Computational Fractal-Based Analysis of MR Susceptibility-Weighted Imaging (SWI) in Neuro-Oncology and Neurotraumatology.

Q3 Neuroscience Advances in neurobiology Pub Date : 2024-01-01 DOI:10.1007/978-3-031-47606-8_23
Antonio Di Ieva
{"title":"Computational Fractal-Based Analysis of MR Susceptibility-Weighted Imaging (SWI) in Neuro-Oncology and Neurotraumatology.","authors":"Antonio Di Ieva","doi":"10.1007/978-3-031-47606-8_23","DOIUrl":null,"url":null,"abstract":"<p><p>Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique able to depict the magnetic susceptibility produced by different substances, such as deoxyhemoglobin, calcium, and iron. The main application of SWI in clinical neuroimaging is detecting microbleedings and venous vasculature. Quantitative analyses of SWI have been developed over the last few years, aimed to offer new parameters, which could be used as neuroimaging biomarkers. Each technique has shown pros and cons, but no gold standard exists yet. The fractal dimension (FD) has been investigated as a novel potential objective parameter for monitoring intratumoral space-filling properties of SWI patterns. We showed that SWI patterns found in different tumors or different glioma grades can be represented by a gradient in the fractal dimension, thereby enabling each tumor to be assigned a specific SWI fingerprint. Such results were especially relevant in the differentiation of low-grade versus high-grade gliomas, as well as from high-grade gliomas versus lymphomas.Therefore, FD has been suggested as a potential image biomarker to analyze intrinsic neoplastic architecture in order to improve the differential diagnosis within clinical neuroimaging, determine appropriate therapy, and improve outcome in patients.These promising preliminary findings could be extended into the field of neurotraumatology, by means of the application of computational fractal-based analysis for the qualitative and quantitative imaging of microbleedings in traumatic brain injury patients. In consideration of some evidences showing that SWI signals are correlated with trauma clinical severity, FD might offer some objective prognostic biomarkers.In conclusion, fractal-based morphometrics of SWI could be further investigated to be used in a complementary way with other techniques, in order to form a holistic understanding of the temporal evolution of brain tumors and follow-up response to treatment, with several further applications in other fields, such as neurotraumatology and cerebrovascular neurosurgery as well.</p>","PeriodicalId":7360,"journal":{"name":"Advances in neurobiology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in neurobiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-031-47606-8_23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Neuroscience","Score":null,"Total":0}
引用次数: 0

Abstract

Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique able to depict the magnetic susceptibility produced by different substances, such as deoxyhemoglobin, calcium, and iron. The main application of SWI in clinical neuroimaging is detecting microbleedings and venous vasculature. Quantitative analyses of SWI have been developed over the last few years, aimed to offer new parameters, which could be used as neuroimaging biomarkers. Each technique has shown pros and cons, but no gold standard exists yet. The fractal dimension (FD) has been investigated as a novel potential objective parameter for monitoring intratumoral space-filling properties of SWI patterns. We showed that SWI patterns found in different tumors or different glioma grades can be represented by a gradient in the fractal dimension, thereby enabling each tumor to be assigned a specific SWI fingerprint. Such results were especially relevant in the differentiation of low-grade versus high-grade gliomas, as well as from high-grade gliomas versus lymphomas.Therefore, FD has been suggested as a potential image biomarker to analyze intrinsic neoplastic architecture in order to improve the differential diagnosis within clinical neuroimaging, determine appropriate therapy, and improve outcome in patients.These promising preliminary findings could be extended into the field of neurotraumatology, by means of the application of computational fractal-based analysis for the qualitative and quantitative imaging of microbleedings in traumatic brain injury patients. In consideration of some evidences showing that SWI signals are correlated with trauma clinical severity, FD might offer some objective prognostic biomarkers.In conclusion, fractal-based morphometrics of SWI could be further investigated to be used in a complementary way with other techniques, in order to form a holistic understanding of the temporal evolution of brain tumors and follow-up response to treatment, with several further applications in other fields, such as neurotraumatology and cerebrovascular neurosurgery as well.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于计算分形的神经肿瘤学和神经创伤学磁共振加权成像 (SWI) 分析。
磁感应强度加权成像(SWI)是一种磁共振成像(MRI)技术,能够描述脱氧血红蛋白、钙和铁等不同物质产生的磁感应强度。SWI 在临床神经成像中的主要应用是检测微出血和静脉血管。过去几年中,SWI 定量分析技术不断发展,旨在提供可用作神经影像生物标记的新参数。每种技术都各有利弊,但目前还没有金标准。分形维度(FD)作为一种新的潜在客观参数被研究用于监测SWI模式的瘤内空间填充特性。我们发现,在不同肿瘤或不同胶质瘤分级中发现的 SWI 模式可以用分形维度的梯度来表示,从而使每个肿瘤都能被赋予特定的 SWI 指纹。因此,分形维度被认为是一种潜在的图像生物标记,可用于分析肿瘤的内在结构,从而改善临床神经影像学的鉴别诊断,确定适当的治疗方法,并改善患者的预后。这些前景广阔的初步研究结果可扩展到神经创伤学领域,通过应用基于分形的计算分析,对脑外伤患者的微出血进行定性和定量成像。总之,可以进一步研究基于分形的 SWI 形态计量学,以便与其他技术互补使用,从而对脑肿瘤的时间演变和后续治疗反应形成整体认识,并进一步应用于神经创伤学和脑血管神经外科等其他领域。
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 去求助
来源期刊
Advances in neurobiology
Advances in neurobiology Neuroscience-Neurology
CiteScore
2.80
自引率
0.00%
发文量
0
期刊最新文献
A Self-Similarity Logic May Shape the Organization of the Nervous System. Advances in Understanding Fractals in Affective and Anxiety Disorders. Analyzing Eye Paths Using Fractals. Box-Counting Fractal Analysis: A Primer for the Clinician. Clinical Sensitivity of Fractal Neurodynamics.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1