Application of pseudocontinuous arterial spin labeling perfusion imaging in children with autism spectrum disorders

Ye, Fang; Du, Lan; Liu, Bing; Yang, Aocai; Liu, Die; Chen, Yue; Lv, Kuan; Xu, Pengfei; Chen, Yuanmei; Liu, Jing; Zhang, Lipeng; Li, Shijun; Shmuel, Amir; Zhang, Qi; Ma, Guolin

doi:10.3389/fnins.2022.1045585

Cited by 5 publications

(4 citation statements)

References 72 publications

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“…The frontal lobe is crucial for children’s social functioning, social cognition, and executive functions, and abnormal CBF values in this region may affect these functions. This is consistent with previous studies, such as those showing ASD patients have social barriers, and a positive correlation between ABC language scores and CBF in the inferior frontal gyrus, indicating potential functional abnormalities or abnormal social tendencies in this area ( Wilcox et al, 2002 ; Ye et al, 2022 ). However, we also noted inconsistencies with previous research.…”

Section: Discussionsupporting

confidence: 93%

Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics

Liu,

Yu,

et al. 2024

Front. Neurosci.

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IntroductionAutism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in motor skills, communication, emotional expression, and social interaction. Accurate diagnosis of ASD remains challenging due to the reliance on subjective behavioral observations and assessment scales, lacking objective diagnostic indicators.MethodsIn this study, we introduced a novel approach for diagnosing ASD, leveraging T1-based gray matter and ASL-based cerebral blood flow network metrics. Thirty preschool-aged patients with ASD and twenty-two typically developing (TD) individuals were enrolled. Brain network features, including gray matter and cerebral blood flow metrics, were extracted from both T1-weighted magnetic resonance imaging (MRI) and ASL images. Feature selection was performed using statistical t-tests and Minimum Redundancy Maximum Relevance (mRMR). A machine learning model based on random vector functional link network was constructed for diagnosis.ResultsThe proposed approach demonstrated a classification accuracy of 84.91% in distinguishing ASD from TD. Key discriminating network features were identified in the inferior frontal gyrus and superior occipital gyrus, regions critical for social and executive functions in ASD patients.DiscussionOur study presents an objective and effective approach to the clinical diagnosis of ASD, overcoming the limitations of subjective behavioral observations. The identified brain network features provide insights into the neurobiological mechanisms underlying ASD, potentially leading to more targeted interventions.

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Section: Discussionsupporting

confidence: 93%

Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics

Liu,

Yu,

et al. 2024

Front. Neurosci.

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“…Subsequent studies have consistently identified decreased perfusion in multiple brain regions in patients with ASD, including the left frontal lobe, bilateral temporal and parietal lobes, fusiform gyrus, medial prefrontal cortex, and anterior cingulate gyrus (Mountz et al, 1995;Ohnishi et al, 2000;Zilbovicius et al, 2000;Fang et al, 2014;Yerys et al, 2018;Ye et al, 2022). Notably, the CBF in the bilateral occipital lobes was found to be negatively correlated with Autism Behavior Checklist scores in the social and autonomy domains, while the CBF in the left frontal, parietal, and temporal lobes showed a positive correlation with scores in the body, object, and language domains (Ye et al, 2022). Indicating CBF alterations in specific brain regions could potentially serve as a biomarker of disease severity in patients with ASD.…”

Section: Cerebrovascular Deficits In Autism Spectrum Disordersmentioning

confidence: 99%

Neurovascular crosstalk and cerebrovascular alterations: an underestimated therapeutic target in autism spectrum disorders

Wang,

Yu,

2023

Front. Cell. Neurosci.

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Normal brain development, function, and aging critically depend on unique characteristics of the cerebrovascular system. Growing evidence indicated that cerebrovascular defects can have irreversible effects on the brain, and these defects have been implicated in various neurological disorders, including autism spectrum disorder (ASD). ASD is a neurodevelopmental disorder with heterogeneous clinical manifestations and anatomical changes. While extensive research has focused on the neural abnormalities underlying ASD, the role of brain vasculature in this disorder remains poorly understood. Indeed, the significance of cerebrovascular contributions to ASD has been consistently underestimated. In this work, we discuss the neurovascular crosstalk during embryonic development and highlight recent findings on cerebrovascular alterations in individuals with ASD. We also discuss the potential of vascular-based therapy for ASD. Collectively, these investigations demonstrate that ASD can be considered a neurovascular disease.

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“…The inclusion criteria for the normal control group were as follows: ① age 2–24 months; ② no abnormalities in the cranial MR imaging results and quality of the MRI scan images meeting the diagnostic requirements; ③ normal Gesell scores; and ④ preterm infants with hypoxic-ischemic encephalopathy, hyperbilirubinemia, CHD, congenital craniocerebral malformation, congenital infectious diseases, chromosomal diseases, or congenital genetic metabolic diseases. This study used the Gesell to measure the Gesell development quotient (DQ) of the subjects in both groups [ 14 ]. Approval for this study was obtained from our institutional ethics committee, and informed consent was obtained from the parents or guardians.…”

Section: Methodsmentioning

confidence: 99%

Quantitative assessment of preoperative brain development in pediatric congenital heart disease patients by synthetic MRI

Xu,

Ma,

Zhang

et al. 2024

Insights Imaging

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Objectives This study investigated the quantitative assessment and application of Synthetic MRI (SyMRI) for preoperative brain development in children with congenital heart disease (CHD). Methods Forty-three CHD patients aged 2–24 months were prospectively included in the observation group, and 43 healthy infants were included in the control group. The SyMRI scans were processed by postprocessing software to obtain T1, T2, and PD maps. The values of T1, T2, and PD in different brain regions were compared with the scores of the five ability areas of the Gesell Development Scale by Pearson correlation analysis. Results In the observation group, the T1 values of the posterior limb of the internal capsule (PLIC), Optic radiation (PTR), cerebral peduncle, centrum semiovale, occipital white matter, temporal white matter, and dentate nucleus were greater than those in the control group. In the observation group, the T2 values of the PLIC, PTR, frontal white matter, occipital white matter, temporal white matter, and dentate nucleus were greater than those in the control group. Pearson correlation analysis revealed that the observation group had significantly lower Development Scale scores. In the observation group, the T2 value of the splenium of the corpus callosum was significantly positively correlated with the personal social behavior score. The AUCs for diagnosing preoperative brain developmental abnormalities in children with CHD using T1 values of the temporal white matter and dentate nucleus were both greater than 0.60. Conclusions Quantitative assessment using SyMRI can aid in the early detection of preoperative brain development abnormalities in children with CHD. Critical relevance statement T1 and T2 relaxation values from SyMRI can be considered as a quantitative imaging marker to detect abnormalities, allowing for early clinical evaluation and timely intervention, thereby reducing neurodevelopmental disorders in these children. Key Points T1 and T2 relaxation values by SyMRI are related to myelin development. Evaluated development quotient markers were lower in the observation compared to the control group. SyMRI can act as a reference indicator for brain development in CHD children. Graphical Abstract

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Application of pseudocontinuous arterial spin labeling perfusion imaging in children with autism spectrum disorders

Cited by 5 publications

References 72 publications

Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics

Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics

Neurovascular crosstalk and cerebrovascular alterations: an underestimated therapeutic target in autism spectrum disorders

Quantitative assessment of preoperative brain development in pediatric congenital heart disease patients by synthetic MRI

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