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前瞻性部署深度学习重建技术有助于实现上腹部 MRI 的高速加速。

Prospective Deployment of Deep Learning Reconstruction Facilitates Highly Accelerated Upper Abdominal MRI.

机构信息

Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany.

Institute of Clinical Epidemiology and Applied Biometry, Tuebingen University Hospital, University of Tuebingen, Tuebingen, Germany.

出版信息

Acad Radiol. 2024 Dec;31(12):4965-4973. doi: 10.1016/j.acra.2024.05.044. Epub 2024 Jul 2.

DOI:10.1016/j.acra.2024.05.044
PMID:38955591
Abstract

RATIONALE AND OBJECTIVES

To compare a conventional T1 volumetric interpolated breath-hold examination (VIBE) with SPectral Attenuated Inversion Recovery (SPAIR) fat saturation and a deep learning (DL)-reconstructed accelerated VIBE sequence with SPAIR fat saturation achieving a 50 % reduction in breath-hold duration (hereafter, VIBE-SPAIR) in terms of image quality and diagnostic confidence.

MATERIALS AND METHODS

This prospective study enrolled consecutive patients referred for upper abdominal MRI from November 2023 to December 2023 at a single tertiary center. Patients underwent upper abdominal MRI with acquisition of non-contrast and gadobutrol-enhanced conventional VIBE-SPAIR (fourfold acceleration, acquisition time 16 s) and VIBE-SPAIR (sixfold acceleration, acquisition time 8 s) on a 1.5 T scanner. Image analysis was performed by four readers, evaluating homogeneity of fat suppression, perceived signal-to-noise ratio (SNR), edge sharpness, artifact level, lesion detectability and diagnostic confidence. A statistical power analysis for patient sample size estimation was performed. Image quality parameters were compared by a repeated measures analysis of variance, and interreader agreement was assessed using Fleiss' κ.

RESULTS

Among 450 consecutive patients, 45 patients were evaluated (mean age, 60 years ± 15 [SD]; 27 men, 18 women). VIBE-SPAIR acquisition demonstrated superior SNR (P < 0.001), edge sharpness (P < 0.001), and reduced artifacts (P < 0.001) with substantial to almost perfect interreader agreement for non-contrast (κ: 0.70-0.91) and gadobutrol-enhanced MRI (κ: 0.68-0.87). No evidence of a difference was found between conventional VIBE-SPAIR and VIBE-SPAIR regarding homogeneity of fat suppression, lesion detectability, or diagnostic confidence (all P > 0.05).

CONCLUSION

Deep learning reconstruction of VIBE-SPAIR facilitated a reduction of breath-hold duration by half, while reducing artifacts and improving image quality.

SUMMARY

Deep learning reconstruction of prospectively accelerated T1 volumetric interpolated breath-hold examination for upper abdominal MRI enabled a 50 % reduction in breath-hold time with superior image quality.

KEY RESULTS

  1. In a prospective analysis of 45 patients referred for upper abdominal MRI, accelerated deep learning (DL)-reconstructed VIBE images with spectral fat saturation (SPAIR) showed better overall image quality, with better perceived signal-to-noise ratio and less artifacts (all P < 0.001), despite a 50 % reduction in acquisition time compared to conventional VIBE. 2) No evidence of a difference was found between conventional VIBE-SPAIR and accelerated VIBE-SPAIR regarding lesion detectability or diagnostic confidence.
摘要

背景和目的

比较常规 T1 容积内插屏气检查(VIBE)与带谱衰减反转恢复(SPAIR)脂肪饱和的深度学习(DL)重建加速 VIBE 序列(屏气时间减少 50%,以下简称 VIBE-SPAIR)在图像质量和诊断信心方面的表现。

材料和方法

这项前瞻性研究纳入了 2023 年 11 月至 12 月在一家三级中心因上腹部 MRI 检查而就诊的连续患者。患者在上腹部进行非对比和钆布醇增强的常规 VIBE-SPAIR(四倍加速,采集时间 16s)和 VIBE-SPAIR(六倍加速,采集时间 8s)检查。由四位读者进行图像分析,评估脂肪抑制均匀性、感知信噪比(SNR)、边缘锐利度、伪影水平、病变检出率和诊断信心。对患者样本量估计进行了统计学功效分析。采用重复测量方差分析比较图像质量参数,采用 Fleiss'κ评估读者间的一致性。

结果

在 450 例连续患者中,有 45 例患者(平均年龄 60 岁±15[标准差];27 名男性,18 名女性)被评估。VIBE-SPAIR 采集的 SNR(P<0.001)、边缘锐利度(P<0.001)和伪影减少(P<0.001)均优于常规 VIBE-SPAIR,在非对比和钆布醇增强 MRI 中具有实质性到几乎完美的读者间一致性(κ:0.70-0.91 和 κ:0.68-0.87)。常规 VIBE-SPAIR 和 VIBE-SPAIR 在脂肪抑制均匀性、病变检出率或诊断信心方面均无差异(均 P>0.05)。

结论

前瞻性加速 T1 容积内插屏气检查的深度学习重建可将屏气时间减少一半,同时减少伪影并提高图像质量。

总结

前瞻性加速上腹部 MRI 的 T1 容积内插屏气检查的深度学习重建可使屏气时间减少 50%,同时提高图像质量。

主要结果

1)在一项对 45 例因上腹部 MRI 检查而就诊的患者的前瞻性分析中,带谱衰减反转恢复(SPAIR)的加速深度学习(DL)重建 VIBE 图像显示出更好的整体图像质量,具有更好的感知信噪比和更少的伪影(均 P<0.001),尽管与常规 VIBE 相比,采集时间减少了 50%。2)常规 VIBE-SPAIR 和加速 VIBE-SPAIR 在病变检出率或诊断信心方面均无差异。

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