用扩散模型实现自由呼吸下心脏动态MRI的实时高质量成像。
Real-time cardiac cine MRI -- A comparison of a diffusion probabilistic model with alternative state-of-the-art image reconstruction techniques for undersampled spiral acquisitions
- 采用基于评分的扩散模型重建欠采样螺旋数据。
- 图像质量与传统方法相当，锐度略优，心功能参数偏差1.6%。
- 适合心律不齐或无法屏气患者，但推理耗时仍需优化。
在16名健康志愿者和5名患者中，对自由呼吸下的欠采样螺旋实时心脏成像进行了研究。使用新型基于评分的扩散模型、变分网络及不同压缩感知方法进行图像重建，并通过专家阅片、标量指标、差值图像与Bland-Altman分析对比临床参考标准。在心律不齐患者中，实时螺旋采集展现更优图像质量。扩散模型、变分网络与l1小波方法整体图像质量相当，但扩散模型略微提升锐度。健康受试者中，实时采集显示的射血分数平均偏高1.6%，但数据采集差异导致不确定性达7.4%。该方法可在不到一分钟内完成全心脏时空成像，且不受屏气或心律影响。然而，基于片段参考的标准评估易受心律不齐和平均效应干扰。扩散模型推理时间过长是临床转化的主要障碍。
原文摘要 · Abstract (English)
ECG-gated cine imaging in breath-hold enables high-quality diagnostics in most patients, arrhythmia and inability to hold breath, however, can severely corrupt outcomes. Real-time cardiac MRI in free-breathing leverages robust and faster investigations regardless of these confounding factors. With the need for sufficient acceleration, adequate reconstruction methods, which transfer data into high quality images, are required. Undersampled spiral real-time acquisitions in free-breathing were conducted in a study with 16 healthy volunteers and 5 patients. Image reconstructions were performed using a novel score-based diffusion model, as well as a variational network and different compressed sensing approaches. The techniques were compared by means of an expert reader study, by calculating scalar metrics and difference images with respect to a segmented reference, and by a Bland-Altman analysis of cardiac functional parameters. In participants with irregular RR-cycles, spiral real-time acquisitions showed superior image quality with respect to the clinical reference standard. Reconstructions using the diffusion model, the variational network and l1-wavelets offered an overall comparable image quality, however sharpness was slightly increased by the diffusion approach. While slightly larger ejection fractions for the real-time acquisitions were exhibited with a bias of 1.6% for healthy subjects, differences in the data acquisition procedure resulted in uncertainties of 7.4%. The proposed real-time technique enables free-breathing acquisitions of spatio-temporal images with high-quality, covering the entire heart in less than one minute. Evaluation of the ejection fractions using the segmented reference can be significantly corrupted due to arrhythmias and averaging effects. Prolonged inference times of the diffusion model represent the main obstacle to overcome for clinical translation.
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