Imputation models and error analysis for phase contrast MR cerebral blood flow measurements.
Imputation models and error analysis for phase contrast MR cerebral blood flow measurements.
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DOI：
10.3389/fphys.2023.1096297
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发表时间：
2023
影响因子：
4
通讯作者：
Borzage, Matthew T.
中科院分区：
文献类型：
--
作者：
Shah, Payal;Doyle, Eamon;Wood, John C.;Borzage, Matthew T.
关键词：
脑血流量（CBF）支持大脑代谢。疾病损害CBF，并且药理学试剂调节CBF。许多技术测量CBF，但是通过供应大脑的四个动脉的相位对比（PC）MR成像是快速和稳健的。然而，技术人员错误、患者运动或迂曲血管会降低颈内动脉（伊卡）或椎动脉（VA）的测量质量。我们假设总CBF可以通过测量这4条供血血管的亚组来估算，而不会对准确性造成过度影响。我们分析了129例患者的PC MR成像，人为排除1条或多条血管以模拟成像质量下降，并为缺失数据开发了插补模型。当至少测量一个伊卡时，我们的模型表现良好，并导致R2值为0.998-0.990，归一化均方根误差值为0.044-0.105，类内相关系数为0.982-0.935。因此，这些模型与PC MR成像测量的CBF的重测变异性相当或上级。我们的插补模型允许在测量CBF时对损坏的血管测量进行回顾性校正，并指导前瞻性CBF采集。
Cerebral blood flow (CBF) supports brain metabolism. Diseases impair CBF, and pharmacological agents modulate CBF. Many techniques measure CBF, but phase contrast (PC) MR imaging through the four arteries supplying the brain is rapid and robust. However, technician error, patient motion, or tortuous vessels degrade quality of the measurements of the internal carotid (ICA) or vertebral (VA) arteries. We hypothesized that total CBF could be imputed from measurements in subsets of these 4 feeding vessels without excessive penalties in accuracy. We analyzed PC MR imaging from 129 patients, artificially excluded 1 or more vessels to simulate degraded imaging quality, and developed models of imputation for the missing data. Our models performed well when at least one ICA was measured, and resulted in R 2 values of 0.998–0.990, normalized root mean squared error values of 0.044–0.105, and intra-class correlation coefficient of 0.982–0.935. Thus, these models were comparable or superior to the test-retest variability in CBF measured by PC MR imaging. Our imputation models allow retrospective correction for corrupted blood vessel measurements when measuring CBF and guide prospective CBF acquisitions.
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