磁共振成像2026，Vol.17Issue(3)：213-220,8.DOI:10.12015/issn.1674-8034.2026.03.031
深度学习联合影像组学在骨骼肌肉疾病的研究进展
Research progress of deep learning combined with radiomics in musculoskeletal diseases
摘要
Abstract
Musculoskeletal diseases are among the most prevalent and debilitating chronic conditions worldwide.With the acceleration of population aging,their incidence continues to rise,posing a major public health challenge.Conventional imaging-based diagnosis relies heavily on the subjective interpretation of clinicians and is limited by high inter-observer variability,insufficient sensitivity for early lesions,and a lack of robust quantitative assessment tools,making it difficult to meet the requirements of precision medicine.In recent years,the rapid development of deep learning and radiomics has provided new technical pathways for intelligent assessment and decision-making in musculoskeletal disorders.This review systematically summarizes the research progress of deep learning and radiomics in a range of musculoskeletal conditions,including osteoarthritis,osteoporosis and fragility fractures,bone tumors and benign-malignant differentiation,muscle diseases and muscle atrophy,as well as tendon and ligament injuries.We focus on their applications in automatic segmentation,computer-aided diagnosis,disease classification,progression prediction,treatment decision support,and prognostic evaluation,highlighting their potential advantages in improving diagnostic accuracy,enabling quantitative characterization of lesions,and supporting individualized therapeutic strategies.In addition,we outline the major challenges currently limiting clinical translation,such as insufficient data standardization,limited model interpretability,suboptimal multicenter generalizability,and uncertainties in implementation pathways.Finally,future research directions are discussed with the aim of providing methodological reference and theoretical support for early diagnosis,prognostic assessment,and precision treatment of musculoskeletal diseases based on deep learning and radiomics.关键词
骨骼肌肉疾病/影像组学/深度学习/图像分割/诊断/预后评估/磁共振成像Key words
musculoskeletal diseases/radiomics/deep learning/image segmentation/diagnosis/prognostic evaluation/magnetic resonance imaging分类
医药卫生引用本文复制引用
魏炳琦,李宜静,张新月,黎韵坛,张露薇,姚茜文,程韶,王上增..深度学习联合影像组学在骨骼肌肉疾病的研究进展[J].磁共振成像,2026,17(3):213-220,8.基金项目
National Natural Science Foundation of China(No.82374490) （No.82374490）
Key R & D projects in Henan Province(No.241111311700) （No.241111311700）
Science and Technology Research Program of Henan Province(No.252102310454). 国家自然科学基金项目(编号:82374490) （No.252102310454）
河南省重点研发专项(编号:241111311700) （编号:241111311700）
2025年河南省科技攻关项目(编号:252102310454) （编号:252102310454）
