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脑性瘫痪中扩散磁共振成像的挑战:一种识别白质通路的建议方法。

The Challenge of Diffusion Magnetic Resonance Imaging in Cerebral Palsy: A Proposed Method to Identify White Matter Pathways.

作者信息

Martinie Ophélie, Karan Philippe, Traverse Elodie, Mercier Catherine, Descoteaux Maxime, Robert Maxime T

机构信息

Centre for Interdisciplinary Research in Rehabilitation and Social Integration, Québec, QC G1M 2S8, Canada.

Department of Rehabilitation, Université Laval, Québec, QC G1V 0A6, Canada.

出版信息

Brain Sci. 2023 Sep 29;13(10):1386. doi: 10.3390/brainsci13101386.

DOI:10.3390/brainsci13101386
PMID:37891755
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10605121/
Abstract

Cerebral palsy (CP), a neuromotor disorder characterized by prenatal brain lesions, leads to white matter alterations and sensorimotor deficits. However, the CP-related diffusion neuroimaging literature lacks rigorous and consensual methodology for preprocessing and analyzing data due to methodological challenges caused by the lesion extent. Advanced methods are available to reconstruct diffusion signals and can update current advances in CP. Our study demonstrates the feasibility of analyzing diffusion CP data using a standardized and open-source pipeline. Eight children with CP (8-12 years old) underwent a single diffusion magnetic resonance imaging (MRI) session on a 3T scanner (Achieva 3.0T (TX), Philips Healthcare Medical Systems, Best, The Netherlands). Exclusion criteria were contraindication to MRI and claustrophobia. Anatomical and diffusion images were acquired. Data were corrected and analyzed using Tractoflow 2.3.0 version, an open-source and robust tool. The tracts were extracted with customized procedures based on existing atlases and freely accessed standardized libraries (ANTs, Scilpy). DTI, CSD, and NODDI metrics were computed for each tract. Despite lesion heterogeneity and size, we successfully reconstructed major pathways, except for a participant with a larger lesion. Our results highlight the feasibility of identifying and quantifying subtle white matter pathways. Ultimately, this will increase our understanding of the clinical symptoms to provide precision medicine and optimize rehabilitation.

摘要

脑瘫(CP)是一种以产前脑损伤为特征的神经运动障碍,会导致白质改变和感觉运动缺陷。然而,由于病变范围带来的方法学挑战,与CP相关的扩散神经影像学文献在数据预处理和分析方面缺乏严谨且一致的方法。目前已有先进的方法来重建扩散信号,并且可以更新CP领域的当前进展。我们的研究证明了使用标准化的开源流程分析CP扩散数据的可行性。八名CP儿童(8至12岁)在一台3T扫描仪(Achieva 3.0T (TX),飞利浦医疗保健公司,荷兰贝斯特)上进行了单次扩散磁共振成像(MRI)检查。排除标准为MRI禁忌证和幽闭恐惧症。采集了解剖图像和扩散图像。使用Tractoflow 2.3.0版本(一个开源且强大的工具)对数据进行校正和分析。根据现有的图谱和可免费访问的标准化库(ANTs、Scilpy),通过定制程序提取纤维束。计算每个纤维束的DTI、CSD和NODDI指标。尽管存在病变异质性和大小差异,但除了一名病变较大的参与者外,我们成功重建了主要通路。我们的结果突出了识别和量化细微白质通路的可行性。最终,这将增进我们对临床症状的理解,以提供精准医疗并优化康复治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/bb354b17e975/brainsci-13-01386-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/fab8e7f7cbc7/brainsci-13-01386-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/32d632d5ce09/brainsci-13-01386-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/a90c61121955/brainsci-13-01386-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/8bfd214ac7b3/brainsci-13-01386-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/68ebbafd7651/brainsci-13-01386-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/e94f351d5504/brainsci-13-01386-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/3433ca3ca2e2/brainsci-13-01386-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/65fc05c4982e/brainsci-13-01386-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/96f192db1eec/brainsci-13-01386-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/bb354b17e975/brainsci-13-01386-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/fab8e7f7cbc7/brainsci-13-01386-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/32d632d5ce09/brainsci-13-01386-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/a90c61121955/brainsci-13-01386-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/8bfd214ac7b3/brainsci-13-01386-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/68ebbafd7651/brainsci-13-01386-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/e94f351d5504/brainsci-13-01386-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/3433ca3ca2e2/brainsci-13-01386-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/65fc05c4982e/brainsci-13-01386-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/96f192db1eec/brainsci-13-01386-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/727e/10605121/bb354b17e975/brainsci-13-01386-g010.jpg

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What's new and what's next in diffusion MRI preprocessing.
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