DeepResolve was capable of resolving high-resolution thin-slice knee MRI from lower-resolution thicker slices, achieving superior quantitative and qualitative diagnostic performance to both conventionally used and state-of-the-art methods.

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‐resolution (90.2 ± 1.7%) and super‐resolution (89.6 ± 2.0%) were significantly higher (P < 0.001) than TCI (86.3 ± 5.6%). Segmentation overlap of super‐resolution with the original‐resolution (DC = 97.6 ± 0.7%) was significantly higher (P < 0.0001) than TCI overlap (DC = 95.0 ± 1.1%). Cartilage image quality for sharpness and contrast levels, and the through‐plane quantitative blur factor for super‐resolution images, was significantly (P < 0.001) better than TCI. Super‐resolution osteophyte detection sensitivity of 80% (76–82%), specificity of 93% (92–94%), and DOR of 32 (22–46) was significantly higher (P < 0.001) than TCI sensitivity of 73% (69–76%), specificity of 90% (89–91%), and DOR of 17 (13–22). Data Conclusion Super‐resolution appears to consistently outperform naïve interpolation and may improve image quality without biasing quantitative biomarkers. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:768–779.

Background Clinical knee MRI protocols require upwards of 15 minutes of scan time. Purpose/Hypothesis To compare the imaging appearance of knee abnormalities depicted with a 5‐minute 3D double‐echo in steady‐state (DESS) sequence with separate echo images, with that of a routine clinical knee MRI protocol. A secondary goal was to compare the imaging appearance of knee abnormalities depicted with 5‐minute DESS paired with a 2‐minute coronal proton‐density fat‐saturated (PDFS) sequence. Study Type Prospective. Subjects Thirty‐six consecutive patients (19 male) referred for a routine knee MRI. Field Strength/Sequences DESS and PDFS at 3T. Assessment Five musculoskeletal radiologists evaluated all images for the presence of internal knee derangement using DESS, DESS+PDFS, and the conventional imaging protocol, and their associated diagnostic confidence of the reading. Statistical Tests Differences in positive and negative percent agreement (PPA and NPA, respectively) and 95% confidence intervals (CIs) for DESS and DESS+PDFS compared with the conventional protocol were calculated and tested using exact McNemar tests. The percentage of observations where DESS or DESS+PDFS had equivalent confidence ratings to DESS+Conv were tested with exact symmetry tests. Interreader agreement was calculated using Krippendorff's alpha. Results DESS had a PPA of 90% (88–92% CI) and NPA of 99% (99–99% CI). DESS+PDFS had increased PPA of 99% (95–99% CI) and NPA of 100% (99–100% CI) compared with DESS (both P < 0.001). DESS had equivalent diagnostic confidence to DESS+Conv in 94% of findings, whereas DESS+PDFS had equivalent diagnostic confidence in 99% of findings (both P < 0.001). All readers had moderate concordance for all three protocols (Krippendorff's alpha 47–48%). Data Conclusion Both 1) 5‐minute 3D‐DESS with separated echoes and 2) 5‐minute 3D‐DESS paired with a 2‐minute coronal PDFS sequence depicted knee abnormalities similarly to a routine clinical knee MRI protocol, which may be a promising technique for abbreviated knee MRI. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Evaluation of accelerated magnetic resonance imaging (MRI) reconstruction methods is imperfect due to the discordance between quantitative image quality metrics (IQMs) and radiologist-perceived image quality. Self-supervised learning (SSL) is a deep learning (DL) method that has become a popular pre-training tool due to its ability to capture generalizable and domain-specific feature representations of the underlying data without the need for labels. In this study, we derive a data-driven self-supervised feature distance (SSFD) IQM to assess MR image reconstruction quality. We demonstrate that SSFD is more highly correlated to three radiologist&rsquo;s perceived image quality on DL-based sparse reconstructions than conventional IQMs.