Kiran Usha, Anitha H, Bhat Shyamasunder N, Naik Roshan Ramakrishna
Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Department of Orthopedics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Eur Spine J. 2025 Sep 13. doi: 10.1007/s00586-025-09342-6.
Accurate pedicle screw placement is crucial for ensuring safety during spine surgery. This study aims to develop and validate a feature-based 3D to 2D registration framework to integrate pre-operative MR with intra-operative X-ray images for estimating the pedicle screw trajectory and achieving robust 3D visualization. The method aims to overcome intensity mismatches and tissue non-correspondence issues inherent to multimodal registration.
A feature-based registration framework was proposed, leveraging vertebral endplates as key features due to their consistency after pedicle screw insertion. The segmented MR images were forward-projected and registered to intra-operative X-ray images using a binary image matching similarity measure, with optimization achieved through CMA-ES. Validation was performed by mapping the registered trajectory position onto pre-operative MR images and further evaluating the accuracy through 3D to 3D registration of pre-operative MR and post-operative CT images.
The framework effectively estimated the pedicle screw trajectory by registering intra-operative images onto pre-operative MR, with errors consistently below 2.5 mm for entry point, endpoint, and directional trajectory. The 3D to 3D registration validated the accuracy, demonstrating precise alignment between trajectory positions across modalities.
The proposed feature-based registration framework provides fast and accurate 3D trajectory information. This method improves surgical precision and offers robust evaluation metrics, making it a reliable tool for spine navigation and clinical diagnosis during pedicle screw placement procedures.
准确放置椎弓根螺钉对于确保脊柱手术安全至关重要。本研究旨在开发并验证一种基于特征的三维到二维配准框架，以将术前磁共振成像（MR）与术中X射线图像相结合，用于估计椎弓根螺钉轨迹并实现稳健的三维可视化。该方法旨在克服多模态配准中固有的强度不匹配和组织对应问题。
提出了一种基于特征的配准框架，利用椎弓根螺钉插入后保持一致的椎体终板作为关键特征。通过使用二元图像匹配相似性度量对分割后的MR图像进行前向投影并配准到术中X射线图像，通过协方差矩阵自适应进化策略（CMA-ES）实现优化。通过将配准后的轨迹位置映射到术前MR图像上，并通过术前MR与术后CT图像的三维到三维配准进一步评估准确性来进行验证。
该框架通过将术中图像配准到术前MR上有效地估计了椎弓根螺钉轨迹，进针点、终点和方向轨迹的误差始终低于2.5毫米。三维到三维配准验证了准确性，表明不同模态下轨迹位置之间精确对齐。
所提出的基于特征的配准框架提供了快速准确的三维轨迹信息。该方法提高了手术精度并提供了稳健的评估指标，使其成为椎弓根螺钉置入手术中脊柱导航和临床诊断的可靠工具。
