Keratoconus staging by decades: a baseline ABCD classification of 1000 patients in the Homburg Keratoconus Center.

BACKGROUND: This retrospective cross-sectional study aims to analyse the keratoconus (KC) stage distribution at different ages within the Homburg Keratoconus Center (HKC). METHODS: 1917 corneae (1000 patients) were allocated to decades of age, classified according to Belin's ABCD KC grading system and the stage distribution was analysed. RESULTS: 73 per cent (n=728) of the patients were males, 27% (n=272) were females. The highest KC prevalence occurred between 21 and 30 years (n=585 corneae, 294 patients). Regarding anterior (A) and posterior (B) curvature, the frequency of A was significantly higher than B in all age groups for stage 0, 1 and 2 (A0>B0; A1>B1; A2>B2; p<0.03, Wilcoxon matched-pairs test). There was no significant difference between the number of A3 and B3, but significantly more corneae were classified as B4 than A4 in all age groups (p<0.02). The most frequent A|B combinations were A4|B4 (n=451), A0|B0 (n=311), A2|B4 (n=242), A2|B2 (n=189) and A1|B2 (n=154). Concerning thinnest pachymetry (C), most corneae in all age groups were classified as C0>C1>C2>C3>C4 (p<0.04, Wilcoxon matched-pairs test). For the best distance visual acuity (D), a significantly higher number of corneae were classified as D1 compared to D0 (p<0.008; D1>D0>D2>D3>D4). CONCLUSION: The stage distributions in all age groups were similar. Early KC rather becomes manifest in the posterior than the anterior corneal curvature whereas advanced stages of posterior corneal curvature coincide with early and advanced stages of anterior corneal curvature. Thus, this study emphasises the necessity of posterior corneal surface assessment in KC as enabled by the ABCD grading system.

Endothelial alterations in 712 keratoconus patients.

PURPOSE: To investigate the effect of the severity of keratoconus on the corneal endothelium using specular microscopy. METHODS: Seven hundred and twelve eyes from the Homburg Keratoconus Center (HKC) database were included in this retrospective study. Corneal endothelium was evaluated using the Tomey EM-3000 specular microscope. Keratoconus-related topographic and tomographic data were obtained from Scheimpflug-based tomography (Oculus Pentacam® HR). Eyes were classified into stages 0 (healthy) to 4 (severe keratoconus) according to the Topographic Keratoconus Classification (TKC). Subgroups were analysed based on contact lens (CL) type (none/rigid/soft). RESULTS: The frequencies of keratoconus stages 0/1/2/3/4 according to TKC were 169/94/206/166/77. The endothelial cell density (ECD) for the endothelial cell area for TKC 0/1/2/3/4 was 2611/2624/2557/2487/2401 cells per mm² and the coefficient of variation (CV) was 40.9/40.0/41.6/46.2/49.0%, respectively. The more severe the keratoconus stage, the lower the endothelial cell count (p < 0.001) and the higher the CV (p < 0.001). No contact lens wearing was noted in 207 eyes (NoCL), rigid CL in 200 (RCL) and soft CL in 54 (SCL). CD for NoCL/RCL/SCL was 2523/2533/2644 per mm² and CV was 41.8/54.1/43.1%, respectively. A significant difference in CV was found between NoCL and RCL (p = 0.02), and no significant difference in CV was found between NoCL and SCL (p = 0.07). Endothelial cell density (ECD) did not differ significantly between NoCL and RCL or SCL. CONCLUSION: Endothelial cell density (ECD) decreases and CV increases significantly with increasing tomographic severity of keratoconus. In patients with RCL compared to eyes without CL wear, we found a statistically significantly higher CV in the endothelial cell size.

[Intraindividual Keratoconus Progression]. / Keratokonusprogression im Seitenvergleich.

Introduction Keratoconus is a typically bilateral, progressive-extending corneal disease. The aim of this work is to evaluate the intraindividual progression of keratoconus. Patients and Methods This single-center retrospective study of disease progression based on topographic data from non-operated keratoconus patients (n = 48) was examined over a period of two years. Seven topographical keratoconus indices derived from Scheimpflug tomography were used to compare both the initial findings, as well as the progression of the fellow eyes. Results The mean observation period was 3.3 ± 0.9 years. The initial findings illustrated that a pair of eyes did not correlate with each other (p > 0.05). When comparing baseline and the progression of the individual indices, a negative correlation was found for all indices (p < 0.05). Progression and age did correlate for index smallest radius (Rmin, (R = 0.376, p = 0.008) and index of height decentration (IHD, R = 0.291, p = 0.045). Regarding the intraindividual progression, we found a weak correlation to the index of surface variance (ISV, R = - 0.399, p = 0.005), index of vertical asymmetry (IVA, R = - 0.291, p = 0.045) and the keratoconus index (KI, R = 0.307, p = 0.038). Conclusions The intraindividual asymmetry, which is typical for keratoconus, could be verified. This study suggests that the progression of keratoconus in one eye is independent of the progression in the fellow eye. In this small group of patients, age relationship to keratoconus could not be demonstrated for all keratoconus indices.

Complementary Keratoconus Indices Based on Topographical Interpretation of Biomechanical Waveform Parameters: A Supplement to Established Keratoconus Indices.

Purpose. To build new models with the Ocular Response Analyzer (ORA) waveform parameters to create new indices analogous to established topographic keratoconus indices. Method. Biomechanical, tomographic, and topographic measurements of 505 eyes from the Homburger Keratoconus Centre were included. Thirty-seven waveform parameters (WF) were derived from the biomechanical measurement with the ORA. Area under curve (ROC, receiver operating characteristic) was used to quantify the screening performance. A logistic regression analysis was used to create two new keratoconus prediction models based on these waveform parameters to resample the clinically established keratoconus indices from Pentacam and TMS-5. Results. ROC curves show the best results for the waveform parameters p1area, p2area, h1, h2, dive1, mslew1, aspect1, aplhf, and dslope1. The new keratoconus prediction model to resample the Pentacam topographic keratoconus index (TKC) was WFTKC = -4.068 + 0.002 × p2area - 0.005 × dive1 - 0.01 × h1 - 2.501 × aplhf, which achieves a sensitivity of 90.3% and specificity of 89.4%; to resample the TMS-5 keratoconus classification index (KCI) it was WFKCI = -3.606 + 0.002 × p2area, which achieves a sensitivity of 75.4% and a specificity of 81.8%. Conclusion. In addition to the biomechanically provided Keratoconus Index two new indices which were based on the topographic gold standards (either Pentacam or TMS-5) were created. Of course, these do not replace the original topographic measurement.

Comparison of 3 biometry devices in cataract patients.

PURPOSE: Accurate biometry is an obligatory preoperative measurement for refractive surgery as well as cataract surgery. A new device based on partial coherence interferometry was compared with 2 currently used biometry devices. SETTING: Department of Ophthalmology, Saarland University Medical Center, Homburg, Germany. DESIGN: Prospective case series. METHODS: Eyes of cataract patients were examined with a functional prototype of the new optical low-coherence reflectometry (OLCR) biometer OA-2000, the standard OLCR biometer Lenstar, and the partial coherence interferometry (PCI) biometer IOLMaster. The results were compared using a Wilcoxon-Mann-Whitney U test and Pearson correlation calculations. RESULTS: A total of 138 eyes of 74 cataract patients were examined. Pearson correlation showed excellent correlation for axial length, anterior chamber depth and keratometry among the 3 devices tested. The highest correlation was found between standard OLCR biometer and PCI biometer for AL, R1, and R2 (r = 1.0, r = 0.936, r = 0.952, respectively; all P ≤ .001). For anterior chamber depth (ACD), the highest correlation was found between the standard OLCR biometer and the new OLCR biometer (r = 0.943; P ≤ .001). The mean values of AL/ACD/R1/R2 differed very little, but the differences were significant (all P ≤ .05) (new OLCR biometer 23.31/3.21/7.74/7.64 mm; standard OLCR biometer 23.30/3.13/7.80/7.60 mm; PCI biometer 23.37/3.00/7.78/7.6 mm). CONCLUSIONS: Compared with other clinical instruments, the new OLCR biometer generated the most accurate results. Differences especially in measurement of axial length were statistically but not clinically significant. The new OLCR biometer yielded results that correlated very well with the values of the PCI biometer and standard OLCR biometer. FINANCIAL DISCLOSURE: None of the authors has a financial or proprietary interest in any material or method mentioned.

Can retinoscopy keep up in keratoconus diagnosis?

PURPOSE: To evaluate the diagnostic potential of retinoscopy in comparison with Amsler-grading, Pentacam and Ocular Response Analyzer (ORA) in classifying keratoconus stages. METHODS: Clinical examination, retinoscopy, Pentacam and ORA were performed in 126 patients. Data of Amsler, retinoscopy, topographic keratoconus classification (TKC) of Pentacam and keratoconus match probability (KMP) of ORA were analyzed. Each of these four classification techniques quotes keratoconus into stage 0 (normal) to 4 (severe). Descriptive analysis and cross tables were used to compare the different devices. RESULTS: For retinoscopy the distribution in the five keratoconus grades normal/suspect/mild/moderate/severe (in numbers) was 34/33/34/17/8. For Amsler it was 37/36/35/12/4, for TKC 38/17/34/31/4, for KMP 32/34/32/15/9. The cross tables show large classification differences of all devices. Overall, classification of retinoscopy and Amsler/TKC/KMP is congruent in 51.6%/36.3%/39.8% of the cases. Of all eyes, Amsler was congruent with TKC/KMP in 54.0%/48.4%, and TKC and KMP were congruent in 53.3%. In a binary decision (normal vs. any stage of mild/moderate/severe) matching between retinoscopy and Amsler/TKC/KMP was 98.6%/88.8%/82.4%. Sensitivity/specificity for retinoscopy and Amsler, TKC, KMP was 98.8%/94.0%, 84.4%/100% and 80.0%/79.1%. CONCLUSIONS: The congruence of keratoconus classification was very poor of all the techniques tested in our study. This applies to objective measures such as TKC, KMP as well as clinical classification techniques such as Amsler and retinoscopy. Compared to TKC and KMP, retinoscopy underestimates keratoconus stages. In contrast, the performance of binary decisions (normal vs. keratoconus) shows a high sensitivity and specificity. Retinoscopy, however, showed a clear clinical use in confirming the diagnosis of keratoconus.

Staging of keratoconus indices regarding tomography, topography, and biomechanical measurements.

PURPOSE: To derive limits of metric keratoconus indices for classification into keratoconus stages. DESIGN: Validity and reliability analysis of diagnostic tools. METHODS: A total of 126 patients from the keratoconus center of Homburg/Saar were evaluated with respect to Amsler criteria, using Pentacam (Keratoconus Index [KI], Topographic Keratoconus Classification [TKC]), Topographic Modeling System (Smolek/Klyce, Klyce/Maeda), and Ocular Response Analyzer (Keratoconus Match Probability [KMP], Keratoconus Match Index [KMI]). Mean value, standard deviation, 90% confidence interval, and the Youden J index for definition of the thresholds were evaluated. RESULTS: For separation of keratoconus stages 0/1/2/3/4 we derived the following optimum thresholds: for KI 1.05/1.15/1.31/1.49 and for KMI 0.77/0.32/-0.08/-0.3. For Smolek/Klyce and Klyce/Maeda high standard deviations and overlapping confidence intervals were found; therefore no discrete thresholds could be defined. Nevertheless, for them we still found a good sensitivity and specificity in discriminating between healthy (stage 0) and keratoconus (stages 2-4) eyes in comparison with the other indices. CONCLUSIONS: We derived thresholds for the metric keratoconus indices KI and KMI, which allow classification of keratoconus stages. These now need to be validated in clinical use. Smolek/Klyce and Klyce/Maeda were not sufficiently sensitive to allow classification into individual stages, but these indices did show a good specificity and sensitivity in discriminating between keratoconus and healthy eyes.

Reproducibility of the optical Biometer OA-1000 (Tomey).

AIM: The OA-1000 (Tomey, Japan) is a new optical biometer, which measures axial length (AL), anterior chamber depth (ACD), and central corneal thickness (CT) utilizing optical interference technology. The aim of this study was to prove the reproducibility which is considered fundamental for other clinical investigations. METHODS: 55 healthy volunteers were enrolled in this study. For each measurement of AL, ACD, and CT the biometer is grabbing a sequence of 10 shots and mean value (mean) and standard deviation (SD) are displayed. Five consecutive measurements were performed and average and standard deviation were assessed. Cronbach's α was derived as a quality measure for reproducibility. RESULTS: For AL measurement Cronbach's α was 1.000, for CT 0.999, and for ACD 0.979, respectively. Mean value for AL was 23.36 ± 1.03 mm, for ACD it was 3.60 ± 0.687 mm, and for CT it was 552.08 ± 29.70 µm, respectively. Standard deviation for AL was 0.013 ± 0.022 mm, for ACD 0.09 ± 0.11 mm, and for CT 2.18 ± 1.75 µm. One correlation was found between mean values for AL and ACD (R = 0.388, P = 0.005); no other correlations were found between mean values or values of standard deviation of AL, ACD, or CT. CONCLUSION: The OA-1000 shows an excellent reproducibility for measurement of AL, ACD, and CT and can be used in clinical practice.

Vignetting and field of view with the KAMRA corneal inlay.

PURPOSE: To evaluate the effect of the KAMRA corneal inlay on the retinal image brightness in the peripheral visual field. METHODS: A KAMRA inlay was "implanted" into a theoretical eye model in a corneal depth of 200 microns. Corneal radius was varied to a steep, normal, and flat (7.37, 7.77, and 8.17 mm) version keeping the proportion of anterior to posterior radius constant. Pupil size was varied from 2.0 to 5.0 mm. Image brightness was determined for field angles from -70° to 70° with and without KAMRA and proportion of light attenuation was recorded. RESULTS: In our parameter space, the attenuation in brightness ranges in between 0 and 60%. The attenuation in brightness is not affected by corneal shape. For large field angles where the incident ray bundle is passing through the peripheral cornea, brightness is not affected. For combinations of small pupil sizes (2.0 and 2.5 mm) and field angles of 20-40°, up to 60% of light may be blocked with the KAMRA. CONCLUSION: For combinations of pupil sizes and field angles, the attenuation of image brightness reaches levels up to 60%. Our theoretical findings have to be clinically validated with detailed investigation of this vignetting effect.

Comparison of the new biometer OA-1000 with IOLMaster and Tomey AL-3000.

BACKGROUND: The OA-1000 (Tomey, Japan) is a new optical biometer, which allows measurements of axial length (AL), anterior chamber depth (ACD) and corneal thickness (CT) due to partial coherence interferometry (PCI) technology. The aim of this study was to compare the OA-1000 results with those obtained with the IOLMaster and contact applanation A-scan ultrasonography. METHODS: We examined 133 eyes of 75 patients with age related cataract. Mean age was 72.0 ± 9.5 years. Biometry measurements of AL and ACD were performed with the Tomey OA-1000 based on PCI, the IOLMaster based on PCI (AL) and slit projection (ACD), and the Tomey AL-3000 based on contact applanation A-scan ultrasonography. RESULTS: Mean AL using the IOLMaster was 23.21 ± 1.08 mm, using the AL-3000 was 22.79 ± 1.04 mm, using the OA-1000 it was 22.97 ± 1.1 mm. Mean ACD using the IOLMaster was 2.99 ± 0.41 mm, using the OA-1000 3.40 ± 0.46 mm, using the Tomey AL-3000 it was 2.93 ± 0.43 mm. Mean difference between the AL and ACD measured with the OA-1000 and the IOLMaster was 0.22 ± 0.047 mm and 0.40 ± 0.33 mm, between OA-1000 and the AL-3000 it was 0.19 ± 0.23 mm and 0.47 ± 0.33 mm, and between IOLMaster and AL-3000 it was 0.42 ± 0.23 and 0.09 ± 0.36 mm. For AL the correlation coefficient R between IOLMaster and OA-1000 was 0.999, between IOLMaster and AL-3000 it was 0.976, between AL-3000 and OA-1000 it was 0.977. For ACD R between IOLMaster and OA-1000 was 0.735, between IOLMaster and AL-3000 it was 0.822, between AL-3000 and OA-1000 it was 0.716 (all p < 0.001). CONCLUSIONS: Compared with other used clinical instruments the OA-1000 generates accurate results. Although differences were found, the OA-1000 provided results that correlated well with the values of IOLMaster and AL-3000.

Precision of ocular response analyzer.

PURPOSE: To evaluate the repeatability of corneal hysteresis (CH) and corneal resistance measurements as well as the consistency of the four shots within each measurement using the ocular response analyzer (ORA, Reichert Ophthalmic Instruments, Depew, NY) and to generate a pool of data of a normal population. METHODS: A total of 45 eyes from 45 healthy volunteers without ocular pathologies and normal visual acuity were enrolled in this study. A sequence of five consecutive measurements was performed with each patient with the ORA. The biomechanical properties of the cornea in terms of CH and corneal resistance factor (CRF) were recorded, as well as the Goldmann-correlated IOP (IOPg) and cornea correlated IOP (IOPcc). The trend in each measurement sequence was analyzed and Cronbach's α was derived for the repeatability. The average of four shots within each measurement was compared with the best signal value (BSV) provided by the internal data processing of the ORA. RESULTS: Mean value for CH was 11.58 and BSV was 11.55. For CRF, mean value was 11.21 and BSV was 11.28. No significant difference was found between the average value and the BSV of one measurement (p > 0.05). No significant difference was found between the average value and the BSV of the five consecutive measurements, only IOPg showed a significant difference (p = 0.017), average value of IOPg is higher than BSV. Within a sequence of five measurements for each individual, the average values of the four shots per measurement for IOPg and IOPcc are decreasing by 1.19 and 1.05 mmHg on average. The repeatability test revealed good results for CH and CRF (all α are higher than 0.9). CONCLUSION: The ORA provides, beside intraocular pressure additional, information about the biomechanical properties of the cornea such as hysteresis and resistance. It proves to yield good repeatability for corneal hysteresis and resistance in normal subjects.

Precision of NIDEK OPD-scan measurements.

PURPOSE: To evaluate the repeatability of wavefront measurements using the NIDEK OPD-Scan. METHODS: A total of 179 eyes from 90 healthy volunteers (57 women and 33 men) with no corneal or lenticular pathology and normal visual acuity were enrolled in this study. Mean patient age was 39 years (range: 17 to 85 years). All patients underwent four consecutive measurements by one examiner with the NIDEK OPD-Scan. Total, corneal, and internal wavefront errors were measured and calculated with the device, using slit retinoscopy. Repeatability of the measurements was evaluated for spherical aberration, coma, and trefoil. RESULTS: The repeatability test revealed a good result for all three higher order aberrations evaluated. The best repeatability values were found for total aberrations, followed by internal and corneal aberrations. CONCLUSIONS: The NIDEK OPD-Scan has good precision in the wavefront measurement of total, corneal, and internal optical aberrations.