Clinical Feasibility of Deep Learning Contrast Synthesis From MR Fingerprinting in Knee Osteoarthritis.
Authors
Affiliations (4)
Affiliations (4)
- Research Unit of Health Sciences and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland.
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland.
- Center for Advanced Imaging Innovation and Research (CAI2R) and the Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.
Abstract
Magnetic Resonance Fingerprinting (MRF) enables rapid quantitative parameter mapping from which synthetic clinical contrast images can be derived using deep learning (DL). This study evaluates the reliability and interchangeability of MRF-derived synthetic knee MRI relative to conventional MRI in patients with osteoarthritis. Prospective single-center comparative study. Between March 2022 and 2023, 78 participants (54 females, mean age 57.2, range 33-78 years) with knee osteoarthritis. 3.0 T; proton density weighted (PDw) imaging, T2-weighted fat-saturated (T2w fs) imaging, and MRF. U-Nets were trained to produce synthetic contrasts from MRF data. Three musculoskeletal radiologists performed MRI OsteoArthritis Knee Score (MOAKS) assessments and image quality evaluation using a Likert scale (1-5). The inter-rater and inter-method reliability were evaluated using prevalence-and-bias-adjusted kappa (PABAK), and percentages of exact matches. Image quality scores were compared using the Wilcoxon test. The limit of statistical significance was set at p < 0.05 and no multiple comparisons corrections were applied. The inter-rater reliability for synthetic MR images varied between 0.980-0.994 (CI 0.975-0.997; exact matches 77.%-89.2%) and for conventional MR images between 0.979 and 0.994 (CI 0.973-0.997; exact matches 75.3%-89.5%). Inter-method reliability between synthetic and conventional MR images was near-perfect: mean PABAK-values and exact matches were 0.927 and 77.9% for cartilage, 0.915 and 89.7% for bone marrow lesions, 0.922 and 65.2% for osteophytes, 0.950 and 72.9% for meniscus pathology, 0.934 and 66.6% for effusion, and 0.857 and 92.5% for Baker's cyst. Average Likert scores were significantly better for conventional than synthetic images: 4.5 vs. 3.9 for PDw and 4.1 vs. 3.2 for T2w fs. MRF-derived DL-based synthetic clinical contrasts provide excellent inter-rater reliability and interchangeability against conventional MR sequences in knee OA; however, image quality needs further development. 2. 2.