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Objective <p>To prospectively compare the scanning efficiency, image quality, and diagnostic performance of deep learning (DL)-based turbo spin-echo sequences (TSE-DL, TSE-DL-FS) with conventional sequences (TSE-SD, TSE-FS) and dual-echo Dixon water–fat separation sequences (TSE-Dixon) in lumbar spine MRI, providing evidence for clinical protocol optimization.</p> Methods <p>A total of 71 patients with lumbar spine disorders were prospectively enrolled. Each underwent five MRI sequences. The DL sequences were reconstructed via a U-Net–based network. Image evaluation was performed by two blinded radiologists using 4-point and 5-point Likert scales. Intergroup comparisons were conducted with the Kruskal–Wallis H test and Bonferroni post-hoc corrections. Signal-to-noise ratio (SNR) was measured using regions of interest (ROI) and compared via one-way ANOVA and Bonferroni tests. Disc–cerebrospinal fluid ratio (DCFR) was calculated and correlated with Pfirrmann grades via Spearman analysis.</p> Results <p>The total scan time of TSE-DL and TSE-DL-FS (118&#xa0;s) was significantly shorter than that of conventional TSE-SD + TSE-FS (202&#xa0;s) and TSE-Dixon (145&#xa0;s), improving efficiency by 41.6% and 18.6%, respectively. Qualitative and quantitative image scores of TSE-DL + TSE-DL-FS were comparable to conventional sequences (<i>P</i> &gt; 0.05), but superior to TSE-Dixon (<i>P</i> &lt; 0.05). Although TSE-Dixon achieved the most homogeneous fat suppression, its SNR was the lowest. DCFR showed a negative correlation with Pfirrmann grade in all sequences, strongest in TSE-DL (<i>r</i> = − 0.655, <i>P</i> &lt; 0.001).</p> Conclusion <p>The combination of DL-reconstructed TSE-DL and TSE-DL-FS sequences can markedly reduce lumbar MRI acquisition time while maintaining diagnostic image quality. Moreover, TSE-DL demonstrates potential benefits in the quantitative evaluation of disc degeneration. This highlights its promise for broader clinical adoption.</p>

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Clinical evaluation of deep learning accelerated lumbar T2-weighted and fat-suppressed MRI sequences

  • 期刊论文

  • 发表日期：

    2026年4月6日

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  • Ran Lv,
  • Yijiang Huang,
  • Nan Chen,
  • Hongtao Hou,
  • Guoqun Mao,
  • Yunzhu Wu,
  • Dominik Nickel,
  • Fuquan Wei

摘要

Objective

To prospectively compare the scanning efficiency, image quality, and diagnostic performance of deep learning (DL)-based turbo spin-echo sequences (TSE-DL, TSE-DL-FS) with conventional sequences (TSE-SD, TSE-FS) and dual-echo Dixon water–fat separation sequences (TSE-Dixon) in lumbar spine MRI, providing evidence for clinical protocol optimization.

Methods

A total of 71 patients with lumbar spine disorders were prospectively enrolled. Each underwent five MRI sequences. The DL sequences were reconstructed via a U-Net–based network. Image evaluation was performed by two blinded radiologists using 4-point and 5-point Likert scales. Intergroup comparisons were conducted with the Kruskal–Wallis H test and Bonferroni post-hoc corrections. Signal-to-noise ratio (SNR) was measured using regions of interest (ROI) and compared via one-way ANOVA and Bonferroni tests. Disc–cerebrospinal fluid ratio (DCFR) was calculated and correlated with Pfirrmann grades via Spearman analysis.

Results

The total scan time of TSE-DL and TSE-DL-FS (118 s) was significantly shorter than that of conventional TSE-SD + TSE-FS (202 s) and TSE-Dixon (145 s), improving efficiency by 41.6% and 18.6%, respectively. Qualitative and quantitative image scores of TSE-DL + TSE-DL-FS were comparable to conventional sequences (P > 0.05), but superior to TSE-Dixon (P < 0.05). Although TSE-Dixon achieved the most homogeneous fat suppression, its SNR was the lowest. DCFR showed a negative correlation with Pfirrmann grade in all sequences, strongest in TSE-DL (r = − 0.655, P < 0.001).

Conclusion

The combination of DL-reconstructed TSE-DL and TSE-DL-FS sequences can markedly reduce lumbar MRI acquisition time while maintaining diagnostic image quality. Moreover, TSE-DL demonstrates potential benefits in the quantitative evaluation of disc degeneration. This highlights its promise for broader clinical adoption.