Ultrasound-Guided Real-Time Spinal Motion Visualization for Spinal Instability Assessment

• URL: http://arxiv.org/abs/2602.12917v1
• Date: Fri, 13 Feb 2026 13:23:29 GMT
• Title: Ultrasound-Guided Real-Time Spinal Motion Visualization for Spinal Instability Assessment
• Authors: Feng Li, Yuan Bi, Tianyu Song, Zhongliang Jiang, Nassir Navab,
• Abstract summary: There is a need for a system capable of visualizing real-time 3D spinal motion while minimizing radiation exposure.<n>The proposed robotic ultrasound framework enables radiation-reduced, real-time 3D visualization of spinal motion.
• Score: 40.77326665667697
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Purpose: Spinal instability is a widespread condition that causes pain, fatigue, and restricted mobility, profoundly affecting patients' quality of life. In clinical practice, the gold standard for diagnosis is dynamic X-ray imaging. However, X-ray provides only 2D motion information, while 3D modalities such as computed tomography (CT) or cone beam computed tomography (CBCT) cannot efficiently capture motion. Therefore, there is a need for a system capable of visualizing real-time 3D spinal motion while minimizing radiation exposure. Methods: We propose ultrasound as an auxiliary modality for 3D spine visualization. Due to acoustic limitations, ultrasound captures only the superficial spinal surface. Therefore, the partially compounded ultrasound volume is registered to preoperative 3D imaging. In this study, CBCT provides the neutral spine configuration, while robotic ultrasound acquisition is performed at maximal spinal bending. A kinematic model is applied to the CBCT-derived spine model for coarse registration, followed by ICP for fine registration, with kinematic parameters optimized based on the registration results. Real-time ultrasound motion tracking is then used to estimate continuous 3D spinal motion by interpolating between the neutral and maximally bent states. Results: The pipeline was evaluated on a bendable 3D-printed lumbar spine phantom. The registration error was $1.941 \pm 0.199$ mm and the interpolated spinal motion error was $2.01 \pm 0.309$ mm (median). Conclusion: The proposed robotic ultrasound framework enables radiation-reduced, real-time 3D visualization of spinal motion, offering a promising 3D alternative to conventional dynamic X-ray imaging for assessing spinal instability.

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