Application of Quantitative Magnetic Resonance Imaging in the Diagnosis of Autism in Children

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Abstract

Objective: To explore the application of quantitative magnetic resonance imaging in the diagnosis of autism in children. Methods: Sixty autistic children aged 2–3 years and 60 age- and sex-matched healthy children participated in the study. All the children were scanned using head MRI conventional sequences, 3D-T1, diffusion kurtosis imaging (DKI), enhanced T2*- weighted magnetic resonance angiography (ESWAN) and 3D-pseudo continuous Arterial Spin-Labeled (3D-pcASL) sequences. The quantitative susceptibility mapping (QSM), cerebral blood flow (CBF), and brain microstructure of each brain area were compared between the groups, and correlations were analyzed. Results: The iron content and cerebral blood flow in the frontal lobe, temporal lobe, hippocampus, caudate nucleus, substantia nigra, and red nucleus of the study group were lower than those in the corresponding brain areas of the control group (P < 0.05). The mean kurtosis (MK), radial kurtosis (RK), and axial kurtosis (AK) values of the frontal lobe, temporal lobe, putamen, hippocampus, caudate nucleus, substantia nigra, and red nucleus in the study group were lower than those of the corresponding brain areas in the control group (P < 0.05). The mean diffusivity (MD) and fractional anisotropy of kurtosis (FAK) values of the frontal lobe, temporal lobe and hippocampus in the control group were lower than those in the corresponding brain areas in the study group (P < 0.05). The values of CBF, QSM, and DKI in frontal lobe, temporal lobe and hippocampus could distinguish ASD children (AUC > 0.5, P < 0.05), among which multimodal technology (QSM, CBF, DKI) had the highest AUC (0.917) and DKI had the lowest AUC (0.642). Conclusion: Quantitative magnetic resonance imaging (including QSM, 3D-pcASL, and DKI) can detect abnormalities in the iron content, cerebral blood flow and brain microstructure in young autistic children, multimodal technology (QSM, CBF, DKI) could be considered as the first choice of imaging diagnostic technology. Clinical Trial Registration: [http://www.chictr.org.cn/searchprojen.aspx], identifier [ChiCTR2000029699].

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Tang, S., Nie, L., Liu, X., Chen, Z., Zhou, Y., Pan, Z., & He, L. (2022). Application of Quantitative Magnetic Resonance Imaging in the Diagnosis of Autism in Children. Frontiers in Medicine, 9. https://doi.org/10.3389/fmed.2022.818404

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