To evaluate the value of Color Doppler ultrasound and magnetic resonance imaging (MRI) findings in diagnosis of juvenile idiopathic arthritis (JIA) activity.
Methods:
A total of 146 knees or ankles in 65 JIA patients were examined by Color Doppler ultrasound
and 56 joints were examined by MRI at the same time. The ultrasonic and MRI characteristics of different disease activity were analyzed.
Results:
Hydrarthrosis
synovial membrane thickening
tendinopathies and bone erosions were common findings in ultrasound of JIA. Hydrarthrosis was found in 61.1%
90.7% and 90.3
% of joints in JIA with low
moderate and high disease activity. Synovial membrane thickening was seen in 18.1%
74.4% and 80.6% in JIA with low
moderate and high disease activity. The higher disease activity had more synovial blood flow signals. MRI findings in JIA were nearly agreed with ultrasound. Hydrarthrosis was found in 50.0%
93.8% and 100% of joints in JIA with low
moderate and high disease activity and synovial membrane thickening was found in 46.4%
87.5% and 91.7% of joints
respectively.
Conclusion:
Color Doppler ultrasound and MRI could provide imaging evidence in assessment and monitoring of JIA activity.
Diagnostic value of simplified MRI sequence in breast diseases
The value of diffusion kurtosis imaging combined with peripheral blood inflammatory markers in predicting the pathological grading of clear cell renal cell carcinoma
A flexible segmentation network for MRI: toward accurate tumor delineation and 3D reconstruction in brain glioma
Prediction of lymphovascular invasion using multiparametric MRI habitat radiomics based on machine learning algorithms in gastric cancer
Application value of multimodal imaging technology based on CT and MRI in the diagnosis and PRETEXT staging of childhood hepatoblastoma
Related Author
HUANG Xing
LIANG Yan
YI Chuang
WANG Yan
REN Junjie
LI Weilan
BA Zhufei
LIU Tao
Related Institution
Department of Radiology, Jilin Provincial People's Hospital
Department of Medical Imaging, North China University of Science and Technology Affiliated Hospital
Department of Cardiothoracic Surgery, KaiLuan General Hospital
Department of Radiology, Cancer Hospital of Dalian University of Technology, Liaoning Cancer Hospital & Institute
Department of Computing Science and Artificial Intelligence, Liaoning Normal University