The Preoperative Diagnostic Value of MRI and Otoneural Tests in Acoustic Neuroma

Author:

Dai Qingqing,Zheng Meijun,Chen Qiurong,Zheng Hong,Li Bilan

Abstract

ObjectivesTo determine the preoperative diagnostic accuracy of MRI and otoneural tests (ONT) for acoustic neuroma (AN) in a cohort of unselected patients with pontocerebellar angle tumors. To find a convenient way to screening out the potential asymptomatic AN patient earlier.DesignThis diagnostic accuracy study was performed in a central hospital and included a consecutive sample of unilateral incipient pontocerebellar angle tumor patients referred for MRI and ONT before surgery. Different AN features of MRI and ONT were collected and concluded into preoperative diagnostic variables or variable combinations. Those of MRI and ONT are analyzed and compared with biopsy results by multivariable receiver operating characteristic (ROC) analysis. The early-stage group, the course of which is 1 year or less, was separately computed and compared.ResultsEighty-three subjects were collected from June 2013 to June 2019; 62 were confirmed AN postoperatively by biopsy, whereas others are not AN. The area under the curve (AUC) of MRI was 0.611, whereas the AUC of ONT was 0.708. In the early-stage group, the AUC of MRI was 0.539, and the AUC of ONT was 0.744.ConclusionsONT was able to identify more subjects affected by unilateral incipient AN than MRI preoperatively. Given that ONT is a functional test for internal auditory canal nerves, it is an optimal screening test for AN patients because it provides more information than MRI for the further clinical plan. It is particularly noteworthy for identifying asymptomatic AN patients and for early stage. Therefore, it may help more patients from unnessesary surgery. Furthermore, an MRI follow-up is suggested if the patient was found alert in ONT.

Funder

National Major Science and Technology Projects of China

Publisher

Frontiers Media SA

Subject

Cancer Research,Oncology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Acoustic neuroma classification algorithm based on mask region convolution neural network;Journal of Radiation Research and Applied Sciences;2024-03

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