Background
The term autism is made up of two parts: autos, which means "self," and ism, which means "inclination" [
1]. Autism Spectrum Disorder (ASD) is a group of developmental disorders of the nervous system. Its main manifestations consist of defects in social interactions, communication, repetitive behaviors and limited interests. Information from the US Department of Education shows that the incidence of autism increases by 10–17% each year [
2]. Due to the rapid and progressive rise of ASD, a lot of research has been done on it recently. A major feature of ASD is the heterogeneity of its clinical features. A diversity of symptoms along with many psychological and physiological comorbidities may be present. Psychological comorbidities include attention–deficit hyperactivity disorder (ADHD), obsessive–compulsive disorder (OCD), anxiety, and intellectual disability [
3]. There is a notable co-occurrence of ADHD with ASD, and the two conditions share many neurological and behavioral similarities. Physiological comorbidities of ASD include epilepsy, sleep disorders, and gastrointestinal (GI) problems [
4]. ASD are caused by genetic or environmental factors or a combination of these. ASD is considered a complex genetic disorder with high heritability. Epidemiological twin studies support the strong genetic component of ASD. Overall, the SFARI (Simons Foundation Autism Research Initiative) gene database, a database of autism candidate genes, lists about 1000 genes associated with ASD. Genes entered into the database are scored based on their strength of association with ASD risk. Despite the genetic heterogeneity, a recent review of the literature reveals that a number of these mutations converge on a common neurodevelopmental pathway involved in neurogenesis, axon guidance, and synapse formation. Non-genetic factors mediating ASD risk could include parental age, maternal nutritional and metabolic status, infection during pregnancy, prenatal stress, and exposure to certain toxins, heavy metals, or drugs [
5]. For many years, brain development and function have been the focus of research in ASD. Experimental and postmortem studies have identified central nervous system (CNS) pathologies at gross morphological level and cellular level, for example, in neurons and glial cells. From these studies, it can be concluded that neuropathologies are evident in ASD. However, research in recent years on immune responses and gut–brain signaling have revealed that pathologies in ASD also exist outside the CNS [
6].
ASD is diagnosed based on behavioral interests and repetitive behaviors [
7]. These social impairments may be related to the interpretation of social signals: evidence from healthy individuals suggest that potentially threatening situations such as others' proximity can trigger a number of physiological responses that help regulate the distance between themselves and others during social interaction [
8] and showing the critical role of social signal interpretation in social interaction [
9]. Individuals with ASD have social impairments, potentially due to the lack of social signal interpretation and, therefore, resulting unable to interpret these signals to guide appropriate behaviors.
In the first step, identifying the clinical biomarkers of ASD using structural brain imaging can pave the way for recognizing the neurobiological causes of the disorder and the brain's areas affected by the disorder. In magnetic resonance imaging studies, there are generally two categories of features: volume-based and surface-based features. Different articles use one or a combination of both.
Several studies have been carried out to diagnose volumetric brain defects in people with autism. These studies reinforced the hypothesis that autistic patients had larger brain volumes than controls [
10‐
15]. Several studies observed that the significant increased areas of gray and white matter volume in the autism group were the frontal, temporal and parietal lobes [
16‐
19]. A more comprehensive study was conducted in 2016 by Haar and colleagues. This study showed an increase in ventricular volume, a decrease in the corpus collasom, and several cortical areas [
20]. Several studies used Gyrification Index (GI) to distinguish between autistic and control groups. This index was higher in several regions in autistic than in the controls [
21‐
24]. Several studies used the Sulcal depth parameter to analyze the shape anomalies of structural images. Abnormalities in the sum region were noticeable in the autistic group [
25,
26]. In 2013, Ecker and colleagues. found, the thickness of the cerebral cortex was significantly larger in the frontal lobe of autistic subjects and the surface area in the orbitofrontal cortex and posterior cingulum in the autism group was lower than the control [
27]. Sum studies examined cortical thickness changes and observed an increase of cortical thickness in several regions of the brain [
20,
27‐
36]. The contradictory results reported in different studies have been due to differences in the imaging methods used, heterogeneity of the subjects and so on.
Since the core cause of many of the symptoms of autism spectrum disorder is due to changes in the structure of the brain, the importance of examining the structural abnormalities of the brain in these children becomes apparent. So far, few studies have been performed on structural abnormalities in the brains of autistic children. This study intended to investigate the images of structural magnetic resonance and also to detect structural abnormalities created in the brain attributable to autism spectrum disorder in children. In this study, to better evaluate, volume and surface features were employed simultaneously.
Discussion
Autism spectrum disorder is associated with increased brain volume in childhood and decreased brain volume in adulthood [
44]. Increased brain volume in autistic people compared to controls confirms the studies [
10‐
19,
29]. Based on the statistical findings of the study presented in , the volume of white matter in the L and R amygdala region of the brain in the autism group shows a meaningful increase compared to the control. The amygdala is part of the limbic system of the brain and is associated with emotional and social behaviors [
45], facial recognition [
46], and cognitive function [
47]. The increase in the volume of this area of the brain in the autistic group approves the research [
13,
15,
48‐
51]. The volume of white matter in some areas located in the frontal and temporal lobes also has a considerable difference between two groups and is higher in the autism one, which confirms the studies [
10,
17,
29,
52]. The frontal lobe in the brain is responsible for reasoning, planning, decision-making, and judgment, and generally controls social and cognitive behaviors [
53]. The Temporal lobe is also involved in understanding language, and emotions, and is an area of sound and speech processing. Both lobes play a role in memory [
54]. The volume of L and R putamen white matter, which is generally engaging in movement and learning [
55], also is higher in the autism one that approves the studies [
56‐
59]. The volume of white matter in the L and R thalamus and L precentral gyrus regions is notably lower in autism group. The thalamus is part of the limbic system of the brain that is the site of information amplification and processing. The precentral gyrus is known as the primary motor cortex which is responsible for voluntary movements [
60]. The decrease in the volume of L and R thalamus confirmed by studies [
61‐
63], however, is in contradiction with the study [
64]. Decreased volume of L precentral gyrus has not been reported in any research. According to the statistical findings of the present analysis in Table
5, the volume of gray matter in the temporal lobe of the brain of autistic individuals compared to controls is meaningfully higher. In addition, considerable growth in the volume of the gray matter of R fusiform gyrus (FFG), L and R Pallidum and L corpus callosum in the autism group is observed. The social problems seen in ASD may be due in part to the dysfunction of FFG [
65]. pallidum plays a role in the regulation of voluntary movements [
66]. The corpus callosum is a group of high-density white matter fibers in the brain that facilitate communication between the hemispheres. The increase in gray matter volume of R fusiform gyrus, L and R pallidum and L corpus callosum in the autism group compared to controls is confirmed by researches [
11,
14], [
67,
68] and [
69‐
73], respectively.
Neuroimaging research shows that human intellectual ability is related to the brain structure, including cortical thickness. Autism spectrum disorder is characterized by impaired cognition and social communication, and in addition to social disabilities [
74]. Therefore, it is expected that the cortical thickness in autistic children is associated with abnormalities. Based on the statistical discoveries in Table
6, the mean and standard deviation of cortical thickness in the autism group, showing a notable increase which approves the studies [
20,
27,
28,
30‐
36]. Furthermore, according to the statistical findings in Table
7, the cortical thickness in the L and R cuneus, R lingual, R paracentral, L parsopercularis and R superior temporal areas in the autism group has a considerable increase. cuneus and lingual are parts of the brain located in the occipital lobe and are engaged in visual processing [
75,
76]. The paracentral controls the sensory and motor nerves of the lower extremity [
77]. Pars operculris is a part of the inferior frontal gyrus located in the Broca area of the brain [
78]. The Broca area in the brain is related to speech production and processing [
79]. Since speech disorder is one of the main features of ASD, this area is one of the main parts that encounter abnormalities in autism spectrum disorder [
80,
81]. The superior temporal is part of the temporal lobe and contains the auditory cortex, which is responsible of processing sounds. It also includes the Wernicke area of the brain, which is the main part for understanding language. This area also plays a vital role in social cognition and impairment of this part is one of the main features of ASD [
82,
83]. Increased cerebral cortical thickness in L and R cuneus, R lingual, R paracentral areas has not been reported in any study. Increased cortical thickness of the L parsopercularis and R superior temporal also confirms studies [
84,
85] and [
30], respectively. In addition, the cortical thickness of L and R parahippocampal areas in the autism group was notably decreased. The parahippocampal is a part of the limbic system of the brain that plays an important role in encoding and retrieving memory [
86]. This finding of the current research confirms the study [
87]. Based on the statistical findings of the present study in Table
8, the Sulcus depth of the cerebellum of L bankssts, L parsopercularis, L parstriangularis, L superior temporal, L and R temporal pole and L insula in the autism group shows a substantial increase [
25,
26,
88,
89]. In ASD, the presence of anomalies in bankssts is the root of the impairment in the social activities [
90]. The parstriangularis, like the parsopercularis, is part of the inferior frontal gyrus located in the Broca area of the brain [
85]. Insula also participates in understanding consciousness and social emotions [
86,
87]. The sulcus depth of the rostral anterior cingulate in the autism group showed a significant decrease compared to the control group, which has not been reported in any study. According to the statistical data of Table
9, the GI of the number of frontal and parietal lobe brain regions in the autism group has increased considerably. Furthermore, this index has increased in L and R lateral occipital, R parstriangularis, L posterior cingulate, L precuneus, in the autism group compared to the control group. This finding of the present analysis confirms the studies [
21‐
24,
91‐
94]. On the other hand, this index in the L entorhinal brain area in the autism group is substantially reduced compared to the control group. Posterior cingulate is involved in memory and emotion [
95,
96] and researches have revealed that abnormality of this region is one of the main aspects of ASD [
97]. The precuneus is a region of the brain that participated in a variety of complex functions, including recall and memory, the integration of information about the environment, mental imagery strategies, memory retrieval, and emotional responses [
98]. The entorhinal is located in the middle of the temporal lobe and acts as an extensive network in memory and time perception [
99]. According to the statistical findings of Table
10, the cortical complexity parameter in all areas of the right hemisphere of the autism group compared to the control group has meaningfully decreased. In addition, there is an important difference between the two groups in the some regions of the brain located in the left hemisphere. So far, no study has been performed to calculate the surface cortical complexity parameter in the DK atlas regions. However, according to the clinical characteristics of autism spectrum disorder and abnormal areas, the findings of the present study can be correctly understood.
Regions in the frontal and parietal cortices, are involved in a number of cognitive operations, including planning, working memory, impulse control, inhibition, and set-shifting. These cognitive domains are often referred to under the umbrella term of “executive functions,” which broadly refers to the set of processes that are employed when an individual is involved in a goal-directed activity. Damage to the frontal cortex, which is considered the “seat” of executive functioning, interrupts the ability of individuals to complete many goal-directed tasks and has been shown to result in the emergence of perseverative and repetitive behaviors, insistence for sameness, and impulsivity, all of which are clinical manifestations of autism spectrum disorders [
100]. Prefrontal cortex is one region of the emotion processing network. The prefrontal cortex is like a control center, helping to guide our actions, and therefore, this area is also involved during emotion regulation. In the recent years, growing attention has paid to the involvement of cerebellar and striatal structures in ASD. In the recent years, growing attention has paid to the involvement of cerebellar and striatal structures in ASD. The cerebellum is involved in both motor and social impairments reported in ASD. Clumsiness and deficits in motor coordination and manual dexterity, abnormal balance gait and posture are all dependent on the cerebellar function and are affected in ASD. These deficits can be detected even in the first months of life, with affected babies exhibiting difficulties positioning their body when carried, hypotonia and uncoordinated movements. The basal ganglia are a group of subcortical nuclei involved primarily in motor skills. The term “Basal Ganglia” refers to the striatum and the globus pallidus, while the substantia nigra (mesencephalon), the subthalamic nuclei (diencephalon) and the pons are related nuclei. Basal ganglia network is shown to be deeply affected in ASD models. In the early 2000s, John Rubenstein and Michael Merzenich formulated the excitation/inhibition (E/I) imbalance hypothesis of ASD, suggesting that the physiopathology of ASD and their related comorbidities may reflect a disturbance in such a balance. Even though their work focused only on the cortical networks, it may be easily extended to striatal networks, as the striatum receives major excitatory inputs from cortices areas and major inhibitory inputs from the local interneurons network [
101].
Autism diagnostic methods are currently based on clinical observations, but these methods have many errors. The use of diagnostic methods in parallel with imaging methods can have a great impact on the design of treatment processes for these patients. There are various methods for treating autism, including speech therapy, occupational therapy, music therapy, game therapy, behavioral therapy. A combination of these treatment methods can reduce the symptoms of this disease and control it. Since autism is a spectrum disorder and the severity of symptoms is not the same in all patients, a fixed treatment method cannot be used for all patients. In general, the method of structural imaging of the brain and the examination of structural abnormalities of the brain of autistic people helps to design personal treatment for each patient and to choose an effective treatment method. Using the method of this study, it is possible to evaluate the effect of therapeutic interventions on the patient's recovery process, and if the desired result is not achieved, another treatment method substituted. With brain structural imaging, the abnormal areas of the brain are identified, and based on the abnormal areas of each person's brain, along with clinical observations, personalized treatment is designed. In addition, after a period of speech therapy, neuroimaging can be done again, and by comparing the results of two imaging sessions, the treatment process can be evaluated and the improvement of structural abnormalities in these areas can be observed, which indicates the progress of the treatment.
Conclusions
This study aimed to investigate and identify structurally abnormality areas of the brain in autism spectrum disorder using structural magnetic resonance imaging. In examining the brain volume using sMRI, simultaneous volume changes of gray matter and cerebral white matter were observed in the autism group. These volume changes are in the form of an increase in the total volume of the brain and white matter of the brain and changing in the volume of white and gray matter in the identified areas of the Hammers volume in the autism group. Examining the brain surface using sMRI also showed abnormalities in the parameters of cerebral cortex thickness, sulcus depth, surface complexity and GI in the autism group. These changes are increasing the mean and standard deviation of the cerebral cortex thickness and changing the mentioned parameters in the specified areas of the DK atlas in the autism group. Changes in the brain structure due to ASD are often related to the clinical features of autism spectrum disorder, such as the Broca and Wernicke areas, which are involved in speech production and speech comprehension. Identifying structurally abnormality areas of the brain and examining their relationship to the clinical features of ASD can pave the way for the correct and early detection of this disorder using structural magnetic resonance imaging. It is also possible to design treatment for autistic people based on the abnormal areas of the brain, and to see the effectiveness of the treatment using imaging.
The impossibility of collecting imaging and clinical information led to the use of ABIDE data. As well as the lack of imaging and clinical data of infants in both autism and control groups, caused the use of subjects in the age range of 5–10 years. In addition, ASD is an extremely heterogenous disorder, were any of the selected patients suffered from associated low IQ, delayed speech, epilepsy or any other forms of associated diseases. Those comorbidities can affect both the volume and surface of brain, which could affect specifity of the diagnosis. Since there is no information about autism associated diseases in selected patients, this problem is one of the limitations of the present study. It is suggested that the study be performed for more detailed research with a higher amount of data. In addition, it can be organized by information from patients who suffer from autism and the control group with younger age. Other methods of analyzing structural magnetic resonance imaging should also be observed. Studies with similar data should be done using other software. The present analysis has focused on the structure of the brain. In future researches, in addition to structural images of the brain, other brain imaging modalities such as fMRI and DTI can be used. Due to the dependence of brain structure on age, studies can be performed in different age groups to identify the effect of age on changes in brain structure due to autism spectrum disorder.
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