Evidence map›Paper›PMID 35175318›Full record

ArticleTranslational vision science & technology2022

Thickness of the Protective Layers of Different Ophthalmic Viscosurgical Devices During Lens Surgery in a Porcine Model.

Melanie Wüst, Philipp Matten, Magdalena Nenning, Oliver Findl

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Article in Translational vision science & technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Melanie WüstFaculty of Optics and Mechatronics, University of Aalen, Aalen, Germany.
Philipp MattenCenter for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
Magdalena NenningVIROS - Vienna Institute for Research in Ocular Surgery, A Karl Landsteiner Institute, Hanusch Hospital, Vienna, Austria.
Oliver FindlVIROS - Vienna Institute for Research in Ocular Surgery, A Karl Landsteiner Institute, Hanusch Hospital, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the thickness of the intraoperative layers of 10 different ophthalmic viscosurgical devices (OVD) covering the corneal endothelium during simulated lens surgery in a porcine model.

methodsThis experimental study took place at the Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria. Ten OVDs with different viscoelastic properties (ProVisc, Z-Hyalin plus, Amvisc plus, DisCoVisc, Healon EndoCoat, Viscoat, Z-Hyalcoat, Combivisc, Duo-Visc, and Twinvisc) were assessed in 10 porcine eyes each, yielding a total of 100 eyes. Simulated cataract surgery was performed with volumetric intraoperative OCT imaging during phacoemulsification and during irrigation/aspiration to determine the remaining amount of OVD coating the endothelium over a scan field of 6 × 6 mm. Indirect visualization of the OVD was enabled by replacing the irrigating solution by a higher scattering diluted milk solution. A deep convolutional neural network (CNN) was used to evaluate OVD layer thickness based on the B-scans.

resultsMedian thickness values after phacoemulsification were lowest for the cohesive OVDs Z-Hyalin plus (38 µm) and ProVisc (39 µm), followed by the combination systems Twinvisc (342 µm) and Duo-Visc (537 µm). Highest values were observed for the dispersive OVDs and the combination system Combivisc (Viscoat: 957 µm; Z-Hyalcoat: 988 µm, Combivisc: 1042 µm; Amvisc plus: 1259 µm; Healon EndoCoat: 1303 µm; DisCoVisc: 1356 µm). The difference between the OVDs was statistically significant (P < 0.01).

conclusionsThe results of this study confirm that at completion of phacoemulsification, thickest residual layers of OVD remain when using dispersive substances, followed by combination systems and lowest thickness values were observed with cohesive OVDs. The use of an intraoperative OCT and a deep convolutional neural network allowed measurements over a large scan field of 6 × 6 mm and a precise evaluation of the OVD layer coating the corneal endothelium. The OVD layer seemed to be more like a ragged terrain instead of a flat layer, indicating that the film-forming effect of dispersive OVDs is the result of their volume rheology rather than a surface interaction. TRANSLATIONAL RELEVANCE: Evaluating the protective properties provides valuable insights into how different OVDs with different viscoelastic properties form layers beneath the corneal endothelium and helps to understand their persistence during the various steps of cataract surgeries.

Indexed as

CataractCataract ExtractionPhacoemulsificationAnimalsEndothelium, CornealHyaluronic AcidSwineHyaluronic Acid

Identifiers

PMID35175318
PMCPMC8857612

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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.