Optical coherence tomography imaging in keratoconus

Topographic Keratoconus Incidence in Greece Diagnosed in Routine Consecutive Cataract Procedures: A Consecutive Case Series of 1250 Cases over 5 Years

Background: Scheimpflug tomography has for many years been an integral part of our pre-operative assessment in cataract extraction. We retrospectively reviewed the incidence of topographic keratoconus and keratoconus suspicion in our routine cataract surgery population over 5 years. Setting: The Laservision Clinical and Research Institute, Athens, Greece. Methods: In 1250 consecutive cataract surgery cases in otherwise naïve eyes, accounting for years 2017 to 2021, we retrospectively evaluated preoperative Pentacam HR imaging. The cases already classified as keratoconus were included in group A. The residual cases were assessed by five different experienced evaluators (two ophthalmic surgeons and three optometrists) for topographic and tomographic keratoconus suspicion based on irregular pachymetry distribution, astigmatism truncation, and/or astigmatic imaging irregularity and included in group B. Regular corneas, by this assessment, were included in group C; irregular corneas, as determined by the evaluators but unrelated to keratoconus, were included in group D. Results: Based on the above, 138 cases (11.08%) were classified by Pentacam tomography as keratoconus and by default were included in group A. Of the residual cases, 314 or 25.12% were classified as suspect keratoconus and included in group B; 725 cases (58%) were classified as normal and non-keratoconus and included in group C; and 73 cases or 5.84% were placed in group D as non-keratoconus but abnormal. There was no disagreement between the five evaluators over any of the cases in groups C and D, and little variance among them for cases included in group B (less than 5% by ANOVA). Conclusions: The incidence of keratoconus and corneas suspicious for keratoconus in Greece appears to be much higher than respective reports from other regions: one in ten Greeks appear to have topographic keratoconus, most not diagnosed even by the age of cataract surgery, and almost an additional one in four may have suspicious corneal imaging for keratoconus. These data strongly imply that routine screening for disease should be promoted among Greeks, especially during puberty, to halt possible progression; moreover, careful screening should be performed when laser vision correction is being considered.

Comparison of corneal measurements in keratoconus eyes with two swept-source-optical coherence tomography devices and a Scheimpflug device

PURPOSE

To assess the feasibility and reliability of biometric measurements taken with the Eyestar 900 device in keratoconus eyes in comparison with those taken with the Pentacam HR and IOLMaster 700.

METHODS

Seventy-five eyes of 75 patients with keratoconus were included. The central corneal thickness (CCT), thinnest point of corneal thickness (TCT), axial length (AL), flat (K1) and steep (K2) anterior and posterior (Kp1, Kp2) keratometry, maximal keratometry (KMax) and anterior chamber depth (ACD) were compared between the Eyestar 900, Pentacam HR and IOLMaster 700. Reliability parameters such as the coefficient of variation (CoV) and intraclass correlation coefficient (ICC) were calculated. Pearson's r was determined to assess the correlation between devices.

RESULTS

A high repeatability (CoV < 1%) and intraclass correlation (ICC > 0.9) was found for all devices, led by AL, TCT, K1 and K2 (CoV 0.01-0.36%; ICC 0.994-1.00). The largest correlation between devices was found for AL (Eyestar vs. IOLMaster, r = 1.0), K1 (Eyestar vs. IOLMaster, r = 0.997) and ACD (Eyestar vs. IOLMaster, r = 0.995; Pentacam vs. IOLMaster, r = 0.987; Eyestar vs. Pentacam, r = 0.983), but there were significant differences in measured values between devices (p < 0.001), whereas the correlation was only slightly lower (r = 0.947 to 0.994) for KMax, CCT, TCT, K2, Kp1 and Kp2.

CONCLUSION

Keratometric and axial length measurements with the Eyestar 900 were feasible and revealed a high repeatability and a good correlation to the other devices in eyes with keratoconus.

Compensatory Corneal Epithelial Changes After Femtolaser - Assisted Intracorneal Rings Implantation in Early and Moderate Cases of Keratoconus

Purpose

To study the compensatory corneal epithelial changes after femtolaser-assisted intracorneal ring segment (ICRS) implantation in early and moderate cases of keratoconus (KC) using anterior segment optical coherence tomography (AS-OCT).

Patients and Methods

A prospective observational non-randomized study of 40 eyes with mild to moderate KC received femtolaser-assisted ICRS implantation. Ferrara ICRS with different arc lengths and thicknesses were used according to the patients' tomographic pattern. Patients had a clear central cornea, keratometry reading < 60 diopters, and corneal thickness > 400 microns. AS-OCT was performed preoperatively and at 1, 3, and 6 months after surgery. Corneal epithelial thickness (CET) was measured over 17 points (2 mm central and 16 points on 2-5 mm and 5-7 mm annular zones) over the pupil center. All data were collected and analyzed.

Results

Comparing the preoperative and postoperative data, there was a statistically significant increase in the CET postoperatively throughout the 6-month follow-up period in all zones (p<0.001). The epithelial thickness (ET) was noticed shortly around and central to the ring ridges by the first month (5-7 mm zone). By the third month, the flattened central cornea (2 mm zone) and the 2-5 mm zone showed a significant increase in ET up to the 6th month.

Conclusion

ICRS implantation in KC results in a thicker and more regular epithelium in the central corneal zone as a secondary response to the corneal stromal changes induced by the implants.

Bismuth Selenide Nanostructured Clusters as Optical Coherence Tomography Contrast Agents: Beyond Gold-Based Particles

Optical coherence tomography (OCT) is an imaging technique currently used in clinical practice to obtain optical biopsies of different biological tissues in a minimally invasive way. Among the contrast agents proposed to increase the efficacy of this imaging method, gold nanoshells (GNSs) are the best performing ones. However, their preparation is generally time-consuming, and they are intrinsically costly to produce. Herein, we propose a more affordable alternative to these contrast agents: Bi₂Se₃ nanostructured clusters with a desert rose-like morphology prepared via a microwave-assisted method. The structures are prepared in a matter of minutes, feature strong near-infrared extinction properties, and are biocompatible. They also boast a photon-to-heat conversion efficiency of close to 50%, making them good candidates as photothermal therapy agents. In vitro studies evidence the prowess of Bi₂Se₃ clusters as OCT contrast agents and prove that their performance is comparable to that of GNSs.

Dissecting the Profile of Corneal Thickness With Keratoconus Progression Based on Anterior Segment Optical Coherence Tomography

Purpose

To characterize the corneal and epithelial thickness at different stages of keratoconus (KC), using a deep learning based corneal segmentation algorithm for anterior segment optical coherence tomography (AS-OCT).

Methods

An AS-OCT dataset was constructed in this study with 1,430 images from 715 eyes, which included 118 normal eyes, 134 mild KC, 239 moderate KC, 153 severe KC, and 71 scarring KC. A deep learning based corneal segmentation algorithm was applied to isolate the epithelial and corneal tissues from the background. Based on the segmentation results, the thickness of epithelial and corneal tissues was automatically measured in the center 6 mm area. One-way ANOVA and linear regression were performed in 20 equally divided zones to explore the trend of the thickness changes at different locations with the KC progression. The 95% confidence intervals (CI) of epithelial thickness and corneal thickness in a specific zone were calculated to reveal the difference of thickness distribution among different groups.

Results

Our data showed that the deep learning based corneal segmentation algorithm can achieve accurate tissue segmentation and the error range of measured thickness was less than 4 μm between our method and the results from clinical experts, which is approximately one image pixel. Statistical analyses revealed significant corneal thickness differences in all the divided zones (P < 0.05). The entire corneal thickness grew gradually thinner with the progression of the KC, and their trends were more pronounced around the pupil center with a slight shift toward the temporal and inferior side. Especially the epithelial thicknesses were thinner gradually from a normal eye to severe KC. Due to the formation of the corneal scarring, epithelial thickness had irregular fluctuations in the scarring KC.

Conclusion

Our study demonstrates that our deep learning method based on AS-OCT images could accurately delineate the corneal tissues and further successfully characterize the epithelial and corneal thickness changes at different stages of the KC progression.

Distribution pattern of total corneal thickness in keratoconus versus normal eyes using an optical coherence tomography

Purpose:

To evaluate the total corneal thickness distribution pattern using a high-resolution spectral-domain optical coherence tomography (HR SD-OCT) for distinguishing normal eyes from keratoconus (KCN).

Methods:

One hundred and forty-four patients were enrolled in three groups (55 normal, 45 mild KCN, and 44 moderate-to-severe KCN eyes) in this prospective diagnostic test study. Total corneal thickness was measured in 8 semi-meridians using HR SD-OCT (Heidelberg Engineering, Heidelberg, Germany) in 5 and 7 mm zones. The central corneal thickness (CCT), corneal focal thinning (minimum thickness [Min], min minus median and maximum [Min-Med, Min-Max]), and asymmetry indices (inferior minus superior [I-S] and supranasal minus infratemporal [SN-IT]) were calculated. One-way analysis of variance and the area under the receiver operating characteristic curve (AUC) were used for the analysis.

Results:

Thinner CCT, lower Min thickness, more negative Min-Max, Min-Med, and greater I-S and SN-IT were found in KCN eyes compared to the control group (P < 0.001). The inferior and IT semi-meridians were the thinnest locations in KCN cases in the 5 mm central zone (P < 0.001). CCT followed by Min-Med had the highest discriminative ability for differentiating mild KCN (AUC, sensitivity and specificity: 0.822, 87.0%, 60.37% and 0.805, 82.93%, 66.0%, respectively) and moderate-to-severe KCN (0.902, 87.82%, 73.08% and 0.892, 85.37%, and 78.85%, respectively) from normal corneas.

Conclusion:

The inferior and IT sectors of the cornea with the largest thickness changes in the 5 mm zone are the most common thinning sites in keratoconic corneas, and CCT and Min-Med are the most sensitive indices for the diagnosis of KCN.

Bilateral Differential Topography-A Novel Topographic Algorithm for Keratoconus and Ectatic Disease Screening

Purpose: The purpose of this study was to establish a novel bilateral differential topographic algorithm and assess its efficacy for screening of keratoconus and corneal ectasia before corneal refractive surgery.

Methods: One hundred and sixty-one consecutive patients (115 men and 46 women, aged 22.8 ± 6.8 years) with keratoconus, including clinical keratoconus, subclinical keratoconus, forme fruste keratoconus (FFK), and corneal ectasia (KC group) and one hundred and seventy-four consecutive patients (97 men and 77 women, aged 25.1 ± 6.7 years) with ametropia (control group) visiting the Eye and ENT hospital of Fudan University from June 2018 to April 2021 were included. Bilateral differential keratometry, elevation, and pachymetry topographies were composed based on raw topographic data obtained by a Scheimpflug imaging anterior segment analyzer. Key bilateral differential characteristic parameters were calculated. SPSS 20 (SPSS Inc., IBM) was used for statistical analyses and the receiver operating characteristic (ROC) curves were used to determine the diagnostic efficacies.

Results: Mann-Whitney tests detected that the front keratometry, front elevation, corneal pachymetry, and back elevation maximal, mean, and standard deviation values within a 1.5-mm radius of the bilateral differential topography were all significantly higher in the KC group than in the control group (all p-values <0.001). The front keratometry mean (ΔFKmean) and standard deviation (ΔFKsd) and the front elevation standard deviation (ΔFEsd) and maximal (ΔFEmax) values within a 1.5-mm radius of the bilateral differential topography yielded the four highest accuracies (area under the ROC curve = 0.985, 0.985, 0.984, and 0.983, respectively) for discriminating KC cases (including FFK cases) from normal cases. Cut-off values of 0.75 diopters (D) for the ΔFKmean, 0.67 D for the ΔFKsd, 2.9 μm for the ΔFEsd, and 14.6 μm for the ΔFEmax had the highest sensitivities (95.7, 95.0, 96.9, and 95.0%, respectively) and specificities (96.0, 97.7, 94.8, and 95.4%, respectively).

Conclusion: Bilateral differential topographic parameters may be efficient for the early detection of keratoconus and corneal ectasia secondary to corneal refractive surgery. This bilateral differential topographic algorithm may complement conventional diagnostic models by improving the sensitivity and specificity of screening for early keratoconus and ectasia before corneal refractive surgeries.

Epithelial and stromal remodelling following femtosecond laser-assisted stromal lenticule addition keratoplasty (SLAK) for keratoconus

The purpose of this study was to evaluate corneal epithelium and stromal remodelling with anterior segment optical coherence tomography in patients who have undergone stromal lenticule addition keratoplasty (SLAK) for advanced keratoconus. This was a prospective non-comparative observational study. Fifteen eyes of 15 patients with advanced keratoconus underwent implantation with a cadaveric, donor negative meniscus-shaped intrastromal lenticule, produced with a femtosecond laser, into a stromal pocket dissected in the recipient cornea at a depth of 120 μm. Simulated keratometry, central corneal thickness (CTT), corneal thinnest point (CTP), central epithelial thickness (CET), central and peripheral lenticule thickness, anterior and posterior stromal thickness were measured. Regional central corneal epithelial thickness (CET) and variations in the inner annular area (IAT) and outer annular area (OAT) were also analysed. All parameters were measured preoperatively and 1, 3, and 6 months postoperatively. The average anterior Sim-k decreased from 59.63 ± 7.58 preoperatively to 57.19 ± 6.33 D 6 months postoperatively. CCT, CTP, CET, and OAT increased and IAT decreased significantly after 1 month. All parameters appeared unchanged at 6-months except that of OAT that further increased. Lenticule thickness was stable. In conclusion we observed that SLAK reshapes the cornea by central flattening with stromal thickening and epithelial thickness restoration.

Dissecting the Profile of Corneal Thickness With Keratoconus Progression Based on Anterior Segment Optical Coherence Tomography

PURPOSE

To characterize the corneal and epithelial thickness at different stages of keratoconus (KC), using a deep learning based corneal segmentation algorithm for anterior segment optical coherence tomography (AS-OCT).

METHODS

An AS-OCT dataset was constructed in this study with 1,430 images from 715 eyes, which included 118 normal eyes, 134 mild KC, 239 moderate KC, 153 severe KC, and 71 scarring KC. A deep learning based corneal segmentation algorithm was applied to isolate the epithelial and corneal tissues from the background. Based on the segmentation results, the thickness of epithelial and corneal tissues was automatically measured in the center 6 mm area. One-way ANOVA and linear regression were performed in 20 equally divided zones to explore the trend of the thickness changes at different locations with the KC progression. The 95% confidence intervals (CI) of epithelial thickness and corneal thickness in a specific zone were calculated to reveal the difference of thickness distribution among different groups.

RESULTS

Our data showed that the deep learning based corneal segmentation algorithm can achieve accurate tissue segmentation and the error range of measured thickness was less than 4 μm between our method and the results from clinical experts, which is approximately one image pixel. Statistical analyses revealed significant corneal thickness differences in all the divided zones (P < 0.05). The entire corneal thickness grew gradually thinner with the progression of the KC, and their trends were more pronounced around the pupil center with a slight shift toward the temporal and inferior side. Especially the epithelial thicknesses were thinner gradually from a normal eye to severe KC. Due to the formation of the corneal scarring, epithelial thickness had irregular fluctuations in the scarring KC.

CONCLUSION

Our study demonstrates that our deep learning method based on AS-OCT images could accurately delineate the corneal tissues and further successfully characterize the epithelial and corneal thickness changes at different stages of the KC progression.

A review of imaging modalities for detecting early keratoconus

OBJECTIVES

Early identification of keratoconus is imperative for preventing iatrogenic corneal ectasia and allowing for early corneal collagen cross-linking treatments to potentially halt progression and decrease transplant burden. However, early diagnosis of keratoconus is currently a diagnostic challenge as there is no uniform screening criteria. We performed a review of the current literature to assess imaging modalities that can be used to help identify subclinical keratoconus.

METHODS

A Pubmed database search was conducted. We included primary and empirical studies for evaluating different modalities of screening for subclinical keratoconus.

RESULTS

A combination of multiple imaging tools, including corneal topography, tomography, Scheimpflug imaging, anterior segment optical coherence tomography, and in vivo confocal microscopy will allow for enhanced determination of subclinical keratoconus. In patients who are diagnostically borderline using a single screening criteria, use of additional imaging techniques can assist in diagnosis. Modalities that show promise but need further research include polarization-sensitive optical coherence tomography, Brillouin microscopy, and atomic force microscopy.

CONCLUSIONS

Recognition of early keratoconus can reduce risk of post-refractive ectasia and reduce transplantation burden. Though there are no current uniform screening criterion, multiple imaging modalities have shown promise in assisting with the early detection of keratoconus.