无对比MRI的人工智能:使用基于深度学习的虚拟原生增强来评估心肌梗塞的痕
Qiang Zhang1,2, Matthew K Burrage1,2,3, Mayooran Shanmuganathan1,2
1Oxford Centre for Clinical Magnetic Resonance Research (Q.Z., M.K.B., M.S., R.A.G., E.L., K.E.T., R.M., J.L.P., C.N., I.A.P., Y.P.L., S.G.M., O.R., S.N., S.K.P., V.M.F.), Radcliffe Department of Medicine, University of Oxford, United Kingdom.
Circulation
|September 20, 2022
概括
虚拟本地增强 (VNE) 创建无对比心脏MRI图像以评估心肌痕,与晚期加多增强 (LGE) 的准确性相匹配. 这种人工智能驱动的方法为改善患者护理提供更快,更便宜的扫描.
科学领域:
- 心血管成像
- 医学的人工智能
- 医疗诊断
背景情况:
- 心血管磁共振晚期加多增强 (LGE) 是评估心肌痕的黄金标准.
- 对心肌痕评估的无对比方法提供了显著的优势,包括缩短扫描时间和成本,并消除与对比相关的风险.
研究的目的:
- 引入和评估虚拟原生增强 (VNE),这是一种用于心肌痕评估的新型无对比技术.
- 将VNE的有效性和图像质量与已建立的LGE技术进行比较.
主要方法:
- VNE利用人工智能 (生成对抗网络) 来从电影成像和原生T1地图中创建类似LGE的图像.
- 这种VNE模型是使用3002个心脏MRI扫描的大量数据集来开发和验证的,这些数据来自775名先前心肌梗塞的患者.
- 使用已知方法进行痕量化 (体积和转移性),并对VNE和LGE进行比较.
主要成果:
- 与LGE相比,VNE在独立运营商的盲目分析中显示出更高的图像质量.
- 在量化痕大小 (R=0. 89) 和转移性 (R=0. 84) 方面,VNE与LGE有很强的相关性.
- 与LGE相比,VNE在痕检测方面取得了84%的整体准确性,具有100%的特异性和77%的灵敏性.
结论:
- VNE是一种高精度,无对比度的心肌痕评估方法,在分布和量化方面与LGE有很好的一致性.
- 它提供优质的图像质量,并有潜力显著降低扫描时间和成本.
- 这种基于人工智能的技术有望提高心血管磁共振成像用于心肌痕评估的可访问性和效率.
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