Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Detection ability of corneal biomechanical parameters for early diagnosis of ectasia

Eye volume 37, pages 1665–1672 (2023)Cite this article

Subjects

Abstract

Purpose

To assess the detection ability of corneal biomechanical parameters for early diagnosis of ectasia.

Methods

This retrospective descriptive-analytical study included 134 normal eyes (control group) from 134 healthy subjects and 128 eyes with asymmetric contralateral corneal ectasia with normal topography (ACE-NT, study group) from 128 subjects with definite keratoconus in the opposite eye. Placido-disk-based corneal topography with TMS-4, Scheimpflug corneal tomography with Pentacam HR, and corneal biomechanical assessment with Corvis ST and ocular response analyzer (ORA) were performed. A general linear model was used to compare Corvis ST and ORA biomechanical parameters between groups, while central corneal thickness (CCT) and biomechanically corrected intraocular pressure (bIOP) were considered covariates. Receiving operator sensitivity curve (ROC) analysis was used to determine the cut-off point with the highest sensitivity and specificity along with the area under the curve (AUC) for each parameter.

Result

All parameters of Corvis ST and ORA showed a statistically significant difference between the two groups except for the first (P = 0.865) and second (P = 0.226) applanation lengths, and deformation amplitude (P = 0.936). The discriminative analysis of corneal biomechanical showed that the highest accuracy for the classic, new, and combined parameters of Corvis ST was related to HCR (AUC: 0.766), IR & DAR (0.846), and TBI (0.966), respectively. Using ORA, the corneal resistance factor (0.866) had a higher detection ability than corneal hysteresis (0.826).

Conclusions

TBI has the best accuracy and the highest effect size for differential diagnosis of normal from ACE-NT eyes with a cut-off point of 0.24.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Receiver operating characteristic (ROC) curves of some corneal biomechanical parameters using both devices in the ACE-NT (n = 128) and normal (n = 134) eyes.

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

References

  1. Ucar M, Cakmak HB, Sen B. A statistical approach to classification of keratoconus. Int J Ophthalmol. 2016;9:1355–7.

    PubMed  PubMed Central  Google Scholar 

  2. Serdarogullari H, Tetikoglu M, Karahan H, Altin F, Elcioglu M. Prevalence of keratoconus and subclinical keratoconus in subjects with astigmatism using pentacam derived parameters. Ophthalmic Vis Res. 2013;8:213–9.

    Google Scholar 

  3. Feizi S, Yaseri M, Kheiri B. Predictive ability of galilei to distinguish subclinical keratoconus and keratoconus from normal corneas. Ophthalmic Vis Res. 2016;11:8–16.

    Article  Google Scholar 

  4. Huseynli S, Abdulaliyeva F. Evaluation of scheimpflug tomography parameters in subclinical keratoconus, clinical keratoconus and normal caucasian eyes. Turk J Ophthalmol. 2018;48:99–108.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Fontes BM, Ambrosio R Jr., Velarde GC, Nose W. Corneal biomechanical evaluation in healthy thin corneas compared with matched keratoconus cases. Arq Bras Oftalmol. 2011;74:13–16.

    Article  PubMed  Google Scholar 

  6. Vinciguerra R, Ambrosio R Jr., Elsheikh A, Roberts CJ, Lopes B, Morenghi E, et al. Detection of keratoconus with a new biomechanical index. J Refract Surg. 2016;32:803–10.

    Article  PubMed  Google Scholar 

  7. Tian L, Ko MW, Wang LK, Zhang JY, Li TJ, Huang YF, et al. Assessment of ocular biomechanics using dynamic ultra high-speed Scheimpflug imaging in keratoconic and normal eyes. J Refract Surg. 2014;30:785–91.

    Article  PubMed  Google Scholar 

  8. Roberts CJ, Dupps WJ Jr. Biomechanics of corneal ectasia and biomechanical treatments. J Cataract Refract Surg. 2014;40:991–8.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Sedaghat MR, Momeni-Moghaddam H, Roberts CJ, Maddah N, Ambrósio R Jr., Hosseini SR. Corneal biomechanical parameters in keratoconus eyes with abnormal elevation on the back corneal surface only versus both back and front surfaces. Sci Rep. 2021;11:11971.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Tabbara KF, Kotb AA. Risk factors for corneal ectasia after LASIK. Ophthalmology. 2006;113:1618–22.

    Article  PubMed  Google Scholar 

  11. Li Y, Chamberlain W, Tan O, Brass R, Weiss JL, Huang D. Subclinical keratoconus detection by pattern analysis of corneal and epithelial thickness maps with optical coherence tomography. J Cataract Refract Surg. 2016;42:284–95.

    Article  PubMed  PubMed Central  Google Scholar 

  12. de Sanctis U, Loiacono C, Richiardi L, Turco D, Mutani B, Grignolo FM. Sensitivity and specificity of posterior corneal elevation measured by Pentacam in discriminating keratoconus/subclinical keratoconus. Ophthalmology. 2008;115:1534–9.

    Article  PubMed  Google Scholar 

  13. Moshirfar MMM, Murri MS, Momeni-Moghaddam H, Ronquillo YC, Hoopes PC. Advances in biomechanical parameters for screening of refractive surgery candidates a review of the literature, Part III. Med Hypothesis Discov Innov Ophthalmol. 2019;8:219–40.

    PubMed  PubMed Central  Google Scholar 

  14. Sedaghat MR, Momeni-Moghaddam H, Yekta A, Elsheikh A, Khabazkhoob M, Ambrosio R Jr, et al. Biomechanically-corrected intraocular pressure compared to pressure measured with commonly used tonometers in normal subjects. Clin Optom. 2019;11:127–33.

    Article  Google Scholar 

  15. Koh S, Ambrósio R Jr., Inoue R, Maeda N, Miki A, Nishida K. Detection of subclinical corneal ectasia using corneal tomographic and biomechanical assessments in a Japanese population. J Refract Surg. 2019;35:383–90.

    Article  PubMed  Google Scholar 

  16. Momeni-Moghaddam H, Hashemi H, Zarei-Ghanavati S, Ostadimoghaddam H, Yekta A, Aghamirsalim M, et al. Four-year changes in corneal biomechanical properties in children. Clin Exp Optom. 2019;102:489–95.

    Article  PubMed  Google Scholar 

  17. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44:837–45.

    Article  CAS  PubMed  Google Scholar 

  18. Ren S, Xu L, Fan Q, Gu Y, Yang K. Accuracy of new Corvis ST parameters for detecting subclinical and clinical keratoconus eyes in a Chinese population. Sci Rep. 2021;11:4962.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zhang H, Tian L, Guo L, Qin X, Zhang D, Li L, et al. Comprehensive evaluation of corneas from normal, forme fruste keratoconus and clinical keratoconus patients using morphological and biomechanical properties. Int Ophthalmol. 2021;41:1247–59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ferreira-Mendes J, Lopes BT, Faria-Correia F, Salomão MQ, Rodrigues-Barros S, Ambrósio R Jr. Enhanced ectasia detection using corneal tomography and biomechanics. Am J Ophthalmol. 2019;197:7–16.

    Article  PubMed  Google Scholar 

  21. Ambrósio R Jr., Lopes BT, Faria-Correia F, Salomão MQ, Bühren J, Roberts CJ, et al. Integration of scheimpflug-based corneal tomography and biomechanical assessments for enhancing ectasia detection. J Refract Surg. 2017;33:434–43.

    Article  PubMed  Google Scholar 

  22. Luz A, Lopes B, Hallahan KM, Valbon B, Fontes B, Schor P, et al. Discriminant value of custom ocular response analyzer waveform derivatives in forme fruste keratoconus. Am J Ophthalmol. 2016;164:14–21.

    Article  PubMed  Google Scholar 

  23. Catalán-López S, Cadarso-Suárez L, López-Ratón M, Cadarso-Suárez C. Corneal biomechanics in unilateral keratoconus and fellow eyes with a scheimpflug-based tonometer. Optom Vis Sci. 2018;95:608–15.

    Article  PubMed  Google Scholar 

  24. Song P, Ren S, Liu Y, Li P, Zeng Q. Detection of subclinical keratoconus using a novel combined tomographic and biomechanical model based on an automated decision tree. Sci Rep. 2022;12:5316.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Tian L, Zhang D, Guo L, Qin X, Zhang H, Zhang H, et al. Comparisons of corneal biomechanical and tomographic parameters among thin normal cornea, forme fruste keratoconus, and mild keratoconus. Eye Vis. 2021;8:44.

    Article  Google Scholar 

  26. Liu Y, Zhang Y, Chen Y. Application of a scheimpflug-based biomechanical analyser and tomography in the early detection of subclinical keratoconus in chinese patients. BMC Ophthalmol. 2021;21:339.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Guo LL, Tian L, Cao K, Li YX, Li N, Yang WQ, et al. Comparison of the morphological and biomechanical characteristics of keratoconus, forme fruste keratoconus, and normal corneas. Semin Ophthalmol. 2021;36:671–8.

    Article  PubMed  Google Scholar 

  28. Heidari Z, Hashemi H, Mohammadpour M, Amanzadeh K, Fotouhi A. Evaluation of corneal topographic, tomographic and biomechanical indices for detecting clinical and subclinical keratoconus: a comprehensive three-device study. Int J Ophthalmol. 2021;14:228–39.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Zhang M, Zhang F, Li Y, Song Y, Wang Z. Early diagnosis of keratoconus in chinese myopic eyes by combining corvis ST with Pentacam. Curr Eye Res. 2020;45:118–23.

    Article  CAS  PubMed  Google Scholar 

  30. Koc M, Aydemir E, Tekin K, Inanc M, Kosekahya P, Kiziltoprak H. Biomechanical analysis of subclinical keratoconus with normal topographic, topometric, and tomographic findings. J Refract Surg. 2019;35:247–52.

    Article  PubMed  Google Scholar 

  31. Chan TCY, Wang YM, Yu M, Jhanji V. Comparison of corneal tomography and a new combined tomographic biomechanical index in subclinical keratoconus. J Refract Surg. 2018;34:616–21.

    Article  PubMed  Google Scholar 

  32. Wang YM, Chan TCY, Yu M, Jhanji V. Comparison of corneal dynamic and tomographic analysis in normal, forme fruste keratoconic, and keratoconic eyes. J Refract Surg. 2017;33:632–8.

    Article  PubMed  Google Scholar 

  33. Kataria P, Padmanabhan P, Gopalakrishnan A, Padmanaban V, Mahadik S, Ambrósio R Jr. Accuracy of Scheimpflug-derived corneal biomechanical and tomographic indices for detecting subclinical and mild keratectasia in a South Asian population. J Cataract Refract Surg. 2019;45:328–36.

    Article  PubMed  Google Scholar 

  34. Kirgiz A, Karaman Erdur S, Atalay K, Gurez C. The role of ocular response analyzer in differentiation of forme fruste keratoconus from corneal astigmatism. Eye Contact Lens. 2019;45:83–87.

    Article  PubMed  Google Scholar 

  35. Galletti JD, Ruiseñor Vázquez PR, Fuentes Bonthoux F, Pförtner T, Galletti JG. Multivariate analysis of the ocular response analyzer’s corneal deformation response curve for early keratoconus detection. J Ophthalmol. 2015;2015:496382.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Kozobolis V, Sideroudi H, Giarmoukakis A, Gkika M, Labiris G. Corneal biomechanical properties and anterior segment parameters in forme fruste keratoconus. Eur J Ophthalmol. 2012;22:920–30.

    Article  PubMed  Google Scholar 

  37. Vinciguerra R, Ambrósio R, Elsheikh A, Roberts CJ, Lopes B, Morenghi E, et al. Detection of keratoconus with a new biomechanical index. J Refractive Surg. 2016;32:803–10.

    Article  Google Scholar 

  38. Sedaghat MR, Momeni-Moghaddam H, Ambrósio R Jr, Heidari HR, Maddah N, Danesh Z. et al. Diagnostic ability of corneal shape and biomechanical parameters for detecting frank keratoconus. Cornea. 2018;37:1025–34.

    Article  PubMed  Google Scholar 

  39. Koh S, Inoue R, Ambrósio R, Jr, Maeda N, Miki A, Nishida K. Correlation between corneal biomechanical indices and the severity of keratoconus. Cornea. 2019;00:1–7.

    Article  Google Scholar 

  40. Perez-Rueda A, Jimenez-Rodriguez D, Castro-Luna G. Diagnosis of subclinical keratoconus with a combined model of biomechanical and topographic parameters. J Clin Med. 2021;10:2746.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Wu Y, Guo LL, Tian L, Xu ZQ, Li Q, Hu J, et al. Comparative analysis of the morphological and biomechanical properties of normal cornea and keratoconus at different stages. Int Ophthalmol. 2021;41:3699–711.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Fontes BM, Ambrósio R Jr., Jardim D, Velarde GC, Nosé W. Corneal biomechanical metrics and anterior segment parameters in mild keratoconus. Ophthalmology. 2010;117:673–9.

    Article  PubMed  Google Scholar 

  43. Pinero DP, Alcon N. In vivo characterization of corneal biomechanics. J Cataract Refract Surg. 2014;40:870–87.

    Article  PubMed  Google Scholar 

  44. Shah S, Laiquzzaman M, Bhojwani R, Mantry S, Cunliffe I. Assessment of the biomechanical properties of the cornea with the ocular response analyzer in normal and keratoconic eyes. Investig Ophthalmol Vis Sci. 2007;48:3026–31.

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the personnel of Didar eye clinic and the participants who made this study possible.

Author information

Authors and Affiliations

  1. Eye Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

    Mohammad-Reza Sedaghat & Helia Shayanfar

  2. Health Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran

    Hamed Momeni-Moghaddam

  3. Department of Optometry, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran

    Javad Heravian & Atiyeh Ansari

  4. Hoopes Vision Research Center, Hoopes Vision, 11820S. State St. #200, Draper, UT, 84020, USA

    Majid Moshirfar

  5. John A. Moran Eye Center, University of Utah School of Medicine, Salt Lake City, UT, USA

    Majid Moshirfar

  6. Utah Lions Eye Bank, Murray, UT, USA

    Majid Moshirfar

Authors
  1. Mohammad-Reza Sedaghat
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hamed Momeni-Moghaddam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Javad Heravian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Atiyeh Ansari
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Helia Shayanfar
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Majid Moshirfar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed to data analysis, drafting or revising the article, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Corresponding author

Correspondence to Hamed Momeni-Moghaddam.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval

This research was approved by the Ethics Committee of the Deputy of Research of Mashhad University of Medical Sciences (Code: IR.MUMS.REC.1399.418).

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

41433_2022_2218_MOESM1_ESM.jpg

Figure S1: A patient with definite keratoconus in the left eye and asymmetric contralateral corneal ectasia with normal topography (ACE-NT) in the right eye.

41433_2022_2218_MOESM2_ESM.jpg

Figure S2: An example of a standard (top left) and ARV (Ambrosio, Roberts, Vinciguerra) printouts (bottom left) of Corvis ST and ORA (right) printout.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sedaghat, MR., Momeni-Moghaddam, H., Heravian, J. et al. Detection ability of corneal biomechanical parameters for early diagnosis of ectasia. Eye 37, 1665–1672 (2023). https://doi.org/10.1038/s41433-022-02218-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41433-022-02218-9

This article is cited by

Search

Advanced search

Quick links