000151261 001__ 151261
000151261 005__ 20250307114714.0
000151261 0247_ $$2doi$$a10.1016/j.compbiomed.2025.109792
000151261 0248_ $$2sideral$$a143057
000151261 037__ $$aART-2025-143057
000151261 041__ $$aeng
000151261 100__ $$aRedaelli, Elena
000151261 245__ $$aA POD-NN methodology to determine in vivo mechanical properties of soft tissues. Application to human cornea deformed by Corvis ST test
000151261 260__ $$c2025
000151261 5060_ $$aAccess copy available to the general public$$fUnrestricted
000151261 5203_ $$aThe interaction between optical and biomechanical properties of the corneal tissue is crucial for the eye’s ability to refract and focus light. The mechanical properties vary among individuals and can change over time due to factors such as eye growth, ageing, and diseases like keratoconus. Estimating these properties is crucial for diagnosing ocular conditions, improving surgical outcomes, and enhancing vision quality, especially given increasing life expectancies and societal demands. Current ex-vivo methods for evaluating corneal mechanical properties are limited and not patient-specific. This study aims to develop a model to estimate in real-time the mechanical properties of the corneal tissue in-vivo. It is composed both by a proof of concept and by a clinical application. Regarding the proof of concept, we used high-fidelity Fluid-Structure Interaction (FSI) simulations of Non-Contact Tonometry (NCT) with Corvis ST® (OCULUS, Wetzlar, Germany) device to create a large dataset of corneal deformation evolution. Proper Orthogonal Decomposition (POD) was applied to this dataset to identify principal modes of variation, resulting in a reduced-order model (ROM). We then trained a Neural Network (NN) using the reduced coefficients, intraocular pressure (IOP), and corneal geometry derived from Pentacam® (OCULUS, Wetzlar, Germany) elevation data to predict the mechanical properties of the corneal tissue. This methodology was then applied to a clinical case in which the mechanical properties of the corneal tissue are estimated based on Corvis ST results. Our method demonstrated the potential for real-time, in-vivo estimation of corneal biomechanics, offering a significant advancement over traditional approaches that require time-consuming numerical simulations. This model, being entirely data-driven, eliminates the need for complex inverse analyses, providing an efficient and accurate tool to be implemented directly in the Corvis ST device.
000151261 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T24-20R$$9info:eu-repo/grantAgreement/EC/H2020/956720/EU/Opto-Biomechanical Eye Research Network/OBERON$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 956720-OBERON$$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-113822RB-C21
000151261 540__ $$9info:eu-repo/semantics/embargoedAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000151261 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000151261 700__ $$0(orcid)0000-0001-9713-1813$$aCalvo, Begoña$$uUniversidad de Zaragoza
000151261 700__ $$0(orcid)0000-0001-7612-266X$$aRodríguez Matas, José Felix
000151261 700__ $$aLuraghi, Giulia
000151261 700__ $$0(orcid)0000-0002-6870-0594$$aGrasa, Jorge$$uUniversidad de Zaragoza
000151261 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000151261 773__ $$g187 (2025), 109792 [18 pp.]$$pComput. biol. med.$$tComputers in biology and medicine$$x0010-4825
000151261 8564_ $$s778085$$uhttps://zaguan.unizar.es/record/151261/files/texto_completo.pdf$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2026-02-11
000151261 8564_ $$s707348$$uhttps://zaguan.unizar.es/record/151261/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2026-02-11
000151261 909CO $$ooai:zaguan.unizar.es:151261$$particulos$$pdriver
000151261 951__ $$a2025-03-07-09:30:47
000151261 980__ $$aARTICLE