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扩散放射组学在自闭症谱系障碍中的亚型和聚类分析:一项临床前研究。

Diffusion radiomics for subtyping and clustering in autism spectrum disorder: A preclinical study.

机构信息

Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA.; Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA; Graduate Program in Cellular and Molecular Biology, University of Wisconsin-Madison, Madison, WI 53706, USA.

Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA.

出版信息

Magn Reson Imaging. 2023 Feb;96:116-125. doi: 10.1016/j.mri.2022.12.003. Epub 2022 Dec 7.

Abstract

Autism spectrum disorder (ASD) is a highly prevalent, heterogenous neurodevelopmental disorder. Neuroimaging methods such as functional, structural, and diffusion MRI have been used to identify candidate imaging biomarkers for ASD, but current findings remain non-specific and likely arise from the heterogeneity present in ASD. To account for this, efforts to subtype ASD have emerged as a potential strategy for both the study of ASD and advancement of tailored behavioral therapies and therapeutics. Towards these ends, to improve upon current neuroimaging methods, we propose combining biologically sensitive neurite orientation dispersion and density index (NODDI) diffusion MR imaging with radiomics image processing to create a new methodological approach that, we hypothesize, can sensitively and specifically capture neurobiology. We demonstrate this method can sensitively distinguish differences between four genetically distinct rat models of ASD (Fmr1, Pten, Nrxn1, Disc1). Further, we demonstrate diffusion radiomic analyses hold promise for subtyping in ASD as we show unsupervised clustering of NODDI radiomic data generates clusters specific to the underlying genetic differences between the animal models. Taken together, our findings suggest the unique application of radiomic analysis on NODDI diffusion MRI may have the capacity to sensitively and specifically disambiguate the neurobiological heterogeneity present in the ASD population.

摘要

自闭症谱系障碍 (ASD) 是一种高度流行的、异质的神经发育障碍。功能、结构和扩散 MRI 等神经影像学方法已被用于确定 ASD 的候选影像学生物标志物,但目前的发现仍然不具有特异性,可能源于 ASD 中的异质性。为了解决这个问题,对 ASD 进行亚型分类的努力已经成为研究 ASD 以及推进针对行为的治疗方法和治疗的一种潜在策略。为此,为了改进当前的神经影像学方法,我们提出将对神经具有敏感性的神经丝取向分散和密度指数 (NODDI) 扩散 MRI 与放射组学图像处理相结合,创建一种新的方法,我们假设该方法可以敏感而具体地捕捉神经生物学。我们证明该方法可以敏感地区分四种不同遗传 ASD 大鼠模型(Fmr1、Pten、Nrxn1、Disc1)之间的差异。此外,我们证明扩散放射组学分析有望对 ASD 进行分类,因为我们表明,NODDI 放射组学数据的无监督聚类可以生成特定于动物模型之间潜在遗传差异的聚类。总之,我们的研究结果表明,在 NODDI 扩散 MRI 上进行放射组学分析的独特应用可能具有区分 ASD 人群中存在的神经生物学异质性的敏感性和特异性。

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本文引用的文献

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Diffusion-Weighted Imaging: Recent Advances and Applications.弥散加权成像:最新进展与应用。
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