Autonomous Establishment of CT-Independent Sections to Obtain Optimum Pedicle-Screw Axis in Direction, Length, and Safety Margin

IF 2.1 3区医学 Q2 SURGERY International Journal of Medical Robotics and Computer Assisted Surgery Pub Date : 2025-03-02 DOI:10.1002/rcs.70049

Amit Kumar, Dwarakanath T. A., Gaurav Bhutani, Dwarakanath Srinivas

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Abstract

Background

Accurate perception of pedicle geometry during pedicle-screw placement surgery is critically important because the margin-for-error is small.

Method

An assessment algorithm is developed to provide machine-independent MultiPlanar Reconstruction (MiMPR) of the pedicle. The reconstruction is independent of the CT-machine frame and enhances patient data portability. Additionally, the algorithm obtains the pedicle-screw axis with optimum direction, length, and margin using MPRs. A method for the autonomous identification of four body features to form a CT-independent vertebral frame, {V}, in the image space is formulated.

Result

Applied to 200 high-resolution CT images, the approach achieved a 100% success rate in defining the pedicle-medial axis and maximum screw diameter considering the safety margin of 2 mm.

Conclusions

The method eliminates subjective assessment. It provides objective assessment in determining the pedicle-medial axis with optimal direction and margin without human annotation. Additionally, it significantly enhances screw placement accuracy in robot-assisted spinal fusion surgeries, regardless of vertebra orientation.

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自主建立与ct无关的切片，以获得最佳椎弓根螺钉轴的方向、长度和安全裕度

背景：在椎弓根螺钉置入手术中，准确感知椎弓根几何形状至关重要，因为误差范围很小。方法开发一种评估算法，提供机器无关的椎弓根多平面重建（MiMPR）。重建是独立于ct机框架和增强患者数据的可移植性。此外，该算法还利用mpr获得了最佳方向、长度和边缘的椎弓根螺钉轴。提出了一种在图像空间中自主识别四种身体特征以形成与ct无关的椎体框架{V}的方法。结果该方法应用于200张高分辨率CT图像，在2 mm的安全范围内，确定椎弓根-内侧轴和最大螺钉直径的成功率为100%。结论该方法消除了主观评价。它为确定最佳椎弓根-内侧轴的方向和边缘提供了客观的评价，无需人工注释。此外，在机器人辅助脊柱融合手术中，无论椎体方向如何，它都能显著提高螺钉放置的准确性。

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来源期刊

International Journal of Medical Robotics and Computer Assisted Surgery 医学-外科

CiteScore

4.50

自引率

12.00%

发文量

131

审稿时长

6-12 weeks

期刊介绍： The International Journal of Medical Robotics and Computer Assisted Surgery provides a cross-disciplinary platform for presenting the latest developments in robotics and computer assisted technologies for medical applications. The journal publishes cutting-edge papers and expert reviews, complemented by commentaries, correspondence and conference highlights that stimulate discussion and exchange of ideas. Areas of interest include robotic surgery aids and systems, operative planning tools, medical imaging and visualisation, simulation and navigation, virtual reality, intuitive command and control systems, haptics and sensor technologies. In addition to research and surgical planning studies, the journal welcomes papers detailing clinical trials and applications of computer-assisted workflows and robotic systems in neurosurgery, urology, paediatric, orthopaedic, craniofacial, cardiovascular, thoraco-abdominal, musculoskeletal and visceral surgery. Articles providing critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies, commenting on ease of use, or addressing surgical education and training issues are also encouraged. The journal aims to foster a community that encompasses medical practitioners, researchers, and engineers and computer scientists developing robotic systems and computational tools in academic and commercial environments, with the intention of promoting and developing these exciting areas of medical technology.