METHODS: Each component of the reconstruction framework was systematically validated and compared to the previously established 5D approach using simulated free-running data (N = 50) and a cohort of 32 patients with congenital heart disease. The impact of intra-bin respiratory motion correction was evaluated in terms of image sharpness while inter-bin respiratory motion compensation was evaluated in terms of reconstruction error, compression of respiratory motion, and image sharpness. The full reconstruction framework (intra-acquisition correction and inter-acquisition compensation of respiratory motion [IIMC] 5D) was evaluated in terms of image sharpness and scoring of image quality by expert reviewers.
RESULTS: Intra-bin motion correction provides significantly (p < 0.001) sharper images for both simulated and patient data. Inter-bin motion compensation results in significant (p < 0.001) lower reconstruction error, lower motion compression, and higher sharpness in both simulated (10/11) and patient (9/11) data. The combined framework resulted in significantly (p < 0.001) sharper IIMC 5D reconstructions (End-expiration (End-Exp): 0.45 ± 0.09, End-inspiration (End-Ins): 0.46 ± 0.10) relative to the previously established 5D implementation (End-Exp: 0.43 ± 0.08, End-Ins: 0.39 ± 0.09). Similarly, image scoring by three expert reviewers was significantly (p < 0.001) higher using IIMC 5D (End-Exp: 3.39 ± 0.44, End-Ins: 3.32 ± 0.45) relative to 5D images (End-Exp: 3.02 ± 0.54, End-Ins: 2.45 ± 0.52).
CONCLUSIONS: The proposed IIMC reconstruction significantly improves the quality of 5D whole-heart MRI. This may be exploited for higher resolution or abbreviated scanning. Further investigation of the diagnostic impact of this framework and comparison to gold standards is needed to understand its full clinical utility, including exploration of respiratory-driven changes in physiological measurements of interest.
方法:使用模拟自由运行数据(N=50)和32例先天性心脏病患者的队列,对重建框架的每个组成部分进行了系统验证,并与先前建立的5D方法进行了比较。在图像清晰度方面评估箱内呼吸运动校正的影响,而在重建误差方面评估箱间呼吸运动补偿,压缩呼吸运动,和图像清晰度。专家评审人员在图像清晰度和图像质量评分方面评估了完整的重建框架(IIMC5D)。
结果:箱内运动校正为模拟数据和患者数据提供了明显(p<10-3)更清晰的图像。箱间运动补偿导致显著(p<10-3)较低的重建误差,较低的运动压缩,和更高的清晰度在模拟(10/11)和患者(9/11)的数据。相对于先前建立的5D实现(End-Exp:0.43±0.08,End-Ins:0.39±0.09),组合框架导致显著(p<10-3)更清晰的IIMC5D重建(End-Exp:0.45±0.09,End-Ins:0.46±0.10)。同样,使用IIMC5D(End-Exp:3.39±0.44,End-Ins:3.32±0.45),相对于5D图像(End-Exp:3.02±0.54,End-Ins:2.45±0.52),三位专家评审的图像评分显著(p<10-3)更高。
结论:提出的IIMC重建显著提高了5D全心MRI的质量。这可以用于更高分辨率或缩写扫描。需要进一步研究该框架的诊断影响并与黄金标准进行比较,以了解其完整的临床实用性,包括探索呼吸驱动的生理测量变化。