Chang Yun Hwa, Kim Ha Youn, Yu In Kyu, Kwak Min Young
Department of Radiology, Eulji University Hospital, Eulji University College of Medicine, Daejeon, Korea.
Department of Otolaryngology-Head and Neck Surgery, Eulji University Hospital, Eulji University School of Medicine, Daejeon, Korea.
Medicine (Baltimore). 2025 Mar 14;104(11):e41880. doi: 10.1097/MD.0000000000041880.
Endolymphatic hydrops (EH) has been visualized on magnetic resonance imaging (MRI) in patients with various inner ear diseases. The purpose of this study was to evaluate the prevalence and risk factors of significant EH on inner ear MRI in patients with 1 or more audiovestibular symptoms and to predict the incidence of significant EH using multivariate analysis and multilayer perceptron artificial neural network modeling. This retrospective study included a total of 135 patients with 1 or more audiovestibular symptoms who do not meet the diagnostic criteria for MD and underwent inner ear MRI at our institution from July 2021 to January 2024. The EH grade of each patient was evaluated, and "significant EH" was considered grade II or III. Of 135 patients with 1 or more audiovestibular symptoms, 48 patients (35.6%) presented with significant EH and 87 patients (64.4%) without significant EH on inner ear MRI. The prevalence of significant EH was higher in males, which was statistically significant (P = .007). The prevalence of significant EH was higher in the right ear, and the mean age of patients with significant EH was 1.94 years higher, but no statistical significance was observed (P = .660 and .456, retrospectively). The odds ratio for significant EH development was 2.696 (95% confidence interval: 1.296-5.607) times higher in men, which was statistically significant. Predicting the incidence of significant EH development using multivariate analysis, sex was the only variable that was statistically significant (P = .008). Based on a predictive model using multilayer perceptron (MLP), the classification accuracy of the model was 79.5%. In our study, the male gender could be related to the risk of developing significant EH in patients with audiovestibular symptoms. The accuracy of our suggested MLP model for predicting the incidence of significant EH was 79.5%, with sex being the highest predictor importance. In the future, inner ear MRI and MLP neural network modeling can be combined as a noninvasive and precise support system in the diagnosis of EH.
内淋巴积水（EH）已在患有各种内耳疾病的患者的磁共振成像（MRI）中显现出来。本研究的目的是评估有1种或更多听前庭症状的患者内耳MRI上显著EH的患病率和危险因素，并使用多变量分析和多层感知器人工神经网络建模预测显著EH的发生率。这项回顾性研究共纳入了135例有1种或更多听前庭症状且不符合梅尼埃病诊断标准的患者，这些患者于2021年7月至2024年1月在我们机构接受了内耳MRI检查。评估了每位患者的EH分级，“显著EH”被认为是II级或III级。在135例有1种或更多听前庭症状的患者中，48例（35.6%）在内耳MRI上表现为显著EH，87例（64.4%）无显著EH。显著EH的患病率在男性中更高，具有统计学意义（P = 0.007）。显著EH的患病率在右耳中更高，且显著EH患者的平均年龄高1.94岁，但未观察到统计学意义（回顾性分析，P = 0.660和0.456）。男性发生显著EH的优势比高2.696倍（95%置信区间：1.296 - 5.607），具有统计学意义。使用多变量分析预测显著EH发生的发生率时，性别是唯一具有统计学意义的变量（P = 0.008）。基于使用多层感知器（MLP）的预测模型，该模型的分类准确率为79.5%。在我们的研究中，男性性别可能与有听前庭症状的患者发生显著EH的风险相关。我们建议的用于预测显著EH发生率的MLP模型的准确率为79.5%，其中性别是预测重要性最高的因素。未来，内耳MRI和MLP神经网络建模可以结合起来，作为EH诊断中的一种非侵入性且精确的支持系统。
