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World J Orthop. Mar 18, 2026; 17(3): 115616
Published online Mar 18, 2026. doi: 10.5312/wjo.v17.i3.115616
Published online Mar 18, 2026. doi: 10.5312/wjo.v17.i3.115616
Limited and frequently overlooked radiological evidence of knee osteoarthritis
Jia-Yao Zhu, Lei Chen, Ju Li, Tao-Tao Xu, Department of Orthopaedics and Traumatology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou 310006, Zhejiang Province, China
Co-first authors: Jia-Yao Zhu and Lei Chen.
Co-corresponding authors: Ju Li and Tao-Tao Xu.
Author contributions: Zhu JY and Chen L wrote the original draft as co-first authors; Li J and Xu TT contributed to conceptualization, writing, reviewing and editing as co-corresponding authors; all authors participated in drafting the manuscript, read and approved the final version of the manuscript.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
Corresponding author: Tao-Tao Xu, MD, PhD, Attending Physician, Associate Professor, Department of Orthopaedics and Traumatology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), No. 54 Youdian Road, Shangcheng District, Hangzhou 310006, Zhejiang Province, China.
Received: October 21, 2025
Revised: November 10, 2025
Accepted: January 5, 2026
Published online: March 18, 2026
Processing time: 146 Days and 10 Hours
Revised: November 10, 2025
Accepted: January 5, 2026
Published online: March 18, 2026
Processing time: 146 Days and 10 Hours
Core Tip
Core Tip: The prevalence of knee osteoarthritis is rising annually, causing chronic pain, impaired joint function, and reduced quality of life. Accurate diagnosis has thus become crucial. With evolving understanding, clinicians must assess all knee compartments comprehensively. The limitations of single diagnostic tools have driven the development of multimodal approaches. These are enhanced by intelligent network technologies that analyze large clinical datasets, enabling deep learning models to improve diagnostic precision.