Alsoof Daniel, McDonald Christopher L, Durand Wesley M, Diebo Bassel G, Kuris Eren O, Daniels Alan H
Department of Orthopedic Surgery, Alpert Medical School of Brown University, Providence, RI, USA.
Department of Orthopedic Surgery, Johns Hopkins, Baltimore, MA, USA.
Int J Spine Surg. 2023 Jun;17(S1):S57-S64. doi: 10.14444/8501. Epub 2023 May 16.
Radiomics is an emerging approach to analyze clinical images with the purpose of revealing quantitative features that are unvisible to the naked eye. Radiomic features can be further combined with clinical data and genomic information to formulate prediction models using machine learning algorithms or manual statistical analysis. While radiomics has been classically applied to tumor analysis, there is promising research in its application to spine surgery, including spinal deformity, oncology, and osteoporosis detection. This article reviews the fundamental principles of radiomic analysis, the current literature relating to the spine, and the limitations of this approach.
放射组学是一种新兴的分析临床图像的方法,目的是揭示肉眼不可见的定量特征。放射组学特征可以进一步与临床数据和基因组信息相结合,使用机器学习算法或手动统计分析来构建预测模型。虽然放射组学传统上已应用于肿瘤分析,但在其应用于脊柱手术方面也有很有前景的研究,包括脊柱畸形、肿瘤学和骨质疏松症检测。本文综述了放射组学分析的基本原理、目前与脊柱相关的文献以及这种方法的局限性。