Advanced Corneal Imaging for Ectasia Diagnosis
Rui Carneiro-Freitas, MD1,2, Marcella Q. Salomão, MD2,3,4, Bernardo T. Lopes, MD2,3,4,Renato Ambrosio Jr, MD, PhD2,3,4*
Copyright : © 2017 Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The diagnosis of corneal ectasia has evolved tremendously over the last decades because of two plain reasons. First, progressive ectasia (keratectasia) arisen as a severe and intricate complication after common elective laser vison correction (LVC) procedures such as LASIK,[1] leading to the essential need to detecting mild ectasia cases or cases who present with high susceptibility for ectasia progression[2]. Second, the advent of alternative treatments for ectatic corneal diseases, such as corneal crosslinking, intracorneal ring segments (ICRS) and customized therapeutic ablations have brought up the inevitability for identifying the cases that will benefit from these procedures, and also for planning such procedures [3,4]
In 1938, Amsler pioneered the work for detecting mild forms of keratoconus, coining the term “forme fruste keratoconus” (FFKC) [5,6]. In longitudinal studies, Amsler used a Placido-disk Polaroid photokeratoscopy to describe irregular patterns on the keratoscopic reflex that did precede clinically detectable signs of keratoconus. The term “fruste” classically refers to an incomplete or abortive presentation of a disease, being also a condition that could progress or not, and opposite to the “forme plaine” or full blown form of the disease. However, FFKC is a complex term, for which there is no real consensus on the definition,4 so that mild or subclinical were advocated to be a more appropriate terminology. Besides nomen clature, Amsler’s method did not gain momentum due to its inherent complexity that made it hard to be reproduced by other researchers. In addition, the clinical relevance for detecting early ectatic disease was relatively limited at that time, which was correlated to the treatment options available for the disease.
In the early 1980s, when refractive surgery emerged as a new subspecialty, the need to comprise a detailed analysis of corneal shape for evaluating patients before and after such procedures become obvious. A quantitative analysis from the Corneascope was developed by Rowsey and coworkers,[7] in an approach that provided contour keratometry in all corneal meridians. Nevertheless, it was the introduction of computerized technologies for videokeratography what provided the first revolution in this field with the development of corneal topography [8]. Placido-disk based computerized corneal topography standardized a reproducible method, generating clinical data for interpretation [9]. Various topographical indexes, such as the ones described by Rabinowitz and McDonnell in 1989, were developed for detecting keratoconus [10]. Interestingly, such data allowed for identifying mild ectatic changes before the development of other clinical signs at slit lamp, or loosing distance spectacle corrected visual acuity (DCVA) [11,12]. Such ability has been the most important argument to support corneal topography as a mandatory exam to screen refractive candidates prior to LVC [13].
Nevertheless, the quest and the need to go beyond corneal topography became unmistakable with the increased number of cases that still developed ectasia despite of normal topography and no other apparent risk factors [14,15]. In addition, there are also cases with irregular corneas that would have been excluded from surgery based on anterior surface characteristics, but had uneventful LASIK with stable outcomes [16] Thereby, the need to augment both the sensitivity and specificity has become unquestionable when considering ectasia diagnosis and screening for ectasia risk prior to LVC.
The development of enhanced diagnostic capabilities should include two distinct elements. The conscious or rational use of objective data is fundamental, as subjective analysis of front surface curvature maps have significant variability among different experts in the field [17]. Also, the need to provide more detailed clinical data through advanced imaging techniques for characterizing the cornea beyond but not excluding front surface curvature data, including corneal tomography and bio mechanical assessments [18-20]
Corneal tomography depicts both the anterior and posterior corneal surfaces, also generating the pachymetric map of the whole cornea.18 This is possible using different technologies, including Scheimpflug imaging,[21,22] very high-frequency digital ultrasound (VHF-US),[23,24] and optical coherence tomography (OCT) [25,26] These methods have different characteristics but they all provide a vast amount of clinical data further than front surface curvature topographic characterization. Interestingly, it has been a challenge to demonstrate that such vast and complex data do provide an improvement on the accuracy to detect mild forms of ectasia over the well-established corneal topography method.2 While longitudinal analysis would provide the ideal design for such studies, the fellow eye with normal topography from patients with clinical ectasia detected in the ipsilateral eye have been considered a good alternative as these eyes have been referred to be forme fruste keratoconus by Klyce [27]. Interestingly, different Scheimpflug systems did involve such model of very asymmetric ectasia cases to develop and further demonstrate an improvement on sensitivity for detecting early forms of ectasia. These include studies involving the Orbscan,[28] Pentacam,[29] Sirius30 and Galilei.[31] These studies generate displays with indices derived from different methods for artificial intelligence to generate objective analysis from the complex tomographic data in order to facilitate clinical decision. For example, the Belin/Ambrósio Enhanced Ectasia Display (BAD), available in the Pentacam, combines the standard and enhanced BFS elevation maps of the front and back surfaces, and the thickness distribution data. Different tomographic parameters are presented as the standard deviation from normality towards disease (d values) and a final BAD-D parameter is calculated based on a regression analysis to maximize accuracy for detecting ectatic disease. Other displays are also available, such as the SCORE analyzer developed by Gatinel and Saad, which is available for the Orbscan [32].
Corneal imaging has evolved also to the ability to analyze individualized layers of the cornea such as the epithelium and Bowman’s layer. We refer to this method as segmental or layered corneal tomography. Reinstein and coworkers developed epithelium thickness indices for detecting keratoconus using VHF-US.[23,33] Huang and coworkers developed a similar approach using the OCT [25,26]. In addition, Sinha-Roy and coworkers analyzed the irregularity of the Bowman's layer (BL) in ectatic and normal corneas and developed a Bowman's roughness index (BRI) which improved, along with epithelial thickness data and BAD-D, the sensitivity for the detection of mild forms of ectasia in studies involving the fellow eye with normal topography from very asymmetric ectasia (VAE) cases.
Nevertheless, it is important to deliberate that some of these VAE cases may be factual unilateral ectasia cases [34] Curiously, there is a consensus that true unilateral keratoconus does not exist, but also that a secondary or induced ectasia, caused by a mechanical process, such as continuous eye rubbing, may occur unilaterally [4]
. This concept is in bargain with the two-hit hypothesis, which considers an underlying genetic predisposition along with external environmental factors [3]. An alternative study for assessing ectasia susceptibility involves the analysis of the preoperative state of cases that developed ectasia after LVC [35]. However, the available clinical data prior to surgery should be a limiting factor for the relevance of such studies. Different groups have designed risk assessment scores, such as the Ectasia Risk Score System (ERSS) by Randleman et al[36] and Ectasia Susceptibility Score (ESS) by Ambrósio et al.[35]
Recent advances in corneal biomechanics have contributed greatly for the understanding of ectasia pathophysiology.[37] The Ocular Response Analyzer® (Reichert Ophthalmic Instruments, Depew, NY)[38] and the Corvis® (OCULUS Optikgeräte GmbH; Wetzlar, Germany)[39] are non-contact t1onometers that monitor corneal deformation response. A novel biomechanical index, the CBI (Corneal Biomechanical Index) was developed by Vinciguerra and coworkers to integrate corneal deformation response (DCR) metrics from the Corvis ST.[40] Ultimately, the integration of biomechanical data and corneal shape data has been proposed for further improving accuracy to detect mild ectasia or even its susceptibility.[15,38] Recent studies were accomplished to develop the TBI (Tomographic Biomechanical Index), which combines from the Corvis ST and tomographic data from the Pentacam HR, through a random forest method with leave-one-out cross validation (RF-LOOCV). This novel index has shown very high accuracy for detecting ectasia, including a very high sensitivity for sub-clinical (fruste) ectasia among eyes with normal topography in very asymmetric patients, performing better than any other parameter tested (Figure 1) [41].
Future studies should consider the impact from LVC procedure and other factors from the environment, including as metrics that reflect ocular surface and allergy. These would be integrated to such shape and biomechanical parameters to assess the risk of ectasia progression. The prognostic information from these analysis would further improve our ability to better select refractive and therapeutic procedures.
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