Autosomal recessive cerebellar ataxias: a diagnostic classification approach according to ocular features

IF 2.6 3区 医学 Q2 BEHAVIORAL SCIENCES
Diego Lopergolo, Francesca Rosini, Elena Pretegiani, Alessia Bargagli, Valeria Serchi, Alessandra Rufa
{"title":"Autosomal recessive cerebellar ataxias: a diagnostic classification approach according to ocular features","authors":"Diego Lopergolo, Francesca Rosini, Elena Pretegiani, Alessia Bargagli, Valeria Serchi, Alessandra Rufa","doi":"10.3389/fnint.2023.1275794","DOIUrl":null,"url":null,"abstract":"Autosomal recessive cerebellar ataxias (ARCAs) are a heterogeneous group of neurodegenerative disorders affecting primarily the cerebellum and/or its afferent tracts, often accompanied by damage of other neurological or extra-neurological systems. Due to the overlap of clinical presentation among ARCAs and the variety of hereditary, acquired, and reversible etiologies that can determine cerebellar dysfunction, the differential diagnosis is challenging, but also urgent considering the ongoing development of promising target therapies. The examination of afferent and efferent visual system may provide neurophysiological and structural information related to cerebellar dysfunction and neurodegeneration thus allowing a possible diagnostic classification approach according to ocular features. While optic coherence tomography (OCT) is applied for the parametrization of the optic nerve and macular area, the eye movements analysis relies on a wide range of eye-tracker devices and the application of machine-learning techniques. We discuss the results of clinical and eye-tracking oculomotor examination, the OCT findings and some advancing of computer science in ARCAs thus providing evidence sustaining the identification of robust eye parameters as possible markers of ARCAs.","PeriodicalId":56016,"journal":{"name":"Frontiers in Integrative Neuroscience","volume":"99 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Integrative Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fnint.2023.1275794","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Autosomal recessive cerebellar ataxias (ARCAs) are a heterogeneous group of neurodegenerative disorders affecting primarily the cerebellum and/or its afferent tracts, often accompanied by damage of other neurological or extra-neurological systems. Due to the overlap of clinical presentation among ARCAs and the variety of hereditary, acquired, and reversible etiologies that can determine cerebellar dysfunction, the differential diagnosis is challenging, but also urgent considering the ongoing development of promising target therapies. The examination of afferent and efferent visual system may provide neurophysiological and structural information related to cerebellar dysfunction and neurodegeneration thus allowing a possible diagnostic classification approach according to ocular features. While optic coherence tomography (OCT) is applied for the parametrization of the optic nerve and macular area, the eye movements analysis relies on a wide range of eye-tracker devices and the application of machine-learning techniques. We discuss the results of clinical and eye-tracking oculomotor examination, the OCT findings and some advancing of computer science in ARCAs thus providing evidence sustaining the identification of robust eye parameters as possible markers of ARCAs.
常染色体隐性遗传小脑性共济失调:根据眼部特征的诊断分类方法
常染色体隐性遗传小脑共济失调症(ARCA)是一组异质性神经退行性疾病,主要影响小脑和/或其传入束,通常伴有其他神经系统或神经系统外的损害。由于 ARCAs 的临床表现相互重叠,而且可导致小脑功能障碍的遗传性、获得性和可逆性病因多种多样,因此鉴别诊断极具挑战性,但考虑到目前正在开发前景广阔的靶向疗法,鉴别诊断也迫在眉睫。对传入和传出视觉系统的检查可提供与小脑功能障碍和神经变性有关的神经生理学和结构信息,从而可根据眼部特征进行诊断分类。光学相干断层扫描(OCT)可用于视神经和黄斑区的参数化,而眼球运动分析则依赖于各种眼球跟踪器设备和机器学习技术的应用。我们讨论了临床和眼动跟踪检查的结果、OCT 的发现以及计算机科学在 ARCA 方面的一些进展,从而为确定稳健的眼球参数作为 ARCA 的可能标记提供了证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Frontiers in Integrative Neuroscience
Frontiers in Integrative Neuroscience Neuroscience-Cellular and Molecular Neuroscience
CiteScore
4.60
自引率
2.90%
发文量
148
审稿时长
14 weeks
期刊介绍: Frontiers in Integrative Neuroscience publishes rigorously peer-reviewed research that synthesizes multiple facets of brain structure and function, to better understand how multiple diverse functions are integrated to produce complex behaviors. Led by an outstanding Editorial Board of international experts, this multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide. Our goal is to publish research related to furthering the understanding of the integrative mechanisms underlying brain functioning across one or more interacting levels of neural organization. In most real life experiences, sensory inputs from several modalities converge and interact in a manner that influences perception and actions generating purposeful and social behaviors. The journal is therefore focused on the primary questions of how multiple sensory, cognitive and emotional processes merge to produce coordinated complex behavior. It is questions such as this that cannot be answered at a single level – an ion channel, a neuron or a synapse – that we wish to focus on. In Frontiers in Integrative Neuroscience we welcome in vitro or in vivo investigations across the molecular, cellular, and systems and behavioral level. Research in any species and at any stage of development and aging that are focused at understanding integration mechanisms underlying emergent properties of the brain and behavior are welcome.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信