A four-dimensional computational model of dynamic contrast-enhanced magnetic resonance imaging measurement of subtle blood-brain barrier leakage.
A four-dimensional computational model of dynamic contrast-enhanced magnetic resonance imaging measurement of subtle blood-brain barrier leakage.
复制标题
动态对比增强磁共振成像测量细微血脑屏障渗漏的四维计算模型。
DOI：
10.1016/j.neuroimage.2021.117786
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发表时间：
2021-04-15
期刊：
影响因子：
5.7
通讯作者：
Thrippleton MJ
中科院分区：
文献类型：
--
作者：
Bernal J;Valdés-Hernández MDC;Escudero J;Heye AK;Sakka E;Armitage PA;Makin S;Touyz RM;Wardlaw JM;Thrippleton MJ
动态增强磁共振成像(DCE-MRI)越来越多地被用于量化和绘制神经退行性疾病(包括脑小血管疾病和痴呆)中血脑屏障(BBB)渗漏的空间分布。然而，泄漏的微妙性质和由此产生的小信号变化使量化具有挑战性。虽然简化的一维模拟探讨了噪声、扫描仪漂移和模型假设的影响，但忽略了诸如粗大运动、k空间采样和运动伪影等时空效应对参数泄漏图的影响。此外，由于实际困难和缺乏参考方法，缺乏设计成像协议所依据的证据。为了解决这些问题，我们提出了一个开源的DCE-MRI采集过程的计算模型，用于生成四维数字参考对象(DROS)，使用高分辨率的脑图谱，并结合真实的患者运动、脑外信号、噪声和k空间采样。使用DROS的模拟表明，时空效应对参数图的视觉外观和测量的组织渗漏率都具有主导影响。该计算模型可以更好地了解微妙的血脑屏障渗漏测量的敏感性和局限性，并为未来的研究提供了一种非侵入性的测试和优化成像方案的方法。
Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to quantify and map the spatial distribution of blood-brain barrier (BBB) leakage in neurodegenerative disease, including cerebral small vessel disease and dementia. However, the subtle nature of leakage and resulting small signal changes make quantification challenging. While simplified one-dimensional simulations have probed the impact of noise, scanner drift, and model assumptions, the impact of spatio-temporal effects such as gross motion, k-space sampling and motion artefacts on parametric leakage maps has been overlooked. Moreover, evidence on which to base the design of imaging protocols is lacking due to practical difficulties and the lack of a reference method. To address these problems, we present an open-source computational model of the DCE-MRI acquisition process for generating four dimensional Digital Reference Objects (DROs), using a high-resolution brain atlas and incorporating realistic patient motion, extra-cerebral signals, noise and k-space sampling. Simulations using the DROs demonstrated a dominant influence of spatio-temporal effects on both the visual appearance of parameter maps and on measured tissue leakage rates. The computational model permits greater understanding of the sensitivity and limitations of subtle BBB leakage measurement and provides a non-invasive means of testing and optimising imaging protocols for future studies.
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