Tang Maxine, Wang Haonan, Wang Shuo, Wali Eisha, Gutbrod Joseph, Singh Amita, Landeras Luis, Janich Martin A, Mor-Avi Victor, Patel Amit R, Patel Hena
Northwestern Medicine, Chicago, IL, United States of America.
GE HealthCare, Waukesha, WI, United States of America.
Magn Reson Imaging. 2025 Oct;122:110460. doi: 10.1016/j.mri.2025.110460. Epub 2025 Jul 14.
Phase-sensitive inversion recovery late gadolinium enhancement (LGE) improves tissue contrast, however it is challenging to combine with a free-breathing acquisition. Deep-learning (DL) algorithms have growing applications in cardiac magnetic resonance imaging (CMR) to improve image quality. We compared a novel combination of a free-breathing single-shot phase-sensitive LGE with respiratory triggering (FB-PS) sequence with DL noise reduction reconstruction algorithm to a conventional segmented phase-sensitive LGE acquired during breath holding (BH-PS).
61 adult subjects (29 male, age 51 ± 15) underwent clinical CMR (1.5 T) with the FB-PS sequence and the conventional BH-PS sequence. DL noise reduction was incorporated into the image reconstruction pipeline. Qualitative metrics included image quality, artifact severity, diagnostic confidence. Quantitative metrics included septal-blood border sharpness, LGE sharpness, blood-myocardium apparent contrast-to-noise ratio (CNR), LGE-myocardium CNR, LGE apparent signal-to-noise ratio (SNR), and LGE burden. The sequences were compared via paired t-tests.
27 subjects had positive LGE. Average time to acquire a slice for FB-PS was 4-12 s versus ∼32-38 s for BH-PS (including breath instructions and break time in between breath hold). FB-PS with medium DL noise reduction had better image quality (FB-PS 3.0 ± 0.7 vs. BH-PS 1.5 ± 0.6, p < 0.0001), less artifact (4.8 ± 0.5 vs. 3.4 ± 1.1, p < 0.0001), and higher diagnostic confidence (4.0 ± 0.6 vs. 2.6 ± 0.8, p < 0.0001). Septum sharpness in FB-PS with DL reconstruction versus BH-PS was not significantly different. There was no significant difference in LGE sharpness or LGE burden. FB-PS had superior blood-myocardium CNR (17.2 ± 6.9 vs. 16.4 ± 6.0, p = 0.040), LGE-myocardium CNR (12.1 ± 7.2 vs. 10.4 ± 6.6, p = 0.054), and LGE SNR (59.8 ± 26.8 vs. 31.2 ± 24.1, p < 0.001); these metrics further improved with DL noise reduction.
A FB-PS sequence shortens scan time by over 5-fold and reduces motion artifact. Combined with a DL noise reduction algorithm, FB-PS provides better or similar image quality compared to BH-PS. This is a promising solution for patients who cannot hold their breath.
相敏反转恢复晚期钆增强（LGE）可改善组织对比度，但与自由呼吸采集相结合具有挑战性。深度学习（DL）算法在心脏磁共振成像（CMR）中的应用日益广泛，以提高图像质量。我们将一种新型的自由呼吸单次激发相敏LGE与呼吸触发（FB-PS）序列与DL降噪重建算法的组合，与在屏气期间采集的传统分段相敏LGE（BH-PS）进行了比较。
61名成年受试者（29名男性，年龄51±15岁）接受了使用FB-PS序列和传统BH-PS序列的临床CMR（1.5T）检查。DL降噪被纳入图像重建流程。定性指标包括图像质量、伪影严重程度、诊断置信度。定量指标包括室间隔-血液边界清晰度、LGE清晰度、血液-心肌表观对比噪声比（CNR）、LGE-心肌CNR、LGE表观信噪比（SNR）和LGE负荷。通过配对t检验对序列进行比较。
27名受试者LGE呈阳性。FB-PS采集一层图像的平均时间为4-12秒，而BH-PS为约32-38秒（包括屏气指令和屏气之间的休息时间）。采用中等DL降噪的FB-PS具有更好的图像质量（FB-PS为3.0±0.7，而BH-PS为1.5±0.6，p<0.0001）、更少的伪影（4.8±0.5对3.4±1.1，p<0.0001）和更高的诊断置信度（4.0±0.6对2.6±0.8，p<0.0001）。采用DL重建的FB-PS与BH-PS相比，室间隔清晰度无显著差异。LGE清晰度或LGE负荷无显著差异。FB-PS具有更高的血液-心肌CNR（17.2±6.9对16.4±6.0，p=0.040）、LGE-心肌CNR（12.1±7.2对10.4±6.6，p=0.054）和LGE SNR（59.8±26.8对31.2±24.1，p<0.001）；这些指标通过DL降噪进一步改善。
FB-PS序列将扫描时间缩短了5倍以上，并减少了运动伪影。与DL降噪算法相结合，FB-PS与BH-PS相比提供了更好或相似的图像质量。这对于无法屏气的患者是一个有前景的解决方案。
