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Utility of accelerated T2-weighted turbo spin-echo imaging with deep learning reconstruction in female pelvic MRI: a multi-reader study

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To determine the clinical feasibility of T2-weighted turbo spin-echo (T2-TSE) imaging with deep learning reconstruction (DLR) in female pelvic MRI compared with conventional T2 TSE in terms of image quality and scan time.

Methods

Between May 2021 and September 2021, 52 women (mean age, 44 years ± 12) who underwent 3-T pelvic MRI with additional T2-TSE using a DLR algorithm were included in this single-center prospective study with patient’s informed consents. Conventional, DLR, and DLR T2-TSE images with reduced scan times were independently assessed and compared by four radiologists. The overall image quality, differentiation of anatomic details, lesion conspicuity, and artifacts were evaluated using a 5-point scale. Inter-observer agreement of the qualitative scores was compared and reader protocol preferences were then evaluated.

Results

In the qualitative analysis of all readers, fast DLR T2-TSE showed significantly better overall image quality, differentiation of anatomic regions, lesion conspicuity, and lesser artifacts than conventional T2-TSE and DLR T2-TSE, despite approximately 50% reduction in scan time (all p < 0.05). The inter-reader agreement for the qualitative analysis was moderate to good. All readers preferred DLR over conventional T2-TSE regardless of scan time and preferred fast DLR T2-TSE (57.7–78.8%), except for one who preferred DLR over fast DLR T2-TSE (53.8% vs. 46.1%).

Conclusion

In female pelvic MRI, image quality and accelerated image acquisition for T2-TSE can be significantly improved by using DLR compared to conventional T2-TSE. Fast DLR T2-TSE was non-inferior to DLR T2-TSE in terms of reader preference and image quality.

Clinical relevance statement

DLR of T2-TSE in female pelvic MRI enables fast imaging along with maintaining optimal image quality compared with parallel imaging-based conventional T2-TSE.

Key Points

• Conventional T2 turbo spin-echo based on parallel imaging has limitations for accelerated image acquisition while maintaining good image quality.

• Deep learning image reconstruction showed better image quality in both images obtained using the same or accelerated image acquisition parameters compared with conventional T2 turbo spin-echo in female pelvic MRI.

• Deep learning image reconstruction enables accelerated image acquisition while maintaining good image quality in the T2-TSE of female pelvic MRI.

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Abbreviations

DLR:

Deep learning reconstruction

GRAPPA:

Generalized autocalibrating partially parallel acquisition

HASTE:

Half-Fourier-acquired single-shot turbo spin echo

NEX:

Number of excitations

SNR:

Signal-to-noise ratio

T2-TSE:

T2-weighted turbo spin-echo

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Acknowledgements

This research was supported by the Soonchunhyang University research fund.

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Authors and Affiliations

  1. Department of Radiology, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, 59 Daesakwan-Ro, Yongsan-Ku, Seoul, 04401, Korea

    Eun Ji Lee, Jiyoung Hwang, Sung Hwan Bae, Jiyun Lim, Yun-Woo Chang, Seong Sook Hong, Eunsun Oh, Bo Da Nam & Jewon Jeong

  2. Department of Biostatistics, Soonchunhyang University Seoul Hospital, Soonchunhyang University College of Medicine, Seoul, Korea

    Suyeon Park

  3. Siemens Healthineers Ltd, Seoul, Korea

    Jae Kon Sung

  4. MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany

    Dominik Nickel

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  1. Eun Ji Lee
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Corresponding author

Correspondence to Jiyoung Hwang.

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Guarantor

The scientific guarantor of this publication is Jiyoung Hwang.

Conflict of interest

Co-authors Jae Kon Sung and Dominik Nickel are employees of Siemens Healthineers or Siemens Healthcare. The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Statistics and biometry

The statistical methods and analysis in this study were reviewed and supervised by a medical statistician. 

Informed consent

Written informed consents were obtained for all participants in this study.

Ethical approval

This prospective study was approved by the institutional review board (IRB 2021-03-017) and written informed consent for additional T2-weighted sequences using deep learning reconstruction was obtained from each individual.

Methodology

  • Prospective

  • Observational study

  • Performed at one institution

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Lee, E.J., Hwang, J., Park, S. et al. Utility of accelerated T2-weighted turbo spin-echo imaging with deep learning reconstruction in female pelvic MRI: a multi-reader study. Eur Radiol 33, 7697–7706 (2023). https://doi.org/10.1007/s00330-023-09781-z

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  • DOI: https://doi.org/10.1007/s00330-023-09781-z

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