How AI may transform musculoskeletal imaging

A Guermazi, P Omoumi, M Tordjman, J Fritz, R Kijowski… - Radiology, 2024‏ - pubs.rsna.org
While musculoskeletal imaging volumes are increasing, there is a relative shortage of
subspecialized musculoskeletal radiologists to interpret the studies. Will artificial intelligence …

[HTML][HTML] MR-imaging in osteoarthritis: current standard of practice and future outlook

J Ehmig, G Engel, J Lotz, W Lehmann, S Taheri… - Diagnostics, 2023‏ - mdpi.com
Osteoarthritis (OA) is a common degenerative joint disease that affects millions of people
worldwide. Magnetic resonance imaging (MRI) has emerged as a powerful tool for the …

Prospective Comparison of Standard and Deep Learning–reconstructed Turbo Spin-Echo MRI of the Shoulder

Y **e, H Tao, X Li, Y Hu, C Liu, B Zhou, J Cai, D Nickel… - Radiology, 2024‏ - pubs.rsna.org
Background Deep learning (DL)–based MRI reconstructions can reduce imaging times for
turbo spin-echo (TSE) examinations. However, studies that prospectively use DL-based …

Feasibility of AI-assisted compressed sensing protocols in knee MR imaging: a prospective multi-reader study

Q Wang, W Zhao, X **ng, Y Wang, P **n, Y Chen… - European …, 2023‏ - Springer
Objectives To evaluate the image quality and diagnostic performance of AI-assisted
compressed sensing (ACS) accelerated two-dimensional fast spin-echo MRI compared with …

[HTML][HTML] A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: past, present and future

FW Roemer, M Jarraya, D Hayashi, MD Crema… - Osteoarthritis and …, 2024‏ - Elsevier
Objective This perspective describes the evolution of semi-quantitative (SQ) magnetic
resonance imaging (MRI) in characterizing structural tissue pathologies in osteoarthritis (OA) …

Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology

SH Park, K Han, JG Lee - La radiologia medica, 2024‏ - Springer
Artificial intelligence (AI) has numerous applications in radiology. Clinical research studies
to evaluate the AI models are also diverse. Consequently, diverse outcome metrics and …

Deep Learning Superresolution for Simultaneous Multislice Parallel Imaging–Accelerated Knee MRI Using Arthroscopy Validation

SS Walter, J Vosshenrich, T Cantarelli Rodrigues… - Radiology, 2025‏ - pubs.rsna.org
Background Deep learning (DL) methods can improve accelerated MRI but require
validation against an independent reference standard to ensure robustness and accuracy …

Accelerated musculoskeletal magnetic resonance imaging

MA Yoon, GE Gold… - Journal of Magnetic …, 2024‏ - Wiley Online Library
With a substantial growth in the use of musculoskeletal MRI, there has been a growing need
to improve MRI workflow, and faster imaging has been suggested as one of the solutions for …

Evaluation of a newly designed deep learning-based algorithm for automated assessment of scapholunate distance in wrist radiography as a surrogate parameter for …

G Keller, K Rachunek, F Springer, M Kraus - La radiologia medica, 2023‏ - Springer
Purpose Not diagnosed or mistreated scapholunate ligament (SL) tears represent a frequent
cause of degenerative wrist arthritis. A newly developed deep learning (DL)-based …

Strategic application of imaging in DMOAD clinical trials: focus on eligibility, drug delivery, and semiquantitative assessment of structural progression

A Guermazi, FW Roemer, MD Crema… - Therapeutic …, 2023‏ - journals.sagepub.com
Despite decades of research efforts and multiple clinical trials aimed at discovering
efficacious disease-modifying osteoarthritis (OA) drugs (DMOAD), we still do not have a drug …