Lesion-Specific Clinical Validation of Deep-Learning-Accelerated Knee MRI: Relevance to Orthopedic and Sports Medicine Practice
TL;DR
Current evidence supports consideration of clinical implementation of accelerated knee MRI protocols incorporating deep-learning reconstruction after local lesion-, protocol-, and vendor-specific validation, but does not establish universal interchangeability across systems or lesion types.
Abstract
Background. Accelerated knee MRI protocols incorporating deep-learning reconstruction (DLR) may shorten examinations, but clinical performance varies by lesion and validation method. Aim. To synthesize lesion-specific clinical evidence, assess acquisition-time reductions, and compare conventional-MRI comparator studies with arthroscopy-referenced validation. Material and methods. A structured literature search identified 22 primary clinical studies. Evidence was classified by validation category and synthesized separately for anterior cruciate ligament (ACL), medial and lateral menisci, articular cartilage, and other structures. Results. Acquisition time was commonly reduced by approximately one-third to one-half, although most protocols combined DLR with other acceleration methods. Clinically useful performance was generally preserved. Evidence was most consistent for ACL tears and generally supportive for medial meniscal tears. Lateral meniscal specificity remained high, but sensitivity was lower and formal non-inferiority was not consistently demonstrated. Cartilage findings were variable and protocol-dependent, while evidence for other structures was limited. Conclusions. Current evidence supports consideration of clinical implementation of accelerated knee MRI protocols incorporating deep-learning reconstruction after local lesion-, protocol-, and vendor-specific validation, but does not establish universal interchangeability across systems or lesion types.