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基于神经网络预测模型的成像中预测放射性曝光时间的研究

Hanghui Hu¹, Jian Zhang², Shuyu Xie¹

¹The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China; Guangxi Hospital Division of The First Affitiated Hospital, Sun Yat-sen University, China.

Clinical neurology and neurosurgery

|January 28, 2025

概括

解剖学和临床因素,如高血压和大动脉门直径显著影响辐射动脉脑血管学暴露时间. 神经网络模型准确地预测了这些持续时间,有助于程序优化.

科学领域:

放射学放射学是一门学科.
医疗成像医学成像
血管干预血管干预

背景情况:

通过辐射动脉进行脑血管造影是一种常见的程序.
优化放射性曝光时间对于患者的安全和图像质量至关重要.

研究的目的:

为了确定放射性动脉脑血管学中放射性暴露持续时间的解剖学和临床预测因素.
在此过程中开发光镜时间的预测模型.

主要方法:

对210名接受放射性动脉脑血管造影的患者的分析.
评估解剖学 (例如,大动脉门直径,无名动脉尺寸) 和临床 (例如高血压) 因素.
神经网络预测模型的开发和验证.

主要成果:

高血压,双关节下关节 - 冠状动脉曲线,以及近邻左常见动脉循环增加了光镜时间.
年龄,大动脉门直径,无名动脉宽度,以及其与大动脉门的角度与光镜时间正相关.
匿名动脉长度与光镜时间呈负相关性. 神经网络模型在训练组中达到80.0%的准确性,在测试组中达到76.9%的准确性 (AUC=0.821).

结论:

几种解剖学变异和临床因素在辐射动脉脑血管造影期间显著影响光镜时间.
结合这些因素的预测模型在估计暴露时间方面表现出很好的准确性.

关键词:

大脑血管造影 - - 大脑血管造影剖析剖析分解跨辐射的方法.血管解剖学血管解剖学

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X-ray Imaging

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