利用 CT 成像计算脑室与蛛网膜下腔容积比,自动检测正常压力脑积水。

Jacob J Knittel, Justin L Hoskin, Dylan J Hoyt, Jonathan A Abdo, Emily L Foldes, Molly M McElvogue, Clay M Oliver, Daniel A Keesler, Terry D Fife, F David Barranco, Kris A Smith, J Gordon McComb, Matthew T Borzage, Kevin S King
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引用次数: 0

摘要

背景与目的:常压性脑积水(NPH)是一种诊断难题,因为其临床症状和影像学表现与正常衰老和其他形式的痴呆相似。识别NPH至关重要,这样患者才能及时接受治疗,改善步态扭曲和生活质量。开发了一种NPH的自动标记物,并在临床CT图像上进行了评估,并在大型患者队列中评估了其效用。材料与方法:回顾性分析2015年1月至2022年1月306例tap检测应答的NPH患者的CT图像。对照CT图像来自于2021年6月至2022年8月期间在急诊科接受头痛评估且CT表现不明显的患者。脑室与蛛网膜下腔体积比(VSR)由成像软件自动计算,并在调整年龄和性别的线性回归模型中用作NPH的预测因子。计算VSR与年龄、性别和受者操作特征的相关性。结果:NPH患者的VSR显著高于对照组(P < 0.001)。重要的是,VSR与年龄无显著相关(P = 0.56, R2 = 0.001)。VSR鉴别NPH的灵敏度和特异度分别为94.1%和92.5%,受试者工作特征曲线下面积为0.99 (95% CI 0.975 ~ 0.995)。结论:头部CT图像上VSR的自动评估识别可能的NPH准确率为93%。对一大批NPH患者的评估支持CT图像临床筛查的普遍性。此外,结果支持脑室-脑沟一致性的效用,放射科医生经常使用,但目前还不是NPH成像标记的公认指南的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Detection of Normal Pressure Hydrocephalus Using CT Imaging for Calculating the Ventricle-to-Subarachnoid Volume Ratio.

Background and purpose: Normal pressure hydrocephalus (NPH) is a diagnostic challenge because its clinical symptoms and imaging appearance resemble normal aging and other forms of dementia. Identifying NPH is essential so that patients can receive timely treatment to improve gait distortion and quality of life. An automated marker of NPH was developed and evaluated on clinical CT images, and its utility was assessed in a large patient cohort.

Materials and methods: A retrospective review was conducted of CT images from 306 tap test-responsive patients with NPH between January 2015 and January 2022. Control CT images were obtained from patients in the emergency department who were evaluated for headache and had unremarkable CT findings between June 2021 and August 2022. The ventricle-to-subarachnoid volume ratio (VSR) was automatically calculated by the imaging software and used as a predictor of NPH in linear regression modeling with adjustment for age and sex. The correlations of VSR with age, sex, and the receiver operating characteristic were computed.

Results: VSR was significantly greater in patients with NPH than controls (P < .001). Importantly, VSR was not significantly correlated with age (P = .56, R2 = 0.001). VSR identifies NPH with a sensitivity and specificity of 94.1% and 92.5%, respectively, with an area under the receiver operating characteristic curve of 0.99 (95% CI 0.975-0.995).

Conclusions: Automated assessment of the VSR on head CT images identified probable NPH with 93% accuracy. The assessment of a large cohort of patients with NPH supports the generalizability of clinical screening of CT images. Moreover, the results support the utility of ventricle-to-sulcal concordance often used by radiologists but not currently a part of the accepted guidelines for imaging markers of NPH.

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