Development and Validation of the Relational Tissue Altered (RTA) Index: Applied Artificial Intelligence for the Assessment of Structural Impact from Laser Vision Correction
Abstract Introduction A retrospective case–control study was carried out to develop a predictive computational model to objectively and accurately represent the impact of laser vision correction (LVC) on the corneal structure. This study involved data from 3278 eyes (1690 patients) that remained sta...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Adis, Springer Healthcare
2025-07-01
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| Series: | Ophthalmology and Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40123-025-01206-y |
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| Summary: | Abstract Introduction A retrospective case–control study was carried out to develop a predictive computational model to objectively and accurately represent the impact of laser vision correction (LVC) on the corneal structure. This study involved data from 3278 eyes (1690 patients) that remained stable after refractive surgery and 105 eyes (66 patients) that developed postoperative ectasia. Methods An artificial intelligence-based machine learning approach was used to create a predictive model for the impact of corneal refractive surgery. The development process was based on the practice of knowledge discovery in databases (KDD) and addressed each step, including data selection, preprocessing, data transformation, data mining, and model evaluation. To evaluate the predictive model output, we analyzed the receiver operating characteristic (ROC) curves to determine the area under the curve (AUC) and the optimal cutoff points, as well as sensitivity and specificity. Results The minimal pachymetry was superior to central (apex) pachymetry for all calculations. The Relational Tissue Altered (RTA) showed the highest AUC performance, with area under the curve (AUC) values of 0.913. These AUC values were significantly higher (according to the DeLong test) than those obtained with Residual Stromal Bed (RSB) values of 0.832 and 0.825 (apex), and Percent Tissue Altered (PTA) values of 0.805 (minimum (min)) and 0.800 (apex). RTA demonstrated a sensitivity of 76.0% (95% confidence interval (CI) 68.8–83.2%) and a specificity of 89.2% (95% CI 86.2–92.2%). PTA min showed a sensitivity of 66.0% (95% CI 58.0–74.0%) and a specificity of 85.4% (95% CI 82.0–88.8%). Conclusions The Relational Tissue Altered (RTA) index provides an objective and data-driven measure of the structural impact induced by laser vision correction (LVC) on the cornea. Compared with traditional parameters such as Residual Stromal Bed (RSB) and Percent Tissue Altered (PTA), which were not originally designed to quantify biomechanical disruption, RTA demonstrated superior performance in characterizing surgical impact. Although not developed as a standalone ectasia predictor, RTA offers unique value when integrated with preoperative assessments of intrinsic corneal susceptibility, including topometric, tomographic, and biomechanical metrics. This synergistic approach holds promise for enhancing risk stratification, refining surgical planning, and advancing the safety and personalization of refractive surgery. |
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| ISSN: | 2193-8245 2193-6528 |