Peer-reviewedCC BYAdvanced science (Weinheim, Baden-Wurttemberg, Germany)
A Multi-Structural Radiomic Digital Phenotyping Framework for Deciphering Preclinical Evolution of Degenerative Meniscal Tears.
11 affiliations
- 1Hebei Medical University Clinical Medicine Postdoctoral Station (Hebei Medical University Third Hospital), Shijiazhuang, Hebei, China.
- 2Department of Orthopaedic Surgery, NHC Key Laboratory of Intelligent Orthopaedic Equipment, Hebei Medical University Third Hospital, Shijiazhuang, Hebei, China.
- 3Department of Orthopaedics, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University & The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, Sichuan, China.
- 4Department of Arthroplasty and Sport Medicine, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University & The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, Sichuan, China.
- 5Department of Orthopaedics, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.
- 6Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
- 7Department of Rheumatology, Kolling Institute, Royal North Shore Hospital and Sydney Musculoskeletal Health, University of Sydney, Australia.
- 8Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.
- 9Clinical Research Centre, Beijing Tsinghua Changgung Hospital, Tsinghua Medicine, Tsinghua University, Beijing, China.
- 10Medical Research Center, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University & The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, Sichuan, China.
- 11Joint Surgery Department, Hebei Medical University Third Hospital, Shijiazhuang, Hebei, China.
Abstract
Degenerative meniscus tears (DMTs) are pivotal in knee osteoarthritis progression, yet conventional MRI often fails to capture the subvisual alterations preceding macroscopic failure. We developed a multi-structural digital risk stratification framework (MSC-RM) that integrates standardized radiomic signatures from six knee structures (femur, tibia, cartilages, and menisci) derived from 3D double-echo steady-state MRI with baseline clinical risk profiles. Utilizing a longitudinal cohort (n = 674), our framework decoded complex degeneration patterns, achieving superior 4-year predictive performance (AUC 0.871). Survival analysis revealed that high-risk individuals had a 6.12-fold greater hazard of developing DMTs than the low-risk group. Furthermore, a reader test with five resident surgeons demonstrated that MSC-RM significantly enhanced diagnostic consistency (Kappa increased from 0.38 to 0.55), effectively bridging the expertise gap. By shifting the paradigm from reactive lesion detection to proactive risk management, this framework provides a scalable strategy for precision preventive medicine and establishes digital biomarkers as critical tools for optimizing musculoskeletal health in aging populations.
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BibTeX
@article{li2026multistructural,
title = {{A Multi-Structural Radiomic Digital Phenotyping Framework for Deciphering Preclinical Evolution of Degenerative Meniscal Tears.}},
author = {Shengfa Li and Hao Liu and Yanbin Zhu and Hang Zhang and Qifeng Tao and Wenbo Zhao and Xin Miao and Shanshan Yang and Tianyu Chen and David Hunter and Changhai Ding and Ting Wang and Juan Wang and Wei Chen},
journal = {Advanced science (Weinheim, Baden-Wurttemberg, Germany)},
year = {2026},
month = oct,
doi = {10.1002/advs.78506},
url = {https://europepmc.org/article/MED/42960748},
note = {CC BY},
}
RIS
TY - JOUR
TI - A Multi-Structural Radiomic Digital Phenotyping Framework for Deciphering Preclinical Evolution of Degenerative Meniscal Tears.
AU - Shengfa Li
AU - Hao Liu
AU - Yanbin Zhu
AU - Hang Zhang
AU - Qifeng Tao
AU - Wenbo Zhao
AU - Xin Miao
AU - Shanshan Yang
AU - Tianyu Chen
AU - David Hunter
AU - Changhai Ding
AU - Ting Wang
AU - Juan Wang
AU - Wei Chen
PY - 2026
DA - 2026/10/30
JO - Advanced science (Weinheim, Baden-Wurttemberg, Germany)
DO - 10.1002/advs.78506
UR - https://europepmc.org/article/MED/42960748
AB - Degenerative meniscus tears (DMTs) are pivotal in knee osteoarthritis progression, yet conventional MRI often fails to capture the subvisual alterations preceding macroscopic failure. We developed a multi-structural digital risk stratification framework (MSC-RM) that integrates standardized radiomic signatures from six knee structures (femur, tibia, cartilages, and menisci) derived from 3D double-echo steady-state MRI with baseline clinical risk profiles. Utilizing a longitudinal cohort (n = 674), our framework decoded complex degeneration patterns, achieving superior 4-year predictive performance (AUC 0.871). Survival analysis revealed that high-risk individuals had a 6.12-fold greater hazard of developing DMTs than the low-risk group. Furthermore, a reader test with five resident surgeons demonstrated that MSC-RM significantly enhanced diagnostic consistency (Kappa increased from 0.38 to 0.55), effectively bridging the expertise gap. By shifting the paradigm from reactive lesion detection to proactive risk management, this framework provides a scalable strategy for precision preventive medicine and establishes digital biomarkers as critical tools for optimizing musculoskeletal health in aging populations.
SN - 2198-3844
ER -