MRI features of responsible contacts in vascular compressive trigeminal neuralgia and prediction modeling

医学 三叉神经痛 接收机工作特性 神经血管束 分级(工程) 磁共振成像 逻辑回归 三叉神经 放射科 曲线下面积 外科 内科学 工程类 土木工程
作者
Yufei Zhao,Jianhua Chen,Rifeng Jiang,Xue Xu,Lin Lin,Yunjing Xue,Qing Duan
出处
期刊:Acta Radiologica [SAGE Publishing]
卷期号:63 (1): 100-109 被引量:7
标识
DOI:10.1177/0284185120983971
摘要

Multiple neurovascular contacts in patients with vascular compressive trigeminal neuralgia often challenge the diagnosis of responsible contacts.To analyze the magnetic resonance imaging (MRI) features of responsible contacts and establish a predictive model to accurately pinpoint the responsible contacts.Sixty-seven patients with unilateral trigeminal neuralgia were enrolled. A total of 153 definite contacts (45 responsible, 108 non-responsible) were analyzed for their MRI characteristics, including neurovascular compression (NVC) grading, distance from pons to contact (Dpons-contact), vascular origin of compressing vessels, diameter of vessel (Dvessel) and trigeminal nerve (Dtrigeminal nerve) at contact. The MRI characteristics of the responsible and non-responsible contacts were compared, and their diagnostic efficiencies were further evaluated using a receiver operating characteristic (ROC) curve. The significant MRI features were incorporated into the logistics regression analysis to build a predictive model for responsible contacts.Compared with non-responsible contacts, NVC grading and arterial compression ratio (84.44%) were significantly higher, Dpons-contact was significantly lower at responsible contacts (P < 0.001, 0.002, and 0.033, respectively). NVC grading had a highest diagnostic area under the ROC curve (AUC) of 0.742, with a sensitivity of 64.44% and specificity of 75.00%. The logistic regression model showed a higher diagnostic efficiency, with an AUC of 0.808, sensitivity of 88.89%, and specificity of 62.04%.Contact degree and position are important MRI features in identifying the responsible contacts of the trigeminal neuralgia. The logistic predictive model based on Dpons-contact, NVC grading, and vascular origin can qualitatively improve the prediction of responsible contacts for radiologists.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
碳烤小肥肠完成签到,获得积分10
1秒前
2秒前
王乐乐哈完成签到 ,获得积分10
2秒前
2秒前
2秒前
Jason完成签到 ,获得积分10
2秒前
Chnp完成签到,获得积分10
4秒前
野性的颜演完成签到,获得积分10
4秒前
4秒前
厘米发布了新的文献求助10
5秒前
BaronR完成签到,获得积分10
6秒前
健康的雁凡完成签到,获得积分10
7秒前
Chnp发布了新的文献求助10
7秒前
蟑先生发布了新的文献求助10
7秒前
cocopan发布了新的文献求助10
7秒前
泡泡糖完成签到,获得积分10
9秒前
xiatian发布了新的文献求助10
11秒前
正经大善人完成签到,获得积分10
12秒前
lemon完成签到 ,获得积分10
16秒前
断水断粮的科研民工完成签到,获得积分10
16秒前
mu完成签到,获得积分10
18秒前
壮壮不爱吃肉完成签到,获得积分10
19秒前
19秒前
tian完成签到,获得积分10
19秒前
安详的海风完成签到,获得积分10
19秒前
有话好好说完成签到 ,获得积分10
19秒前
dejavu完成签到,获得积分10
20秒前
xiatian完成签到,获得积分10
22秒前
23秒前
wbbb完成签到,获得积分10
23秒前
结草兹发布了新的文献求助10
23秒前
丰富语蕊应助mu采纳,获得50
24秒前
24秒前
feiyang完成签到 ,获得积分10
28秒前
科研通AI6.3应助枫华采纳,获得10
29秒前
皮皮虾完成签到,获得积分10
29秒前
厘米完成签到,获得积分20
29秒前
大头雪糕完成签到 ,获得积分10
29秒前
keyanyu完成签到 ,获得积分10
30秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
The Redesign of International Investment Contracts 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7537328
求助须知:如何正确求助?哪些是违规求助? 9122200
关于积分的说明 19486554
捐赠科研通 7135274
什么是DOI,文献DOI怎么找? 3257570
关于科研通互助平台的介绍 2424938
邀请新用户注册赠送积分活动 2245553