PurposeTo develop a respiratory motion correction framework to accelerate free‐breathing three‐dimensional (3D) whole‐heart coronary lumen and coronary vessel wall MRI.MethodsWe developed a 3D flow‐independent approach for vessel wall imaging based on the subtraction of data with and without T2‐preparation prepulses acquired interleaved with image navigators. The proposed method corrects both datasets to the same respiratory position using beat‐to‐beat translation and bin‐to‐bin nonrigid corrections, producing coregistered, motion‐corrected coronary lumen and coronary vessel wall images. The proposed method was studied in 10 healthy subjects and was compared with beat‐to‐beat translational correction (TC) and no motion correction for the left and right coronary arteries. Additionally, the coronary lumen images were compared with a 6‐mm diaphragmatic navigator gated and tracked scan.ResultsNo significant differences (P > 0.01) were found between the proposed method and the gated and tracked scan for coronary lumen, despite an average improvement in scan efficiency to 96% from 59%. Significant differences (P < 0.01) were found in right coronary artery vessel wall thickness, right coronary artery vessel wall sharpness, and vessel wall visual score between the proposed method and TC.ConclusionThe feasibility of a highly efficient motion correction framework for simultaneous whole‐heart coronary lumen and vessel wall has been demonstrated. Magn Reson Med 77:1894–1908, 2017. © 2016 International Society for Magnetic Resonance in Medicine
Purpose To develop a new high‐dimensionality undersampled patch‐based reconstruction (HD‐PROST) for highly accelerated 2D and 3D multi‐contrast MRI. Methods HD‐PROST jointly reconstructs multi‐contrast MR images by exploiting the highly redundant information, on a local and non‐local scale, and the strong correlation shared between the multiple contrast images. This is achieved by enforcing multi‐dimensional low‐rank in the undersampled images. 2D magnetic resonance fingerprinting (MRF) phantom and in vivo brain acquisitions were performed to evaluate the performance of HD‐PROST for highly accelerated simultaneous T 1 and T 2 mapping. Additional in vivo experiments for reconstructing multiple undersampled 3D magnetization transfer (MT)‐weighted images were conducted to illustrate the impact of HD‐PROST for high‐resolution multi‐contrast 3D imaging. Results In the 2D MRF phantom study, HD‐PROST provided accurate and precise estimation of the T 1 and T 2 values in comparison to gold standard spin echo acquisitions. HD‐PROST achieved good quality maps for the in vivo 2D MRF experiments in comparison to conventional low‐rank inversion reconstruction. T 1 and T 2 values of white matter and gray matter were in good agreement with those reported in the literature for MRF acquisitions with reduced number of time point images (500 time point images, ~2.5 s scan time). For in vivo MT‐weighted 3D acquisitions (6 different contrasts), HD‐PROST achieved similar image quality than the fully sampled reference image for an undersampling factor of 6.5‐fold. Conclusion HD‐PROST enables multi‐contrast 2D and 3D MR images in a short acquisition time without compromising image quality. Ultimately, this technique may increase the potential of conventional parameter mapping.
The proposed approach enables free-breathing whole-heart 3D CMRA with isotropic sub-millimeter resolution in <5 min and achieves improved coronary artery visualization in a short and predictable scan time.
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.
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