The sacrum and sacroiliac joints pose a long-standing challenge for adequate imaging because of their complex anatomical form, oblique orientation, and posterior location in the pelvis, making them subject to superimposition. The sacrum and sacroilia...
PURPOSE: This study is to compare the precision and safety of the orthopaedic robot with conventional fluoroscopy for assisted percutaneous sacroiliac joint screw implantation.
PURPOSE: To develop a deep learning-based metal artifact reduction technique (dl-MAR) and quantitatively compare metal artifacts on dl-MAR-corrected CT-images, orthopedic metal artifact reduction (O-MAR)-corrected CT-images and uncorrected CT-images ...
PURPOSE: The purpose of this study was to develop and evaluate a deep learning model to detect bone marrow edema (BME) in sacroiliac joints and predict the MRI Assessment of SpondyloArthritis International Society (ASAS) definition of active sacroili...
OBJECTIVE: Robot-assisted pedicle screw placement in spinal fusion has been well studied. However, few studies have evaluated robot-assisted sacroiliac joint (SIJ) fusion. The aim of this study was to compare surgical characteristics, accuracy, and c...
OBJECTIVES: This study aimed to evaluate the performance of a deep learning radiomics (DLR) model, which integrates multimodal MRI features and clinical information, in diagnosing sacroiliitis related to axial spondyloarthritis (axSpA).
International journal of rheumatic diseases
39690496
OBJECTIVES: The aim of this study is to develop and validate a model for predicting axial spondyloarthritis (axSpA) based on sacroiliac joint (SIJ)-MRI imaging findings and clinical risk factors.
OBJECTIVES: To assess the ability of a previously trained deep-learning algorithm to identify the presence of inflammation on MRI of sacroiliac joints (SIJ) in a large external validation set of patients with axial spondyloarthritis (axSpA).