000170436 001__ 170436
000170436 005__ 20260420103355.0
000170436 0247_ $$2doi$$a10.1007/s10439-026-04057-1
000170436 0248_ $$2sideral$$a148913
000170436 037__ $$aART-2026-148913
000170436 041__ $$aeng
000170436 100__ $$aFantaci, Benedetta$$uUniversidad de Zaragoza
000170436 245__ $$aBiomechanically informed patient-specific in silico models for laser refractive surgery
000170436 260__ $$c2026
000170436 5060_ $$aAccess copy available to the general public$$fUnrestricted
000170436 5203_ $$aPurpose: Corneal biomechanics plays a key role in the planning and outcomes of laser refractive surgery. This study presents a validated methodology for simulating patient-specific refractive treatments, focusing on the optomechanical effects of the three most commonly performed procedures: PRK, LASIK, and SMILE.
Methods: For the first time, patient-specific mechanical properties of the cornea were incorporated into finite element simulations. These properties were estimated using an artificial neural network trained on in silico data from fluid–structure interaction models of non-contact tonometry. The tool takes as input corneal deformation images acquired with the Corvis ST device, intraocular pressure (IOP), and corneal geometry obtained from Pentacam imaging. IOP is estimated independently of corneal geometry and mechanical properties using a novel algorithm developed in prior studies. The methodology was tested on a cohort of 58 eyes from 29 patients who underwent one of the three procedures.
Results: By integrating patient-specific geometry, IOP, and biomechanical characterization, the proposed framework successfully simulated postoperative corneal responses, yielding a mean dioptric error of +0.40 ± 0.30 D relative to clinical outcomes. Among the three procedures, SMILE produced the highest mechanical impact on the corneal model.
Conclusion: This study introduces a personalized, biomechanically informed approach to simulate corneal behavior following refractive surgery. The proposed framework enhances surgical planning and improves prediction of postoperative refractive stability, offering a step toward personalized refractive correction and safer, more predictable clinical outcomes.
000170436 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FEDER/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$$9info:eu-repo/grantAgreement/ES/MICINN/PID2023-147987OB-C31$$9info:eu-repo/grantAgreement/ES/UZ/ICTS NANBIOSIS-U27 Unit-CIBER-BBN
000170436 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000170436 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000170436 700__ $$aRedaelli, Elena
000170436 700__ $$aMartí, Mònica
000170436 700__ $$aJulio, Gemma
000170436 700__ $$aBarraquer, Anton
000170436 700__ $$aLamarca, Jose
000170436 700__ $$0(orcid)0000-0002-6870-0594$$aGrasa, Jorge$$uUniversidad de Zaragoza
000170436 700__ $$0(orcid)0000-0001-9713-1813$$aCalvo, Begoña$$uUniversidad de Zaragoza
000170436 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000170436 773__ $$g(2026), [22 pp.]$$pAnn. biomed. eng.$$tAnnals of Biomedical Engineering$$x0090-6964
000170436 8564_ $$s3507664$$uhttps://zaguan.unizar.es/record/170436/files/texto_completo.pdf$$yVersión publicada
000170436 8564_ $$s2356682$$uhttps://zaguan.unizar.es/record/170436/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000170436 909CO $$ooai:zaguan.unizar.es:170436$$particulos$$pdriver
000170436 951__ $$a2026-04-18-10:49:32
000170436 980__ $$aARTICLE