Keywords

Introduction

The attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by some specific behavioral patterns and cognitive dysfunctions, which could progress, causing difficulties in the school and/or work environment.

Although ADHD syndrome is characterized by attention deficit, hyperactivity, and impulsivity, not all these symptoms have to be present, as many subtypes have been described. Multiple previous subtypes have been modified (combined, with attention deficit dominance or hyperactive/impulsivity dominance), and currently the term “clinical presentations” is accepted, with the caveat that these presentations can vary during the patient’s life [1].

According to the World Health Organization, ADHD is diagnosed in approximately 7% of the children population and 5% of the adult population [2].

ADHD is hereditary in 80% of the cases. In approximately 70–80% of children with ADHD, the disorder would persist into adolescence; and in approximately 30–65% cases, it would persist into adulthood. However, the manifestation of the disorder will change during life time, particularly in response to treatment.

Current evidence regarding the etiology points to multiple causes. There appears to be a series of biological disorders interacting among them as well as environmental and psychosocial factors. Early concepts, such as “minimal brain dysfunction,” have evolved into different microbiological, pathophysiological, imaging, and genetic implications. Similarly, although psychosocial factors are not considered a dominant cause, many studies have found important association between a dysfunctional family and the development of symptoms. This is also the case for other behavioral disorders. Therein, this factors should be considered in the design of therapeutic interventions.

Overall, 62 clinical trials across the world have proven improved efficacy of methylphenidate in the treatment of ADHD, as compared with other drugs. However, there is consensus by experts in the field that following pharmacologic treatment, a multidisciplinary approach to include psychological, educational, and social support is warranted.

Among the neurochemical factors, there is a well-known dysregulation in the production of neurotransmitters, primarily dopamine and noradrenaline. Thus, an accurate initial diagnosis is important, followed by pharmacological treatment to normalize the production of neurotransmitters.

The diagnostic is clinical. As pointed before, an adequate clinic approach with an accurate diagnostic hypothesis is important, as it would lead to a pertinent complementary workup. ADHD is diagnosed by the DSM-IV and V criteria [3, 4]. The ICD-10 criteria, by the World Health Organization, can also be used for diagnosis and follow a similar approach.

In approximately 40–60% of children with ADHD, the symptoms would persist to adulthood [5, 6]. The prevalence of ADHD in adults – following the DSM-IV criteria – is estimated as 1–2% [7]. In adulthood, hyperactivity is decreased and less conspicuous than attention deficit, leading to increased overlook of symptoms and under diagnosis [8]. However, in patients with persistent hyperactivity, there is frequently a detriment in their work performance, progressive social issues, low self-esteem, and increased likelihood of motor vehicle accidents with increased risk of substance abuse and psychiatric disorders [9]. Due to its high prevalence, associated global detrimental, as well as its chronicity, ADHD was recognized as a significant public health problem in 2002. In 1991, Biederman et al. [10] recognized many disorders commonly associated to ADHD. Oppositional defiant disorder (ODD), mood and affective disorders, learning disabilities, and social misbehavior are some of them. They found that more than 50% of children and adolescents with ADHD will have at least one associated comorbidity/disorder. Also, approximately 40–60% of patients with ADHD presented ODD and approximately 20–40% social misbehavior, which traduce in increased risk of substance abuse, violence, and bribery, as well as increased risk for teenage pregnancy.

Most adults with ADHD have an associated comorbid disorder. One of the most frequent is antisocial personality (14–24%). Others include borderline personality (14%), affective disorders with depression (20%), bipolar disorder (20%), anxiety (up to 50%), social phobia (32%), panic attacks (15%), obsessive-compulsive disorder (20%), and drug abuse (20–30%).

Any improvement in the capacity to predict ADHD natural history is important, not only for patient counseling but also for taking appropriate therapeutic decisions, as well as to define or stratify an adequate population where pharmacological treatment and clinical trials would be most beneficial.

Cerebral Neuroimaging Techniques

The structural alterations related to behavior and the cognitive deficit model described in children with ADHD suggest a compromise of frontal areas similarly described in adults with detrimental executive functions and working memory. Thus, a dysfunctional frontal cortex – and/or its functionally related regions of the brain – is most likely related to the neuropsychological alterations underlying ADHD. Neuroimaging studies have been used to evaluate this model, with not only structural but also functional assessment.

Most structural studies (on computed tomography or magnetic resonance imaging) have found some evidence of anomalies in the frontal cortex or basal ganglia, supporting the idea of a frontal-subcortical syndrome. Many functional studies (PET, SPECT, fMRI) have found similar abnormalities in the metabolism or blood flow of the mentioned brain areas.

Development and validation of minimally invasive biomarkers for ADHD is an important step. It would help in early diagnosis, evaluation of disease progression, and also in defining an adequate target population for clinical trials and new therapeutic agents.

One of the main advantages of MRI studies is the lack of ionizing radiation, as opposed to computed tomography and other imaging techniques. Moreover, MRI has greater versatility combining anatomic images with functional techniques such as perfusion, diffusion, or spectroscopy.

Morphometric MRI

The gold standard for volumetric measurements in most prior MRI studies is the manual delineation of anatomic structures. However, it requires significant training and is very time-consuming. For these reasons, it is not widespread and is not possible in studies with large number of subjects. As an alternative, many semi-automatic methods of segmentation have been proposed, reducing operator cost. These methods differ in the level of automation. One group requires manual intervention to delineate anatomic landmarks, to select initial regions of interest, or to localize seeds within the anatomic structure with the subsequent automatic delineation of the borders. Other group of methods are based on an atlas from previously segmented patients, the software deforms the atlas to fit each new case, and the labels are migrated to the segmented portions [11].

In addition to volumetric studies of anatomical structures as above, others have proposed the analysis of the spatial distribution of the anatomical differences, targeting usually atrophic regions. To achieve this goal, different maps of regional atrophy throughout the evolution of the disease are created.

Significantly decreased volume of the dorsolateral prefrontal cortex – as well as related regions such as caudate nucleus, anterior cingulate gyrus, and cerebellum – has been found in neuroimaging studies of pediatric populations. The volumetric abnormalities of the brain and cerebellum persist with time, whereas the caudate nucleus abnormalities tend to disappear [12, 13].

MR imaging has proven useful to obtain necessary information of the brain regions compromised by ADHD. There is general agreement regarding decreased volume in areas involving executive function and attention (prefrontal and striated areas). However, there are some inconsistencies , particularly regarding laterality differences in the brain volume (right versus left hemispheres).

Decreased volumes have been found in the right frontal lobe as well as the cingulate and striate region [4]. MRI studies with an appropriate sample (n > 30) have demonstrated decrease in volume of the right caudate nucleus. One study evaluating 50 children with ADHD found decreased mean volume of the right caudate nucleus, in comparison with a control group, suggesting abnormalities in the frontostriatal circuitry [14]. Decreased total brain volume – without asymmetric differences – was found in 50 girls with ADHD [15]. The same author also found decreased volume of the right globus pallidus and right anterior frontal region in 50 boys with ADHD [16].

In the pediatric population with ADHD, decrease in the volume of the striatum is consistently reported in voxel-based morphometric (VBM) studies , reinforcing the probable importance of this structure in the pathophysiology of this disorder [17, 18]. Early during childhood, ADHD is associated consistently with decrease in volume of the striatum.

On the other hand, striatum anomalies are rare in imaging studies using voxel-based morphometry (VBM) in adults with ADHD. It is possible that this discrepancy is related to the normalization of the striatum morphology with age and with long-term treatment. If this is the case, striatum anomalies seem to be related to symptoms in childhood. However, they would not explain the persistency of symptoms during adulthood [19].

Developmental coordination disorder (DCD) is a prevalent childhood movement disorder, impacting the ability to perform movement skills at an age-appropriate level. Recently, 44 children aged 7.8–12 years have been studied with VBM, including 22 children with DCD and 22 typically developing controls. In DCD children, they found a significant, large, right lateralized reductions in gray matter volume in the medial and middle frontal and superior frontal gyri compared to controls. Decreased volume of the gray matter in the pre-motor frontal region might be related to the characteristic motor deficits in DCD. Thus, functional improvement in children with DCD can be accomplished by directed interventions in motor planning, attention, and functional executive processes associated with the regions of decreased gray matter volume [20].

Neuroimaging studies provide vital information related to the neurobiology of ADHD, but there still exists a wide gap in relevant information. A voxel-based cortical thickness and voxel-based morphometry study were performed to examine neuroanatomic distinctions in 18 children/adolescents aged 7.5–13 years diagnosed with DSM-IV TR as ADHD (nonmedicated). They were compared with 18 healthy matched controls. Voxel-based cortical thickness findings in ADHD children/adolescents revealed reduced cortical thickness in the left superior frontal, left orbitofrontal, and left dorsal anterior cingulate cortex. Voxel-based morphometry findings confirmed decreased gray matter volume in the left orbitofrontal, left middle frontal/dorsolateral prefrontal, left middle temporal, and left cerebellum in comparison to control group. A decrease in white matter volume was also observed in the left inferior frontal and left calcarine region of ADHD children/adolescents. Findings might relate to possible abnormal neuroanatomical development patterns in ADHD children [21].

In an extensive study that included 307 patients with ADHD, 169 unaffected siblings and 196 typically developing controls (mean age 17.2 [range 8–30] years) showed that brain areas involved in decision-making, motivation, cognitive control, and motor functioning (precentral gyrus, medial and orbitofrontal cortex, and cingulate cortices) had significantly smaller gray matter volume in participants with ADHD than in controls. Investigation of unaffected siblings indicated familiarity of four of the structural brain differences, supporting their potential in molecular genetic analyses in ADHD research [22].

Using gray matter morphometry and probabilistic tractography combined with multivariate statistical modeling (partial least squares regression and support vector regression), anomalies have been identified within the fronto-accumbal circuit in childhood ADHD, which were associated with increased aggression. More specifically, children with ADHD showed reduced right accumbal volumes and frontal-accumbal white matter connectivity compared with HC. The magnitude of the accumbal volume reductions within the ADHD group was significantly correlated with increased aggression, an effect mediated by the relationship between the accumbal volume and impulsivity. Furthermore, aggression, but not impulsivity, was significantly explained by multivariate measures of fronto-accumbal white matter connectivity and cortical thickness within the orbitofrontal cortex [23].

Another study with voxel-based morphometry (VBM) using the DARTEL approach has shown significantly smaller gray matter volume in subjects with ADHD compared to their matched controls within the anterior cingulate cortex, the occipital cortex, bilateral hippocampus/amygdala, and in widespread cerebellar regions. Further, reductions of the anterior cingulated cortex gray matter volume were found to correlate with scores of selective inattention [24].

A large number of structural neuroimaging studies have used voxel-based morphometry to identify gray matter abnormalities in youths with conduct problems, but the findings have been disparate and few have been replicated. Anisotropic effect-size signed differential mapping was used for voxel-based meta-analyses. Statistical parametric maps comparing gray matter differences between youths with conduct problems and typically developing youths were available for 11 of the studies, with peak coordinates available for the remaining studies. Youths with conduct problems had decreased gray matter volume in the left amygdala (Fig. 44.1) (extending into anterior insula), right insula (extending ventrolaterally into the prefrontal cortex and inferiorly into the superior temporal gyrus), left medial superior frontal gyrus (extending into the right anterior cingulate cortex), and left fusiform gyrus. Subgroup meta-analysis assessing age-at-onset effects identified reduced gray matter volume in the left anterior insula (extending into amygdala). Meta-regression analyses revealed that greater scores on measures of callous-unemotional traits were associated with a lower reduction in gray matter volume in the left putamen. The proportion of male and female youths in the sample was associated with decreased gray matter volume in the left amygdala and increased gray matter volume in the right inferior temporal cortex. While there was no association with comorbid attention-deficit/hyperactivity disorder or intelligence quotient, age range was associated with gray matter differences in the left amygdala [25].

Fig. 44.1
figure 1

3D reconstruction of right and left amygdala

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Girls have been underrepresented in past studies on ADHD [26], probably due to the predominance of male subjects in clinical settings [27]. Females with ADHD have fewer hyperactive/impulsive symptoms and more inattentive symptoms, present more commonly with the predominantly inattentive subtype, and tend to be underdiagnosed when compared to boys with ADHD.

ADHD in adulthood is a serious and frequent psychiatric disorder with the core symptoms, inattention, impulsivity, and hyperactivity. Increased cortical thickness in the left occipital cortex may represent a mechanism to compensate for dysfunctional attentional networks in male adult ADHD patient [28].

Some studies have pointed to the relation of limbic structures in the pathogenesis of ADHD. Recently, using manual segmentation on MR images, Nickel et al. compared the volume of the amygdala and hippocampus in 30 patients with ADHD and 30 control subjects. They did not find a significant difference in the volumes. However, patients with significantly increased hyperactivity demonstrated decreased volume of the left amygdala. This suggests that limbic alterations might be significantly related to hyperactive symptoms in ADHD [29].

In other study, voxel-based morphometry (VBM) was applied to 44 adults with ADHD, combined subtype, aged 18–54 years, and 44 healthy controls matched for age, sex, and IQ. Here, ADHD patients showed reduced gray matter volume in the right supplementary motor area. Using more lenient thresholds, they also observed reductions in the subgenual anterior cingulate and right dorsolateral prefrontal cortices and increases in the basal ganglia, specifically in the left caudate nucleus and putamen. There was a positive correlation between the cumulative stimulant dose and volume in the right supplementary motor area and dorsolateral prefrontal cortices clusters, suggesting that adults with ADHD show brain structural changes in regions belonging to the so-called cool executive function network . Thus, long-term stimulant medication may act to normalize these gray matter GM alterations [30] (Fig. 44.2a, b).

Fig. 44.2
figure 2

(a, b) Measurements of cortical thickness and standard deviation in adult patient with ADHD compared with group of healthy patients of the same sex and age

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131 patients with ADHD, whom had stopped the previous use of stimulant medication for 6 months, and 95 healthy control subjects (18–58 years of age) were studied with VBM. The results showed that ADHD in adulthood is associated with global rather than regional volumetric abnormalities and that previous use of stimulant medication does not seem to modify subsequent brain volumes in a significant way [31]

Recently, radiomics were used. It consist in the extraction from magnetic resonance imaging scans of a large amount of quantitative information from digital imaging features. Using radiomics, they can build and evaluate classification models based on pathological subtyping. The researchers examined 83 children aged 7–14 with newly diagnosed and never-treated ADHD, including children with the inattentive ADHD subtype (ADHD-1) and the combined subtype (ADHD-C). The scientists compared these MRI results with those of a control group of 87 healthy children of the same age and screened relevant radiomics signatures from more than 3,100 quantitative features extracted from the gray and white matter. They found alterations in the shape of the left temporal lobe, bilateral cuneus, and areas around left central sulcus, and these differences contributed significantly to distinguishing ADHD from typically developing controls. Within the ADHD population, features involve in the default mode network and the insular cortex significantly contributed to discriminating the ADHD inattentive subtype from the combined subtype. They could discriminate patients with ADHD with control subjects with 73.7% accuracy and discriminate ADHD-1 from ADHD-C patients with over 80.1% accuracy [32]

Attention-deficit/hyperactivity disorder + comorbid oppositional defiant disorder (ADHD+ODD) and ADHD-only were associated with volumetric reductions in brain areas crucial for attention, (working) memory, and decision-making. Volumetric reductions of frontal lobes were largest in the attention-deficit/hyperactivity disorder + comorbid oppositional defiant disorder (ADHD+ODD) group, possibly underlying observed larger impairments in neurocognitive functions. Previously reported striatal abnormalities in ADHD may be caused by comorbid conduct disorder rather than oppositional defiant disorder (ODD) [33]

Functional MRI

Relations between structural anomalies and functional deficits have also been studied in ADHD. For 756 human participants in the ADHD-200 sample, they produce gray and white matter volume maps with voxel-based morphometry, as well as whole-brain functional connectomes. Joint independent component analysis was performed, and the resulting transmodal components were tested for differential expression in ADHD versus healthy controls. Four components showed greater expression in ADHD. They have been observed reduced default mode network (DMN) and task-positive networks (TPN) segregation co-occurring with structural abnormalities in dorsolateral prefrontal cortex and anterior cingulate cortex, two important cognitive control regions. They also observed altered intranetwork connectivity in default mode network, dorsal attention network , and visual network, with co-occurring distributed structural deficits. There was strong evidence of spatial correspondence across modalities: for all four components, the impact of the respective component on gray matter at a region strongly predicted the impact on functional connectivity at that region. Overall, these results show that ADHD involves multiple, cohesive modality spanning deficits, each one of which exhibits strong spatial overlap in the pattern of structural and functional alterations [34]

Studies performed with fMRI and MEG have found hypoactivation of the prefrontal cortex, predominantly in the right hemisphere as well as the caudate nucleus and anterior cingulate, and differences in the activation of the basal ganglia [35, 36].

Compared to the healthy controls, the ADHD in children showed significantly decreased functional connectivity that primarily involved the default mode network and frontoparietal network regions and cross-network long-range connections. Further graph-based network analysis revealed that the ADHD in children had fewer connections, lower network efficiency, and more functional modules compared with the healthy controls. The attention-deficit/hyperactivity disorder-related alterations in functional connectivity but not topological organization were correlated with clinical symptoms of the attention-deficit/hyperactivity disorder children and differentiated the patients from the healthy controls with a good performance. Taken together, these signs suggest a less integrated functional brain network in children with ADHD due to selective disruption of key long-range connections, with important implications for understanding the neural substrates of ADHD, particularly executive dysfunction [37].

A study explored age-related brain network differences between ADHD patients and typically developing (TD) subjects using resting state fMRI (rs-fMRI) for three age groups of children, adolescents, and adults. They collected rs-fMRI data from 184 individuals (27 ADHD children and 31 TD children; 32 ADHD adolescents and 32 TD adolescents; and 31 ADHD adults and 31 TD adults). The Brainnetome Atlas was used to define nodes in the network analysis. They compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality, a well-known measure of nodal centrality. The left middle temporal gyrus showed significant interaction effects between disease status (i.e., ADHD or TD) and age (i.e., child, adolescent, or adult). Additional regions were identified at a relaxed threshold. Many of the identified regions (the left inferior frontal gyrus, the left middle temporal gyrus, and the left insular gyrus) were related to cognitive function, suggesting that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients [38].

Studies with functional imaging in children are rare. Positron emission tomography offers information of the brain glucose metabolism, globally and in selected areas. Studies performed with small samples in adolescence have found no abnormalities in the brain glucose metabolism [39, 40].

Magnetic Resonance Spectroscopy

The most frequently used spectroscopy is that originated from hydrogen nucleus. The most frequently evaluated metabolites are N-acetyl-aspartate (NAA), myo-inositol (mI), choline (Cho), creatine (Cr), and glutamate + glutamine (Glx) (Fig. 44.3).

Fig. 44.3
figure 3

A typical in vivo example of linear combination model spectrum in the same area with metabolite peaks. mI myo-inositol, Cho choline compounds, Cr creatine, Glx glutamate + glutamine, NAA N-acetyl-aspartate

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NAA is a marker of neuronal and axonal viability and density. Myo-inositol has been regarded as glial marker located in the astrocytes, as product of myelin degradation, and the most important osmolyte or cell volume regulator. Choline is a marker of the phospholipid metabolism and cellular membrane turnover marker, reflecting cellular proliferation. Creatine is used as internal reference value, since it is the most stable cerebral metabolite. It has a role in the energetic system of the brain and in the osmoregulation. Lactate peak indicates anaerobic glycolysis in tumors. Lipid peak indicates necrosis and/or disruption of myelin sheath. Glutamate is an important neurotoxic brain marker. Excess of glutamate can produce neuronal death through excitotoxic processes [41]. It is also assumed that glutamate in the frontal circuits is an important regulator of dopamine [42,43,44], and through a feedback mechanism, the concentration of dopamine can influence the concentration of glutamate [45, 46].

Magnetic resonance spectroscopy may be necessary to obtain information from living tissues [47]. A previous study of 23 ADHD patients does not find significant differences in the neurometabolites of the dorsal-lateral frontal region [48]. There are three studies that show an increase in N-acetylaspartate/creatine ratios in children with ADHD in the right frontal region [49] and in the left semioval center, respectively [50, 51].

In vivo phosphorus 31 magnetic resonance spectroscopy (31P MRS) has shown lower bilateral membrane phospholipid (MPL) precursor levels in the basal ganglia and higher MPL precursor levels in the inferior parietal region (primarily right side) in 31 psychostimulant-naive children with ADHD (mean [SD] age, 8.1 [1.2] years; range, 6.1–10.0 years) as compared with 36 healthy control children (mean [SD] age, 8.1 [1.3] years; range, 6.1–10.4 years), and these results are suggestive of possible progressive, nonlinear, and sequential alterations implicating a bottom-up developmental dysfunction in parts of the cortico-striato-thalamo-cortical network in ADHD [52].

Conclusion

ADHD is a social problem and not just a problem for the sick, their families, and educators. It impacts society and the general policy of nations. It is still necessary to carry out public education campaigns to make people aware of the reasons why everyone, as a society, should be seriously concerned about ADHD and we must support research to conquer this disease. The diagnosis is clinical, but neuroradiological techniques can be used in research studies.

In the future, imaging-based disease classification will gain importance versus the diagnostic and statistical manual of mental disorders. Standardization will be necessary to clinically validate these technique, but they will prove useful as they advance, in particular in data acquisition and analysis. Interventional psychoradiology will also be developed.