用低剂量动态4D影像评估关节运动，助力术后精准诊疗
4D Virtual Imaging Platform for Dynamic Joint Assessment via Uni-Plane X-ray and 2D-3D Registration
- 结合3D CBCT与2D X-ray，通过深度学习实现动态融合成像
- 模拟测试达0.235毫米亚体素精度，成功率99.18%
- 适合骨科手术后关节运动量化分析，临床验证有效
传统CT无法捕捉动态承重关节运动。功能评估尤其是术后情况，需要四维（4D）影像，但现有方法受限于辐射过量或2D技术空间信息不全。本文提出一个集成的4D关节分析平台：(1) 双机械臂锥形束CT（CBCT）系统，采用可编程无机架轨迹，专为直立扫描优化；(2) 混合成像流程，融合静态3D CBCT与动态2D X射线，结合基于深度学习的预处理、3D-2D投影及迭代优化；(3) 临床验证的定量运动学评估框架。模拟研究显示，该方法实现0.235毫米亚体素精度，成功率达99.18%，优于传统与前沿注册方法。临床验证进一步准确量化了全膝关节置换术（TKA）患者胫骨平台运动及内外侧变异。该4D CBCT平台实现快速、精确、低剂量的动态关节成像，为生物力学研究、精准诊断和个性化骨科护理提供新可能。
原文摘要 · Abstract (English)
Conventional computed tomography (CT) lacks the ability to capture dynamic, weight-bearing joint motion. Functional evaluation, particularly after surgical intervention, requires four-dimensional (4D) imaging, but current methods are limited by excessive radiation exposure or incomplete spatial information from 2D techniques. We propose an integrated 4D joint analysis platform that combines: (1) a dual robotic arm cone-beam CT (CBCT) system with a programmable, gantry-free trajectory optimized for upright scanning; (2) a hybrid imaging pipeline that fuses static 3D CBCT with dynamic 2D X-rays using deep learning-based preprocessing, 3D-2D projection, and iterative optimization; and (3) a clinically validated framework for quantitative kinematic assessment. In simulation studies, the method achieved sub-voxel accuracy (0.235 mm) with a 99.18 percent success rate, outperforming conventional and state-of-the-art registration approaches. Clinical evaluation further demonstrated accurate quantification of tibial plateau motion and medial-lateral variance in post-total knee arthroplasty (TKA) patients. This 4D CBCT platform enables fast, accurate, and low-dose dynamic joint imaging, offering new opportunities for biomechanical research, precision diagnostics, and personalized orthopedic care.
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