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DOI: 10.1371/journal.pone.0172573
论文题名:
Generalized min-max bound-based MRI pulse sequence design framework for wide-range T1 relaxometry: A case study on the tissue specific imaging sequence
作者: Yang Liu; John R. Buck; Vasiliki N. Ikonomidou
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2017
发表日期: 2017-2-21
卷: 12, 期:2
语种: 英语
英文关键词: NMR relaxation ; Magnetic resonance imaging ; Relaxation (physics) ; Optimization ; Vector spaces ; Monte Carlo method ; Cerebrospinal fluid ; Perturbation (geology)
英文摘要: This paper proposes a new design strategy for optimizing MRI pulse sequences for T1 relaxometry. The design strategy optimizes the pulse sequence parameters to minimize the maximum variance of unbiased T1 estimates over a range of T1 values using the Cramér-Rao bound. In contrast to prior sequences optimized for a single nominal T1 value, the optimized sequence using our bound-based strategy achieves improved precision and accuracy for a broad range of T1 estimates within a clinically feasible scan time. The optimization combines the downhill simplex method with a simulated annealing process. To show the effectiveness of the proposed strategy, we optimize the tissue specific imaging (TSI) sequence. Preliminary Monte Carlo simulations demonstrate that the optimized TSI sequence yields improved precision and accuracy over the popular driven-equilibrium single-pulse observation of T1 (DESPOT1) approach for normal brain tissues (estimated T1 700–2000 ms at 3.0T). The relative mean estimation error (MSE) for T1 estimation is less than 1.7% using the optimized TSI sequence, as opposed to less than 7.0% using DESPOT1 for normal brain tissues. The optimized TSI sequence achieves good stability by keeping the MSE under 7.0% over larger T1 values corresponding to different lesion tissues and the cerebrospinal fluid (up to 5000 ms). The T1 estimation accuracy using the new pulse sequence also shows improvement, which is more pronounced in low SNR scenarios.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0172573&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/25902
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Department of Electrical and Computer Engineering, University of Massachusetts Dartmouth, Dartmouth, MA, United States of America;Department of Electrical and Computer Engineering, University of Massachusetts Dartmouth, Dartmouth, MA, United States of America;Department of Bioengineering, George Mason University, Fairfax, VA, United States of America

Recommended Citation:
Yang Liu,John R. Buck,Vasiliki N. Ikonomidou. Generalized min-max bound-based MRI pulse sequence design framework for wide-range T1 relaxometry: A case study on the tissue specific imaging sequence[J]. PLOS ONE,2017-01-01,12(2)
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