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PURPOSE: To evaluate the accuracy of three-dimensional (3D) chemical exchange saturation transfer (CEST) imaging with a compressed sensing (CS) and sensitivity encoding (SENSE) technique (CS-SENSE) for full z-spectrum acquisition. METHODS: All images were acquired on 3-T magnetic resonance imaging (MRI) scanner. In the phantom study, we used the acidoCEST imaging. The phantoms were prepared in seven vials containing different concentrations of iopamidol mixed in phosphate-buffered solution with different pH values. The CEST ratios were calculated from the two CEST effects. We compared the CEST ratios obtained with three different 3D CEST imaging protocols (CS-SENSE factor 5, 7, 9) with those obtained with the 2D CEST imaging as a reference standard. In the clinical study, 21 intracranial tumor patients (mean 49.7 ± 17.2 years, 7 males and 14 females) were scanned. We compared the intratumor magnetization transfer ratio asymmetry (MTRasym) obtained with 3D CEST imaging with those obtained with 2D CEST imaging as a reference standard. RESULTS: A smaller CS-SENSE factor resulted in higher agreement and better correlations with the 2D CEST imaging in the phantom study (CS-SENSE 5; ICC = 0.977, R2 = 0.8943, P < 0.0001: CS-SENSE 7; ICC = 0.970, R2 = 0.9013, P < 0.0001: CS-SENSE 9; ICC = 0.934, R2 = 0.8156 P < 0.0001). In the brain tumors, the means and percentile values of MTRasym at 2.0 and 3.5 ppm showed high linear correlations (R2 = 0.7325-0.8328, P < 0.0001) and high ICCs (0.859-0.907), which enabled successful multi-slice CEST imaging. CONCLUSIONS: The 3D CEST imaging with CS-SENSE provided equivalent contrast to 2D CEST imaging; moreover, a z-spectrum with a wide scan range could be obtained.

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PURPOSE: To evaluate the optimal sequence for high-resolution magnetic resonance imaging (MRI) of the triangular fibrocartilage complex (TFCC) using compressed sensing-sensitivity encoding (CS-SENSE). METHODS: Three-dimensional fast field echo T2-weighted images were obtained from 13 healthy volunteers using the original, high spatial resolution sequence with CS-SENSE [HR (CS-SENSE)] and without CS-SENSE (HR) and super-high spatial resolution sequence with CS-SENSE [S-HR (CS-SENSE)] and without CS-SENSE (S-HR). For qualitative analysis, the number of patients affected by motion artifacts in each sequence was counted, and the visualization of the TFCC anatomic structures and overall image quality were categorized. For the quantitative analysis, relative signal intensity (SI) and relative contrast of the lunate bone marrow, lunate cartilage, and disk proper in the wrist joint were all calculated. RESULTS: The HR (CS-SENSE) sequence showed better visualization scores than the original sequence in the triangular ligament at the ulnar styloid tip, dorsal radioulnar ligament, and ulnotriquetral ligament. Similarly, the S-HR (CS-SENSE) sequence showed better visualization scores than the original sequence in the triangular ligament at the ulnar styloid tip and dorsal radioulnar ligament. Overall image quality scores were not significantly different, and motion artifacts in the HR and S-HR sequences were observed in 3 of the 13 patients. In contrast, the original sequence showed higher values than those in the HR (CS-SENSE) and S-HR (CS-SENSE) sequences in relative SI of the bone marrow and relative contrast of the cartilage-bone marrow and cartilage-disk proper. CONCLUSIONS: Out of the three sequences, the HR (CS-SENSE) sequence provided the highest visualization score and diagnostically sufficient image quality score, although relative SI and relative contrast were low. The HR (CS-SENSE) sequence may be clinically useful for imaging TFCCs.

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BACKGROUND: Magnetic resonance imaging (MRI) has the limitation of low imaging speed. Acceleration methods using under-sampled k-space data have been widely exploited to improve data acquisition without reducing the image quality. Sensitivity encoding (SENSE) is the most commonly used method for multi-channel imaging. However, SENSE has the drawback of severe g-factor artifacts when the under-sampling factor is high. This paper applies generative adversarial networks (GAN) to remove g-factor artifacts from SENSE reconstructions. METHODS: Our method was evaluated on a public knee database containing 20 healthy participants. We compared our method with conventional GAN using zero-filled (ZF) images as input. Structural similarity (SSIM), peak signal to noise ratio (PSNR), and normalized mean square error (NMSE) were calculated for the assessment of image quality. A paired student's t-test was conducted to compare the image quality metrics between the different methods. Statistical significance was considered at P<0.01. RESULTS: The proposed method outperformed SENSE, variational network (VN), and ZF + GAN methods in terms of SSIM (SENSE + GAN: 0.81±0.06, SENSE: 0.40±0.07, VN: 0.79±0.06, ZF + GAN: 0.77±0.06), PSNR (SENSE + GAN: 31.90±1.66, SENSE: 22.70±1.99, VN: 31.35±2.01, ZF + GAN: 29.95±1.59), and NMSE (×10-7) (SENSE + GAN: 0.95±0.34, SENSE: 4.81±1.33, VN: 0.97±0.30, ZF + GAN: 1.60±0.84) with an under-sampling factor of up to 6-fold. CONCLUSIONS: This study demonstrated the feasibility of using GAN to improve the performance of SENSE reconstruction. The improvement of reconstruction is more obvious for higher under-sampling rates, which shows great potential for many clinical applications.

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PURPOSE: The widespread clinical use of chemical exchange saturation transfer (CEST) imaging is hampered by relatively long scan times due to its requirement that multiple saturation-offset image frames be acquired. Here, a novel variably-accelerated sensitivity encoding (vSENSE) method is proposed that provides faster CEST acquisition than conventional SENSE. THEORY AND METHODS: The vSENSE method fully samples one CEST saturation frame, then undersamples the other frames variably. The fully-sampled frame, in conjunction with newly proposed incoherence absorption and artifact suppression strategies, improves the accuracy of sensitivity maps and permits higher acceleration factors for the other undersampled frames than regular SENSE. vSENSE is validated in a phantom, a normal volunteer and eight brain tumor patients at 3 Tesla. RESULTS: vSENSE with an acceleration factor of four generated a 3-6 times smaller error on average than conventional SENSE (P ≤ 0.02), with acceleration factors of 2-4, as compared with full k-space reconstruction. vSENSE permitted four-fold acceleration for amide proton transfer-weighted images, while regular SENSE could only provide a factor of two. When conventional SENSE is used with vSENSE's variable undersampling pattern, erroneous (∼9%) z-spectra result. CONCLUSION: The vSENSE method enabled twice the acceleration and generated more accurate images than conventional SENSE. Magn Reson Med 77:2225-2238, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

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Parallel imaging (PI) is widely used for imaging acceleration by means of coil spatial sensitivities associated with phased array coils (PACs). By employing a time-division multiplexing technique, a single-channel rotating radiofrequency coil (RRFC) provides an alternative method to reduce scan time. Strategically combining these two concepts could provide enhanced acceleration and efficiency. In this work, the imaging acceleration ability and homogeneous image reconstruction strategy of 4-element rotating radiofrequency coil array (RRFCA) was numerically investigated and experimental validated at 7T with a homogeneous phantom. Each coil of RRFCA was capable of acquiring a large number of sensitivity profiles, leading to a better acceleration performance illustrated by the improved geometry-maps that have lower maximum values and more uniform distributions compared to 4- and 8-element stationary arrays. A reconstruction algorithm, rotating SENSitivity Encoding (rotating SENSE), was proposed to provide image reconstruction. Additionally, by optimally choosing the angular sampling positions and transmit profiles under the rotating scheme, phantom images could be faithfully reconstructed. The results indicate that, the proposed technique is able to provide homogeneous reconstructions with overall higher and more uniform signal-to-noise ratio (SNR) distributions at high reduction factors. It is hoped that, by employing the high imaging acceleration and homogeneous imaging reconstruction ability of RRFCA, the proposed method will facilitate human imaging for ultra high field MRI.

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