Intraoperative adaptive eye model based on instrument-integrated OCT for robot-assisted vitreoretinal surgery.

IF 2.3 3区 医学 Q3 ENGINEERING, BIOMEDICAL International Journal of Computer Assisted Radiology and Surgery Pub Date : 2025-05-01 Epub Date: 2025-02-08 DOI:10.1007/s11548-025-03325-0
Marius Briel, Ludwig Haide, Maximilian Hess, Jan Schimmelpfennig, Philipp Matten, Rebekka Peter, Matthias Hillenbrand, Eleonora Tagliabue, Franziska Mathis-Ullrich
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Abstract

Purpose: Pars plana vitrectomy (PPV) is the most common surgical procedure performed by retinal specialists, highlighting the need for model-based assistance and automation in surgical treatment. An intraoperative retinal model provides precise anatomical information relative to the surgical instrument, enhancing surgical precision and safety.

Methods: This work focuses on the intraoperative parametrization of retinal shape using 1D instrument-integrated optical coherence tomography distance measurements combined with a surgical robot. Our approach accommodates variability in eye geometries by transitioning from an initial spherical model to an ellipsoidal representation, improving accuracy as more data is collected through sensor motion.

Results: We demonstrate that ellipsoid fitting outperforms sphere fitting for regular eye shapes, achieving a mean absolute error of less than 40  μ m in simulation and below 200  μ m on 3D printed models and ex vivo porcine eyes. The model reliably transitions from a spherical to an ellipsoidal representation across all six tested eye shapes when specific criteria are satisfied.

Conclusion: The adaptive eye model developed in this work meets the accuracy requirements for clinical application in PPV within the central retina. Additionally, the global model effectively extrapolates beyond the scanned area to encompass the retinal periphery.This capability enhances PPV procedures, particularly through virtual boundary assistance and improved surgical navigation, ultimately contributing to safer surgical outcomes.

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基于仪器集成OCT的机器人辅助玻璃体视网膜手术术中自适应眼模型。
目的:玻璃体切割(PPV)是视网膜专家最常用的外科手术,强调了基于模型的辅助和手术治疗自动化的需求。术中视网膜模型提供了相对于手术器械的精确解剖信息,提高了手术精度和安全性。方法:结合手术机器人,采用1D仪器集成光学相干断层成像距离测量技术,对术中视网膜形态进行参数化。我们的方法通过从初始的球形模型过渡到椭球体表示来适应眼睛几何形状的可变性,随着通过传感器运动收集更多数据,提高了精度。结果:我们证明椭球拟合优于球体拟合,在模拟中实现了小于40 μ m的平均绝对误差,在3D打印模型和离体猪眼上实现了小于200 μ m的平均绝对误差。当满足特定的标准时,该模型在所有六种被测试的眼睛形状上可靠地从球形过渡到椭球体表示。结论:本研究建立的适应性眼模型满足临床应用于视网膜中心内PPV的精度要求。此外,全局模型有效地外推超出扫描区域,以涵盖视网膜周边。这种能力增强了PPV程序,特别是通过虚拟边界辅助和改进的手术导航,最终有助于更安全的手术结果。
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来源期刊
International Journal of Computer Assisted Radiology and Surgery
International Journal of Computer Assisted Radiology and Surgery ENGINEERING, BIOMEDICAL-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
5.90
自引率
6.70%
发文量
243
审稿时长
6-12 weeks
期刊介绍: The International Journal for Computer Assisted Radiology and Surgery (IJCARS) is a peer-reviewed journal that provides a platform for closing the gap between medical and technical disciplines, and encourages interdisciplinary research and development activities in an international environment.
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