Year : 2018  |  Volume : 11  |  Issue : 2  |  Page : 50-55

Update on neuroimaging in psychiatric disorders


Specialist Radiologist, Radiology Department, Thumbay Clinics, 4184 Ajman, United Arab of Emirates

Date of Web Publication26-Jun-2018

Correspondence Address:
Mohamed Walaaeldin Elfaal
Specialist Radiologist, Radiology Department, Thumbay Clinics, 4184 Ajman
United Arab of Emirates
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/HMJ.HMJ_13_18

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  Abstract 


Psychoradiology is a newly emerging filed describes the application of the neuroimaging techniques in analysing psychiatric conditions. Previously in psychiatry only gross structural abnormalities, that might cause psychosis, could be detected. Neuroimaging was used to detect and to differentiate depression from neurodegenerative disorders or brain tumours. Recently, functional neuroimaging, mostly in the form of functional magnetic resonance imaging, molecular neuroimaging with positron-emission tomography or single photon emission tomography, facilitates the identification of therapeutic targets, the determination of the dose of a new drug needed to occupy its target in the brain, following up the effect of the treatment and the selection of patients for clinical trials.

Keywords: Neuroimaging, psychiatric disorders, psychoradiology


How to cite this article:
Elfaal MW. Update on neuroimaging in psychiatric disorders. Hamdan Med J 2018;11:50-5

How to cite this URL:
Elfaal MW. Update on neuroimaging in psychiatric disorders. Hamdan Med J [serial online] 2018 [cited 2018 Sep 24];11:50-5. Available from: http://www.hamdanjournal.org/text.asp?2018/11/2/50/235228




  Epidemiology Top


Mental disorders, including depression, bipolar disorder, schizophrenia and anxiety disorders represent some of the most serious and intractable of all diseases. They cause untold suffering and a massive economic burden on the society. It is estimated that one in every four American adults suffer from a mental disorder in any given year, and depression is among the leading causes of disability worldwide. Unfortunately, psychiatric disorders are also among the most mysterious of all diseases. Their underlying causes are still poorly understood, and their diagnosis is still based purely on behavioural criteria.[1]


  Technical Concepts Top


Voxel-based morphometric study

Voxel-based morphometric (VBM) was defined as 'a voxel-wise' comparison of the local concentration of grey matter (GM) between two groups of patients.[2]

Functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) is a relatively new procedure that uses MRI to measure the tiny metabolic changes that take place in an active part of the brain.[3]

Diffusion tensor imaging (DTI) is an MRI-based neuroimaging technique which makes it possible to estimate the location, orientation and anisotropy of the brain's white matter (WM) tracts.[4]

Fractional anisotropy (FA) is used in DTI, and it is a scalar value between zero and one that describes the degree of anisotropy of a diffusion process. A value of zero means that diffusion is isotropic, i.e., it is unrestricted (or equally restricted) in all directions. A value of one means that diffusion occurs only along one axis and is fully restricted along all other directions. FA is a measure often used in diffusion imaging where it is thought to reflect fibre density, axonal diameter and myelination in WM. The FA is an extension of the concept of eccentricity of conic sections in three dimensions, normalised to the unit range.[5]

Fibre tracking uses the diffusion tensor to track fibres along their whole length.

Magnetic resonance spectroscopy (MRS) is a specialised technique associated with MRI [Graph 1] and [Graph 2].[6]



MRS, also known as nuclear magnetic resonance spectroscopy, it is a non-invasive and ionising-radiation-free analytical technique that has been used to study metabolic changes in brain tumours, strokes, seizure disorders, Alzheimer's disease, depression and other diseases affecting the brain. It has also been used to study the metabolism of other organs such as muscles.[8]


  Applications and Radiological Features Top


Schizophrenia

Schizophrenia is a serious genetic illness with a lifetime incidence of 1% in the general population during adolescence and early adulthood.[9] It is characterised by a diversity of complex symptoms that range from positive symptoms such as delusions and auditory hallucinations to negative symptoms such as apathy, anhedonia, blunted affect, poverty of speech and broad cognitive deficits in domains such as attention, memory and language.[10]

Brain structure

VBM changes, most consistently in the left superior temporal gyrus and left medial temporal lobe.[11]

An increased ventricle-to-caudate ratio computed using VBM analysis was suggested as a possible early biomarker of schizophrenia.[12]

Brain volumes were reduced by 2.7% in the first-schizophrenic- episode medication-naïve patients compared to the brain volumes of healthy control patients.[13] Patients with recurrent episodes of illness show extended alterations in the mentioned brain areas in addition to bilateral GM loss in the prefrontal cortex, hippocampus, amygdala and basal ganglia, suggesting that brain abnormalities are not static but progress over time [Figure 1].[14]
Figure 1: Voxel-based morphometry findings. Regions showing significant volume reduction between patients with and without tardive dyskinesia. Threshold set at P = 0.05 corrected for multiple comparisons across space[30]

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Brain function

Alterations of task-induced brain activation in fMRI have been described in schizophrenia. Two core findings across studies are a decrease of frontal activations, referred to as hypofrontality, and increased activation of midline structures such as the anterior cingulate cortex (ACC), interpreted as resting-state activations that persist inappropriately into task conditions.[15]

It also shows decreased connectivity between the bilateral auditory cortex regions in patients with auditory hallucinations [Figure 2].[16]
Figure 2: A Functional magnetic resonance imaging study of the patients with schizophrenia. While they performed a working memory task, the less the prefrontal cortex (red) activated and the more dopamine increased in the striatum (green)[31]

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Autism spectrum disorder

Autism spectrum disorder (ASD) is relatively common neurodevelopmental disorders, affecting approximately 1/150 children.[17] ASDs are characterised by three core symptoms, namely, impaired social reciprocity, communication difficulties and repetitive stereotyped behaviours. Motor function, attention and other cognitive domains may also be affected.[18]

Brain structure

ASD is known to display early alterations in WM development.[19] Over proportional brain growth [11] accompanied by mainly frontally increased FA values in young children [19] is followed by WM [20] and GM [21] volume reduction and FA value decrease in older children, adolescents and adults with ASD compared to healthy controls [Figure 3].[22]
Figure 3: Decreased fractional anisotropy and increased mean diffusivity in participants with autism spectrum disorder compared to normal controls. TBSS analysis revealed that participants with autism spectrum disorder showed widespread fractional anisotropy reductions in major white matter tracts (a), while they showed increased mean diffusivity in similar white matter tracts (b). For each statistical analysis, significance level was set at P < 0.05, TFCE-corrected. For visualization purpose, significant regions were thickened using tbss_fill. R: Right, L: Left, ART: Anterior thalamic radiation, CG: Cingulum, CST: corticospinal tract, FMJ: Forceps major, IFO: inferior fronto-occipital fasciculus, IFL: Inferior longitudinal fasciculus, SLF: Superior longitudinal fasciculus, and UF: Uncinate fasciculus[32]

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Brain function

fMRI studies showed alterations in memory,[23] recognition of face expression,[24] selective attention,[25] cognitive control and executive function, self- and-other reflection,[26] self-representation, and motor response inhibition in patients with ASD [Figure 4].[27]
Figure 4: Functional magnetic resonance imaging images of mirror neuron areas (a) control group, (b) autistic spectrum disorders group and (c) areas where the activation differences was significantly greater in control group - pars opercularis[33]

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Mood disorders

Mood disorders can be classified as primary (functional) or secondary (i.e., presumed to be directly caused by a cerebral or other physical disorder).[28]

Bipolar disorder

Bipolar disorder is a clinically heterogeneous disorder characterised by alternating periods of depression and mania interspersed with periods of euthymia.[29]

The structural brain abnormalities reported in the MRI studies were increased volumes of the lateral ventricles (17% increases) and the third ventricle, a decreased cross-sectional area of the corpus callosum and increased high-signal intensity regions in the WM. The high-signal intensity in cortical (frequently in the frontal lobes) and subcortical regions, but not periventricular WM regions, is most consistently reported in association with bipolar disorder.[34] However, high-signal intensity WM regions are non-specific and reflect cerebrovascular damage, astrocytic gliosis, dilated perivascular spaces and demyelination.[35]

The subgenual ACC volume is reduced by 39% in bipolar depressed patients. Lithium, a mainstay drug for acute mania, augments the GM volume in patients with bipolar disorder.[36]

Reduced N-acetylaspartate and abnormal choline, myo-inositol and Glx levels, accompanied by altered phospholipid metabolism (at 31P MR spectroscopy) point strongly towards a shift from oxidative phosphorylation to glycolysis due to the mitochondrial dysfunction with bipolar disorder.[37]

Unipolar mood disorder Ex. Major depressive disorder

The main subtype of unipolar mood disorder is a major depressive disorder. The major depressive disorder is characterised by one or more episodes of anhedonia, a sense of guilt, impaired concentration, fatigue, loss of sleep and suicidal thoughts.[10]

Most of the MR findings overlap between those of major depression and bipolar disease because these two conditions share common depressive episodes. Many researchers tend to study mood disorders and affective illnesses, which include major depression and bipolar disease. However, this leads to overlapping findings and some difficulty interpreting them. The prefrontal cortex and the anterior limbic structures are key players in the altered emotional processing and cognitive disturbances in major depression, as in bipolar disorder.[38] The majority of volumetric MR studies have revealed GM loss and volume reductions in subregions of the prefrontal cortex, medial temporal lobe, amygdala and hippocampus across all age ranges [Figure 5].[39]
Figure 5: Regions of differences in gray matter volume in medication-naïve participants with major depressive disorder. (a) The axial image (Z = 8 mm Montreal Neurological Institute coordinate plane) shows the regions of significantly decreased gray matter volume in right dorsolateral prefrontal cortex in medication-naïve participants with major depressive disorder, compared to healthy controls (P < 0.05, corrected). (b) The axial image (Z = 42 mm Montreal Neurological Institute coordinate plane) shows the regions of significantly decreased gray matter volume in left middle frontal gyrus in medication-naïve participants with major depressive disorder, compared to healthy controls (P < 0.05, corrected). (c) The axial image (Z = 11 mm Montreal Neurological Institute coordinate plane) shows the regions of significantly increased gray matter volume in left thalamus in medication-naïve participants with major depressive disorder, compared to healthy controls (P < 0.05, corrected). (d) The axial image (Z = 3 mm Montreal Neurological Institute coordinate plane) shows the regions of significantly increased gray matter volume in right insula in medication-naïve participants with major depressive disorder, compared to healthy controls (P < 0.05, corrected). The color bar represents the range of T values. R = right[40]

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Abnormal Glx concentrations and γ-aminobutyric acid peaks have been found in several proton MR spectroscopic studies. In a meta-analysis of proton MR spectroscopic studies of major depressive disorder, decreased rather than increased (as in bipolar disorder) glutamate levels were found in depressed individuals.[41]

Attention-deficit hyperactivity disorder

Attention-deficit hyperactivity disorder is defined on the basis of developmentally inappropriate symptoms such as lack of attention, motor restlessness and impulsivity.[4]

Structural

The most frequent alteration seen in children with attention-deficit hyperactivity disorder is a 3%–4% of the reduction in total cerebral and cerebellar volumes. There is also a substantial decrease in the WM of non-medicated children, that is, inversely related to age and suggesting early damage.[42]

The frontostriatal circuitry is Key in understanding the pathogenesis of this disorder. These systems regulate attention shifting, planning, executive function, working memory, response inhibition and reward motivation.[43]

Cortical thinning in the medial prefrontal cortex was found to be a predictor of poorer clinical outcome at 5 years.[44]

Dorsal ACC volume is reduced in both adults and children with attention-deficit hyperactivity disorder.[4]

In diffusion-tensor studies

Aberrant anatomic connectivity has been detected in not only the frontostriatal regions but also the parietal and occipital regions in these patients. Many of these regions are connected to the cerebellum.[45] Reduced FA in the prefrontal-striatal fibre tracts of both children with attention-deficit hyperactivity disorder and their parents correlated positively with the go/no-go task (attention), revealing the heritability of aberrant frontostriatal systems.[46] A dysfunctional basal ganglia and hypoactivation of the frontostriatal systems substantiate the reported structural abnormalities in the same regions.[47]

Functional magnetic resonance imaging

fMRI studies had revealed hypoactivation of the cerebellum and only a trend towards hypoactivation of the prefrontal cortex when the working memory of children and adults with Attention-deficit hyperactivity disorder was tested [Figure 6].[48]
Figure 6: Functional magnetic resonance imaging is revealing information about brain regions and processes involved in attention deficits[50]

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Spectroscopy

An increased choline/Cr ratio in the ACC in medication-naïve adults with attention-deficit hyperactivity disorder and in the basal ganglia of medication-naïve children with attention-deficit hyperactivity disorder suggests subtle structural membrane alterations.[49]

A study done by Dr. Margaretha Dramsdahl[7] stated that the main finding of a reduced ratio of Glu/Cre in the left midfrontal region in participants with attention-deficit hyperactivity disorder (ADHD) supports the hypothesis of ADHD as a hypoglutamatergic condition.[51] Glutamate is an important neurotransmitter in cognitive processes [52] and seems to have a central role in neurotransmission.[53] The dorsal ACC, in turn, plays a crucial role in the exertion of cognitive,[54] and a glutamatergic deficit in the midfrontal region including the dorsal ACC may contribute to the impaired cognitive control in persons with ADHD [Figure 7].[50]
Figure 7: The position of the 20-mm × 20-mm × 20-mm voxel in the midfrontal region.[7]

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  Conclusion Top


Even though, that specific diagnostic tool not established, MR researches in psychiatry are playing a fundamental role in removing the societal stigma of psychiatric illness by helping to document objective structural and functional differences in the brains of psychiatric patients. It discloses the mystery of the psychiatric diseases and helps in understanding the structural and functional changes happen with it.

Currently, there are many limitations facing the newly emerging psychoradiology field to be established as a diagnostic filed, mainly due to variation in brain activity among people with the same diagnosis; moreover, the psychiatric conditions can look quite different in different individuals, also the overlap between different diseases, as the different psychiatric conditions often share similar symptoms and imaging findings. Finally, similar brain areas are involved in different psychiatric conditions.

We hope and expect in the future that systematic approach using multimodal neuroimaging and a variety of analysis methods would have the potential to identify reliable biomarkers for specific psychiatric disorders. With on-going progress being made in neuroimaging methods, neuroimaging holds clear promise in helping to diagnose and quantify psychiatric diseases.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]



 

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