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 <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11548_2025_3325_Article_IEq1.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">$\upmu \hbox {m}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="normal">μ</mi> <mtext>m</mtext> </mrow> </math></EquationSource> </InlineEquation> in simulation and below 200 <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11548_2025_3325_Article_IEq2.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="26" /> </InlineMediaObject> <EquationSource Format="TEX">$\upmu \hbox {m}$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi mathvariant="normal">μ</mi> <mtext>m</mtext> </mrow> </math></EquationSource> </InlineEquation> 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.

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

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2025年2月8日

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Marius Briel,
Ludwig Haide,
Maximilian Hess,
Jan Schimmelpfennig,
Philipp Matten,
Rebekka Peter,
Matthias Hillenbrand,
Eleonora Tagliabue,
Franziska Mathis-Ullrich

摘要

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 $\upmu \hbox {m}$ $μ m$ in simulation and below 200 $\upmu \hbox {m}$ $μ m$ 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.