新的眼动仪测量系统:自闭症谱系障碍早期诊断的价值

Raymond Kong Wang, Kenneth Kwong, Kevin Liu, Xue-Jun Kong
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引用次数: 0

摘要

背景眼动追踪(ET)正在成为自闭症谱系障碍(ASD)的一种有前途的早期客观筛查方法,但它需要更可靠、灵敏度和特异性更高的指标才能用于临床。方法本研究介绍了一套新型 ET 指标:兴趣区(AOI)转换计数(ASC)、沿自决路径的有利兴趣区转换(FAS)和兴趣区空缺计数(AVC)。这些指标适用于被诊断为 ASD 的幼儿和学龄前儿童。通过线性回归评估了这些新的 ET 指标与自闭症诊断观察表第二版(ADOS-2)评分之间的相关性。此外,还评估了预测诊断的临界分数的敏感性和特异性。结果我们的研究结果表明,在这个高危人群中,与非 ASD 儿童相比,ASD 儿童的 FAS 和 ASC 明显较低,而 AVC 则较高(P < 0.05)。总固定时间和瞳孔大小没有明显差异(P 0.05)。此外,FAS 与 ADOS-2 总分和社会情感 (SA) 分量表呈负相关(p < 0.05)。在这些新的 ET 指标中,AVC 的灵敏度(88%-100%)和特异度(80%-88%)最好,临界值为 0.305-0.306,其次是 FAS 和 ASC,可用于区分 ASD 和非 ASD 的诊断。结论这项研究证实了创新性 ET 指标 FAS、AVC 和 ASC 的实用性,它们的灵敏度和特异性都有显著提高,从而加强了 ASD 筛查和诊断过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New Eye Tracking Metrics System: The Value in Early Diagnosis of Autism Spectrum Disorder
Background Eye tracking (ET) is emerging as a promising early and objective screening method for autism spectrum disorders (ASD), but it requires more reliable metrics with enhanced sensitivity and specificity for clinical use. Methods This study introduces a suite of novel ET metrics: Area of Interest (AOI) Switch Counts (ASC), Favorable AOI Shifts (FAS) along self-determined pathways, and AOI Vacancy Counts (AVC). These metrics were applied to toddlers and preschoolers diagnosed with ASD. The correlation between these new ET metrics and Autism Diagnostic Observation Schedule, Second Edition (ADOS-2) scores was assessed using linear regression. Sensitivity and specificity of the cut-off scores were also evaluated to predict diagnosis. Results Our findings indicate significantly lower FAS and ASC and higher AVC (P < 0.05) in children with ASD compared to their non-ASD counterparts within this high-risk cohort. There were no significant differences in total fixation time or pupil size (p > 0.05). Additionally, FAS was negatively correlated with ADOS-2 total scores and the social affect (SA) subscale (p < 0.05). Among these new ET metrics, AVC yielded the best sensitivity (88-100%) and specificity (80-88%) with a cut-off score of 0.305-0.306, followed by FAS and ASC for distinguishing ASD from non-ASD for diagnosis. Conclusions This study confirms the utility of innovative ET metrics FAS, AVC, and ASC, which exhibit markedly improved sensitivity and specificity, enhancing ASD screening and diagnostic processes.
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