Early diagnosis of subclinical keratoconus by wavefront parameters using Scheimpflug, Placido and Hartmann–Shack based devices

Combined corneal biomechanical and tomographical indices in subclinical and forme fruste keratoconus

PURPOSE

Evaluation of combined corneal tomographic and biomechanical parameters in subclinical/forme fruste keratoconus (ScKC/FFKC).

DESIGN

Cross-sectional observational case-control study.

METHODS INCLUSION CRITERIA

Thirty-one eyes with ScKC (fellow eye of KC with any one sign: keratometry >47 diopters, cylinder >1.5 D, central corneal thickness <500 µm, with/without abnormal topography) or FFKC (fellow eye of KC with normal topography and slit lamp examination) >13 years (cases) and 44 eyes of age-matched 22 healthy subjects (controls).

EXCLUSION CRITERIA

Clinically diagnosed KC, presence of corneal scars, and prior ocular surgery eyes.

STUDY PARAMETERS

Sixteen Pentacam, 15 Corvis ST, and five Sirius parameters were analyzed using paired sample t -test, and a subsample found to be significantly different was used in receiver operating characteristic curve analysis. The Youden index was calculated, and Pearson's correlation analysis was done.

RESULTS

Five Pentacam, three Corvis ST, and two Sirius parameters had an area under curve (AUC) >0.75. Tomographic and biomechanical index (TBI) (cutoff 0.59, 95% specificity, 77% sensitivity), Belin Ambrosio enhanced ecstasia display (cutoff 1.8, 81% specificity, 80% sensitivity), and symmetry index of posterior corneal curvature (cutoff 0.16, 97% specificity, 67% sensitivity) best identified early KC. TBI strongly correlated with maximum Pentacam parameters in both cases and controls. Corvis biomechanical index strongly correlated only in cases, and SP-A1-SD weakly correlated in cases.

CONCLUSION

Upon combined analysis, the average sensitivity and specificity, respectively, of top three parameters (according to AUC) from Pentacam and Corvis ST were 74.1% and 95.4% for posterior elevation and TBI.

TRIAL REGISTRATION

The trial was registered in Clinical Trial Registry of India on January 28, 2022. The Trial Registration Number is REF/2022/01/050638.

Multi-modal imaging for the detection of early keratoconus: a narrative review

Keratoconus is a common progressive corneal disorder that can be associated with significant ocular morbidity. Various corneal imaging techniques have been used for the diagnosis of established cases. However, in the early stages of the disease, which include subclinical keratoconus and forme fruste keratoconus, detection of such cases can be challenging. The importance of detecting such cases is very important because early intervention can halt disease progression, improve visual outcomes and prevent postrefractive surgery ectasia associated with performing corneal refractive procedures in such patients. This narrative review aimed to examine several established and evolving imaging techniques for the detection of early cases of keratoconus. The utilization of combinations of these techniques may further increase their diagnostic ability.

Comparing the clinical applicability of wavefront phase imaging in keratoconus versus normal eyes

The aim of this work is to quantitatively assess the wavefront phase of keratoconic eyes measured by the ocular aberrometer t·eyede (based on WaveFront Phase Imaging Sensor), characterized by a lateral resolution of 8.6 µm without requiring any optical element to sample the wavefront information. We evaluated the parameters: root mean square error, Peak-to-Valley, and amplitude of the predominant frequency (Fourier Transform analysis) of a section of the High-Pass filter map in keratoconic and healthy cohorts. Furthermore, we have analyzed keratoconic eyes that presented dark-light bands in this map to assess their period and orientation with the Fourier Transform. There are significant statistical differences (p value < 0.001) between healthy and keratoconic eyes in the three parameters, demonstrating a tendency to increase with the severity of the disease. Otherwise, the quantification of the bands reveals that the width is independent of eye laterality and keratoconic stage as orientation, which tends to be oblique. In conclusion, the quantitative results obtained with t·eyede could help to diagnose and monitor the progression of keratoconus.

Comparison of different corneal imaging modalities using artificial intelligence for diagnosis of keratoconus: a systematic review and meta-analysis

PURPOSE

This review was designed to compare different corneal imaging modalities using artificial intelligence (AI) for the diagnosis of keratoconus (KCN), subclinical KCN (SKCN), and forme fruste KCN (FFKCN).

METHODS

A comprehensive systematic search was conducted in scientific databases, including Web of Science, PubMed, Scopus, and Google Scholar based on the PRISMA statement. Two independent reviewers assessed all potential publications on AI and KCN up to March 2022. The Critical Appraisal Skills Program (CASP) 11-item checklist was used to evaluate the validity of the studies. Eligible articles were categorized into three groups (KCN, SKCN, and FFKCN) and included in the meta-analysis. The pooled estimate of accuracy (PEA) was calculated for all selected articles.

RESULTS

The initial search yielded 575 relevant publications, of which 36 met the CASP quality criteria and were included in the analysis. Qualitative assessment showed that Scheimpflug and Placido combined with biomechanical and wavefront evaluations improved KCN detection (PEA, 99.2, and 99.0, respectively). The Scheimpflug system (92.25 PEA, 95% CI, 94.76-97.51) and a combination of Scheimpflug and Placido (96.44 PEA, 95% CI, 93.13-98.19) had the highest diagnostic accuracy for the detection of SKCN and FFKCN, respectively. The meta-analysis outcomes showed no significant difference between the CASP score and accuracy of the publications (all P > 0.05).

CONCLUSIONS

Simultaneous Scheimpflug and Placido corneal imaging methods provide high diagnostic accuracy for early detection of keratoconus. The use of AI models improves the discrimination of keratoconic eyes from normal corneas.

Corneal layer thickness in keratoconus using optical coherence tomography

CLINICAL RELEVANCE

Accurate thickness measurement of corneal layers using anterior segment OCT can be used to improve visual outcomes. Understanding its applications is essential for optometric practices to enhance eye care procedures.

BACKGROUND

To evaluate the thicknesses of different corneal layers for identifying keratoconus (KCN) and subclinical keratoconus (SKCN) using spectral-domain optical coherence tomography (SD-OCT).

METHODS

This prospective study analyzed 60 eyes with KCN, 48 eyes with SKCN, and 53 normal eyes. The central corneal thickness (CCT) and thicknesses of the epithelium, Bowman, stroma, and Descemet-endothelium layers were measured using SD-OCT. One way analysis of variance and the area under the curve (AUC) were used to evaluate the parameters. The Delong method was used to compare AUCs.

RESULTS

In KCN, CCT and thicknesses of epithelium, Bowman, stroma, and Descemet-endothelium layers were 495.5 ± 41.7, 52.6 ± 6.4,11.5 ± 1.4, 415.5 ± 38.9, and 12.3 ± 1.7 µm, respectively. These thickness values were respectively 524.5 ± 33.3, 56.8 ± 6.8, 11.5 ± 1.6, 439.8 ± 30.6, and 12.4 ± 1.7 µm in SKCN and 563.8 ± 37.9, 57.7 ± 6.9, 12.2 ± 1.6, 469.5 ± 33.7, and 12.8 ± 2.1µm in normal group. Total cornea and stroma in KCN and SKCN, and epithelium in KCN were significantly thinner compared to the normal group (P < 0.001). The highest AUC values were observed for CCT in KCN (AUC 0.90) and SKCN (AUC 0.782). The diagnostic accuracy was significantly higher for stromal thickness in KCN (sensitivity 81.7%, specificity 73.6%, AUC 0.871) and SKCN (sensitivity 80.0%, specificity 56.6%, AUC 0.751) than other individual corneal layers (Delong, P < 0.001)                                    .

CONCLUSION

CCT can accurately distinguish keratoconus from normal eyes. However, central corneal stromal thinning was the most sensitive diagnostic index for early detection of SKCN. Developing standardized stromal maps may be helpful for detecting SKCN.

Advanced Corneal Imaging in Keratoconus: A Report by the American Academy of Ophthalmology

PURPOSE

To review the published literature on the diagnostic capabilities of the newest generation of corneal imaging devices for the identification of keratoconus.

METHODS

Corneal imaging devices studied included tomographic platforms (Scheimpflug photography, OCT) and functional biomechanical devices (imaging an air impulse on the cornea). A literature search in the PubMed database for English language studies was last conducted in February 2023. The search yielded 469 citations, which were reviewed in abstract form. Of these, 147 were relevant to the assessment objectives and underwent full-text review. Forty-five articles met the criteria for inclusion and were assigned a level of evidence rating by the panel methodologist. Twenty-six articles were rated level II, and 19 articles were rated level III. There were no level I evidence studies of corneal imaging for the diagnosis of keratoconus found in the literature. To provide a common cross-study outcome measure, diagnostic sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were extracted. (A perfect diagnostic test that identifies all cases properly has an AUC of 1.0.) RESULTS: For the detection of keratoconus, sensitivities for all devices and parameters (e.g., anterior or posterior corneal curvature, corneal thickness) ranged from 65% to 100%. The majority of studies and parameters had sensitivities greater than 90%. The AUCs ranged from 0.82 to 1.00, with the majority greater than 0.90. Combined indices that integrated multiple parameters had an AUC in the mid-0.90 range. Keratoconus suspect detection performance was lower with AUCs ranging from 0.66 to 0.99, but most devices and parameters had sensitivities less than 90%.

CONCLUSIONS

Modern corneal imaging devices provide improved characterization of the cornea and are accurate in detecting keratoconus with high AUCs ranging from 0.82 to 1.00. The detection of keratoconus suspects is less accurate with AUCs ranging from 0.66 to 0.99. Parameters based on single anatomic locations had a wide range of AUCs. Studies with combined indices using more data and parameters consistently reported high AUCs.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Early, Forme Fruste keratoconus and normal thin cornea, evaluation of sensitive parameters by combined Placido Scheimpflug topography

PURPOSE

To determine the sensitive indices distinguishing forme-fruste keratoconus (FFKC) and early keratoconus (early KC) from thin normal corneas, and their cutoff values using Sirius topography.

METHODS

156 eyes with normal thin corneas < 500 um (group 1), 99 eyes with early KC (group 2) and 41 eyes with FFKC (group 3), were assessed retrospectively for: corneal keratometric indices, pachymetry indices, corneal aberrations, elevation indices; thinnest corneal point elevation, Q value, root mean square (RMS) withRMS/ area (RMS/A); and KC summary indices of front and back surfaces; surface asymmetry index (SIf, SIb), elevation at KC vertex (KVf, KVb), Baiocchi-Calossi-Versaci index (BCVf, BCVb) and summation of its vector (BCV). Cutoff values were calculated.

RESULTS

Keratometry indices were significantly different between early KC and thin normal cases (apex front curvature had the highest area-under-the-ROC-curve (AUROC) (0.926) in early KC, while only apex curvature and coordinates were significant in FFKC cases. Pachymetry indices did not show any significance in differentiating either early KC or FFKC from normal thin corneas. KC summary indices were highly significant among the 3 groups. The highest AUROC was observed with KVb in early KC (0.987) and with KVf in FFKC (0.831). Vertical coma and vertical trefoil showed the highest significance of all aberration parameters differentiating the 3 groups. Thinnest point elevation, RMS and RMS/A showed the highest AUROC in differentiating early KC and FFKC cases from thin normal corneas.

CONCLUSION

Comparing early KC and FFKC to thin normal corneas, Sirius provided high precision in prediction.

Prevalence of subclinical keratoconus and impact on adults undergoing routine, uncomplicated age-related cataract extraction

Aim

To determine the prevalence of subclinical keratoconus (SKCN) among individuals undergoing routine, uncomplicated age-related cataract surgery and its impact on visual and refractive outcomes.

Patient and Methods

At a major academic ophthalmology department in the United States, we reviewed records of patients aged 50 years and older who underwent surgery from January 2011 to June 2022. We excluded patients who had poor-quality or unreliable tomographic data, previous corneal surgery, keratorefractive procedures, and significant vision-limiting ocular pathology. We defined SKCN if an eye had a Belin-Ambrósio enhanced ectasia index (BAD-D) ≥1.7, which was based on the results of a meta-analysis of large studies. In addition to the BAD-D cutoff, the eye had to deviate significantly on at least one of seven additional parameters: 1) posterior elevation at thinnest point, 2) index of vertical asymmetry, 3) index of surface variation, 4) total front higher order aberrations, 5) front vertical coma, 6) front secondary vertical coma, 7) back vertical coma. An individual had SKCN if at least one eye met the tomography-based classification and did not have manifest KCN in either eye. Visual and refractive outcomes data were acquired from patients of one experienced cataract surgeon with cases done from July 2021 to June 2022. Statistical significance was set at p < 0.05.

Results

Among 5592 eyes from 3828 individuals, the prevalence of SKCN was 24.7% (95% CI, 23.4 - 26.1, 945 individuals), and the prevalence of KCN was 1.9% (95% CI, 1.6 - 2.4, 87 individuals). The prevalence of SKCN did not increase with age and was more prevalent among females and non-white races. Median post-operative month one distance-corrected visual acuity (DCVA) and proportion of eyes with improvement in DCVA were similar between normal and SKCN eyes. The proportion of eyes reaching ±0.5 and ±1.0 diopter within the refractive target were similar between normal and SKCN eyes.

Conclusion

SKCN is highly prevalent and should be detected but is unlikely to have a significant deleterious effect on outcomes in routine, uncomplicated cataract surgery.

Corneal characteristics in Down syndrome patients with normal and keratoconic cornea

Purpose

To determine the reference range of corneal indices in Down syndrome patients with normal corneas (DS-N) and to compare it with the corneal indices in Down syndrome patients with keratoconic corneas (DS-KC).

Methods

A study was conducted using the data of 154 eyes of 154 DS-N and 25 eyes of 25 DS-KC patients. Eighteen indices related to thickness, anterior chamber, keratometry, elevation, and aberrations routinely used for KC diagnosis were extracted from the Pentacam.

Results

The mean age of the participants in DS-N and DS-KC groups was 16.73 ± 4.70 and 16.56 ± 4.22 years (P = 0.852). In the DS-N group, 95% CI were 511.65–520.31 for minimum corneal thickness, 2.97–3.07 for anterior chamber depth (ACD), 46.83–47.37 for maximum keratometry (Kmax), 46.13–46.62 for zonal Kmax at 3 mm, 0.35–0.58 for inferior-superior asymmetry (I-S value), 1.56–1.88 for Belin/Ambrósio display-total deviation, 8.65–10.79 for best-fit-sphere posterior elevation at the thinnest point, and 0.18–0.22 for corneal vertical coma. The age-related change in I-S value and corneal spherical aberration (SA) was significant (both P < 0.05). There were significant inter-gender differences in 11 indices; the female DS patients had shallower, steeper, more elevated, and more aberrated corneas (all P < 0.05). There were significant differences in all indices except for ACD (P = 0.372) and corneal SA (P = 0.169) between DS-N and DS-KC groups.

Conclusion

In DS patients aged 10–30 years, the reference ranges of corneal indices are different from the range reported for non-DS subjects and are close to values reported for mild KC non-DS cases. The normal values are different between DS male and female; hence, sex-specific ranges should be considered for diagnosis of corneal abnormality in DS patients.

Comparison of Anterior Corneal Aberrometry, Keratometry and Pupil Size with Scheimpflug Tomography and Ray Tracing Aberrometer

This study aimed to assess the anterior corneal wavefront aberrations, keratometry, astigmatism vectors and pupil size between Pentacam HR® (Oculus Optikgeraete GmbH, Wetzlar, Germany) and iTrace® (Tracey Technologies Corp., Houston, TX, USA). In this observational study, 100 eyes (50 healthy volunteers) were scanned in mesopic light condition with a Pentacam HR® and iTrace®. Anterior corneal aberrations (spherical aberration (Z40), vertical coma (Z3 − 1), horizontal coma (Z3 + 1)), keratometry in the flattest (K1) and steepest meridian (K2), mean astigmatism, astigmatic vectors (J0 and J45), and pupil size were measured. We found a significant difference in Z40 (Pentacam®: +0.30 ± 0.11 µm and iTrace®: −0.03 µm ± 0.05 µm; p < 0.01) with no correlation between the devices (r = −0.12, p = 0.22). The devices were in complete agreement for Z3 − 1 (p = 0.78) and Z3 + 1 (p = 0.39), with significant correlation between the machines (r = −0.38, p < 0.01 and r = −0.6, p < 0.01). There was no difference in K1, K2 and mean astigmatism. J0 was negative with both devices (against-the-rule astigmatism), but there was no correlation. J45 was negative with the Pentacam HR® (more myopic oblique astigmatism) but significantly correlated between the devices. Pupil size was smaller with Pentacam HR® (p < 0.01). In summary, these devices cannot be used interchangeably. Corneal Z40 was significantly different with more negative Z40 with iTrace® compared to Pentacam HR®. iTrace® operates with lower illumination, giving larger pupil size than Pentacam HR®, which uses intense blue light during measurement. No correlation was found for J0. Pentacam HR® had a trend to record more negative J45 (myopic oblique astigmatism).

Evaluation of corneal topography, pachymetry and higher order aberrations for detecting subclinical keratoconus

PURPOSE

To compare corneal topography, pachymetry and higher order aberrations in keratoconic and normal eyes; to investigate their association in keratoconic eyes; and to determine their diagnostic ability for detecting subclinical keratoconus in a Nepalese population.

METHODS

Ninety-six eyes of 48 keratoconus patients and 50 normal eyes of 50 control subjects were included in this study. The eyes of keratoconus patients were classified into four different study groups: subclinical, stage 1, stage 2 and advanced stage keratoconus. In each eye, corneal topography, pachymetry and corneal aberrometry indices were measured using a Sirius corneal tomographer. The study parameters of keratoconic eyes were compared with normal eyes, and the possible association of corneal aberrometry with topography and pachymetry indices was investigated. The area under curve (AUC) of receiver operating characteristic (ROC) curves along with optimal cutoff values with best sensitivity and specificity were also determined for each index to detect subclinical keratoconus.

RESULTS

All the indices except average keratometry measurements (K_avg and mm_avg ) and spherical aberration (SA) were found to be significantly different in subclinical keratoconus compared to the control group (p < 0.05). In keratoconic eyes, all corneal aberrations were significantly correlated with the topography and pachymetry indices (range of ρ: -0.25 to 0.96; all p < 0.05) except for trefoil and minimum corneal thickness (Thk_min ). All the indices except K_avg , mm_avg and SA showed excellent diagnostic ability (AUC > 0.90) in detecting subclinical keratoconus. The cutoff values proposed for the asymmetry index of the corneal back surface (SI_b ), Strehl ratio of point spread function (PSF), coma and Baiocchi-Calossi-Versaci index of corneal back surface (BCV_b ) each showed excellent sensitivity (100%) and specificity (≥97%).

CONCLUSIONS

Corneal higher order aberrations were found to be significantly elevated in subclinical keratoconus compared to healthy controls. SI_b , PSF, coma and BCV_b were identified as the most powerful Sirius indices for the detection of subclinical keratoconus.

Agreement between anterior segment swept source-OCT and Scheimpflug imaging corneal aberration measurements in healthy eyes

PURPOSE

To assess agreement between corneal aberration measurements made through swept-source optical coherence tomography using a new anterior segment imaging device (Anterion) and a Scheimpflug imaging device (Pentacam HR) in healthy subjects.

METHODS

Cross-sectional study. In 50 eyes of 50 healthy subjects, 14 aberration parameters (7 across the anterior corneal surface and 7 across the total surface) were measured in 4 mm and 6 mm optic zones using each device: oblique trefoil (Z3_-3), vertical coma (Z3_-1), horizontal coma (Z3_1), horizontal trefoil (Z3_3), spherical aberration (Z4_0), root mean square (RMS) lower order aberrations (LOA) and RMS higher order aberrations (HOA). Data for the two devices were compared through intraclass correlation coefficients (ICC), paired t tests, limits of agreement (LoA) and Bland Altman plots.

RESULTS

Vertical coma was the only corneal aberration parameter that consistently showed excellent agreement (ICC > 0.8, mean difference -0.019, LoA -0.165 to 0.126). Good agreement (ICC = 0.75) between the devices was observed for RMS HOA, but this was slightly worse in the 6 mm optical zone (ICC = 0.667 for anterior RMS HOA). No over- or underestimation trend by one or other device was noted. Agreement was poor to moderate for the rest of the corneal parameters (ICC 0.2 to 0.7).

CONCLUSION

Despite good agreement overall for vertical coma and RMS HOA values, agreement for the remaining corneal aberration measurements was poor to moderate. As mean differences in our sample were overall small, in normal eyes these devices could be clinically judged as interchangeable.

Comparison of Artificial Intelligence-Based Machine Learning Classifiers for Early Detection of Keratoconus

Purpose

To compare the agreement between artificial intelligence (AI)-based classifiers and clinical experts in categorizing normal cornea from ectatic conditions.

Methods

Prospective diagnostic test study at Noor Eye Hospital. Two hundred twelve eyes of 212 patients were categorized into three groups of 92 normal, 52 subclinical keratoconus (SKCN), and 68 KCN eyes based on clinical findings by 3 independent expert examiners. All cases were then categorized using four different classifiers: Pentacam Belin/Ambrosio enhanced ectasia total deviation value (BADD) and Topographic Keratoconus Classification (TKC), Sirius Phoenix, and OPD-Scan III Corneal Navigator. The performance of classifiers and their agreement with expert opinion were investigated using the sensitivity, specificity, and Kappa index (κ).

Results

For detecting SKCN, Phoenix had the highest agreement with the clinical diagnosis (sensitivity, specificity, and κ of 84.62%, 90.0%, and 0.70, respectively) followed by BADD (55.56%, 86.08%, 0.42), TKC (26.92%, 97.50%, 0.30), and Corneal Navigator (30.77%, 93.75%, 0.29). For KCN diagnosis, the highest agreement with expert opinion was seen for Phoenix (80.02%, 96.60%, 0.79), BADD (95.59%, 85.42%, 0.75), TKC (95.59%, 84.03%, 0.73), and Corneal Navigator (67.65%, 96.45%, 0.68). Analysis of different classifiers showed that Phoenix had the highest accuracy for differentiating KCN (91.24%) and SKCN (88.68%) compared to other classifiers.

Conclusions

Although AI-based classifiers, especially Sirius Phoenix, can be very helpful in detecting early keratoconus, they cannot replace clinical experts’ opinions, particularly for decision-making before refractive surgery. Albeit, there may be concerns about the accuracy of clinical experts as well.

Artificial intelligence applications in different imaging modalities for corneal topography

Interpretation of topographical maps used to detect corneal ectasias requires a high level of expertise. Several artificial intelligence (AI) technologies have attempted to interpret topographic maps. The purpose of this study is to provide a review of AI algorithms in corneal topography from the perspectives of an eye care professional, a biomedical engineer, and a data scientist. A systematic literature review using Web of Science, Pubmed, and Google Scholar was performed from 2010 to 2020 on themes regarding imaging modalities, their parameters, purpose, and conclusions and their samples and performance related to AI in corneal topography. We provide a comprehensive summary of advances in corneal imaging and its applications in AI. Combined metrics from the Dual Scheimpflug and Placido device could be a good starting point to try AI models in corneal imaging systems. The range of area under the receiving operating curve for AI in keratoconus detection and classification was from 0.87 to 1, sensitivity was from 0.89 to 1, and specificity was from 0.82 to 1. A combination of different types of AI applications to corneal ectasia diagnosis is recommended.

Analysis of OPD-Scan and Pentacam Parameters for Early Keratoconus Detection

BACKGROUND

PURPOSE: To evaluate Pentacam and OPD-Scan parameters in the early detection of keratoconus.

DESIGN

Retrospective case-control study.

METHODS

Case group included 50 clinically unaffected fellow eyes diagnosed with asymmetric keratoconus showing subtle qualitative changes at the 0.5-D sensitivity OPD-Scan scale, as well as normal anterior and back elevation difference map at Belin/Ambrósio enhanced ectasia display (BAD) at the Pentacam. Control group included 172 normal eyes that underwent Lasik surgery and presented no complications throughout the 2-year follow-up period. OPD-Scan and Pentacam parameters were compared, calculating sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). A multivariate analysis was performed using Pentacam or OPD-Scan variables, and a model using variables of both devices.

RESULTS

Pentacam variables with AUC ≥0.8 were keratoconus index (0.85), index of height decentration (0.81), and overall deviation at BAD (0.8). OPD-Scan variables with AUC ≥0.8 were keratoconus prediction index (0.83), surface asymmetry index (0.83), and total of higher-order trefoil aberration (0.8). In the multivariate analysis, the AUC was 0.85 in the case of OPD-Scan whereas it was 0.89 in the case of Pentacam. When combining all variables from the 2 devices, the AUC was 0.93, with a sensitivity of 82% and a specificity of 94%.

CONCLUSIONS

Several parameters of OPD-Scan and Pentacam can be useful to differentiate cases from normal control eyes, demonstrating even better results when combining parameters of both devices. Anterior corneal indexes were the most important parameters to discriminate both groups.

Crosslinking und Keratokonus

Ein Keratokonus führt zu einer progressiven Vorwölbung und Verdünnung der Hornhaut. Um dies aufzuhalten, kann ein Crosslinking durchgeführt werden. Dabei ist eine Behandlung nach dem „Dresdener Protokoll“ eine effektive und sichere Behandlungsmöglichkeit, aber auch zahlreiche neue Anwendungsprotokolle (akzeleriertes Crosslinking, transepitheliales Crosslinking) und sogar weitere Indikationen (refraktive Eingriffe, infektiöse Keratitis) wurden in den letzten Jahren veröffentlicht.

[Crosslinking and Keratoconus]

Keratoconus leads to a progressive protrusion and thinning of the cornea. In order to stop this, corneal crosslinking can be performed if the progression of the disease is proven. Crosslinking according to the "Dresden protocol" includes abrasion of the corneal epithelium, application of riboflavin eye drops and irradiation with UV-A light of an intensity of 3 mW/cm² for 30 minutes. The efficacy has been shown in several prospective randomized studies. One of the more recent developments is accelerated crosslinking, which allows a shorter irradiation time. On the other hand, the possibility of transepithelial crosslinking was presented, which does not require an abrasion of the cornea. This should reduce the occurrence of postoperative pain. The range of indications has also been expanded. Corneal crosslinking is used for post-LASIK keratectasia as well. It is also being considered for use in infectious keratitis. Topographically controlled crosslinking can likewise be used to try to positively influence the refractive power of the cornea. The risks of crosslinking include the occurrence of pain, haze or scarring, endothelial cell damage and, rarely, the occurrence of keratitis.

Evaluation of corneal topographic, tomographic and biomechanical indices for detecting clinical and subclinical keratoconus: a comprehensive three-device study

AIM

To evaluate the diagnostic ability of topographic and tomographic indices with Pentacam and Sirius as well as biomechanical parameters with Corvis ST for the detection of clinical and subclinical forms of keratoconus (KCN).

METHODS

In this prospective diagnostic test study, 70 patients with clinical KCN, 79 patients with abnormal findings in topography and tomography maps with no evidence on clinical examination (subclinical KCN), and 68 normal control subjects were enrolled. The accuracy of topographic, tomographic, and biomechanical parameters was evaluated using the area under the receiver operating characteristic curve (AUC) and cross-validation analysis. The Delong method was used for comparing AUCs.

RESULTS

In distinguishing KCN from normal, all parameters showed statistically significant differences between the two groups (P<0.001). Indices with the perfect diagnostic ability (AUC≥0.999) were Sirius KCN vertex of back (KVb), Pentacam random forest index (PRFI), Pentacam index of height decentration (IHD), and Corvis integrated tomographic/biomechanical index (TBI). In distinguishing subclinical KCN from normal, Sirius symmetry index of back (SIb; AUC=0.908), Pentacam inferior-superior difference (IS) value (AUC=0.862), PRFI (AUC=0.847), and Corvis TBI (AUC=0.820) performed best. There were no significant differences between the highest AUCs within keratoconic groups (DeLong, P>0.05).

CONCLUSION

In clinical KCN, all topographic, tomographic, and biomechanical indices have acceptable outcomes in terms of sensitivity and specificity. However, in differentiating subclinical forms of KCN from normal corneas, curvature-based parameters (SIb and IS value) followed by integrated indices (PRFI and TBI) are the most powerful tools for early detection of KCN.

Tomography-based definition of keratoconus for Down syndrome patients

Background

To assess the diagnostic ability of Pentacam HR (Oculus Optikgeräte, GmbH, Wetzlar, Germany) tomographic indices in discriminating keratoconus (KC) and KC suspect (KCS) in 10- to 30-year-old patients with Down syndrome (DS).

Methods

In this study, DS patients were enrolled through special needs schools, the National Down Syndrome Society, and relevant non-profit organizations. Diagnoses were made independently by two experienced specialists. Forty Pentacam indices related to corneal thickness, volume, density, keratometry, power, shape, aberration, and elevation were extracted. For each index, the accuracy for KC and KCS diagnosis was evaluated using discriminant analysis and the area under receiver operating characteristic curve (AUROC). From each enrolled case, data from only one eye was entered in the analyses.

Results

Analyses were performed on data from 25 KC, 46 KCS, and 154 non-ectatic DS eyes. The best discriminants for KC were anterior higher order aberrations (HOA) (cutoff > 0.643, AUROC = 0.879), posterior vertical coma (cutoff > 0.0702 μm, AUROC = 0.875), anterior vertical coma (cutoff > 0.4124 μm, AUROC = 0.868), and total HOA (cutoff > 0.608, AUROC = 0.867). The difference between AUROCs were not statistically significant (all P > 0.05). For KCS, the best discriminants were minimum corneal thickness (cutoff ≤ 480.0 μm, AUROC = 0.775), corneal volume (cutoff ≤ 55.3 μm, AUROC = 0.727) and Belin Ambrosio display-total deviation (BAD-D) (cutoff > 2.23, AUROC = 0.718) with no significant difference between AUROCs (all P > 0.05).

Conclusions

In this sample of DS patients, best KC discriminators were HOA and coma which showed good diagnostic ability. For KCS, best predictors were minimum corneal thickness, corneal volume, and BAD-D with relatively good diagnostic ability. Defining a new set of KC diagnostic criteria for DS patients is suggested.

A predictive model for early diagnosis of keratoconus

BACKGROUND

The diagnosis of keratoconus in the early stages of the disease is necessary to initiate an early treatment of keratoconus. Furthermore, to avoid possible refractive surgery that could produce ectasias. This study aims to describe the topographic, pachymetric and aberrometry characteristics in patients with keratoconus, subclinical keratoconus and normal corneas. Additionally to propose a diagnostic model of subclinical keratoconus based in binary logistic regression models.

METHODS

The design was a cross-sectional study. It included 205 eyes from 205 patients distributed in 82 normal corneas, 40 early-stage keratoconus and 83 established keratoconus. The rotary Scheimpflug camera (Pentacam® type) analyzed the topographic, pachymetric and aberrometry variables. It performed a descriptive and bivariate analysis of the recorded data. A diagnostic and predictive model of early-stage keratoconus was calculated with the statistically significant variables.

RESULTS

Statistically significant differences were observed when comparing normal corneas with early-stage keratoconus/ in variables of the vertical asymmetry to 90° and the central corneal thickness. The binary logistic regression model included the minimal corneal thickness, the anterior coma to 90° and posterior coma to 90°. The model properly diagnosed 92% of cases with a sensitivity of 97.59%, specificity 98.78%, accuracy 98.18% and precision 98.78%.

CONCLUSIONS

The differential diagnosis between normal cases and subclinical keratoconus depends on the mínimum corneal thickness, the anterior coma to 90° and the posterior coma to 90°.