June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
A Finite Element Model to Predict the Effect of Femtosecond Laser Trabeculotomy (FLT) Glaucoma Treatment Parameters
Author Affiliations & Notes
  • Eric Robert Mikula
    Ophthalmology, University of California Irvine, Irvine, California, United States
    ViaLase, Inc., Aliso Viejo, California, United States
  • Gagik Djotyan
    Wigner Fizikai Kutatokozpont, Budapest, Budapest, Hungary
  • Kinga Kranitz
    Ophthalmology, Semmelweis Egyetem, Budapest, Budapest, Hungary
  • Zoltán Nagy
    Ophthalmology, Semmelweis Egyetem, Budapest, Budapest, Hungary
  • Tibor Juhasz
    Ophthalmology, University of California Irvine, Irvine, California, United States
    ViaLase, Inc., Aliso Viejo, California, United States
  • Footnotes
    Commercial Relationships   Eric Mikula ViaLase, Inc. , Code E (Employment), ViaLase, Inc. , Code P (Patent); Gagik Djotyan ViaLase, Inc. , Code C (Consultant/Contractor); Kinga Kranitz None; Zoltán Nagy None; Tibor Juhasz ViaLase, Inc. , Code E (Employment), ViaLase, Inc. , Code P (Patent)
  • Footnotes
    Support   NIH EY030304
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 166 – A0359. doi:
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    • Get Citation

      Eric Robert Mikula, Gagik Djotyan, Kinga Kranitz, Zoltán Nagy, Tibor Juhasz; A Finite Element Model to Predict the Effect of Femtosecond Laser Trabeculotomy (FLT) Glaucoma Treatment Parameters. Invest. Ophthalmol. Vis. Sci. 2022;63(7):166 – A0359.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : FLT is an innovative, non-invasive glaucoma procedure which aims to reduce intraocular pressure (IOP) via the creation of aqueous humor (AH) drainage channels through the trabecular meshwork (TM) and into Schlemm’s canal (SC). As of this writing, the optimal physical treatment parameters of drainage channel(s) for FLT are not known. The purpose of this study was to develop a finite element model (FEM) to help predict the optimal drainage channel size (cross-sectional area) for IOP reduction.

Methods : The 3D finite element model of the human eye and the conventional AH outflow pathway used data published in the literature to inform the geometry of the anterior chamber (AC), TM, SC, and collector channels (CC). The major boundary conditions consisted of an AH inflow rate source term (2.5 uL/min) and the episcleral venous pressure, which comprised a pressure condition on the distal boundary of the CC’s (9 mmHg). The TM and CC’s were modeled as porous material, with given permeabilities, to approximate the resistance to AH outflow found in these tissues in-vivo. The permeability of the TM and CC’s was estimated by comparing iterative FEM simulations with IOP data collected from ex-vivo experiments as well as unpublished preliminary clinical data. FLT was modelled by applying a block-like channel of connecting the anterior chamber to SC.

Results : Table 1 shows the finite element model predictions for IOP values following FLT using drainage channels of varying cross-sectional dimension. A channel size of 100 µm x 100 µm was found to achieve approximately (±2%) the maximal achievable IOP reduction (pressure within SC). Beyond this size, no appreciable increase in IOP reduction was achieved. This is in relative agreement with experimental laboratory as well as clinical results which demonstrated similar IOP reduction with channels measuring 200 µm x 500 µm.

Conclusions : The finite element model of FLT developed in this study demonstrates initial predictive power regarding drainage channel geometry and subsequent IOP reduction. Furthermore, the model shows the potential for reducing drainage channel size significantly, thus reducing procured time and overall tissue alteration, without sacrificing IOP performance. Importantly, the model suggests that drainage channel geometry may be chosen to fine-tune IOP reduction, thus optimizing the FLT procedure for a particular patient.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

 

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