Ultrafast multi-slice chemical exchange saturation transfer imaging scheme based on segmented spatiotemporal encoding

Acquisition sequences and reconstruction methods for fast chemical exchange saturation transfer imaging

Chemical exchange saturation transfer (CEST) imaging is an emerging molecular magnetic resonance imaging (MRI) technique that has been developed and employed in numerous diseases. Based on the unique saturation transfer principle, a family of CEST-detectable biomolecules in vivo have been found capable of providing valuable diagnostic information. However, CEST MRI needs a relatively long scan time due to the common long saturation labeling module and typical acquisition of multiple frequency offsets and signal averages, limiting its widespread clinical applications. So far, a plethora of imaging schemes and techniques has been developed to accelerate CEST MRI. In this review, the key acquisition and reconstruction methods for fast CEST imaging are summarized from a practical and systematic point of view. The first acquisition sequence section describes the major development of saturation schemes, readout patterns, ultrafast z-spectroscopy, and saturation-editing techniques for rapid CEST imaging. The second reconstruction method section lists the important advances of parallel imaging, compressed sensing, sparsity in the z-spectrum, and algorithms beyond the Fourier transform for speeding up CEST MRI.

Magnetic Resonance pH Imaging in Stroke – Combining the Old With the New

The study of stroke has historically made use of traditional spectroscopy techniques to provide the ground truth for parameters like pH. However, techniques like ³¹P spectroscopy have limitations, in particular poor temporal and spatial resolution, coupled with a need for a high field strength and specialized coils. More modern magnetic resonance spectroscopy (MRS)-based imaging techniques like chemical exchange saturation transfer (CEST) have been developed to counter some of these limitations but lack the definitive gold standard for pH that ³¹P spectroscopy provides. In this perspective, both the traditional (³¹P spectroscopy) and emerging (CEST) techniques in the measurement of pH for ischemic imaging will be discussed. Although each has its own advantages and limitations, it is likely that CEST may be preferable simply due to the hardware, acquisition time and image resolution advantages. However, more experiments on CEST are needed to determine the specificity of endogenous CEST to absolute pH, and ³¹P MRS can be used to calibrate CEST for pH measurement in the preclinical model to enhance our understanding of the relationship between CEST and pH. Combining the two imaging techniques, one old and one new, we may be able to obtain new insights into stroke physiology that would not be possible otherwise with either alone.

Clinical translation of amide proton transfer (APT) MRI for ischemic stroke: a systematic review (2003-2020)

Amide proton transfer (APT) magnetic resonance imaging (MRI) is a pH-sensitive imaging technique that can potentially complement existing clinical imaging protocol for the assessment of ischemic stroke. This review aims to summarize the developments in the clinical research of APT imaging of ischemic stroke after 17 years of progress since its first preclinical study in 2003. Three electronic databases: PubMed, Scopus, and Cochrane Library were systematically searched for articles reporting clinical studies on APT imaging of ischemic stroke. Only articles in English published between 2003 to 2020 that involved patients presenting ischemic stroke-like symptoms that underwent APT MRI were included. Of 1,093 articles screened, 14 articles met the inclusion criteria with a total of 282 patients that had been scanned using APT imaging. Generally, the clinical studies agreed APT effect to be hypointense in ischemic tissue compared to healthy tissue, allowing for the detection of ischemic stroke. Other uses of APT imaging have also been investigated in the studies, including penumbra identification, predicting long term clinical outcome, and serving as a biomarker for supportive treatment monitoring. The published results demonstrated the potential of APT imaging in these applications, but further investigations and larger trials are needed for conclusive evidence. Future studies are recommended to report the result of asymmetry analysis at 3.5 ppm along with the findings of the study to reduce this contribution to the heterogeneity of experimental methods observed and to facilitate effective comparison of results between studies and centers. In addition, it is important to focus on the development of fast 3D imaging for full volumetric ischemic tissue assessment for clinical translation.

Accelerating CEST MRI in the mouse brain at 9.4 T by exploiting sparsity in the Z-spectrum domain

PURPOSE

Chemical exchange saturation transfer (CEST) is an MR contrast modality offering an enhanced sensitivity for the detection of dilute metabolites with exchangeable protons. Quantitative analysis requires the acquisition of a number of images (usually between 20 and 50 RF offsets) per Z-spectrum, leading to long acquisition times of the order of 5-40 min in practice. In this work, we explore the possibility of employing sparsity in the Z-spectrum domain (irradiation offset dimension) to provide an accelerated acquisition scheme without compromising the quality of reconstructed CEST spectra.

METHOD AND THEORY

Ex vivo and in vivo data were acquired on an experimental, small animal 9.4 T system. Three different reconstruction methods were tested: k-Z SPARSE, k-Z SLR and k-Z principal component analysis (PCA) using retrospective undersampling with net acceleration factors R = 2, 3, 5. The quality of the reconstructed data was compared with respect to CEST spectra and full magnetization transfer ratio (MTR) asymmetry maps.

RESULTS

In both phantom and in vivo data, CEST spectra and the resulting MTR asymmetry maps were reconstructed without significant deterioration in data quality. For a low acceleration factor (R = 2, 3) all applied methods resulted in similar data quality, while for high acceleration factor (R = 5) only k-Z PCA and k-Z SLR could be used. Loss in spatial resolution was observed in reconstruction with k-Z PCA for all acceleration factors. An example of prospective undersampling with acceleration factor R = 3 and k-Z PCA reconstruction demonstrates improved CEST maps when compared with fully sampled data acquisition with either three times longer scan duration or threefold prolonged acquisition window per frequency offset.

CONCLUSION

The acquisition time of CEST spectra can be significantly accelerated by exploiting the sparsity of the Z-domain. For prospective and retrospective analysis using k-Z PCA, an acceleration factor of up to R = 3 can be used without significant loss in data quality.

Super-resolved water/fat image reconstruction based on single-shot spatiotemporally encoded MRI

Single-shot spatiotemporally encoded (SPEN) MRI has been validated to possess considerable performance in both spatial and temporal resolution. Water/fat separation is essential for MRI applications in which only water signal is needed. In this article, a super-resolved water/fat image reconstruction method (dubbed SWAF) combined prior knowledge was developed based on single-shot SPEN MRI. The point spread function of spatiotemporal encoding under multiple chemical shifts situation was derived and used for constructing an equation for SWAF image reconstruction. By processing the prior chemical shift information with filtering operation, an initial spin density profile of water/fat and a weighting matrix for water/fat residual artifacts suppression were obtained to guide the reconstruction process. A l₁ norm minimization problem with regularization was exploited to reconstruct separated water/fat images with high spatial resolution and less residual/aliasing artifacts. Numeric simulation and experiments on water-oil phantom and rat abdomen/neck imaging demonstrated the effectiveness and robustness of this new method. The SWAF method proposed herein would promote the application of SPEN MRI in the cases where water/fat separation is required.

Analysis of model-based and model-free CEST effect quantification methods for different medical applications

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) holds great potential to provide new metabolic information for clinical applications such as tumor, stroke and Parkinson's Disease diagnosis. Many active research and developments have been conducted to translate this emerging MRI technique for routine clinical applications. In general, there are two CEST quantification techniques: (i) model-free and (ii) model-based techniques. The reliability of these quantification techniques depends heavily on the experimental conditions and quality of the collected data. Errors such as noise may lead to misleading quantification results and thus inaccurate diagnosis when CEST imaging becomes a standard or routine imaging scan in the future. This paper investigates the accuracy and robustness of these quantification techniques under different signal-to-noise (SNR) levels and magnetic field strengths. The quantified CEST effect before and after adding random Gaussian White Noise using model-free and model-based quantification techniques were compared. It was found that the model-free technique consistently yielded larger average percentage error across all tested parameters compared to its model-based counterpart, and that the model-based technique could withstand SNR of about 3 times lower than the model-free technique. When applied on noisy brain tumor, ischemic stroke, and Parkinson's Disease clinical data, the model-free technique failed to produce significant differences between normal and abnormal tissue whereas the model-based technique consistently generated significant differences. Although the model-free technique was less accurate and robust, its simplicity and thus speed would still make it a good approximate when the SNR was high (>50) or when the CEST effect was large and well-defined. For more accurate CEST quantification, model-based techniques should be considered. When SNR was low (<50) and the CEST effect was small such as those acquired from clinical field strength scanners, which are generally 3T and below, model-based techniques should be considered over model-free counterpart to maintain an average percentage error of less than 44% even under very noisy condition as tested in this work.