Brain structure network model analyzing method for teen-age autism

Abstract

The invention discloses a brain structure network model analyzing method for teen-age autism. The method comprises the steps that a brain structure network model is built, wherein through preprocessing of original data of a brain structure image, brain area division, definition of brain structure network nodes and edges and binarization processing, the brain structure network model is built; permutation test is conducted, wherein the effectiveness of tested samples in an autism patient group and a normal control group is tested; the brain structure network model is analyzed, wherein the brainstructure network model of the autism patient group and the brain structure network model of the normal control group are subjected to complicated network attribute comparison and analysis. By using the brain structure image gray matter volumes of all the brain areas, the brain structure network model is built, through the complicated network attribute comparison and analysis of the brain structure network models of the autism patient group and the normal control group, the brain structure network of the autism patient is more comprehensively and accurately analyzed and studied, and a study direction is provided for the autism, internet addiction, smoking addiction, online game addiction, cognition and other health fields.

Description

technical field [0001] The invention belongs to the technical fields of medical image processing and analysis, autism, internet addiction, smoking addiction, online game addiction and cognition, and in particular relates to a brain structure network model analysis method for juvenile autism. Background technique [0002] Autism in adolescents is one of the representative diseases of widespread developmental disorders common in children. Judging from the current statistical data, the prevalence of autism is about 3 / 10,000, and the incidence rate of boys is much higher than that of girls, about 3.5 times. [0003] Autism seriously interferes with the intellectual development of the child's brain and normal psychological development. If not treated in time, the child will have symptoms such as social interaction barriers, communication barriers, and narrow interests, which will also be a torment for the child's family. In addition, the children are also at risk of developing o...

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Problems solved by technology

[0005] In 2006, Dapretto M analyzed the abnormalities of mirror neurons in the brains of patients with autism and found that children with autism had no mirror neuron activity in the inferior frontal gyrus, and the intensity of neuron activity in this area was negatively correlated with the severity of social impairment in children. Related; in 2011, Ozonoff S et al. calculated the estimated value of relapse risk of autism in the siblings of the affected children, and found that the relapse risk of male subjects was almost tripled, while if the male subjects had a younger In 2015, Qiao constructed the whole brain functional connectivity of autistic patients in the resting state based on functional magnetic resonance imaging technology, and found that compared with There are abnormal functional connections in normal people. However, when analyzing and studying the abnormal position in the brain of autistic patients, the degree value of a single node is used as the basis. In 2018, Li et al. proposed that optical brain imaging technology is more suitable for brain image acquisition of children with autism, and used near-infrared spectroscopy (NIRS) and Diffuse Correlation Spectroscopy (DCS), respectively measure blood oxygen metabolism and blood flow activity in the cortex, and send this information into a machine learning model for prediction. However, near-infrared spectroscopy (NIRS) has the weakness of limited detection depth. It is mainly concentrated in the surface cortex area. At the same time, due to the effect of light scattering, the spatial resolution of imaging is relatively low, generally in the range of millimeters to centimeters, and it is impossible to conduct in-depth and accurate research on brain structures.

At present, there is no method that can accurately analyze the differences between the brain structure network of autistic patients and normal people, which has greatly hindered the analysis and research of adolescent autism

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