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Feasibility of Augmented Reality-Guided Robotic Ultrasound with Cone-Beam CT Integration for Spine Procedures

Tianyu Song, Felix Pabst, Feng Li, Yordanka Velikova, Miruna-Alexandra Gafencu, Yuan Bi, Ulrich Eck, Nassir Navab

Abstract

Accurate needle placement in spine interventions is critical for effective pain management, yet it depends on reliable identification of anatomical landmarks and careful trajectory planning. Conventional imaging guidance often relies both on CT and X-ray fluoroscopy, exposing patients and staff to high dose of radiation while providing limited real-time 3D feedback. We present an optical see-through augmented reality (OST-AR)-guided robotic system for spine procedures that provides in situ visualization of spinal structures to support needle trajectory planning. We integrate a cone-beam CT (CBCT)-derived 3D spine model which is co-registered with live ultrasound, enabling users to combine global anatomical context with local, real-time imaging. We evaluated the system in a phantom user study involving two representative spine procedures: facet joint injection and lumbar puncture. Sixteen participants performed insertions under two visualization conditions: conventional screen vs. AR. Results show that AR significantly reduces execution time and across-task placement error, while also improving usability, trust, and spatial understanding and lowering cognitive workload. These findings demonstrate the feasibility of AR-guided robotic ultrasound for spine interventions, highlighting its potential to enhance accuracy, efficiency, and user experience in image-guided procedures.

Feasibility of Augmented Reality-Guided Robotic Ultrasound with Cone-Beam CT Integration for Spine Procedures

Abstract

Accurate needle placement in spine interventions is critical for effective pain management, yet it depends on reliable identification of anatomical landmarks and careful trajectory planning. Conventional imaging guidance often relies both on CT and X-ray fluoroscopy, exposing patients and staff to high dose of radiation while providing limited real-time 3D feedback. We present an optical see-through augmented reality (OST-AR)-guided robotic system for spine procedures that provides in situ visualization of spinal structures to support needle trajectory planning. We integrate a cone-beam CT (CBCT)-derived 3D spine model which is co-registered with live ultrasound, enabling users to combine global anatomical context with local, real-time imaging. We evaluated the system in a phantom user study involving two representative spine procedures: facet joint injection and lumbar puncture. Sixteen participants performed insertions under two visualization conditions: conventional screen vs. AR. Results show that AR significantly reduces execution time and across-task placement error, while also improving usability, trust, and spatial understanding and lowering cognitive workload. These findings demonstrate the feasibility of AR-guided robotic ultrasound for spine interventions, highlighting its potential to enhance accuracy, efficiency, and user experience in image-guided procedures.
Paper Structure (17 sections, 7 equations, 7 figures, 1 table)

This paper contains 17 sections, 7 equations, 7 figures, 1 table.

Figures (7)

  • Figure 1: AR-Guided Needle Insertion. The system integrates robotic ultrasound, CBCT, and AR visualization into a unified framework, providing intuitive guidance during needle insertion for spine procedures.
  • Figure 2: System Overview. The pipeline integrates robotic CBCT, robotic ultrasound, and AR into a unified framework, enabling in situ AR visualization of spine anatomy and needle guidance. ($\boldsymbol{\bullet}$) represents CBCT volume acquisition, ($\boldsymbol{\bullet}$) depicts ultrasound and robot state acquisition, and ($\boldsymbol{\bullet}$) indicates the visualization process.
  • Figure 3: Transformation Chain for System Registration. Note that the transformations shown with solid arrows are acquired, while the transformations with dashed arrows are derived. ($\boldsymbol{\bullet}$) represents transformations in the virtual domain, ($\boldsymbol{\bullet}$) corresponds to transformations in the real world, and ($\boldsymbol{\bullet}$) denotes the registration between virtual and real robot.
  • Figure 4: AR Guidance Visualization. Raycasting from the needle guide onto the CT-derived spine model yields the predicted intersection point (marked in red) between the needle and the spine model.
  • Figure 5: Study Setup. Experimental configuration with robotic arm, ultrasound probe, lumbar spine phantom, and screen-based guidance interface.
  • ...and 2 more figures