Utility of deep learning super‐resolution in the context of osteoarthritis MRI biomarkers

作者：Akshay Chaudhari, Kathryn J. Stevens, Jeff Wood, Amit Chakraborty, Eric K. Gibbons, Zhongnan Fang, Arjun Desai, Jin Hyung Lee, Garry E. Gold, Brian A. Hargreaves · 发表于：Journal of Magnetic Resonance Imaging · 年份：2019 · DOI：10.1002/jmri.26872 · 被引用次数：72 · 研究领域：Bone and Joint Diseases、Osteoarthritis Treatment and Mechanisms、Advanced Image Processing Techniques

BACKGROUND: Super-resolution is an emerging method for enhancing MRI resolution; however, its impact on image quality is still unknown. PURPOSE: To evaluate MRI super-resolution using quantitative and qualitative metrics of cartilage morphometry, osteophyte detection, and global image blurring. STUDY TYPE: Retrospective. POPULATION: In all, 176 MRI studies of subjects at varying stages of osteoarthritis. FIELD STRENGTH/SEQUENCE: Original-resolution 3D double-echo steady-state (DESS) and DESS with 3× thicker slices retrospectively enhanced using super-resolution and tricubic interpolation (TCI) at 3T. ASSESSMENT: A quantitative comparison of femoral cartilage morphometry was performed for the original-resolution DESS, the super-resolution, and the TCI scans in 17 subjects. A reader study by three musculoskeletal radiologists assessed cartilage image quality, overall image sharpness, and osteophytes incidence in all three sets of scans. A referenceless blurring metric evaluated blurring in all three image dimensions for the three sets of scans. STATISTICAL TESTS: Mann-Whitney U-tests compared Dice coefficients (DC) of segmentation accuracy for the DESS, super-resolution, and TCI images, along with the image quality readings and blurring metrics. Sensitivity, specificity, and diagnostic odds ratio (DOR) with 95% confidence intervals compared osteophyte detection for the super-resolution and TCI images, with the original-resolution as a reference. RESULTS: DC for the original-res...