对比增强与非对比MRI图像脑容量测量的比较分析。

IF 2.5 4区医学 Q3 NEUROSCIENCES

Neuroscience Letters Pub Date : 2025-02-06 DOI:10.1016/j.neulet.2025.138118

Aniket Aman , Aaryaman Hoskote , Kshitij S. Jadhav , Bharat Aggarwal

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引用次数: 0

摘要

背景：临床脑MRI扫描，包括对比增强（CE-MR）图像，由于技术异质性，代表了神经科学研究未充分利用的资源。目的：评估CE-MR扫描与非对比MR （NC-MR）扫描在正常人中形态测量的可靠性。方法：使用CAT12和SynthSeg + 分割工具对59名正常参与者（年龄21-73 岁）的t1加权CE-MR和NC-MR扫描进行比较。分析了体积测量和年龄预测效果。结果：SynthSeg + 在CE-MR和NC-MR扫描之间对大多数脑结构显示出高可靠性（ICCs > 0.90），脑脊液和心室容积存在差异。CAT12表现不一致。使用SynthSeg + 的年龄预测模型对两种扫描类型产生了可比较的结果。结论：SynthSeg + 等基于深度学习的方法可以可靠地处理CE-MR扫描进行形态计量分析，有可能扩大临床获得的CE-MR图像在神经影像学研究中的应用。

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Comparative analysis of brain volumetric measurements between contrast-enhanced and non-contrast MRI images

Background

Clinical brain MRI scans, including contrast-enhanced (CE-MR) images, represent an underutilized resource for neuroscience research due to technical heterogeneity.

Purpose

To evaluate the reliability of morphometric measurements from CE-MR scans compared to non-contrast MR (NC-MR) scans in normal individuals.

Methods

T1-weighted CE-MR and NC-MR scans from 59 normal participants (aged 21–73 years) were compared using CAT12 and SynthSeg+ segmentation tools. Volumetric measurements and age prediction efficacy were analyzed.

Results

SynthSeg+ demonstrated high reliability (ICCs > 0.90) for most brain structures between CE-MR and NC-MR scans, with discrepancies in CSF and ventricular volumes. CAT12 showed inconsistent performance. Age prediction models using SynthSeg + yielded comparable results for both scan types.

Conclusion

Deep learning-based approaches like SynthSeg+ can reliably process CE-MR scans for morphometric analysis, potentially broadening the application of clinically acquired CE-MR images in neuroimaging research.

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来源期刊

Neuroscience Letters 医学-神经科学

CiteScore

5.20

自引率

0.00%

发文量

408

审稿时长

50 days

期刊介绍： Neuroscience Letters is devoted to the rapid publication of short, high-quality papers of interest to the broad community of neuroscientists. Only papers which will make a significant addition to the literature in the field will be published. Papers in all areas of neuroscience - molecular, cellular, developmental, systems, behavioral and cognitive, as well as computational - will be considered for publication. Submission of laboratory investigations that shed light on disease mechanisms is encouraged. Special Issues, edited by Guest Editors to cover new and rapidly-moving areas, will include invited mini-reviews. Occasional mini-reviews in especially timely areas will be considered for publication, without invitation, outside of Special Issues; these un-solicited mini-reviews can be submitted without invitation but must be of very high quality. Clinical studies will also be published if they provide new information about organization or actions of the nervous system, or provide new insights into the neurobiology of disease. NSL does not publish case reports.