Skip to main content
Top
Published in: European Radiology 9/2022

Open Access 07-04-2022 | Magnetic Resonance Imaging | Musculoskeletal

Feasibility of an accelerated 2D-multi-contrast knee MRI protocol using deep-learning image reconstruction: a prospective intraindividual comparison with a standard MRI protocol

Authors: Judith Herrmann, Gabriel Keller, Sebastian Gassenmaier, Dominik Nickel, Gregor Koerzdoerfer, Mahmoud Mostapha, Haidara Almansour, Saif Afat, Ahmed E. Othman

Published in: European Radiology | Issue 9/2022

Login to get access

Abstract

Objectives

The aim of this study was to evaluate the image quality and diagnostic performance of a deep-learning (DL)–accelerated two–dimensional (2D) turbo spin echo (TSE) MRI of the knee at 1.5 and 3 T in clinical routine in comparison to standard MRI.

Material and methods

Sixty participants, who underwent knee MRI at 1.5 and 3 T between October/2020 and March/2021 with a protocol using standard 2D–TSE (TSES) and DL–accelerated 2D–TSE sequences (TSEDL), were enrolled in this prospective institutional review board–approved study. Three radiologists assessed the sequences regarding structural abnormalities and evaluated the images concerning overall image quality, artifacts, noise, sharpness, subjective signal-to-noise ratio, and diagnostic confidence using a Likert scale (1–5, 5 = best).

Results

Overall image quality for TSEDL was rated to be excellent (median 5, IQR 4–5), significantly higher compared to TSES (median 5, IQR 4 – 5, p < 0.05), showing significantly lower extents of noise and improved sharpness (p < 0.001). Inter- and intra-reader agreement was almost perfect (κ = 0.92–1.00) for the detection of internal derangement and substantial to almost perfect (κ = 0.58–0.98) for the assessment of cartilage defects. No difference was found concerning the detection of bone marrow edema and fractures. The diagnostic confidence of TSEDL was rated to be comparable to that of TSES (median 5, IQR 5–5, p > 0.05). Time of acquisition could be reduced to 6:11 min using TSEDL compared to 11:56 min for a protocol using TSES.

Conclusion

TSEDL of the knee is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared to TSES, reducing the acquisition time about 50%.

Key Points

• Deep-learning reconstructed TSE imaging is able to almost halve the acquisition time of a three-plane knee MRI with proton density and T1-weighted images, from 11:56 min to 6:11 min at 3 T.
• Deep-learning reconstructed TSE imaging of the knee provided significant improvement of noise levels (p < 0.001), providing higher image quality (p < 0.05) compared to conventional TSE imaging.
• Deep-learning reconstructed TSE imaging of the knee had similar diagnostic performance for internal derangement of the knee compared to standard TSE.
Appendix
Available only for authorised users
Literature
1.
go back to reference Vahey TN, Meyer SF, Shelbourne KD, Klootwyk TE (1994) MR imaging of anterior cruciate ligament injuries. Magn Reson Imaging Clin N Am 2:365–380CrossRef Vahey TN, Meyer SF, Shelbourne KD, Klootwyk TE (1994) MR imaging of anterior cruciate ligament injuries. Magn Reson Imaging Clin N Am 2:365–380CrossRef
2.
go back to reference Schnaiter JW, Roemer F, McKenna-Kuettner A et al (2018) Diagnostic accuracy of an MRI protocol of the knee accelerated through parallel imaging in correlation to arthroscopy. Rofo 190:265–272CrossRef Schnaiter JW, Roemer F, McKenna-Kuettner A et al (2018) Diagnostic accuracy of an MRI protocol of the knee accelerated through parallel imaging in correlation to arthroscopy. Rofo 190:265–272CrossRef
3.
go back to reference Smith C, McGarvey C, Harb Z et al (2016) Diagnostic efficacy of 3-T MRI for knee injuries using arthroscopy as a reference standard: a meta-analysis. AJR Am J Roentgenol 207:369–377CrossRef Smith C, McGarvey C, Harb Z et al (2016) Diagnostic efficacy of 3-T MRI for knee injuries using arthroscopy as a reference standard: a meta-analysis. AJR Am J Roentgenol 207:369–377CrossRef
4.
go back to reference Fritz J, Fritz B, Thawait GG, Meyer H, Gilson WD, Raithel E (2016) Three-dimensional CAIPIRINHA SPACE TSE for 5-minute high-resolution MRI of the knee. Invest Radiol 51:609–617CrossRef Fritz J, Fritz B, Thawait GG, Meyer H, Gilson WD, Raithel E (2016) Three-dimensional CAIPIRINHA SPACE TSE for 5-minute high-resolution MRI of the knee. Invest Radiol 51:609–617CrossRef
5.
go back to reference Notohamiprodjo M, Horng A, Pietschmann MF et al (2009) MRI of the knee at 3T: first clinical results with an isotropic PDfs-weighted 3D-TSE-sequence. Invest Radiol 44:585–597CrossRef Notohamiprodjo M, Horng A, Pietschmann MF et al (2009) MRI of the knee at 3T: first clinical results with an isotropic PDfs-weighted 3D-TSE-sequence. Invest Radiol 44:585–597CrossRef
6.
go back to reference Kijowski R, Davis KW, Blankenbaker DG, Woods MA, Del Rio AM, De Smet AA (2012) Evaluation of the menisci of the knee joint using three-dimensional isotropic resolution fast spin-echo imaging: diagnostic performance in 250 patients with surgical correlation. Skeletal Radiol 41:169–178CrossRef Kijowski R, Davis KW, Blankenbaker DG, Woods MA, Del Rio AM, De Smet AA (2012) Evaluation of the menisci of the knee joint using three-dimensional isotropic resolution fast spin-echo imaging: diagnostic performance in 250 patients with surgical correlation. Skeletal Radiol 41:169–178CrossRef
7.
go back to reference Del Grande F, Delcogliano M, Guglielmi R et al (2018) Fully automated 10-minute 3D CAIPIRINHA SPACE TSE MRI of the knee in adults: a multicenter, multireader, multifield-strength validation study. Invest Radiol 53:689–697CrossRef Del Grande F, Delcogliano M, Guglielmi R et al (2018) Fully automated 10-minute 3D CAIPIRINHA SPACE TSE MRI of the knee in adults: a multicenter, multireader, multifield-strength validation study. Invest Radiol 53:689–697CrossRef
9.
go back to reference Schlemper J, Caballero J, Hajnal JV, Price AN, Rueckert D (2018) A deep cascade of convolutional neural networks for dynamic MR image reconstruction. IEEE Trans Med Imaging 37:491–503CrossRef Schlemper J, Caballero J, Hajnal JV, Price AN, Rueckert D (2018) A deep cascade of convolutional neural networks for dynamic MR image reconstruction. IEEE Trans Med Imaging 37:491–503CrossRef
10.
go back to reference Hammernik K, Klatzer T, Kobler E et al (2018) Learning a variational network for reconstruction of accelerated MRI data. Magn Reson Med 79:3055–3071CrossRef Hammernik K, Klatzer T, Kobler E et al (2018) Learning a variational network for reconstruction of accelerated MRI data. Magn Reson Med 79:3055–3071CrossRef
11.
go back to reference Flack VF, Afifi A, Lachenbruch P, Schouten H (1988) Sample size determinations for the two rater kappa statistic. Psychometrika 53:321–325CrossRef Flack VF, Afifi A, Lachenbruch P, Schouten H (1988) Sample size determinations for the two rater kappa statistic. Psychometrika 53:321–325CrossRef
12.
go back to reference Knoll F, Hammernik K, Kobler E, Pock T, Recht MP, Sodickson DK (2019) Assessment of the generalization of learned image reconstruction and the potential for transfer learning. Magn Reson Med 81:116–128CrossRef Knoll F, Hammernik K, Kobler E, Pock T, Recht MP, Sodickson DK (2019) Assessment of the generalization of learned image reconstruction and the potential for transfer learning. Magn Reson Med 81:116–128CrossRef
14.
go back to reference Kannengiesser S, Maihle B, Nadar M (2016) Universal iterative denoising of complex-valued volumetric MR image data using supplementary information. Proc ISMRM, pp 1779 Kannengiesser S, Maihle B, Nadar M (2016) Universal iterative denoising of complex-valued volumetric MR image data using supplementary information. Proc ISMRM, pp 1779
15.
go back to reference Chaudhari AS, Fang Z, Kogan F et al (2018) Super-resolution musculoskeletal MRI using deep learning. Magn Reson Med 80:2139–2154CrossRef Chaudhari AS, Fang Z, Kogan F et al (2018) Super-resolution musculoskeletal MRI using deep learning. Magn Reson Med 80:2139–2154CrossRef
16.
go back to reference Defazio A, Murrell T, Recht MP (2020) MRI banding removal via adversarial training. arXiv preprint arXiv:200108699 Defazio A, Murrell T, Recht MP (2020) MRI banding removal via adversarial training. arXiv preprint arXiv:200108699
17.
go back to reference Notohamiprodjo M, Horng A, Kuschel B et al (2012) 3D-imaging of the knee with an optimized 3D-FSE-sequence and a 15-channel knee-coil. Eur J Radiol 81:3441–3449CrossRef Notohamiprodjo M, Horng A, Kuschel B et al (2012) 3D-imaging of the knee with an optimized 3D-FSE-sequence and a 15-channel knee-coil. Eur J Radiol 81:3441–3449CrossRef
18.
go back to reference Lee S, Lee GY, Kim S, Park YB, Lee HJ (2020) Clinical utility of fat-suppressed 3-dimensional controlled aliasing in parallel imaging results in higher acceleration sampling perfection with application optimized contrast using different flip angle evolutions MRI of the knee in adults. Br J Radiol 93:20190725CrossRef Lee S, Lee GY, Kim S, Park YB, Lee HJ (2020) Clinical utility of fat-suppressed 3-dimensional controlled aliasing in parallel imaging results in higher acceleration sampling perfection with application optimized contrast using different flip angle evolutions MRI of the knee in adults. Br J Radiol 93:20190725CrossRef
19.
go back to reference Fritz J, Raithel E, Thawait GK, Gilson W, Papp DF (2016) Six-fold acceleration of high-spatial resolution 3D SPACE MRI of the knee through incoherent k-space undersampling and iterative reconstruction-first experience. Investig Radiol 51:400–409CrossRef Fritz J, Raithel E, Thawait GK, Gilson W, Papp DF (2016) Six-fold acceleration of high-spatial resolution 3D SPACE MRI of the knee through incoherent k-space undersampling and iterative reconstruction-first experience. Investig Radiol 51:400–409CrossRef
20.
go back to reference Fritz J, Fritz B, Zhang J et al (2017) Simultaneous multislice accelerated turbo spin echo magnetic resonance imaging: comparison and combination with in-plane parallel imaging acceleration for high-resolution magnetic resonance imaging of the knee. Invest Radiol 52:529–537CrossRef Fritz J, Fritz B, Zhang J et al (2017) Simultaneous multislice accelerated turbo spin echo magnetic resonance imaging: comparison and combination with in-plane parallel imaging acceleration for high-resolution magnetic resonance imaging of the knee. Invest Radiol 52:529–537CrossRef
21.
go back to reference Iuga AI, Abdullayev N, Weiss K et al (2020) Accelerated MRI of the knee. Quality and efficiency of compressed sensing. Eur J Radiol 132:109273CrossRef Iuga AI, Abdullayev N, Weiss K et al (2020) Accelerated MRI of the knee. Quality and efficiency of compressed sensing. Eur J Radiol 132:109273CrossRef
22.
go back to reference Matcuk GR, Gross JS, Fields BKK, Cen S (2020) Compressed sensing MR imaging (CS-MRI) of the knee: assessment of quality, inter-reader agreement, and acquisition time. Magn Reson Med Sci 19:254–258CrossRef Matcuk GR, Gross JS, Fields BKK, Cen S (2020) Compressed sensing MR imaging (CS-MRI) of the knee: assessment of quality, inter-reader agreement, and acquisition time. Magn Reson Med Sci 19:254–258CrossRef
23.
go back to reference Niitsu M, Ikeda K (2003) Routine MR examination of the knee using parallel imaging. Clin Radiol 58:801–807CrossRef Niitsu M, Ikeda K (2003) Routine MR examination of the knee using parallel imaging. Clin Radiol 58:801–807CrossRef
24.
go back to reference Kreitner KF, Romaneehsen B, Krummenauer F, Oberholzer K, Muller LP, Duber C (2006) Fast magnetic resonance imaging of the knee using a parallel acquisition technique (mSENSE): a prospective performance evaluation. Eur Radiol 16:1659–1666CrossRef Kreitner KF, Romaneehsen B, Krummenauer F, Oberholzer K, Muller LP, Duber C (2006) Fast magnetic resonance imaging of the knee using a parallel acquisition technique (mSENSE): a prospective performance evaluation. Eur Radiol 16:1659–1666CrossRef
25.
go back to reference Deshmane A, Gulani V, Griswold MA, Seiberlich N (2012) Parallel MR imaging. J Magn Reson Imaging 36:55–72CrossRef Deshmane A, Gulani V, Griswold MA, Seiberlich N (2012) Parallel MR imaging. J Magn Reson Imaging 36:55–72CrossRef
26.
go back to reference Benali S, Johnston PR, Gholipour A et al (2018) Simultaneous multi-slice accelerated turbo spin echo of the knee in pediatric patients. Skeletal Radiol 47:821–831CrossRef Benali S, Johnston PR, Gholipour A et al (2018) Simultaneous multi-slice accelerated turbo spin echo of the knee in pediatric patients. Skeletal Radiol 47:821–831CrossRef
29.
go back to reference Gassenmaier S, Afat S, Nickel D, Mostapha M, Herrmann J, Othman AE (2021) Deep learning-accelerated T2-weighted imaging of the prostate: reduction of acquisition time and improvement of image quality. Eur J Radiol 137:109600CrossRef Gassenmaier S, Afat S, Nickel D, Mostapha M, Herrmann J, Othman AE (2021) Deep learning-accelerated T2-weighted imaging of the prostate: reduction of acquisition time and improvement of image quality. Eur J Radiol 137:109600CrossRef
32.
go back to reference Quatman CE, Hettrich CM, Schmitt LC, Spindler KP (2011) The clinical utility and diagnostic performance of magnetic resonance imaging for identification of early and advanced knee osteoarthritis: a systematic review. Am J Sports Med 39:1557–1568CrossRef Quatman CE, Hettrich CM, Schmitt LC, Spindler KP (2011) The clinical utility and diagnostic performance of magnetic resonance imaging for identification of early and advanced knee osteoarthritis: a systematic review. Am J Sports Med 39:1557–1568CrossRef
33.
go back to reference Jaspan ON, Fleysher R, Lipton ML (2015) Compressed sensing MRI: a review of the clinical literature. Br J Radiol 88:20150487CrossRef Jaspan ON, Fleysher R, Lipton ML (2015) Compressed sensing MRI: a review of the clinical literature. Br J Radiol 88:20150487CrossRef
34.
go back to reference Lustig M, Donoho D, Pauly JM (2007) Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med 58:1182–1195CrossRef Lustig M, Donoho D, Pauly JM (2007) Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med 58:1182–1195CrossRef
Metadata
Title
Feasibility of an accelerated 2D-multi-contrast knee MRI protocol using deep-learning image reconstruction: a prospective intraindividual comparison with a standard MRI protocol
Authors
Judith Herrmann
Gabriel Keller
Sebastian Gassenmaier
Dominik Nickel
Gregor Koerzdoerfer
Mahmoud Mostapha
Haidara Almansour
Saif Afat
Ahmed E. Othman
Publication date
07-04-2022
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 9/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08753-z

Other articles of this Issue 9/2022

European Radiology 9/2022 Go to the issue