Evidence map›Paper›PMID 36246942›Full record

ArticleOphthalmology science2021

Clinical Evaluation of an Instrument-Integrated OCT-Based Distance Sensor for Robotic Vitreoretinal Surgery.

Matteo Giuseppe Cereda, Salvatore Parrulli, Y G M Douven, Koorosh Faridpooya, Saskia van Romunde, Gereon Hüttmann, Tim Eixmann, Hinnerk Schulz-Hildebrandt, Gernot Kronreif, Maarten Beelen and 1 more

Open access · goldAbstract read
In one paragraph

Article in Ophthalmology science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
2.1field-weighted citation impact, top 13% of its field
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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Intraoperative fusion of models and data for robust distance sensing.International journal of computer assisted radiology and surgery · 2026
    Article
  6. Article
  7. Article
  8. Review
  9. Unsupervised out-of-distribution detection for safer robotically guided retinal microsurgery.International journal of computer assisted radiology and surgery · 2023
    Article
  10. Review
  11. 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

11 authors at 5 institutions in 4 countries.

Matteo Giuseppe CeredaEye Clinic, Department of Biomedical and Clinical Science "Luigi Sacco," Sacco Hospital, University of Milan, Milan, Italy.
Salvatore ParrulliEye Clinic, Department of Biomedical and Clinical Science "Luigi Sacco," Sacco Hospital, University of Milan, Milan, Italy.
Y G M DouvenDepartment of Mechanical Engineering, University of Technology, Eindhoven, The Netherlands.
Koorosh FaridpooyaRotterdam Eye Hospital, Rotterdam, The Netherlands.
Saskia van RomundeRotterdam Eye Hospital, Rotterdam, The Netherlands.
Gereon HüttmannMedical Laser Center Lübeck GmbH, Lübeck, Germany.
Tim EixmannMedical Laser Center Lübeck GmbH, Lübeck, Germany.
Hinnerk Schulz-HildebrandtMedical Laser Center Lübeck GmbH, Lübeck, Germany.
Gernot KronreifACMIT Gmbh, Wiener Neustadt, Austria.
Maarten BeelenPreceyes B.V., Eindhoven, The Netherlands.
Marc D de SmetPreceyes B.V., Eindhoven, The Netherlands.
Medizinisches Laserzentrum Lübeck (Germany) · DERotterdam Eye Hospital · NLUniversity of Milan · ITAustrian Center for Medical Innovation and Technology · ATEindhoven University of Technology · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To assess the efficacy of an instrument-integrated OCT (iiOCT)-based distance sensor during robotic vitreoretinal surgery using the Preceyes Surgical System (PSS; Preceyes B.V.). Design: Single-center interventional study. Participants: Patients requiring vitreoretinal surgery. Methods: Five patients were enrolled. Standard preoperative OCT images were obtained. After vitrectomy, a predefined set of actions was performed using the iiOCT-based sensor. Images then were processed to assess the signal-to-noise ratio (SNR) at various angles to the retina and at different distances between the instrument tip and the retinal surface. Preoperative and intraoperative OCT images were compared qualitatively and quantitatively. Main Outcomes Measures: The feasibility in performing surgical tasks using the iiOCT-based sensor during vitreoretinal surgery, the SNR when imaging the retina, differences among intraoperative and preoperative OCT images, and characteristics of intraoperative retinal movements detected with the iiOCT-based probe. Results: Surgeons were able to perform all the tasks but one. The PSS was able to maintain a fixed distance. The SNR of the iiOCT-based sensor signal was adequate to determine the distance to the retina and to control the PSS. Analysis of iiOCT-based sensor A-scans identified 3 clearly distinguishable retinal layers, including the inner retinal boundary and the interface at the retinal pigment epithelium-Bruch's membrane. Thickness values differed by less than 5% from that measured by preoperative OCT, indicating its accuracy. The Fourier analysis of iiOCT-based sensor recordings identified anteroposterior retinal movements attributed to heartbeat and respiration. Conclusions: This iiOCT-based sensor was tested successfully and promises reliable use during robot-assisted surgery. An iiOCT-based sensor is a promising step toward OCT-guided robotic retinal surgery.

Indexed as

iiOCT, instrument-integrated OCTILM, internal limiting membraneOCTOCT distance sensorPSS, Preceyes Surgical SystemRobotic vitreoretinal surgeryRPE, retinal pigment epitheliumSNR, signal-to-noise ratio

Identifiers

PMID36246942
PMCPMC9560530
OpenAlexW3214833019

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.