Radiomics in ophthalmology: a systematic review.

IF 4.7 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
European Radiology Pub Date : 2025-01-01 Epub Date: 2024-07-21 DOI:10.1007/s00330-024-10911-4
Haiyang Zhang, Huijie Zhang, Mengda Jiang, Jiaxin Li, Jipeng Li, Huifang Zhou, Xuefei Song, Xianqun Fan
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引用次数: 0

Abstract

Background: 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.

Method: 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).

Results: 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.

Conclusions: 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.

Clinical relevance statement: 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.

Key points: 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.

Abstract Image

眼科放射组学:系统综述。
背景:放射组学在各种眼科疾病的医学图像分析方面具有巨大潜力。近来,这一领域的研究工作层出不穷。本系统综述旨在全面评估放射组学在眼科领域的优势和局限性:根据系统综述和荟萃分析首选报告项目(PRISMA)指南,我们按照预先注册的方案(PROSPERO:CRD42023446317)进行了系统综述。我们在 PubMed、Embase 和 Cochrane 数据库中搜索了有关该主题的原始研究,并进行了全面的描述性整合。此外,我们还通过放射组学质量评分(RQS)对纳入的研究进行了质量评估:结果:从最初搜索到的 227 项研究中,最终筛选出 41 篇文章进行进一步分析。这些文章包括五种疾病类别的研究,涵盖七种成像模式。放射组学模型表现强劲,曲线下面积(AUC)值大多在 0.7-1.0 之间。中等的RQS(平均分:11.17/36)表明,大多数研究都是回顾性的单中心分析,没有经过外部验证:结论:放射组学在眼科领域具有广阔的应用前景,可协助诊断、早期筛查和预后治疗反应。人工智能算法对眼科放射组学模型的构建大有裨益。本研究强调了放射组学在眼科领域的优势和挑战,并提出了未来改进的潜在途径:放射组学是一种有价值的方法,可用于生成创新的成像标记物,提高临床诊断和治疗的效率,并在许多眼科疾病的临床背景下辅助决策,从而改善患者的整体预后:放射组学在眼科领域引起了广泛关注。文章包括五种疾病类别和七种成像模式,其AUC值大多在0.7以上。目前的研究很少有前瞻性和多中心的研究,这凸显了未来高质量研究的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
European Radiology
European Radiology 医学-核医学
CiteScore
11.60
自引率
8.50%
发文量
874
审稿时长
2-4 weeks
期刊介绍: European Radiology (ER) continuously updates scientific knowledge in radiology by publication of strong original articles and state-of-the-art reviews written by leading radiologists. A well balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes ER an indispensable source for current information in this field. This is the Journal of the European Society of Radiology, and the official journal of a number of societies. From 2004-2008 supplements to European Radiology were published under its companion, European Radiology Supplements, ISSN 1613-3749.
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