High‐sensitivity CEST mapping using a spatiotemporal correlation‐enhanced method

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Purpose: To develop a steady-state saturation with radial readout chemical exchange saturation transfer (starCEST) for acquiring CEST images at 3 Tesla (T). The polynomial Lorentzian line-shape fitting approach was further developed for extracting amideCEST intensities at this field. Method: StarCEST MRI using periodically rotated overlapping parallel lines with enhanced reconstruction-based spatial sampling was implemented to acquire Zspectra that are robust to brain motion. Multi-linear singular value decomposition postprocessing was applied to enhance the CEST SNR. The egg white phantom studies were performed at 3T to reveal the contributions to the 3.5 ppm CEST signal.Based on the phantom validation, the amideCEST peak was quantified using the polynomial Lorentzian line-shape fitting, which exploits the inverse relationship between Z-spectral intensity and the longitudinal relaxation rate in the rotating frame.The 3D turbo spin echo CEST was also performed to compare with the starCEST method. Results: The amideCEST peak showed a negligible peak B 1 dependence between 1.2 µT and 2.4 µT. The amideCEST images acquired with starCEST showed much improved image quality, SNR, and motion robustness compared to the conventional 3D turbo spin echo CEST method with the same scan time. The amideCEST contrast extracted by the polynomial Lorentzian line-shape fitting method trended toward a stronger gray matter signal (1.32% ± 0.30%) than white matter (0.92% ± 0.08%; P = .02, n = 5). When calculating the magnetization transfer contrast and T 1 -corrected rotating frame relaxation rate maps, amideCEST again was not significantly different for white matter and gray matter.How to cite this article: Sui R, Chen L, Li Y, et al. Whole-brain amide CEST imaging at 3T with a steady-state radial MRI acquisition.

Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Whole‐brain amide CEST imaging at 3T with a steady‐state radial MRI acquisition

Sui

Chen

et al. 2021

Self Cite

“…However, such an approach does not take into account the spatial information and the spatial correlations inside the acquired images. Recently, a new approach using multilinear singular value decomposition that exploits spatiotemporal correlations has been proposed for denoising CEST‐MRI images 70 . This method succeeded in recovering CEST contrast from in vivo data, although a robust validation with corrupted ground‐truth data was not performed.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of a similarity anisotropic diffusion denoising approach for improving in vivo CEST‐MRI tumor pH imaging

Romdhane

Villano

Irrera

et al. 2021

Purpose: Chemical exchange saturation transfer MRI provides new approaches for investigating tumor microenvironment, including tumor acidosis that plays a key role in tumor progression and resistance to therapy. Following iopamidol injection, the detection of the contrast agent inside the tumor tissue allows measurements of tumor extracellular pH. However, accurate tumor pH quantifications are hampered by the low contrast efficiency of the CEST technique and by the low SNR of the acquired CEST images, hence in a reduced detectability of the injected agent. This work aims to investigate a novel denoising method for improving both tumor pH quantification and accuracy of CEST-MRI pH imaging. Methods: An hybrid denoising approach was investigated for CEST-MRI pH imaging based on the combination of the nonlocal mean filter and the anisotropic diffusion tensor method. The denoising approach was tested in simulated and in vitro data and compared with previously reported methods for CEST imaging and with established denoising approaches. Finally, it was validated with in vivo data to improve the accuracy of tumor pH maps. Results: The proposed method outperforms current denoising methods in CEST contrast quantification and detection of the administered contrast agent at several increasing noise levels with simulated data. In addition, it achieved a better pH quantification in in vitro data and demonstrated a marked improvement in contrast detection and a substantial improvement in tumor pH accuracy in in vivo data. Conclusion: The proposed approach effectively reduces the noise in CEST images and increases the sensitivity detection in CEST-MRI pH imaging.

Whole‐brain steady‐state CEST at 3 T using MR Multitasking

Han

Cheema

Lee

et al. 2021

Chemical exchange saturation transfer is a noncontrast MRI technique that indirectly detects exchangeable protons in the water pool by presaturation at different frequency offsets. [1][2][3] Chemical exchange saturation transfer MRI provides a novel contrast mechanism to image important physiological information, such as pH and metabolite concentration. 4,5 It can be applied to detect and diagnose various pathologies, such as cancer, 6 ischemia, 2,7 and lymphedema. 8