Latest advancements in imaging techniques in OA.
Daichi HayashiFrank W RoemerThomas M LinkXiaojuan LiFeliks KoganNeil A SegalPatrick OmoumiAli GuermaziPublished in: Therapeutic advances in musculoskeletal disease (2022)
The osteoarthritis (OA) research community has been advocating a shift from radiography-based screening criteria and outcome measures in OA clinical trials to a magnetic resonance imaging (MRI)-based definition of eligibility and endpoint. For conventional morphological MRI, various semiquantitative evaluation tools are available. We have lately witnessed a remarkable technological advance in MRI techniques, including compositional/physiologic imaging and automated quantitative analyses of articular and periarticular structures. More recently, additional technologies were introduced, including positron emission tomography (PET)-MRI, weight-bearing computed tomography (CT), photon-counting spectral CT, shear wave elastography, contrast-enhanced ultrasound, multiscale X-ray phase contrast imaging, and spectroscopic photoacoustic imaging of cartilage. On top of these, we now live in an era in which artificial intelligence is increasingly utilized in medicine. Osteoarthritis imaging is no exception. Successful implementation of artificial intelligence (AI) will hopefully improve the workflow of radiologists, as well as the level of precision and reproducibility in the interpretation of images.
Keyphrases
- artificial intelligence
- computed tomography
- contrast enhanced
- magnetic resonance imaging
- positron emission tomography
- high resolution
- dual energy
- deep learning
- machine learning
- big data
- clinical trial
- image quality
- rheumatoid arthritis
- knee osteoarthritis
- diffusion weighted imaging
- healthcare
- randomized controlled trial
- mental health
- mass spectrometry
- contrast enhanced ultrasound
- fluorescence imaging
- quality improvement
- physical activity
- pet imaging
- photodynamic therapy
- convolutional neural network
- weight gain