Technetium 99m ethylcysteinate dimer single-photon emission computed tomography (SPECT) during intellectual stress test in children and adolescents with pure versus comorbid attention-deficit hyperactivity disorder (ADHD)

Eigenvector Centrality Characterization on fMRI Data: Gender and Node Differences in Normal and ASD Subjects : Author name

With the budding interests of structural and functional network characteristics as potential parameters for abnormal brains, an essential and thus simpler representation and evaluations have become necessary. Eigenvector centrality measure of functional magnetic resonance imaging (fMRI) offer region wise network representations through fMRI diagnostic maps. The article investigates the suitability of network node centrality values to discriminate ASD subject groups compared to typically developing controls following a boxplot formalism and a classification and regression tree model. Region wise differences between normal and ASD subjects primarily belong to the frontoparietal, limbic, ventral attention, default mode and visual networks. The reduced number of regions-of-interests (ROI) clearly suggests the benefit of automated supervised machine learning algorithm over the manual classification method.

SPECT Functional Neuroimaging Distinguishes Adult Attention Deficit Hyperactivity Disorder From Healthy Controls in Big Data Imaging Cohorts

Background: The diagnosis of attention deficit hyperactivity disorder (ADHD) relies on history and observation, as no reliable biomarkers have been identified. In this study, we compared a large single diagnosis group of patients with ADHD (combined, inattentive, and hyperactive) to healthy controls using brain perfusion single-photon emission computed tomography (SPECT) imaging to determine specific brain regions which could serve as potential biomarkers to reliably distinguish ADHD. Methods: In a retrospective analysis, subjects (n = 1,135) were obtained from a large multisite psychiatric database, where resting state (baseline) and on-task SPECT scans were obtained. Only baseline scans were analyzed in the present study. Subjects were separated into two groups - Group 1 (n = 1,006) was composed of patients who only met criteria for ADHD with no comorbid diagnoses, while a control group (n = 129) composed of individuals who did not meet criteria for any psychiatric diagnosis, brain injury, or substance use served as a non-matched control. SPECT regions of interests (ROIs) and visual readings were analyzed using binary logistic regression. Predicted probabilities from this analysis were inputted into a Receiver Operating Characteristic analysis to identify sensitivity, specificity, and accuracy. Results: The baseline ROIs and visual readings show significant separations from healthy controls. Sensitivity of the visual reads was 100% while specificity was >97%. The sensitivity and specificity of the post-hoc ROI analysis were both 100%. Decreased perfusion was primarily seen in the orbitofrontal cortices, anterior cingulate gyri, areas of the prefrontal cortices, basal ganglia, and temporal lobes. In addition, ROI analysis revealed some unexpected areas with predictive value in distinguishing ADHD, such as cerebellar subregions and portions of the temporal lobes. Conclusions: Brain perfusion SPECT distinguishes adult ADHD patients without comorbidities from healthy controls. Areas which were highly significantly different from control and thus may serve as biomarkers in baseline SPECT scans included: medial anterior prefrontal cortex, left anterior temporal lobe, and right insular cortex. Future studies of these potential biomarkers in ADHD patients with comorbidities are warranted.

Multi-modal, Multi-measure, and Multi-class Discrimination of ADHD with Hierarchical Feature Extraction and Extreme Learning Machine Using Structural and Functional Brain MRI

Structural and functional MRI unveil many hidden properties of the human brain. We performed this multi-class classification study on selected subjects from the publically available attention deficit hyperactivity disorder ADHD-200 dataset of patients and healthy children. The dataset has three groups, namely, ADHD inattentive, ADHD combined, and typically developing. We calculated the global averaged functional connectivity maps across the whole cortex to extract anatomical atlas parcellation based features from the resting-state fMRI (rs-fMRI) data and cortical parcellation based features from the structural MRI (sMRI) data. In addition, the preprocessed image volumes from both of these modalities followed an ANOVA analysis separately using all the voxels. This study utilized the average measure from the most significant regions acquired from ANOVA as features for classification in addition to the multi-modal and multi-measure features of structural and functional MRI data. We extracted most discriminative features by hierarchical sparse feature elimination and selection algorithm. These features include cortical thickness, image intensity, volume, cortical thickness standard deviation, surface area, and ANOVA based features respectively. An extreme learning machine performed both the binary and multi-class classifications in comparison with support vector machines. This article reports prediction accuracy of both unimodal and multi-modal features from test data. We achieved 76.190% (p < 0.0001) classification accuracy in multi-class settings as well as 92.857% (p < 0.0001) classification accuracy in binary settings. In addition, we found ANOVA-based significant regions of the brain that also play a vital role in the classification of ADHD. Thus, from a clinical perspective, this multi-modal group analysis approach with multi-measure features may improve the accuracy of the ADHD differential diagnosis.

Cerebral Perfusion Changes in Post-Concussion Syndrome: A Prospective Controlled Cohort Study

The biology of post-concussive symptoms is unclear. Symptoms are often increased during activities, and have been linked to decreased cerebrovascular reactivity and perfusion. The aim of this study was to examine cerebral blood flow (CBF) in children with different clinical recovery patterns following mild traumatic brain injury (mTBI). This was a prospective controlled cohort study of children with mTBI (ages 8 to 18 years) who were symptomatic with post-concussive symptoms at one month post-injury (symptomatic, n = 27) and children who had recovered quickly (asymptomatic, n = 24). Pseudo continuous arterial spin labeling magnetic resonance imaging (MRI) was used to quantify CBF. The mTBI groups were imaged at 40 days post-injury. Global and regional CBF were compared with healthy controls of similar age and sex but without a history of mTBI (n = 21). Seventy-two participants (mean age: 14.1 years) underwent neuroimaging. Significant differences in CBF were found: global CBF was higher in the symptomatic group and lower in the asymptomatic group compared with controls, (F(2,69) 9.734; p < 0.001). Post-injury symptom score could be predicted by pre-injury symptoms and CBF in presence of mTBI (adjusted R2 = 0.424; p < 0.001). Altered patterns of cerebral perfusion are seen following mTBI and are associated with the recovery trajectory. Symptomatic children have higher CBF. Children who "recovered" quickly, have decreased CBF suggesting that clinical recovery precedes the cerebral recovery. Further longitudinal studies are required to determine if these perfusion patterns continue to change over time.

Functional Connectivity of Child and Adolescent Attention Deficit Hyperactivity Disorder Patients: Correlation with IQ

Attention deficit hyperactivity disorder (ADHD) is a pervasive neuropsychological disorder that affects both children and adolescents. Child and adolescent ADHD patients exhibit different behavioral symptoms such as hyperactivity and impulsivity, but not much connectivity research exists to help explain these differences. We analyzed openly accessible resting-state functional magnetic resonance imaging (rs-fMRI) data on 112 patients (28 child ADHD, 28 adolescent ADHD, 28 child normal control (NC), and 28 adolescent NC). We used group independent component analysis (ICA) and weighted degree values to identify interaction effects of age (child and adolescent) and symptom (ADHD and NC) in brain networks. The frontoparietal network showed significant interaction effects (p = 0.0068). The frontoparietal network is known to be related to hyperactive and impulsive behaviors. Intelligence quotient (IQ) is an important factor in ADHD, and we predicted IQ scores using the results of our connectivity analysis. IQ was predicted using degree centrality values of networks with significant interaction effects of age and symptom. Actual and predicted IQ scores demonstrated significant correlation values, with an error of about 10%. Our study might provide imaging biomarkers for future ADHD and intelligence studies.

Connectivity Analysis and Feature Classification in Attention Deficit Hyperactivity Disorder Sub-Types: A Task Functional Magnetic Resonance Imaging Study

Attention deficit hyperactivity disorder (ADHD) is a pervasive neuropsychiatric disorder. Patients with different ADHD subtypes show different behaviors under different stimuli and thus might require differential approaches to treatment. This study explores connectivity differences between ADHD subtypes and attempts to classify these subtypes based on neuroimaging features. A total of 34 patients (13 ADHD-IA and 21 ADHD-C subtypes) underwent functional magnetic resonance imaging (fMRI) with six task paradigms. Connectivity differences between ADHD subtypes were assessed for the whole brain in each task paradigm. Connectivity measures of the identified regions were used as features for the support vector machine classifier to distinguish between ADHD subtypes. The effectiveness of connectivity measures of the regions were tested by predicting ADHD-related Diagnostic and Statistical Manual of Mental Disorders (DSM) scores. Significant connectivity differences between ADHD subtypes were identified mainly in the frontal, cingulate, and parietal cortices and partially in the temporal, occipital cortices and cerebellum. Classifier accuracy for distinguishing between ADHD subtypes was 91.18 % for both gambling punishment and emotion task paradigms. Linear prediction under the two task paradigms showed significant correlation with DSM hyperactive/impulsive score. Our study identified important brain regions from connectivity analysis based on an fMRI paradigm using gambling punishment and emotion task paradigms. The regions and associated connectivity measures could serve as features to distinguish between ADHD subtypes.

Brain perfusion single photon emission computed tomography in major psychiatric disorders: From basics to clinical practice

Brain single photon emission computed tomography (SPECT) is a well-established and reliable method to assess brain function through measurement of regional cerebral blood flow (rCBF). It can be used to define a patient's pathophysiological status when neurological or psychiatric symptoms cannot be explained by anatomical neuroimaging findings. Though there is ample evidence validating brain SPECT as a technique to track human behavior and correlating psychiatric disorders with dysfunction of specific brain regions, only few psychiatrists have adopted brain SPECT in routine clinical practice. It can be utilized to evaluate the involvement of brain regions in a particular patient, to individualize treatment on basis of SPECT findings, to monitor the treatment response and modify treatment, if necessary. In this article, we have reviewed the available studies in this regard from existing literature and tried to present the evidence for establishing the clinical role of brain SPECT in major psychiatric illnesses.

Extreme learning machine-based classification of ADHD using brain structural MRI data

BACKGROUND

Effective and accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) is currently of significant interest. ADHD has been associated with multiple cortical features from structural MRI data. However, most existing learning algorithms for ADHD identification contain obvious defects, such as time-consuming training, parameters selection, etc. The aims of this study were as follows: (1) Propose an ADHD classification model using the extreme learning machine (ELM) algorithm for automatic, efficient and objective clinical ADHD diagnosis. (2) Assess the computational efficiency and the effect of sample size on both ELM and support vector machine (SVM) methods and analyze which brain segments are involved in ADHD.

METHODS

High-resolution three-dimensional MR images were acquired from 55 ADHD subjects and 55 healthy controls. Multiple brain measures (cortical thickness, etc.) were calculated using a fully automated procedure in the FreeSurfer software package. In total, 340 cortical features were automatically extracted from 68 brain segments with 5 basic cortical features. F-score and SFS methods were adopted to select the optimal features for ADHD classification. Both ELM and SVM were evaluated for classification accuracy using leave-one-out cross-validation.

RESULTS

We achieved ADHD prediction accuracies of 90.18% for ELM using eleven combined features, 84.73% for SVM-Linear and 86.55% for SVM-RBF. Our results show that ELM has better computational efficiency and is more robust as sample size changes than is SVM for ADHD classification. The most pronounced differences between ADHD and healthy subjects were observed in the frontal lobe, temporal lobe, occipital lobe and insular.

CONCLUSION

Our ELM-based algorithm for ADHD diagnosis performs considerably better than the traditional SVM algorithm. This result suggests that ELM may be used for the clinical diagnosis of ADHD and the investigation of different brain diseases.

Brain cortical thickness in ADHD: age, sex, and clinical correlations

OBJECTIVE

Longitudinal magnetic resonance imaging (MRI) studies have shown reduced cortical thickness (CT) in individuals with ADHD, but this abnormality disappears with age, suggesting developmental delay. However, cross-sectional MRI studies have shown reduced CT, suggesting abnormal development. The aim of this study was to compare whole-brain CT in male and female children, adolescents, and adults with ADHD with whole-brain CT in matched control participants.

METHOD

MRI scans were performed on ADHD and control participants.

RESULTS

CT data revealed differences in right hemisphere (RH) only. Reduced CT was observed predominantly in the frontoparietal region. However, increased CT was observed predominantly in the occipital lobe. The CT differences were correlated with severity of ADHD. Analysis of sex differences revealed that location, number, and magnitude of CT differences were different between males and females in each age group.

CONCLUSION

These data support the hypothesis that anatomical abnormalities in ADHD represent abnormal development rather than developmental delay.

1H MRSI of middle frontal gyrus in pediatric ADHD

Neuroimaging studies in multiple modalities have implicated the left or right dorsolateral prefrontal cortex (here, middle frontal gyrus) in attentional functions, in ADHD, and in dopamine agonist treatment of ADHD. The far lateral location of this cortex in the brain, however, has made it difficult to study with magnetic resonance spectroscopy (MRS). We used the smaller voxel sizes of the magnetic resonance spectroscopic imaging (MRSI) variant of MRS, acquired at a steep coronal-oblique angle to sample bilateral middle frontal gyrus in 13 children and adolescents with ADHD and 13 age- and sex-matched healthy controls. Within a subsample of the ADHD patients, aspects of attention were also assessed with the Trail Making Task. In right middle frontal gyrus only, mean levels of N-acetyl-aspartate + N-acetyl-aspartyl-glutamate (tNAA), creatine + phosphocreatine (Cr), choline-compounds (Cho), and myo-inositol (mI) were significantly lower in the ADHD than in the control sample. In the ADHD patients, lower right middle frontal Cr was associated with worse performance on Trails A and B (focused attention, concentration, set-shifting), while the opposite relationship held true for the control group on Trails B. These findings add to evidence implicating right middle frontal cortex in ADHD. Lower levels of these multiple species may reflect osmotic adjustment to elevated prefrontal cortical perfusion in ADHD and/or a previously hypothesized defect in astrocytic production of lactate in ADHD resulting in decelerated energetic metabolism (Cr), membrane synthesis (Cho, mI), and acetyl-CoA substrate for NAA synthesis. Lower Cr levels may indicate attentional or executive impairments.

Effects of methylphenidate on olfaction and frontal and temporal brain oxygenation in children with ADHD

OBJECTIVE

Olfaction and attention-deficit-/hyperactivity disorder (ADHD) are mediated by dopamine metabolism and fronto-temporal functioning converging in recent findings of increased olfactory sensitivity in children with ADHD modulated by methylphenidate (MPH) and altered frontal and temporal oxygenation in adults with ADHD.

METHOD

We investigated olfactory sensitivity, discrimination, and identification (Sniffin' Sticks) in 27 children and adolescents with ADHD under chronic MPH medication and after a wash-out period of at least 14 half-lives in balanced order and 22 controls comparable for handedness, age, and intelligence. In addition, inferior frontal and temporal oxygenation was measured by means of functional near-infrared spectroscopy (fNIRS) during the presentation of 2-phenylethanol. Group differences in regard to sex distribution were statistically controlled for by analysis of covariance.

RESULTS

Patients did not differ from controls in any olfactory domain under treatment with MPH. Cessation of medication led to a significant increase in olfactory discrimination. Controls displayed typical inferior frontal and temporal brain activity in response to passive olfactory stimulation, while brain oxygenation was diminished in the patient group when assessed without medication. Under medication ADHD patients showed a trend for a normalisation of brain activity in the temporal cortex.

CONCLUSIONS

The here reported effects of MPH cessation on olfactory discrimination and frontal and temporal oxygenation along with previous findings of increased olfactory sensitivity in medication-naïve ADHD children and its normalisation under chronic MPH treatment lead to the conclusion that MPH exerts differential chronic effects vs. acute cessation effects on altered olfactory function in ADHD. These effects are most probably mediated by modulation of the dopaminergic system.

Reduced right frontal cortical thickness in children, adolescents and adults with ADHD and its correlation to clinical variables: a cross-sectional study

OBJECTIVE

Some longitudinal magnetic resonance imaging (MRI) studies have shown reduced volume or cortical thickness (CT) in the frontal cortices of individuals with attention-deficit/hyperactivity disorder (ADHD). These studies indicated that the aforementioned anatomical abnormalities disappear during adolescence. In contrast, cross-sectional studies on adults with ADHD have shown anatomical abnormalities in the frontal lobe region. It is not known whether the anatomical abnormalities in ADHD are a delay or a deviation in the encephalic maturation. The aim of this study was to compare CT in the frontal lobe of children, adolescents and adults of both genders presenting ADHD with that in corresponding healthy controls and to explore its relationship with the severity of the illness.

METHOD

An MRI scan study was performed on never-medicated ADHD patients. Twenty-one children (6-10 year-olds), twenty adolescents (14-17 year-olds) and twenty adults (25-35 year-olds) were matched with healthy controls according to age and sex. CT measurements were performed using the Freesurfer image analysis suite.

RESULTS

The data showed regions in the right superior frontal gyrus where CT was reduced in children, adolescents and adults with ADHD in contrast to their respective healthy controls. The CT of these regions correlated with the severity of the illness.

CONCLUSIONS

In subjects with ADHD, there is a thinning of the cortical surface in the right frontal lobe, which is present in the children, adolescents and in adults.

Perfusion magnetic resonance imaging in psychiatry

INTRODUCTION

Cerebral perfusion imaging using magnetic resonance imaging (MRI) is widely used in the research and clinical fields to assess the profound changes in blood flow related to ischemic events such as acute stroke, chronic steno-occlusive disease, vasospasm, and abnormal vessel formations from congenital conditions or tumoral neovascularity. With continuing improvements in the precision of MRI-based perfusion techniques, it is increasingly feasible to use this tool in the study of the subtle brain perfusion changes occurring in psychiatric illnesses. This article aims to review the existing literature on applications of perfusion MRI in psychiatric disorder and substance abuse research. The article also provides a brief introductory overview of dynamic susceptibility contrast MRI and arterial spin labeling techniques. An outlook of necessary steps to bring perfusion MRI into the realm of clinical psychiatry as a diagnostic tool is brought forth. Opportunities for research in unexplored disorders and with higher field strengths are briefly examined.

METHODS

PubMed, ISI Web of Knowledge & Scopus were used to search the literature and cross reference several neuropsychiatric disorders with a search term construct, including "magnetic resonance imaging," "dynamic susceptibility contrast," "arterial spin labeling," perfusion or "cerebral blood flow" or "cerebral blood volume" or "mean transit time." The list of disorders used in the search included schizophrenia, depression and bipolar disorder, dementia and Alzheimer's disease, Parkinson's disease, posttraumatic stress disorder, autism, Asperger disease, attention deficit, Tourette syndrome, obsessive-compulsive disorder, Huntington's disease, bulimia nervosa, anorexia nervosa, and substance abuse. For each disorder for which perfusion MRI studies were found, a brief overview of the disorder symptoms, treatment, prevalence, and existing models is provided, and previous findings from nuclear medicine-based perfusion imaging are overviewed. Findings of perfusion MRI studies are then summarized, and overlap of findings are discussed. Overarching conclusions are made, or an outlook for future work in the area is offered, where appropriate.

RESULTS

Despite the now fairly broad availability of perfusion MRI, only a limited number of studies were found using this technology. The search produced 13 studies of schizophrenia, 7 studies in major depression, 12 studies in Alzheimer's disease, and 2 studies in Parkinson's disease. Drug abuse and other disorders have mainly been studied with nuclear medicine-based perfusion imaging. The literature concerning the use of perfusion imaging in psychiatry has not been reviewed in the last 5 years or more. The use of MRI for perfusion measurements in psychiatry has not been reviewed in 10 years.

CONCLUSIONS

Although MRI-based perfusion imaging in psychiatry has mainly been used as a research tool, a path is progressively being cleared for its application in clinical diagnostic and treatment monitoring. The precision of perfusion MRI methods now rivals that of nuclear medicine-based perfusion imaging techniques. Because of their noninvasive nature, arterial spin labeling methods have gained popularity in studies of neuropsychiatric disorders such as schizophrenia, depression, Alzheimer's, and Parkinson's diseases. Perfusion imaging measurements have yet to be included within the diagnostic criteria of neuropsychiatric disorders despite having shown to have great discriminant power in specific disorders. As this young methodology continues to improve and research studies demonstrate the correlation of measured perfusion abnormalities to microcirculatory abnormalities and neuropsychiatric symptomatology, the idea of including such a test within diagnostic criteria for certain mental illnesses becomes increasingly plausible.

Effects of long-term methylphenidate treatment: a pilot follow-up clinical and SPECT study

BACKGROUND

Although abnormalities in the regional cerebral blood flow (rCBF) responses to methylphenidate (MPH) treatment have been reported in children with attention deficit hyperactivity disorder (ADHD), there are few prospective longitudinal studies assessing the long-term effects of MPH and discontinuation effects after chronic treatment.

METHODS

The authors studied ten drug-naive children (2 girls, 8 boys, mean age+/-S.D.=9.60+/-1.96) diagnosed with ADHD by the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) diagnostic criteria, using (99m)Tc-HMPAO-single photon emission computed tomography (SPECT). Patients were studied at baseline (visit 1), after 2 months of MPH treatment (visit 2) and after a drug-free period of 2 months following 12 months of MPH treatment (visit 3) at doses of 1 mg/kg/day. We evaluated SPECT data visually and semi-quantitatively.

RESULTS

Two months of chronic MPH treatment resulted in visually detectable improvement in hypoperfusion in the right frontal cortex and all areas of temporal cortex with the exception of left lateral temporal cortex. This improvement was still detectable on visual evaluations of SPECT data after 2 months of treatment discontinuation. The treatment effects that were detected visually were not statistically significant in semi-quantitative analyses.

CONCLUSIONS

Treatment effects of chronic MPH treatment may persist long after the discontinuation of the treatment.

Attention-deficit hyperactivity disorder in girls: epidemiology and management

Attention-deficit hyperactivity disorder (ADHD) in girls is a topic of growing research and clinical interest. For many years, girls with ADHD have been ignored and overshadowed by hyperkinetic and impulsive boys, but they are now attracting interest in an effort to understand the similarities and differences in the prevalence, symptoms, familial risk, comorbidities and treatment of ADHD in the two sexes. A review of past and current literature finds that the symptoms of ADHD are not sex specific, but that identification of girls with ADHD is hampered by parental and teacher bias, and confusion. Girls are more likely to be inattentive without being hyperactive or impulsive, compared with boys. Girls and boys share the same familial risk patterns, as well as similar, although not identical, comorbidity or impairment patterns. The risk of non-treatment is as great in girls as it is in boys; up to 70-80% of identified children will have persistent symptoms and impairment that extends into adolescence and adulthood. Treatment modalities are equally effective in girls and boys. Stimulants, non-stimulants and behavioural modalities are the mainstays of effective treatment.

Attention-deficit hyperactivity disorder (ADHD)

Approaches to the diagnosis and treatment of attention-deficit hyperactivity disorder (ADHD) are undergoing a major change as a result of information from studies on the genetics of ADHD and the use of new neuroimaging technologies. Moreover, pharmacogenomics, although still in its infancy, will provide a basis for much more sophisticated treatment strategies for ADHD, particularly once more information is available about the genetics of ADHD. Even at this point in time, there is some pertinent information available that, although not ready for application in clinical settings, nonetheless provides a broader perspective for the clinician. In terms of etiology, ADHD is a neuropsychiatric disorder. There is a genetic basis in about 80% of the cases, involving a number of different genes, and in about 20% of the cases, ADHD is the result of an acquired insult to the brain. Some individuals likely have both genetic and acquired forms. Although medication works well in many cases of ADHD, optimal treatment of ADHD requires integrated medical and behavioral treatment. The family plays a crucial role in the management of children with ADHD. Because there is often a very high degree of comorbidity between ADHD and learning disabilities, teachers also have a great deal to contribute in the day-to-day management of these children. Early recognition and treatment prevent the development of more serious psychopathology in adolescence and adulthood.