Francesco Versaci

Use of a Support Vector Machine for Keratoconus and Subclinical Keratoconus Detection by Topographic and Tomographic Data

PURPOSE To define a new classification method for the diagnosis of keratoconus based on corneal measurements provided by a Scheimpflug camera combined with Placido corneal topography (Sirius, CSO, Florence, Italy). DESIGN Retrospective case series. PARTICIPANTS We analyzed the examinations of 877 eyes with keratoconus, 426 eyes with subclinical keratoconus, 940 eyes with a history of corneal surgery (defined as abnormal), and 1259 healthy control eyes. METHODS For each group, eyes were divided into a training and a validation set. A support vector machine (SVM) was used to analyze the corneal measurements and classify the eyes into the 4 groups of participants. The classifier was trained to consider the indices obtained from both the anterior and posterior corneal surfaces or only from the anterior corneal surface. MAIN OUTCOME MEASURES Symmetry index of front and back corneal curvature, best fit radius of the front corneal surface, Baiocchi Calossi Versaci front index (BCV(f)) and BCV back index (BCV(b)), root mean square of front and back corneal surface higher order aberrations, and thinnest corneal point were analyzed. The diagnostic performance of the classifier was evaluated. RESULTS The accuracy of the classifier was excellent both with and without the data generated from the posterior corneal surface and corneal thickness because the number of true predictions was greater than 95% and 93%, respectively, in all classes. Precision improved most when posterior corneal surface data were included, especially in cases of subclinical keratoconus. Using the data from both anterior and posterior corneal surfaces and pachymetry allowed the SVM to increase its sensitivity from 89.3% to 96.0% in abnormal eyes, 92.8% to 95.0% in eyes with keratoconus, 75.2% to 92.0% in eyes with subclinical keratoconus, and 93.1% to 97.2% in normal eyes. CONCLUSIONS The classification algorithm showed high accuracy, precision, sensitivity, and specificity in discriminating among abnormal eyes, eyes with keratoconus or subclinical keratoconus, and normal eyes. Including the posterior corneal surface and thickness parameters markedly improved the sensitivity in the diagnosis of subclinical keratoconus. Classification may be particularly useful in excluding eyes with early signs of corneal ectasia when screening patients for excimer laser surgery.

Influence of posterior corneal astigmatism on total corneal astigmatism in eyes with moderate to high astigmatism

Purpose To evaluate the influence of posterior corneal astigmatism on total corneal astigmatism in patients with 1.00 diopter (D) or more of corneal astigmatism. Setting Private practice, Bologna, Italy. Design Prospective case series. Methods Corneal astigmatism was measured using a Scheimpflug camera combined with a corneal topographer (Sirius). Keratometric astigmatism, anterior corneal astigmatism, posterior corneal astigmatism, and total corneal astigmatism were evaluated. Vector analysis was performed according to the Næser method. Results One hundred fifty‐seven eyes were enrolled. Keratometric astigmatism was with the rule (WTR), against the rule (ATR), and oblique in 84.0%, 11.5%, and 4.5% of eyes, respectively. Posterior corneal astigmatism exceeded 0.50 D and 1.00 D in 55.4% of eyes and 5.7% of eyes, respectively. The mean posterior corneal astigmatism was 0.54 D, inclined 91 degrees in relation to the steeper anterior corneal meridian. The steepest meridian was vertically aligned in 93.0% of cases. Compared with total corneal astigmatism, keratometric astigmatism overestimated WTR astigmatism by a mean of 0.22 D ± 0.32 (SD), underestimated ATR astigmatism by 0.21 ± 0.26 D, and overestimated oblique astigmatism by 0.13 ± 0.37 D. In the whole sample, a difference in astigmatism magnitude of 0.50 D or more was detected between keratometric astigmatism and total corneal astigmatism in 16.6% of cases and the difference in the location of the steep meridian was greater than 10 degrees in 3.8% of cases. Conclusion In patients who are candidates for surgical correction of astigmatism, measuring only the anterior corneal curvature can lead to inaccurate evaluation of the total corneal astigmatism. Financial Disclosure Mr. Versaci and Mr. Vestri are employees of Costruzione Strumenti Oftalmici Srl. No author has a financial or proprietary interest in any material or method mentioned.

Instrumentation for Diagnosis of Keratoconus

In-depth knowledge of the profile of the corneal surface is not only essential in the diagnosis or treatment of keratoconus but it is important in many other aspects of clinical practice: the current methods to detect, diagnose, and monitor the evolution of keratoconus morphologically are computerized videokeratoscopy, corneal tomography, and optical scanning tomography both in the Scheimpflug configuration as well as based on optical coherence. The physical principles, advantages, and contraindications of the three diagnostic technologies are presented, following their historical developments: furthermore, a list of morphological features that can be derived from corneal topography and tomography is presented, pointing at their use and their characteristics.