Advanced deep learning-based image reconstruction in lumbar spine MRI at 0.55 T - Effects on image quality and acquisition time in comparison to conventional deep learning-based reconstruction.

Objectives: To evaluate an optimized deep leaning-based image post-processing technique in lumbar spine MRI at 0.55 T in terms of image quality and image acquisition time. Materials and methods: Lumbar spine imaging was conducted on 18 patients using a 0.55 T MRI scanner, employing conventional (CDLR) and advanced (ADLR) deep learning-based post-processing techniques. Two musculoskeletal radiologists visually evaluated the images using a 5-point Likert scale to assess image quality and resolution. Quantitative assessment in terms of signal intensities (SI) and contrast ratios was performed by region of interest measurements in different body-tissues (vertebral bone, intervertebral disc, spinal cord, cerebrospinal fluid and autochthonous back muscles) to investigate differences between CDLR and ADLR sequences. Results: The images processed with the advanced technique (ADLR) were rated superior to the conventional technique (CDLR) in terms of signal/contrast, resolution, and assessability of the spinal canal and neural foramen. The interrater agreement was moderate for signal/contrast (ICC = 0.68) and good for resolution (ICC = 0.77), but moderate for spinal canal and neuroforaminal assessability (ICC = 0.55). Quantitative assessment showed a higher contrast ratio for fluid-sensitive sequences in the ADLR images. The use of ADLR reduced image acquisition time by 44.4%, from 14:22 min to 07:59 min. Conclusions: Advanced deep learning-based image reconstruction algorithms improve the visually perceived image quality in lumbar spine imaging at 0.55 T while simultaneously allowing to substantially decrease image acquisition times. Clinical relevance: Advanced deep learning-based image post-processing techniques (ADLR) in lumbar spine MRI at 0.55 T significantly improves image quality while reducing image acquisition time.

Comparing Metal Artifact Severity and Ability to Assess Near-Metal Anatomy Between 0.55 T and 1.5 T MRI in Patients with Metallic Spinal Implants-A Scanner Comparison Study.

RATIONALE AND OBJECTIVES: To compare image quality and metal artifact severity at 0.55 T and 1.5 T MRI in patients with spinal implants following posterior fusion surgery. MATERIALS AND METHODS: 50 consecutive patients (mean age: 69 ±â€¯12 years) who underwent 0.55 T and 1.5 T MRI following posterior fusion surgery of the lumbar or thoracolumbar spine were included. Examinations used metal artifact reduction protocols from clinical routine. Images were rated by two fellowship-trained musculoskeletal radiologists for image quality, ability to assess the spinal canal and the neural foramina, and artifact severity on 5-point Likert scales. Additionally, differences in artifact severity and visibility of near-metal anatomy among implant sizes (1-level vs. 2-level vs. >2-levels) were evaluated. RESULTS: Signal/contrast (mean: 4.0 ±â€¯0.3 [0.55 T] vs. 4.4 ±â€¯0.6 [1.5 T]; p < .001) and resolution (3.8 ±â€¯0.5 vs. 4.2 ±â€¯0.7; p < .001) were rated lower at 0.55 T. The ability to assess the spinal canal (4.4 ±â€¯0.5 vs. 4.2 ±â€¯0.9; p = .69) and the neural foramina (3.8 ±â€¯0.5 vs. 3.8 ±â€¯0.9; p = .19) were however rated equally good with excellent interrater agreement (range: 0.84-0.94). Susceptibility artifacts were rated milder at 0.55 T (1.8 ±â€¯0.5 vs. 3.0 ±â€¯0.6; p < .001). For implant size-based subgroups, the visibility of near-metal anatomy decreased with implant length at 1.5 T, but remained unchanged at 0.55 T. In consequence, the spinal canal and neural foramina could be better assessed at 0.55 T in patients with multi-level implants (4.4 ±â€¯0.5 vs. 3.6 ±â€¯1.1; p < .001). CONCLUSION: Metal artifacts of spinal implants are substantially less pronounced at 0.55 T MRI. When examining patients with multi-level posterior fusion, this translates into a superior ability to assess near-metal anatomy, where 1.5 T MRI reaches diagnostic limitations.

New-Generation 0.55 T MRI of the Knee-Initial Clinical Experience and Comparison With 3 T MRI.

OBJECTIVES: The aim of this study was to compare the detection rate of and reader confidence in 0.55 T knee magnetic resonance imaging (MRI) findings with 3 T knee MRI in patients with acute trauma and knee pain. MATERIALS AND METHODS: In this prospective study, 0.55 T and 3 T knee MRI of 25 symptomatic patients (11 women; median age, 38 years) with suspected internal derangement of the knee was obtained in 1 setting. On the 0.55 T system, a commercially available deep learning image reconstruction algorithm was used (Deep Resolve Gain and Deep Resolve Sharp; Siemens Healthineers), which was not available on the 3 T system. Two board-certified radiologists reviewed all images independently and graded image quality parameters, noted MRI findings and their respective reporting confidence level for the presence or absence, as well as graded the bone, cartilage, meniscus, ligament, and tendon lesions. Image quality and reader confidence levels were compared ( P < 0.05 = significant), and clinical findings were correlated between 0.55 T and 3 T MRI by calculation of the intraclass correlation coefficient (ICC). RESULTS: Image quality was rated higher at 3 T compared with 0.55 T studies (each P ≤ 0.017). Agreement between 0.55 T and 3 T MRI for the detection and grading of bone marrow edema and fractures, ligament and tendon lesions, high-grade meniscus and cartilage lesions, Baker cysts, and joint effusions was perfect for both readers. Overall identification and grading of cartilage and meniscal lesions showed good agreement between high- and low-field MRI (each ICC > 0.76), with lower agreement for low-grade cartilage (ICC = 0.77) and meniscus lesions (ICC = 0.49). There was no difference in readers' confidence levels for reporting lesions of bone, ligaments, tendons, Baker cysts, and joint effusions between 0.55 T and 3 T (each P > 0.157). Reader reporting confidence was higher for cartilage and meniscal lesions at 3 T (each P < 0.041). CONCLUSIONS: New-generation 0.55 T knee MRI, with deep learning-aided image reconstruction, allows for reliable detection and grading of joint lesions in symptomatic patients, but it showed limited accuracy and reader confidence for low-grade cartilage and meniscal lesions in comparison with 3 T MRI.

The role of mutations in COL6A3 in isolated dystonia.

Specific mutations in COL6A3 have recently been reported as the cause of isolated recessive dystonia, which is a rare movement disorder. In all patients, at least one mutation was located in Exons 41 and 42. In an attempt to replicate these findings, we assessed by direct sequencing the frequency of rare variants in Exons 41 and 42 of COL6A3 in 955 patients with isolated or combined dystonia or with another movement disorder with dystonic features. We identified nine heterozygous carriers of rare variants including five different missense mutations and an extremely rare synonymous variant. In these nine patients, we sequenced the remaining 41 coding exons of COL6A3 to test for a second mutation in the compound heterozygous state. In only one of them, a second rare variant was identified (Thr732Met + Pro3082Arg). Of note, this patient had been diagnosed with Parkinson´s disease (with dystonic posturing) due to homozygous PINK1 mutations. The COL6A3 mutations clearly did not segregate with the disease in the four affected siblings of this family. Further, there was no indication for a disease-modifying effect of the COL6A3 mutations since disease severity or age at onset did not correlate with the number of COL6A3 mutated alleles in this family. In conjunction with the relatively high frequency of homozygous carriers of reported mutations in publically available databases, our data call a causal role for variants in COL6A3 in isolated dystonia into question.