Yang Lvlin, Niu Dongsheng, Bai Zhigang, Ma Jun, Sun Xichun, Liang Yuqi, Zhang Jie
Department of Orthopedics, Autonomous Region People's Hospital of Ningxia Medical University, China.
Adv Clin Exp Med. 2020 Jun;29(6):701-706. doi: 10.17219/acem/121522.
Osteoarthritis represents a kind of chronic and degenerative joint disease characterized by articular cartilage injury and osteoproliferation. Osteoarthritis especially poses a serious threat to the elderly patients. At present, the diagnosis of osteoarthritis mainly consists of clinical examination, X-ray examination, magnetic resonance imaging (MRI), and arthroscopy. However, limitations and misdiagnosis are found within the single method.
This article intends to investigate the feasibility of assessing the condition of knee osteoarthritis through quantitative analysis of cartilage using nuclear magnetic resonance 3D fast-spin spoiled gradient-recalled echo (NMR 3D-FS-SPGR) imaging and γ-glutamic acid carboxylase (GGCX) detection in synovial fluid.
A total of 60 patients with primary knee osteoarthritis were enrolled. All the patients were staged and received 3D-FS-SPGR sequence MRI scan for grading based on scan results and cartilage injury. Cartilage tissues were collected for immunohistochemistry (IHC). The GGCX in cartilage was detected using western blotting to analyze the correlation with arthritis.
The condition of articular cartilage injury in arthritis patients was clearly observed using 3D-FS-SPGR sequence. The expression of GGCX was decreased in 46 patients (p < 0.05). The expression of GGCX in synovial fluid was significantly reduced following upstaging (p < 0.05). The sensitivity measured using combined 3D-FS-SPGR imaging and synovial fluid GGCX detection for the evaluation of arthritis condition was significantly higher than that of the single detection method (p < 0.05).
Our data showed that the sensitivity of combined detection was obviously higher than single detection for the evaluation of arthritis. The 3D-FS-SPGR combined with synovial fluid GGCX detection could be treated as a promising strategy for arthritis evaluation.
