4.5 Article

Comparisons of corneal biomechanical and tomographic parameters among thin normal cornea, forme fruste keratoconus, and mild keratoconus

期刊

EYE AND VISION
卷 8, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s40662-021-00266-y

关键词

Thin normal cornea; Forme fruste keratoconus; Mild keratoconus; Corneal biomechanical parameters

资金

  1. National Natural Science Foundation of China [31370952, 31470914, 31600758, 82171101]
  2. Beijing Nova Program [Z181100006218099]
  3. Open Research Fund from Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing Tongren Hospital, Beihang University & Capital Medical University [BHTR-KFJJ-202001]

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Through matching CCT using Scheimpflug imaging and Corvis ST technology, the study found significant differences in dynamic corneal response and tomographic parameters among FFKC, MKC, and TNC eyes with TCT <= 500μm. Some parameters showed good potential for differentiating between different eye conditions.
Background To compare the dynamic corneal response (DCR) and tomographic parameters of thin normal cornea (TNC) with thinnest corneal thickness (TCT) (<= 500 mu m), forme fruste keratoconus (FFKC) and mild keratoconus (MKC) had their central corneal thickness (CCT) matched by Scheimpflug imaging (Pentacam) and corneal visualization Scheimpflug technology (Corvis ST). Methods CCT were matched in 50 eyes with FFKC, 50 eyes with MKC, and 53 TNC eyes with TCT <= 500 mu m. The differences in DCR and tomographic parameters among the three groups were compared. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic significance of these parameters. Back propagation (BP) neural network was used to establish the keratoconus diagnosis model. Results Fifty CCT-matched FFKC eyes, 50 MKC eyes and 50 TNC eyes were included. The age and biomechanically corrected intraocular pressure (bIOP) did not differ significantly among the three groups (all P > 0.05). The index of height asymmetry (IHA) and height decentration (IHD) differed significantly among the three groups (all P < 0.05). IHD also had sufficient strength (area under the ROC curves (AUC) > 0.80) to differentiate FFKC and MKC from TNC eyes. Partial DCR parameters showed significant differences between the MKC and TNC groups, and the deflection amplitude of the first applanation (A1DA) showed a good potential to differentiate (AUC > 0.70) FFKC and MKC from TNC eyes. Diagnosis model by BP neural network showed an accurate diagnostic efficiency of about 91%. Conclusions The majority of the tomographic and DCR parameters differed among the three groups. The IHD and partial DCR parameters assessed by Corvis ST distinguished FFKC and MKC from TNC when controlled for CCT.

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