Radiomics-Based Prediction of Long-Term Treatment Response of Vestibular Schwannomas Following Stereotactic Radiosurgery

医学 放射外科 前庭神经鞘瘤 无线电技术 接收机工作特性 磁共振成像 回顾性队列研究 前庭系统 队列 放射科 核医学 内科学 放射治疗
作者
Patrick Langenhuizen,Svetlana Zinger,Sieger Leenstra,Henricus P. M. Kunst,Jef J. S. Mulder,Patrick E. J. Hanssens,Peter H. N. de With,Jeroen B. Verheul
出处
期刊:Otology & Neurotology [Lippincott Williams & Wilkins]
卷期号:41 (10): e1321-e1327 被引量:20
标识
DOI:10.1097/mao.0000000000002886
摘要

Stereotactic radiosurgery (SRS) is one of the treatment modalities for vestibular schwannomas (VSs). However, tumor progression can still occur after treatment. Currently, it remains unknown how to predict long-term SRS treatment outcome. This study investigates possible magnetic resonance imaging (MRI)-based predictors of long-term tumor control following SRS.Retrospective cohort study.Tertiary referral center.Analysis was performed on a database containing 735 patients with unilateral VS, treated with SRS between June 2002 and December 2014. Using strict volumetric criteria for long-term tumor control and tumor progression, a total of 85 patients were included for tumor texture analysis.All patients underwent SRS and had at least 2 years of follow-up.Quantitative tumor texture features were extracted from conventional MRI scans. These features were supplied to a machine learning stage to train prediction models. Prediction accuracy, sensitivity, specificity, and area under the receiver operating curve (AUC) are evaluated.Gray-level co-occurrence matrices, which capture statistics from specific MRI tumor texture features, obtained the best prediction scores: 0.77 accuracy, 0.71 sensitivity, 0.83 specificity, and 0.93 AUC. These prediction scores further improved to 0.83, 0.83, 0.82, and 0.99, respectively, for tumors larger than 5 cm.Results of this study show the feasibility of predicting the long-term SRS treatment response of VS tumors on an individual basis, using MRI-based tumor texture features. These results can be exploited for further research into creating a clinical decision support system, facilitating physicians, and patients to select a personalized optimal treatment strategy.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
曲奇吐司完成签到,获得积分10
刚刚
动听鑫鹏发布了新的文献求助10
1秒前
1秒前
1秒前
2秒前
小丸子发布了新的文献求助30
2秒前
大力的丹亦完成签到,获得积分10
2秒前
3秒前
丘比特应助慕课魔芋采纳,获得10
3秒前
4秒前
浮游应助明理的依柔采纳,获得10
4秒前
千江有水完成签到,获得积分10
5秒前
CipherSage应助鳗鱼中心采纳,获得10
5秒前
6秒前
浅笑丶沫完成签到,获得积分10
6秒前
张真源完成签到 ,获得积分10
6秒前
viviya发布了新的文献求助10
7秒前
平淡映易发布了新的文献求助10
7秒前
7秒前
浮游应助动听鑫鹏采纳,获得10
8秒前
9秒前
Sonder完成签到 ,获得积分10
9秒前
无敌猫猫头完成签到,获得积分20
10秒前
耍酷的莫言完成签到,获得积分20
11秒前
Hello应助xiuxiu采纳,获得10
11秒前
11秒前
昆工完成签到 ,获得积分10
11秒前
12秒前
12秒前
斯文败类应助卷毛羊在忙采纳,获得10
12秒前
粉粉完成签到,获得积分10
13秒前
今后应助冷傲曼冬采纳,获得10
13秒前
赘婿应助nxdjmzm采纳,获得10
13秒前
13秒前
14秒前
周周完成签到,获得积分10
15秒前
鸿渐于陆完成签到,获得积分10
15秒前
半夏应助默默的冷荷采纳,获得10
17秒前
666发布了新的文献求助10
17秒前
高分求助中
(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
Zeolites: From Fundamentals to Emerging Applications 1500
Architectural Corrosion and Critical Infrastructure 1000
Early Devonian echinoderms from Victoria (Rhombifera, Blastoidea and Ophiocistioidea) 1000
2026国自然单细胞多组学大红书申报宝典 800
Research Handbook on Corporate Governance in China 800
Elgar Concise Encyclopedia of Polar Law 520
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 4906147
求助须知:如何正确求助?哪些是违规求助? 4183849
关于积分的说明 12991886
捐赠科研通 3950084
什么是DOI,文献DOI怎么找? 2166302
邀请新用户注册赠送积分活动 1184902
关于科研通互助平台的介绍 1091161