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. 2022 Jul 6;8(4):1759-1769.
doi: 10.3390/tomography8040148.

Reduction in Acquisition Time and Improvement in Image Quality in T2-Weighted MR Imaging of Musculoskeletal Tumors of the Extremities Using a Novel Deep Learning-Based Reconstruction Technique in a Turbo Spin Echo (TSE) Sequence

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Reduction in Acquisition Time and Improvement in Image Quality in T2-Weighted MR Imaging of Musculoskeletal Tumors of the Extremities Using a Novel Deep Learning-Based Reconstruction Technique in a Turbo Spin Echo (TSE) Sequence

Daniel Wessling et al. Tomography. .

Abstract

Background: The aim of this study was to assess the technical feasibility and the impact on image quality and acquisition time of a deep learning-accelerated fat-saturated T2-weighted turbo spin echo sequence in musculoskeletal imaging of the extremities. Methods: Twenty-three patients who underwent MRI of the extremities were prospectively included. Standard T2w turbo inversion recovery magnitude (TIRMStd) imaging was compared to a deep learning-accelerated T2w TSE (TSEDL) sequence. Image analysis of 23 patients with a mean age of 60 years (range 30−86) was performed regarding image quality, noise, sharpness, contrast, artifacts, lesion detectability and diagnostic confidence. Pathological findings were documented measuring the maximum diameter. Results: The analysis showed a significant improvement for the T2 TSEDL with regard to image quality, noise, contrast, sharpness, lesion detectability, and diagnostic confidence, as compared to T2 TIRMStd (each p < 0.001). There were no differences in the number of detected lesions. The time of acquisition (TA) could be reduced by 52−59%. Interrater agreement was almost perfect (κ = 0.886). Conclusion: Accelerated T2 TSEDL was technically feasible and superior to conventionally applied T2 TIRMStd. Concurrently, TA could be reduced by 52−59%. Therefore, deep learning-accelerated MR imaging is a promising and applicable method in musculoskeletal imaging.

Keywords: accelerated turbo spin echo MRI; artificial intelligence; deep learning; musculoskeletal imaging; musculoskeletal tumors.

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Conflict of interest statement

Dominik Nickel is an employee of Siemens Healthcare. Siemens Healthcare is a financial partner of the Radiological Department of the University Hospital of Tübingen.

Figures

Figure 1
Figure 1
Bland-Altman plot to display the differences in the measurements of the lesion diameter between the T2-weighted TIRMStd and the TSEDL in reader 1 (left) and reader 2 (right).
Figure 2
Figure 2
Comparison of T2-weighted TSEDL and T2 TIRMStd. The T2 TIRMStd shows a better image quality, contrast, and sharpness.
Figure 3
Figure 3
Follow up MRI examination of a 49-year-old with a T2w hyperintense lesion (arrows) of the right proximal femur, the finding would be compatible with enchondroma. The TSEDL shows a better image quality, contrast, sharpness, and noise and thus, allows a better diagnostic confidence.
Figure 4
Figure 4
Follow-up MRI examination of an 81-year-old patient with Merkel cell carcinoma. As an incidental finding, the coronal TIRMStd sequence shows a lipoma of the medial vastus muscle. The T2w TSEDL shows a better image quality, noise, and sharpness than the TIRMStd.
Figure 5
Figure 5
Follow-up MR examination of a 56-year-old male patient with histopathologically proven myxofibrosarcoma. T2w TSEDL allows a better delineation of the conglomerate tumor of the left thigh due to better image quality, noise, sharpness, and contrast.

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