Baseline MRI osteitis and tenosynovitis were independent predictors of 2 year MRI damage progression in RA patients in clinical remission, while independent predictors of radiographic damage progression were age and gender. Following an MRI treat-to-target strategy, low scores of patient-reported outcomes and low tender joint count predicted achievement of stringent remission.
Efficacy and safety of intra-articular therapies in rheumatic and musculoskeletal diseases: an overview of systematic reviews
Precision Medicine and Artificial Intelligence – The Perfect Fit for Autoimmunity
Doppler ultrasound predicts successful discontinuation of biological DMARDs in rheumatoid arthritis patients in clinical remission
Predictors of joint damage progression and stringent remission in patients with established rheumatoid arthritis in clinical remission.
Quantitative Imaging in Inflammatory Arthritis: Between Tradition and Innovation.
Radiologic imaging is crucial for diagnosing and monitoring rheumatic inflammatory diseases. Particularly the emerging approach of precision medicine has increased the interest in quantitative imaging. Extensive research has shown that ultrasound allows a quantification of direct signs such as bone erosions and synovial thickness. Dual-energy X-ray absorptiometry and high-resolution peripheral quantitative computed tomography (CT) contribute to the quantitative assessment of secondary signs such as osteoporosis or lean mass loss. Magnetic resonance imaging (MRI), using different techniques and sequences, permits in-depth evaluations. For instance, the perfusion of the inflamed synovium can be quantified by dynamic contrast-enhanced imaging or diffusion-weighted imaging, and cartilage injury can be assessed by mapping (T1ρ, T2). Furthermore, the increased metabolic activity characterizing the inflammatory response can be reliably assessed by hybrid imaging (positron emission tomography [PET]/CT, PET/MRI). Finally, advances in intelligent systems are pushing forward quantitative imaging. Complex mathematical algorithms of lesions’ segmentation and advanced pattern recognition are showing promising results.