Gerb Johannes, Kirsch Valerie, Kierig Emilie, Brandt Thomas, Dieterich Marianne, Boegle Rainer
German Center for Vertigo and Balance Disorders (DSGZ), LMU University Hospital, Ludwig-Maximilians-University (LMU) Munich, Marchioninistraße 15, 81377, Munich, Germany.
Department of Neurology, LMU University Hospital, LMU Munich, Munich, Germany.
Sci Rep. 2025 Feb 21;15(1):6414. doi: 10.1038/s41598-025-90842-2.
Spatial normalization of multisubject inner ear imaging data is challenging, due to both substantial intraindividual differences and the small size of the organ compared to other intracranial structures. Automatic whole brain co-registration to standard space can only roughly co-align the peripheral vestibular endorgan, and complemental manual registration is highly time-consuming. Here, we compared the accuracy of four geometry-maintaining co-registration methods (one semi-manual method and three automatic methods). High-resolution structural T2-MRI of 153 inner ears from patients and healthy participants were co-registered to an inner-ear atlas. The semi-manual method used a three-point landmark-based approach (3P), two automatic methods were based on unassisted standard algorithms (Advanced Normalization Tools (ANTs), Elastix (EL)), while the fourth automatic method utilized a volumetrically dilated, atlas-based mask (thick inner ear, TIE) for probabilistic inner ear masking. Registration accuracy was evaluated by neurotologists blinded to the respective registration paradigm, and the resulting median volumes were quantified using colocalization analyses. The mask-aided automatic approach showed the best ratings, followed by the semi-manual three-point landmark-based registration (mean ratings (lower: better) TIE 2.21 ± 1.15; 3P 2.58 ± 0.61; EL 3.42 ± 1.06; ANTs 3.49 ± 1.26). The semi-manual method had the lowest rate of insufficient registrations, followed by TIE (3P: 3.70%; TIE: 8.28%; EL: 22.66%; ANTs: 27.02%). TIE showed the highest colocalization metrics with the atlas. Only TIE and 3P allowed for sufficient semicircular canal visualization in method-wise average volumes. Overall, geometry-preserving spatial normalization of multisubject inner ear imaging data is possible and could allow groupwise examinations of the bony labyrinth or temporal bone morphology in the future.
多主体内耳成像数据的空间归一化具有挑战性，这是由于个体内部存在显著差异，且与其他颅内结构相比，该器官体积较小。自动全脑与标准空间的配准只能大致对齐外周前庭终器，而补充的手动配准非常耗时。在此，我们比较了四种保持几何形状的配准方法（一种半自动方法和三种自动方法）的准确性。对来自患者和健康参与者的153个内耳的高分辨率结构T2-MRI进行了与内耳图谱的配准。半自动方法采用基于三点地标法（3P），两种自动方法基于无辅助的标准算法（高级归一化工具（ANTs）、弹性配准软件（EL）），而第四种自动方法利用基于图谱的体积扩张掩码（厚内耳，TIE）进行概率性内耳掩膜。由对各自配准范式不知情的神经耳科医生评估配准准确性，并使用共定位分析对所得的中位数体积进行量化。掩码辅助自动方法的评分最佳，其次是基于三点地标的半自动配准（平均评分（越低越好）：TIE 2.21±1.15；3P 2.58±0.61；EL 3.42±1.06；ANTs 3.49±1.26）。半自动方法的配准不足率最低，其次是TIE（3P：3.70%；TIE：8.28%；EL：22.66%；ANTs：27.02%）。TIE与图谱的共定位指标最高。仅TIE和3P在方法平均体积中能实现足够的半规管可视化。总体而言，多主体内耳成像数据的保持几何形状的空间归一化是可行的，并且未来可能允许对骨迷路或颞骨形态进行分组检查。
