MRI signal-based quantification of subchondral bone at the tibial plateau: a population study

Activation of the extracellular-signal-regulated kinase (ERK)/c-Jun N-terminal kinase (JNK) signal pathway and osteogenic factors in subchondral bone of patients with knee osteoarthritis

Background

The objectives of this study was to explore the activation of the extracellular-signal-regulated kinase (ERK) and c-Jun N-terminal kinase (JNK) signaling pathway and osteogenesis-related factors in the subchondral bone of patients with knee osteoarthritis (OA).

Methods

Ten patients with primary OA who underwent total knee arthroplasty in the Department of Arthritis Surgery of our hospital were enrolled, and subchondral bone tissue samples were obtained during the operation. He staining and saffron staining were used to observe the arrangement of chondrocytes in the patient tissues. The protein expression levels of JNK, p-JNK, ERK, p-ERK, Runx2 and OMD in subchondral bone were detected by Western Blot. Knee osteoarthritis mice were established. He staining was used to observe the arrangement of subchondral bone cells in the knee joint of mice. Cellular mineralized nodules were determined by alizarin red staining.

Results

Firstly, in general and staining, it was observed that the subchondral bone lesions of knee OA participants were obvious. Compared with normal knee joints, the levels of phosphorylation-c-Jun N-terminal kinase (P-JNK) and phosphorylation-extracellular-signal-regulated kinase (P-ERK) in the subchondral bone of knee arthritis participants were significantly increased (P<0.05). The level of osteomodulin (OMD) was significantly reduced (P<0.05). Secondly, compared with normal mice, the levels of JNK, P-JNK, OMD, ERK, and P-ERK in the model group were significantly different (P<0.05). At 2-8 weeks, the JNK and P-JNK levels in the mice model group increased significantly over time (P<0.05), and the OMD level decreased significantly over time (P<0.05). The levels of ERK and P-ERK fluctuated over time. Thirdly, osteoblasts were treated with different concentrations of anisomycin, and stained with alizarin red after continuous culture for 24 and 48 h, respectively. It was found that all the cells were stained with orange-red mineralized nodules. As the concentration of anisomycin was increased, the number of cell mineralization nodules was significantly larger, and the positive rate of chemical nodules increased. Different concentrations of anisomycin were given to interfere with the osteoblasts of mice. When anisomycin was administered at a dose of 25 ng, the OMD level reached the highest level. When the concentration of anisomycin was increased, the osteocalcin (OCN) level also showed an upward trend.

Conclusions

The process by which the JNK signaling pathway regulates OMD may be closely related to the pathological changes of subchondral bone in patients with knee OA, and is involved in the occurrence and development of knee arthritis.

MRI texture analysis of subchondral bone at the tibial plateau

OBJECTIVES

To determine the feasibility of MRI texture analysis as a method of quantifying subchondral bone architecture in knee osteoarthritis (OA).

METHODS

Asymptomatic subjects aged 20-30 (group 1, n = 10), symptomatic patients aged 40-50 (group 2, n = 10) and patients scheduled for knee replacement aged 55-85 (group 3, n = 10) underwent high spatial resolution T1-weighted coronal 3T knee MRI. Regions of interest were created in the medial (MT) and lateral (LT) tibial subchondral bone from which 20 texture parameters were calculated. T2 mapping of the tibial cartilage was performed in groups 1 and 2. Mean parameter values were compared between groups using ANOVA. Linear discriminant analysis (LDA) was used to evaluate the ability of texture analysis to classify subjects correctly.

RESULTS

Significant differences in 18/20 and 12/20 subchondral bone texture parameters were demonstrated between groups at the MT and LT respectively. There was no significant difference in mean MT or LT cartilage T2 values between group 1 and group 2. LDA demonstrated subject classification accuracy of 97 % (95 % CI 91-100 %).

CONCLUSION

MRI texture analysis of tibial subchondral bone may allow detection of alteration in subchondral bone architecture in OA. This has potential applications in understanding OA pathogenesis and assessing response to treatment.

KEY POINTS

• Improved techniques to monitor OA disease progression and treatment response are desirable • Subchondral bone (SB) may play significant role in the development of OA • MRI texture analysis is a method of quantifying changes in SB architecture • Pilot study showed that this technique is feasible and reliable • Significant differences in SB texture were demonstrated between individuals with/without OA.

Quantitative analysis of tibial subchondral bone: Texture analysis outperforms conventional trabecular microarchitecture analysis

BACKGROUND

The aim of this study was to compare two different methods of quantitative assessment of tibial subchondral bone in osteoarthritis (OA): statistical texture analysis (sTA) and trabecular microarchitecture analysis (tMA).

METHODS

Asymptomatic controls aged 20-30 (n = 10), patients aged 40-50 with chronic knee pain but without established OA (n = 10) and patients aged 55-85 with advanced OA scheduled for knee replacement (n = 10) underwent knee MR imaging at 3 Tesla with a three-dimensional gradient echo sequence to allow sTA and tMA. tMA and sTA features were calculated using region of interest creation in the medial (MT) and lateral (LT) tibial subchondral bone. Features were compared between groups using one-way analysis of variance. The two most discriminating tMA and sTA features were used to construct exploratory discriminant functions to assess the ability of the two methods to classify participants.

RESULTS

No tMA features were significantly different between groups at either MT or LT. 17/20 and 11/20 sTA features were significantly different between groups at the MT/LT, respectively (P < 0.001). Discriminant functions created using tMA features classified 12/30 participants correctly (40% accuracy; 95% confidence interval [CI], 22-58%) based on MT data and 9/30 correctly (30%,; 95% CI, 14-46) based on LT data. Discriminant functions using sTA features classified 16/30 participants correctly (53%; 95% CI, 35-71) based on MT data and 14/30 correctly (47%; 95% CI, 29-65) based on LT data.

CONCLUSION

sTA features showed more significant differences between the three study groups and improved classification accuracy compared with tMA features.