Suppr超能文献

基于3D模型的超分辨率运动校正心脏T1映射

3D model-based super-resolution motion-corrected cardiac T1 mapping.

作者信息

Hufnagel Simone, Metzner Selma, Kerkering Kirsten Miriam, Aigner Christoph Stefan, Kofler Andreas, Schulz-Menger Jeanette, Schaeffter Tobias, Kolbitsch Christoph

机构信息

Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.

Charité Medical Faculty University Medicine, Berlin, Germany.

出版信息

Phys Med Biol. 2022 Dec 9;67(24). doi: 10.1088/1361-6560/ac9c40.

Abstract

. To provide 3D high-resolution cardiac T1 maps using model-based super-resolution reconstruction (SRR).. Due to signal-to-noise ratio limitations and the motion of the heart during imaging, often 2D T1 maps with only low through-plane resolution (i.e. slice thickness of 6-8 mm) can be obtained. Here, a model-based SRR approach is presented, which combines multiple stacks of 2D acquisitions with 6-8 mm slice thickness and generates 3D high-resolution T1 maps with a slice thickness of 1.5-2 mm. Every stack was acquired in a different breath hold (BH) and any misalignment between BH was corrected retrospectively. The novelty of the proposed approach is the BH correction and the application of model-based SRR on cardiac T1 Mapping. The proposed approach was evaluated in numerical simulations and phantom experiments and demonstrated in four healthy subjects.. Alignment of BH states was essential for SRR even in healthy volunteers. In simulations, respiratory motion could be estimated with an RMS error of 0.18 ± 0.28 mm. SRR improved the visualization of small structures. High accuracy and precision (average standard deviation of 69.62 ms) of the T1 values was ensured by SRR while the detectability of small structures increased by 40%.. The proposed SRR approach provided T1 maps with high in-plane and high through-plane resolution (1.3 × 1.3 × 1.5-2 mm). The approach led to improvements in the visualization of small structures and precise T1 values.

摘要

使用基于模型的超分辨率重建(SRR)来提供三维高分辨率心脏T1图谱。由于信噪比限制以及成像过程中心脏的运动,通常只能获得具有低层面分辨率(即切片厚度为6 - 8毫米)的二维T1图谱。在此,提出了一种基于模型的SRR方法,该方法将多组切片厚度为6 - 8毫米的二维采集数据进行合并,并生成切片厚度为1.5 - 2毫米的三维高分辨率T1图谱。每组采集数据均在不同的屏气(BH)状态下进行,并且对BH之间的任何错位进行了回顾性校正。所提出方法的新颖之处在于BH校正以及基于模型的SRR在心脏T1映射中的应用。该方法在数值模拟和体模实验中进行了评估,并在四名健康受试者中得到了验证。即使在健康志愿者中,BH状态的对齐对于SRR也是至关重要的。在模拟中,呼吸运动的估计均方根误差为0.18±0.28毫米。SRR改善了小结构的可视化效果。SRR确保了T1值的高精度和高精确度(平均标准差为69.62毫秒),同时小结构的可检测性提高了40%。所提出的SRR方法提供了具有高平面内分辨率和高层面分辨率(1.3×1.3×1.5 - 2毫米)的T1图谱。该方法在小结构的可视化和精确的T1值方面取得了改进。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验