AI in MSK - What You Need to Know (2021)-T2-CMK05-2021

Video Transcription

Video Summary

The presentation discusses the importance and advancements in accelerating musculoskeletal MRI (MSKMR) using AI-driven deep learning techniques. Accelerating MRI is crucial for enhancing patient comfort, particularly in pediatrics, improving image quality by reducing motion artifacts, and increasing MR imaging accessibility in Low and Middle-Income Countries (LMICs). Traditional methods like parallel imaging and compressed sensing face limitations such as reduced image quality at higher speeds. Deep learning can potentially resolve the speed vs. quality trade-off, using techniques like undersampling in MR images, allowing faster acquisition while maintaining or enhancing image quality. Various studies demonstrated that deep learning could significantly boost image quality in MSK imaging, making images interchangeable with traditionally sampled images. Prospective studies showcased deep learning's effectiveness in clinical settings with improved diagnostic accuracy and reduced noise. The session also covers other deep learning applications in radiology, such as in osteoarthritis imaging and teaching AI to radiology residents. Although AI in MRI disease detection, especially for the knee, shows promise, the need for continuous development and monitoring to ensure adaptability and effectiveness in diverse clinical settings is emphasized.

Keywords

musculoskeletal MRI

AI-driven deep learning

accelerating MRI

image quality

motion artifacts

LMICs

undersampling

diagnostic accuracy

radiology applications