Radiomics in ophthalmology: a systematic review.

Abstract

Radiomics holds great potential in medical image analysis for various ophthalmic diseases. In recent times, there have been numerous endeavors in this area of research. This systematic review aims to provide a comprehensive assessment of the strengths and limitations of radiomics in ophthalmology. Conforming to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, we conducted a systematic review with a pre-registered protocol (PROSPERO: CRD42023446317). We explored the PubMed, Embase, and Cochrane databases for original studies on this topic and made a comprehensive descriptive integration. Furthermore, the included studies underwent quality assessment by the radiomics quality score (RQS). A total of 41 articles from an initial search of 227 studies were finally selected for further analysis. These articles included research across five disease categories and covered seven imaging modalities. The radiomics models demonstrated robust performance, with area under the curve (AUC) values mostly falling within 0.7-1.0. The moderate RQS (mean score: 11.17/36) indicated that most studies were retrospectively, single-center analyses without external validation. Radiomics holds promising utility in the field of ophthalmology, assisting diagnosis, early-stage screening, and prognostication of treatment response. Artificial intelligence algorithms significantly contribute to the construction of radiomics models in ophthalmology. This study highlights the strengths and challenges of radiomics in ophthalmology and suggests potential avenues for future improvement. Radiomics represents a valuable approach for generating innovative imaging markers, enhancing efficiency in clinical diagnosis and treatment, and aiding decision-making in clinical contexts of many ophthalmic diseases, thereby improving overall patient prognosis. Radiomics has attracted extensive attention in the field of ophthalmology. Articles included five disease categories over seven imaging modalities, consistently yielding AUCs mostly above 0.7. Current research has few prospective and multi-center studies, underlining the necessity for future high-quality studies.