Dekhil Omar, Ali Mohamed, El-Nakieb Yaser, Shalaby Ahmed, Soliman Ahmed, Switala Andrew, Mahmoud Ali, Ghazal Mohammed, Hajjdiab Hassan, Casanova Manuel F, Elmaghraby Adel, Keynton Robert, El-Baz Ayman, Barnes Gregory
Bioimaging Lab, Bioengineering Department, University of Louisville, Louisville, KY, United States.
Department of Electrical and Computer Engineering, Abu Dhabi University, Abu Dhabi, United Arab Emirates.
Front Psychiatry. 2019 Jul 4;10:392. doi: 10.3389/fpsyt.2019.00392. eCollection 2019.
Autism spectrum disorder is a neuro-developmental disorder that affects the social abilities of the patients. Yet, the gold standard of autism diagnosis is the autism diagnostic observation schedule (ADOS). In this study, we are implementing a computer-aided diagnosis system that utilizes structural MRI (sMRI) and resting-state functional MRI (fMRI) to demonstrate that both anatomical abnormalities and functional connectivity abnormalities have high prediction ability of autism. The proposed system studies how the anatomical and functional connectivity metrics provide an overall diagnosis of whether the subject is autistic or not and are correlated with ADOS scores. The system provides a personalized report per subject to show what areas are more affected by autism-related impairment. Our system achieved accuracies of 75% when using fMRI data only, 79% when using sMRI data only, and 81% when fusing both together. Such a system achieves an important next step towards delineating the neurocircuits responsible for the autism diagnosis and hence may provide better options for physicians in devising personalized treatment plans.
自闭症谱系障碍是一种影响患者社交能力的神经发育障碍。然而，自闭症诊断的金标准是自闭症诊断观察量表（ADOS）。在本研究中，我们正在实施一种计算机辅助诊断系统，该系统利用结构磁共振成像（sMRI）和静息态功能磁共振成像（fMRI）来证明解剖学异常和功能连接异常都具有很高的自闭症预测能力。所提出的系统研究解剖学和功能连接指标如何提供对受试者是否患有自闭症的全面诊断，以及它们与ADOS评分的相关性。该系统为每个受试者提供个性化报告，以显示哪些区域受自闭症相关损伤的影响更大。我们的系统仅使用fMRI数据时准确率为75%，仅使用sMRI数据时准确率为79%，两者融合时准确率为81%。这样一个系统朝着描绘负责自闭症诊断的神经回路迈出了重要的下一步，因此可能为医生制定个性化治疗方案提供更好的选择。
