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Objective <p>Two-point Dixon MRI is widely used for lumbar plexus imaging but often yields incomplete fat suppression due to neglecting fat’s multi-peak spectrum. This study developed and evaluated a post-processing algorithm that accounts for the multi-peak fat spectrum to achieve more effective fat suppression.</p> Methods <p>A novel Dark-fat processing algorithm was developed to enhance fat suppression in water-only MR images from standard two-point Dixon reconstruction. It was evaluated using a custom fat/water phantom, prospectively in a healthy volunteer, and retrospectively in 30 patients who underwent clinical lumbar plexus imaging between March and October 2023. Imaging was done using FFE (or GRE)-Dixon, TSE (or FSE)-Dixon, and mDixon-Quant. Quantitative metrics (SNR, apparent SNR (aSNR), and apparent CNR (aCNR)) and qualitative assessments by two radiologists were analyzed. Statistical significance was determined using Welch’s t-test (<i>p</i> &lt; 0.05) and Wilcoxon signed-rank test with Benjamini-Krieger-Yekutieli correction (q &lt; 0.05).</p> Results <p>The Dark-fat processing (i) substantially decreased fat signal in water-only images (84% reduction) in phantom from two-point TSE-Dixon and was statistically not different from the reference standard, multi-echo mDixon-Quant (<i>p</i> = 0.58); (ii) improved overall fat suppression (q &lt; 0.05, effect size = 0.67 and 0.92), while there was no significant difference in the anatomical visualization; (iii) significantly reduced aSNR in the subcutaneous fat (<i>p</i> &lt; 0.0001, effect size &gt; 1) and muscle (<i>p</i> &lt; 0.01, effect size = 0.81); and (iv) did not alter aCNR between nerve and muscle tissue (<i>p</i> = 0.27, effect size = 0.29).</p> Conclusion <p>Dark-fat processing enables efficient and complete fat suppression in two-point Dixon acquisitions, especially TSE-Dixon, significantly enhancing lumbar plexus image quality. When implemented offline and as a retrospective method, it requires no change to scan time and can be applied to any two-point Dixon dataset.</p>

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Efficient and complete fat suppression in two-point Dixon MR imaging: sequence considerations and assessment in lumbar plexus imaging

  • 期刊论文

  • 发表日期：

    2026年3月3日

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  • Sheng-Qing Lin,
  • Durga Udayakumar,
  • Sebastian Fonseca,
  • Neela Batthula,
  • Flavio Duarte Silva,
  • Avneesh Chhabra,
  • Ananth J. Madhuranthakam

摘要

Objective

Two-point Dixon MRI is widely used for lumbar plexus imaging but often yields incomplete fat suppression due to neglecting fat’s multi-peak spectrum. This study developed and evaluated a post-processing algorithm that accounts for the multi-peak fat spectrum to achieve more effective fat suppression.

Methods

A novel Dark-fat processing algorithm was developed to enhance fat suppression in water-only MR images from standard two-point Dixon reconstruction. It was evaluated using a custom fat/water phantom, prospectively in a healthy volunteer, and retrospectively in 30 patients who underwent clinical lumbar plexus imaging between March and October 2023. Imaging was done using FFE (or GRE)-Dixon, TSE (or FSE)-Dixon, and mDixon-Quant. Quantitative metrics (SNR, apparent SNR (aSNR), and apparent CNR (aCNR)) and qualitative assessments by two radiologists were analyzed. Statistical significance was determined using Welch’s t-test (p < 0.05) and Wilcoxon signed-rank test with Benjamini-Krieger-Yekutieli correction (q < 0.05).

Results

The Dark-fat processing (i) substantially decreased fat signal in water-only images (84% reduction) in phantom from two-point TSE-Dixon and was statistically not different from the reference standard, multi-echo mDixon-Quant (p = 0.58); (ii) improved overall fat suppression (q < 0.05, effect size = 0.67 and 0.92), while there was no significant difference in the anatomical visualization; (iii) significantly reduced aSNR in the subcutaneous fat (p < 0.0001, effect size > 1) and muscle (p < 0.01, effect size = 0.81); and (iv) did not alter aCNR between nerve and muscle tissue (p = 0.27, effect size = 0.29).

Conclusion

Dark-fat processing enables efficient and complete fat suppression in two-point Dixon acquisitions, especially TSE-Dixon, significantly enhancing lumbar plexus image quality. When implemented offline and as a retrospective method, it requires no change to scan time and can be applied to any two-point Dixon dataset.