We present OREHAS (Optimized Recognition & Evaluation of volumetric Hydrops in the Auditory System), the first fully automatic pipeline for volumetric quantification of endolymphatic hydrops (EH) from routine 3D-SPACE-MRC and 3D-REAL-IR MRI. The system integrates three components -- slice classification, inner ear localization, and sequence-specific segmentation -- into a single workflow that computes per-ear endolymphatic-to-vestibular volume ratios (ELR) directly from whole MRI volumes, eliminating the need for manual intervention. Trained with only 3 to 6 annotated slices per patient, OREHAS generalized effectively to full 3D volumes, achieving Dice scores of 0.90 for SPACE-MRC and 0.75 for REAL-IR. In an external validation cohort with complete manual annotations, OREHAS closely matched expert ground truth (VSI = 74.3%) and substantially outperformed the clinical syngo.via software (VSI = 42.5%), which tended to overestimate endolymphatic volumes. Across 19 test patients, vestibular measurements from OREHAS were consistent with syngo.via, while endolymphatic volumes were systematically smaller and more physiologically realistic. These results show that reliable and reproducible EH quantification can be achieved from standard MRI using limited supervision. By combining efficient deep-learning-based segmentation with a clinically aligned volumetric workflow, OREHAS reduces operator dependence, ensures methodological consistency. Besides, the results are compatible with established imaging protocols. The approach provides a robust foundation for large-scale studies and for recalibrating clinical diagnostic thresholds based on accurate volumetric measurements of the inner ear.

翻译：我们提出了OREHAS（听觉系统体积性积水优化识别与评估），这是首个从常规3D-SPACE-MRC和3D-REAL-IR MRI实现内淋巴积水体积定量的全自动流程。该系统将三个组件——切片分类、内耳定位和序列特异性分割——集成到单一工作流中，直接从完整MRI体积计算每侧耳的内淋巴-前庭体积比，无需人工干预。仅使用每位患者3至6张标注切片进行训练，OREHAS便能有效泛化至完整3D体积，在SPACE-MRC和REAL-IR序列上分别达到0.90和0.75的Dice分数。在一个具有完整人工标注的外部验证队列中，OREHAS与专家标注结果高度吻合（VSI = 74.3%），并显著优于临床syngo.via软件（VSI = 42.5%），后者倾向于高估内淋巴体积。在19名测试患者中，OREHAS的前庭测量结果与syngo.via一致，而其内淋巴体积则系统性更小且更符合生理实际。这些结果表明，通过有限监督即可从标准MRI实现可靠且可重复的内淋巴积水定量。OREHAS将高效的基于深度学习的分割与临床导向的体积工作流相结合，降低了操作者依赖性，确保了方法学一致性。此外，其结果与现有成像协议兼容。该方法为大规模研究以及基于精确内耳体积测量重新校准临床诊断阈值提供了坚实基础。