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Magnetic resonance fingerprinting based on realistic vasculature in mice.

ABSTRACT: Magnetic resonance fingerprinting (MRF) was recently proposed as a novel strategy for MR data acquisition and analysis. A variant of MRF called vascular MRF (vMRF) followed, that extracted maps of three parameters of physiological importance: cerebral oxygen saturation (SatO2), mean vessel radius and cerebral blood volume (CBV). However, this estimation was based on idealized 2-dimensional simulations of vascular networks using random cylinders and the empirical Bloch equations convolved with a diffusion kernel. Here we focus on studying the vascular MR fingerprint using real mouse angiograms and physiological values as the substrate for the MR simulations. The MR signal is calculated ab initio with a Monte Carlo approximation, by tracking the accumulated phase from a large number of protons diffusing within the angiogram. We first study the identifiability of parameters in simulations, showing that parameters are fully estimable at realistically high signal-to-noise ratios (SNR) when the same angiogram is used for dictionary generation and parameter estimation, but that large biases in the estimates persist when the angiograms are different. Despite these biases, simulations show that differences in parameters remain estimable. We then applied this methodology to data acquired using the GESFIDE sequence with SPIONs injected into 9 young wild type and 9 old atherosclerotic mice. Both the pre injection signal and the ratio of post-to-pre injection signals were modeled, using 5-dimensional dictionaries. The vMRF methodology extracted significant differences in SatO2, mean vessel radius and CBV between the two groups, consistent across brain regions and dictionaries. Further validation work is essential before vMRF can gain wider application.

SUBMITTER: Pouliot P

PROVIDER: S-EPMC5368007 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Magnetic resonance fingerprinting based on realistic vasculature in mice.

Pouliot Philippe P Gagnon Louis L Lam Tina T Avti Pramod K PK Bowen Chris C Desjardins Michèle M Kakkar Ashok K AK Thorin Eric E Sakadzic Sava S Boas David A DA Lesage Frédéric F

NeuroImage 20161231

Magnetic resonance fingerprinting (MRF) was recently proposed as a novel strategy for MR data acquisition and analysis. A variant of MRF called vascular MRF (vMRF) followed, that extracted maps of three parameters of physiological importance: cerebral oxygen saturation (SatO<sub>2</sub>), mean vessel radius and cerebral blood volume (CBV). However, this estimation was based on idealized 2-dimensional simulations of vascular networks using random cylinders and the empirical Bloch equations convol ...[more]

PMID: 28043909

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Project description:PURPOSE:Cardiac magnetic resonance fingerprinting (cMRF) has been recently introduced to simultaneously provide T1 , T2 , and M0 maps. Here, we develop a 3-point Dixon-cMRF approach to enable simultaneous water specific T1 , T2 , and M0 mapping of the heart and fat fraction (FF) estimation in a single breath-hold scan. METHODS:Dixon-cMRF is achieved by combining cMRF with several innovations that were previously introduced for other applications, including a 3-echo GRE acquisition with golden angle radial readout and a high-dimensional low-rank tensor constrained reconstruction to recover the highly undersampled time series images for each echo. Water-fat separation of the Dixon-cMRF time series is performed to allow for water- and fat-specific T1 , T2 , and M0 estimation, whereas FF estimation is extracted from the M0 maps. Dixon-cMRF was evaluated in a standardized T1 -T2 phantom, in a water-fat phantom, and in healthy subjects in comparison to current clinical standards: MOLLI, SASHA, T2 -GRASE, and 6-point Dixon proton density FF (PDFF) mapping. RESULTS:Dixon-cMRF water T1 and T2 maps showed good agreement with reference T1 and T2 mapping techniques (R2 > 0.99 and maximum normalized RMSE ~5%) in a standardized phantom. Good agreement was also observed between Dixon-cMRF FF and reference PDFF (R2 > 0.99) and between Dixon-cMRF water T1 and T2 and water selective T1 and T2 maps (R2 > 0.99) in a water-fat phantom. In vivo Dixon-cMRF water T1 values were in good agreement with MOLLI and water T2 values were slightly underestimated when compared to T2 -GRASE. Average myocardium septal T1 values were 1129 ± 38 ms, 1026 ± 28 ms, and 1045 ± 32 ms for SASHA, MOLLI, and the proposed water Dixon-cMRF. Average T2 values were 51.7 ± 2.2 ms and 42.8 ± 2.6 ms for T2 -GRASE and water Dixon-cMRF, respectively. Dixon-cMRF FF maps showed good agreement with in vivo PDFF measurements (R2 > 0.98) and average FF in the septum was measured at 1.3%. CONCLUSION:The proposed Dixon-cMRF allows to simultaneously quantify myocardial water T1 , water T2 , and FF in a single breath-hold scan, enabling multi-parametric T1 , T2 , and fat characterization. Moreover, reduced T1 and T2 quantification bias caused by water-fat partial volume was demonstrated in phantom experiments.

Dataset Information

Magnetic resonance fingerprinting based on realistic vasculature in mice.

Publications

Magnetic resonance fingerprinting based on realistic vasculature in mice.

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