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Updated: Sep 16, 2025

Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure

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从临床获得的大脑MRI中确定儿科神经成像研究的"临床对照"的系统协议

Dabriel Zimmerman^1,2,3, Ayan S Mandal^1,2,3, Benjamin Jung^1,2,3

¹Department of Child and Adolescent Psychiatry and Behavioral Science Children's Hospital of Philadelphia, Philadelphia, PA.

bioRxiv : the preprint server for biology

|July 9, 2025

概括

我们开发了一种协议,使用人工智能辅助审查从临床档案中识别健康儿科大脑MRI扫描. 这种方法有助于为神经发育研究建立更大,更多样化的数据集.

科学领域:

儿科神经成像儿童神经成像
人工智能的人工智能
医疗信息学医疗信息学

背景情况:

儿科神经成像研究需要大量,多样化的数据集,以进行强大的AI模型开发.
临床大脑MRI档案代表了一个巨大的,未充分利用的研究资源.
现有的临床数据往往缺乏足够的表征以用于研究.

研究的目的:

来自临床档案的儿童脑部MRI扫描识别有限的成像病理学的系统协议.
为了使回顾性临床MRI数据用于神经发育研究的重新利用.
支持创建大型,可泛化的数据集,用于研究典型的大脑发育和神经遗传条件.

主要方法:

开发了一种用于放射学报告的机器辅助手动审查协议.
与专家神经放射学家和非临床医生的评分师一起实施了标准化的评分方案.
根据病理和图像质量进行分类扫描,以确定合适的对照.

主要成果:

该协议有助于识别"具有有限成像病理性的扫描".
这种方法可以利用大型的临床成像档案 (例如,在CHOP>250,000扫描).
能够解决人口偏见和增加研究中的样本大小.

结论:

该协议提供了一种可扩展和可靠的方法来识别临床对照脑MRI.
方便创建大型数据集,以提高神经成像研究中的可复制性.
支持大规模研究典型的大脑发育和神经遗传障碍.

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