Integration of longitudinal load-bearing tissue MRI radiomics and neural network to predict knee osteoarthritis incidence
This study presents a novel approach integrating longitudinal MRI-based radiomics and clinical variables to predict knee osteoarthritis (KOA) incidence using machine learning. By leveraging deep learning for auto-segmentation and machine learning for predictive modeling, this research provides a more interpretable and clinically applicable method for early KOA detection. The introduction of a Radiomics Score System enhances the potential for radiomics as a virtual image-based biopsy tool, facilitating non-invasive, personalized risk assessment for KOA patients. The findings support the translation of advanced imaging and AI-driven predictive models into clinical practice, aiding early diagnosis, personalized treatment planning, and risk stratification for KOA progression. This model has the potential to be integrated into routine musculoskeletal imaging workflows, optimizing early intervention strategies and resource allocation for high-risk populations. Future validation across diverse cohorts will further enhance its clinical utility and generalizability.
Authors
- Yun Yang (ORCID: https://orcid.org/0000-0001-9892-5615)
- Tianyu Chen (ORCID: https://orcid.org/0000-0001-7056-2947)
- Guowei Zeng (ORCID: https://orcid.org/0000-0003-1530-3883)
- Changhai Ding (ORCID: https://orcid.org/0000-0002-9479-730X)
- Yin Wang (ORCID: https://orcid.org/0000-0002-8137-7496)
- Haixiong Miao
- Yin-xiao Peng (ORCID: https://orcid.org/0009-0005-4175-7696)
- Zhijia Wen
- Shanhong Liu (ORCID: https://orcid.org/0000-0002-2022-3389)
- Shengfa Li (ORCID: https://orcid.org/0009-0005-6801-7102)
- Zhengrui Liu
- Lili Chen (ORCID: https://orcid.org/0000-0002-9965-8990)
- Zhong Zhang (ORCID: https://orcid.org/0000-0001-8915-7036)
- Jun Li (ORCID: https://orcid.org/0000-0003-4353-5761)
- Xing Wang (ORCID: https://orcid.org/0000-0001-8762-5617)
- Lan Chen (ORCID: https://orcid.org/0000-0002-9625-347X)
- Wei Chen (ORCID: https://orcid.org/0000-0002-2933-5678)
- Xiaogang Wang (ORCID: https://orcid.org/0000-0001-7325-3314)
- Hao Liu (ORCID: https://orcid.org/0000-0001-6194-4345)
- Bin Yu (ORCID: https://orcid.org/0000-0002-2453-7852)
- Li Xu (ORCID: https://orcid.org/0000-0003-2721-0377)
- Shengjie Wang (ORCID: https://orcid.org/0000-0001-8467-3031)
- Yingze Zhang (ORCID: https://orcid.org/0000-0001-8042-6105)
- Yang Wang (ORCID: https://orcid.org/0000-0002-5596-2982)
- Wei Zhao (ORCID: https://orcid.org/0000-0002-7130-7670)
- Huilin Wan (ORCID: https://orcid.org/0009-0006-6234-5778)
- Deng Zhao (ORCID: https://orcid.org/0000-0003-2529-5821)
- Ruyu Liao
- Jian Chen (ORCID: https://orcid.org/0009-0008-9395-5389)
- Yanbin Zhu (ORCID: https://orcid.org/0009-0006-0036-7736)
Institutions
- Hebei Medical University (CN)
- Jinan University (CN)
- Third Hospital of Hebei Medical University (CN)
- Third Affiliated Hospital of Southern Medical University (CN)
- Third People's Hospital of Chengdu (CN)
- Zhujiang Hospital (CN)
- Chongqing Three Gorges Central Hospital (CN)
- Huizhou Central People's Hospital (CN)
- Guangdong Provincial People's Hospital (CN)
- Chongqing Three Gorges University (CN)
- Southern Medical University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Journal of Orthopaedic Translation
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1016/j.jot.2025.01.007
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08