界定前庭裂隙瘤的肿瘤生长:对比增强 T1 加权磁共振成像的容积观察者间变异性研究。

IF 2.4 3区 医学 Q2 CLINICAL NEUROLOGY Neuroradiology Pub Date : 2024-11-01 Epub Date: 2024-07-09 DOI:10.1007/s00234-024-03416-w
Stefan Cornelissen, Sammy M Schouten, Patrick P J H Langenhuizen, Suan Te Lie, Henricus P M Kunst, Peter H N de With, Jeroen B Verheul
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引用次数: 0

摘要

目的:对于前庭分裂瘤(VS)患者,越来越多地采用保守观察法。因此,准确可靠的肿瘤体积监测非常重要。目前,以肿瘤体积增加 20% 为临界值被广泛用于定义前庭神经分裂瘤的肿瘤生长。本研究通过观测者间的研究,探讨了肿瘤体积对 VS 体积测量的一致性限值(LoA)的依赖性:这项回顾性研究包括 100 名接受对比增强 T1 加权 MRI 检查的 VS 患者。五名观察者对图像进行了体积注释。观察者的一致性和可靠性是通过使用平均值一致性极限(LOAM)法估算的 LoA 和类内相关系数(ICC)来衡量的:100 名患者的平均肿瘤体积中位数为 903 立方毫米(IQR:193-3101)。根据肿瘤体积四分位数将患者分为四个体积大小类别。肿瘤体积最小的四分位数相对于平均值的LOAM值为26.8%(95% CI:23.7-33.6),而肿瘤体积最大的四分位数的LOAM值为7.3%(95% CI:6.5-9.7),排除瘤周囊肿后,LOAM值为4.8%(95% CI:6.5-9.7):结论:结论:VS 容积标注的一致性限值受肿瘤体积的影响,因为 LoA 会随着肿瘤体积的增大而提高。因此,与目前广泛使用的 20% 临界值相比,对于大于 200 立方毫米的肿瘤,可在较早阶段可靠地检测到生长。然而,对于非常小的肿瘤,在评估其生长时,应采用比以前认为的更高的一致性限值。
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Defining tumor growth in vestibular schwannomas: a volumetric inter-observer variability study in contrast-enhanced T1-weighted MRI.

Purpose: For patients with vestibular schwannomas (VS), a conservative observational approach is increasingly used. Therefore, the need for accurate and reliable volumetric tumor monitoring is important. Currently, a volumetric cutoff of 20% increase in tumor volume is widely used to define tumor growth in VS. The study investigates the tumor volume dependency on the limits of agreement (LoA) for volumetric measurements of VS by means of an inter-observer study.

Methods: This retrospective study included 100 VS patients who underwent contrast-enhanced T1-weighted MRI. Five observers volumetrically annotated the images. Observer agreement and reliability was measured using the LoA, estimated using the limits of agreement with the mean (LOAM) method, and the intraclass correlation coefficient (ICC).

Results: The 100 patients had a median average tumor volume of 903 mm3 (IQR: 193-3101). Patients were divided into four volumetric size categories based on tumor volume quartile. The smallest tumor volume quartile showed a LOAM relative to the mean of 26.8% (95% CI: 23.7-33.6), whereas for the largest tumor volume quartile this figure was found to be 7.3% (95% CI: 6.5-9.7) and when excluding peritumoral cysts: 4.8% (95% CI: 4.2-6.2).

Conclusion: Agreement limits within volumetric annotation of VS are affected by tumor volume, since the LoA improves with increasing tumor volume. As a result, for tumors larger than 200 mm3, growth can reliably be detected at an earlier stage, compared to the currently widely used cutoff of 20%. However, for very small tumors, growth should be assessed with higher agreement limits than previously thought.

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来源期刊
Neuroradiology
Neuroradiology 医学-核医学
CiteScore
5.30
自引率
3.60%
发文量
214
审稿时长
4-8 weeks
期刊介绍: Neuroradiology aims to provide state-of-the-art medical and scientific information in the fields of Neuroradiology, Neurosciences, Neurology, Psychiatry, Neurosurgery, and related medical specialities. Neuroradiology as the official Journal of the European Society of Neuroradiology receives submissions from all parts of the world and publishes peer-reviewed original research, comprehensive reviews, educational papers, opinion papers, and short reports on exceptional clinical observations and new technical developments in the field of Neuroimaging and Neurointervention. The journal has subsections for Diagnostic and Interventional Neuroradiology, Advanced Neuroimaging, Paediatric Neuroradiology, Head-Neck-ENT Radiology, Spine Neuroradiology, and for submissions from Japan. Neuroradiology aims to provide new knowledge about and insights into the function and pathology of the human nervous system that may help to better diagnose and treat nervous system diseases. Neuroradiology is a member of the Committee on Publication Ethics (COPE) and follows the COPE core practices. Neuroradiology prefers articles that are free of bias, self-critical regarding limitations, transparent and clear in describing study participants, methods, and statistics, and short in presenting results. Before peer-review all submissions are automatically checked by iThenticate to assess for potential overlap in prior publication.
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