Work

OCT-PRO: A Multimodal Model Integrating OCT and Clinical Traits to Predict Postoperative Outcomes in Cataract Patients

Year: 2025

Type: article

Abstract: Purpose: To develop and validate OCT-PRO, a multimodal machine learning model integrating OCT images and clinical traits to predict postoperative visual outcomes in cataract patients. Design: Multicenter prospective cohort study. Participants: A total of 2225 eyes from 1911 cataract patients were enrolled, including 1304 participants from Zhongshan Ophthalmic Center for model development and 607 from 6 hospitals across China for external testing. Methods: All participants underwent standardized preoperative examinations including macular OCT and clinical data collection, followed by phacoemulsification and intraocular lens implantation. Postoperative best-corrected visual acuity (BCVA) was assessed at 4 weeks after surgery. A multimodal model was constructed using deep learning techniques, combining image features extracted via InceptionResNetV2 and structured metadata processed by fully connected layers. Model performance was assessed using mean absolute error (MAE) and root mean square error (RMSE) and compared with traditional laser interferometry and ophthalmologist predictions. Subgroup analysis and explainability assessments were conducted to evaluate generalizability and model attention. Main Outcome Measures: Prediction error of postoperative BCVA (logarithm of the minimum angle of resolution [logMAR]) measured by MAE and RMSE. Results: < 0.001). Subgroup analyses confirmed consistent advantages of OCT-PRO across different cataract subtypes and baseline preoperative BCVA groups. Model interpretability analysis highlighted the importance of preoperative BCVA, age, and macular foveal structure, with greater reliance on OCT features than clinical metadata-especially in complex or low preoperative BCVA cases. In a head-to-head comparison, the model consistently outperformed both junior and senior ophthalmologists in predictive accuracy across various clinical subtypes. Conclusions: OCT-PRO enables accurate prediction of postoperative visual outcomes in cataract surgery, outperforming conventional methods and ophthalmologists. It holds promise as a valuable decision-support tool to assist surgical decision-making and improve health care resource allocation. Financial Disclosures: The author has no/the authors have no proprietary or commercial interest in any materials discussed in this article.

Source: Ophthalmology Science

DOI: 10.1016/j.xops.2025.101013