Horne Ashley, Abravan Azadeh, Fornacon-Wood Isabella, O'Connor James P B, Price Gareth, McWilliam Alan, Faivre-Finn Corinne
Division of Cancer Sciences, The University of Manchester, Manchester, M13 9NT, United Kingdom.
Department of Thoracic Oncology, The Christie NHS Foundation Trust, Manchester, M20 4BX, United Kingdom.
Br J Radiol. 2025 May 1;98(1169):653-668. doi: 10.1093/bjr/tqaf051.
Radiomics is a health technology that has the potential to extract clinically meaningful biomarkers from standard of care imaging. Despite a wealth of exploratory analysis performed on scans acquired from patients with lung cancer and existing guidelines describing some of the key steps, no radiomic-based biomarker has been widely accepted. This is primarily due to limitations with methodology, data analysis, and interpretation of the available studies. There is currently a lack of guidance relating to the entire radiomic workflow from study design to critical appraisal. This guide, written with early career lung cancer researchers, describes a more complete radiomic workflow. Lung cancer image analysis is the focus due to some of the unique challenges encountered such as patient movement from breathing. The guide will focus on CT imaging as these are the most common scans performed on patients with lung cancer. The aim of this article is to support the production of high-quality research that has the potential to positively impact outcome of patients with lung cancer.
放射组学是一种健康技术,有潜力从标准护理影像中提取具有临床意义的生物标志物。尽管对肺癌患者的扫描进行了大量探索性分析,且现有指南描述了一些关键步骤,但尚无基于放射组学的生物标志物被广泛接受。这主要是由于现有研究在方法、数据分析和解读方面存在局限性。目前,从研究设计到批判性评价的整个放射组学工作流程缺乏相关指导。本指南是与肺癌研究领域的早期职业研究人员共同撰写的,描述了一个更完整的放射组学工作流程。由于遇到一些独特的挑战,如患者呼吸导致的移动,肺癌图像分析成为重点。本指南将聚焦于CT成像,因为这是对肺癌患者进行的最常见扫描。本文的目的是支持开展高质量研究,有望对肺癌患者的治疗结果产生积极影响。