Evidence map›Paper›PMID 41044813›Full record

ArticleThe international journal of medical robotics + computer assisted surgery : MRCAS2025

Magnification-Invariant Retinal Distance Estimation for Vitreoretinal Surgery Using a Laser Aiming Beam.

Arpita Routray, Chaniya Jaroenkunathum, Sungwook Yang, Robert Maclachlan, Jennifer Adeghate, Marjan Fooladi, Joseph Martel, Cameron N Riviere

Abstract read
In one paragraph

Article in The international journal of medical robotics + computer assisted surgery : MRCAS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Magnification-Invariant Retinal Distance Estimation for Vitreoretinal Surgery Using a Laser Aiming Beam.The international journal of medical robotics + computer assisted surgery : MRCAS · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Arpita RoutrayThe Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Chaniya JaroenkunathumBiomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Sungwook YangCenter for Intelligent & Interactive Robotics, AIRobot Institute, Korea Institute of Science and Technology (KIST), Seoul, Korea.
Robert MaclachlanThe Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Jennifer AdeghateDepartment of Ophthalmology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Marjan FooladiDepartment of Ophthalmology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Joseph MartelDepartment of Ophthalmology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Cameron N RiviereThe Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-6749-3140

Funding

A handheld tissue force microscopeR01GM153059 · NIGMS · CARNEGIE-MELLON UNIVERSITY · PI Cameron N Riviere · 2024 to 2026
$1.3M
NIGMS NIH HHS R01 GM153059NIGMS NIH HHS R01GM153059
6 · The paper itself

Abstract

backgroundVirtual fixtures in robot-assisted retinal surgery require knowledge of the position of the retina with respect to the surgical tool to be effective. Retinal surface estimation is a difficult problem due to the lack of features in the captured microscope imagery and a complex light path. A laser aiming beam attached to the tool can be easily detected in the microscope imagery and provide valuable information about the location of the surface.

methodsWe propose using the area of a laser aiming beam attached to the surgical tool to determine the distance of the tool from the retina. This area was modified in accordance with the tool width to ensure independence from microscope magnification. Retinal distance is predicted using a dual Kalman filter that combines distance inferred from this metric with information from an optical tracker that tracks the position of the tool in a global coordinate system. This updates both the state and parameters of the system in parallel and allows us to predict retinal distance even with errors in initial parameters.

resultsThe laser metric's independence from microscope magnification is demonstrated by plotting the metric at 3 different magnifications for a number of angles. We also predict the distance of the tool from the retina for various random angles at each magnification with median errors of less than 100 μm. Finally, we predict distance at each magnification during freehand motion and validate our results using a force sensor placed underneath the phantom.

conclusionsUsing the area of laser aiming beam attached to the surgical tool, our method can predict the distance of the surgical tool to the retina with errors that are acceptable for implementing virtual fixtures during robot-assisted retinal surgery. The predicted distance is also independent of microscope magnification and can work when initial parameters are not precisely known. Future work will involve adapting this method to in vivo environments and further reduction in prediction errors.

Indexed as

LasersRetinaRobotic Surgical ProceduresSurgery, Computer-AssistedVitreoretinal SurgeryAlgorithmsHumansMicroscopyrobot‐assisted surgerytremor compensationvitreoretinal microsurgery

Identifiers

PMID41044813
PMCPMC12494965

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.