Robust motion correction in CEST imaging exploiting low-rank approximation of the z-spectrum

Whole-cerebrum guanidino and amide CEST mapping at 3 T by a 3D stack-of-spirals gradient echo acquisition

PURPOSE

To develop a 3D, high-sensitivity CEST mapping technique based on the 3D stack-of-spirals (SOS) gradient echo readout, the proposed approach was compared with conventional acquisition techniques and evaluated for its efficacy in concurrently mapping of guanidino (Guan) and amide CEST in human brain at 3 T, leveraging the polynomial Lorentzian line-shape fitting (PLOF) method.

METHODS

Saturation time and recovery delay were optimized to achieve maximum CEST time efficiency. The 3DSOS method was compared with segmented 3D EPI (3DEPI), turbo spin echo, and gradient- and spin-echo techniques. Image quality, temporal SNR (tSNR), and test-retest reliability were assessed. Maps of Guan and amide CEST derived from 3DSOS were demonstrated on a low-grade glioma patient.

RESULTS

The optimized recovery delay/saturation time was determined to be 1.4/2 s for Guan and amide CEST. In addition to nearly doubling the slice number, the gradient echo techniques also outperformed spin echo sequences in tSNR: 3DEPI (193.8 ± 6.6), 3DSOS (173.9 ± 5.6), and GRASE (141.0 ± 2.7). 3DSOS, compared with 3DEPI, demonstrated comparable GuanCEST signal in gray matter (GM) (3DSOS: [2.14%-2.59%] vs. 3DEPI: [2.15%-2.61%]), and white matter (WM) (3DSOS: [1.49%-2.11%] vs. 3DEPI: [1.64%-2.09%]). 3DSOS also achieves significantly higher amideCEST in both GM (3DSOS: [2.29%-3.00%] vs. 3DEPI: [2.06%-2.92%]) and WM (3DSOS: [2.23%-2.66%] vs. 3DEPI: [1.95%-2.57%]). 3DSOS outperforms 3DEPI in terms of scan-rescan reliability (correlation coefficient: 3DSOS: 0.58-0.96 vs. 3DEPI: -0.02 to 0.75) and robustness to motion as well.

CONCLUSION

The 3DSOS CEST technique shows promise for whole-cerebrum CEST imaging, offering uniform contrast and robustness against motion artifacts.

CEST-MRI for body oncologic imaging: are we there yet?

Chemical exchange saturation transfer (CEST) MRI has gained recognition as a valuable addition to the molecular imaging and quantitative biomarker arsenal, especially for characterization of brain tumors. There is also increasing interest in the use of CEST-MRI for applications beyond the brain. However, its translation to body oncology applications lags behind those in neuro-oncology. The slower migration of CEST-MRI to non-neurologic applications reflects the technical challenges inherent to imaging of the torso. In this review, we discuss the application of CEST-MRI to oncologic conditions of the breast and torso (i.e., body imaging), emphasizing the challenges and potential solutions to address them. While data are still limited, reported studies suggest that CEST signal is associated with important histology markers such as tumor grade, receptor status, and proliferation index, some of which are often associated with prognosis and response to therapy. However, further technical development is still needed to make CEST a reliable clinical application for body imaging and establish its role as a predictive and prognostic biomarker.

7 tricks for 7 T CEST: Improving the reproducibility of multipool evaluation provides insights into the effects of age and the early stages of Parkinson's disease

The objective of the current study was to optimize the postprocessing pipeline of 7 T chemical exchange saturation transfer (CEST) imaging for reproducibility and to prove this optimization for the detection of age differences and differences between patients with Parkinson's disease versus normal subjects. The following 7 T CEST MRI experiments were analyzed: repeated measurements of a healthy subject, subjects of two age cohorts (14 older, seven younger subjects), and measurements of 12 patients with Parkinson's disease. A slab-selective, B 1 + -homogeneous parallel transmit protocol was used. The postprocessing, consisting of motion correction, smoothing, B 0 -correction, normalization, denoising, B 1 + -correction and Lorentzian fitting, was optimized regarding the intrasubject and intersubject coefficient of variation (CoV) of the amplitudes of the amide pool and the aliphatic relayed nuclear Overhauser effect (rNOE) pool within the brain. Seven "tricks" for postprocessing accomplished an improvement of the mean voxel CoV of the amide pool and the aliphatic rNOE pool amplitudes of less than 5% and 3%, respectively. These postprocessing steps are: motion correction with interpolation of the motion of low-signal offsets (1) using the amide pool frequency offset image as reference (2), normalization of the Z-spectrum using the outermost saturated measurements (3), B 0 correction of the Z-spectrum with moderate spline smoothing (4), denoising using principal component analysis preserving the 11 highest intensity components (5), B 1 + correction using a linear fit (6) and Lorentzian fitting using the five-pool fit model (7). With the optimized postprocessing pipeline, a significant age effect in the amide pool can be detected. Additionally, for the first time, an aliphatic rNOE contrast between subjects with Parkinson's disease and age-matched healthy controls in the substantia nigra is detected. We propose an optimized postprocessing pipeline for CEST multipool evaluation. It is shown that by the use of these seven "tricks", the reproducibility and, thus, the statistical power of a CEST measurement, can be greatly improved and subtle changes can be detected.

Motion correction for three-dimensional chemical exchange saturation transfer imaging without direct water saturation artifacts

In chemical exchange saturation transfer (CEST) MRI, motion correction is compromised by the drastically changing image contrast at different frequency offsets, particularly at the direct water saturation. In this study, a simple extension for conventional image registration algorithms is proposed, enabling robust and accurate motion correction of CEST-MRI data. The proposed method uses weighted averaging of motion parameters from a conventional rigid image registration to identify and mitigate erroneously misaligned images. Functionality of the proposed method was verified by ground truth datasets generated from 10 three-dimensional in vivo measurements at 3 T with simulated realistic random rigid motion patterns and noise. Performance was assessed using two different criteria: the maximum image misalignment as a measure for the robustness against direct water saturation artifacts, and the spectral error as a measure of the overall accuracy. For both criteria, the proposed method achieved the best scores compared with two motion-correction algorithms specifically developed to handle the varying contrasts in CEST-MRI. Compared with a straightforward linear interpolation of the motion parameters at frequency offsets close to the direct water saturation, the proposed method offers better performance in the absence of artifacts. The proposed method for motion correction in CEST-MRI allows identification and mitigation of direct water saturation artifacts that occur with conventional image registration algorithms. The resulting improved robustness and accuracy enable reliable motion correction, which is particularly crucial for an automated and carefree evaluation of spectral CEST-MRI data, e.g., for large patient cohorts or in clinical routines.

A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging tool which allows the specific detection of metabolites that contain exchangeable amide, amine, and hydroxyl protons. Decades of development have progressed CEST imaging from an initial concept to a clinical imaging tool that is used to assess tumor metabolism. The first translation efforts involved brain imaging, but this has now progressed to imaging other body tissues. In this review, we summarize studies using CEST MRI to image a range of tumor types, including breast cancer, pelvic tumors, digestive tumors, and lung cancer. Approximately two thirds of the published studies involved breast or pelvic tumors which are sites that are less affected by body motion. Most studies conclude that CEST shows good potential for the differentiation of malignant from benign lesions with a number of reports now extending to compare different histological classifications along with the effects of anti-cancer treatments. Despite CEST being a unique 'label-free' approach with a higher sensitivity than MR spectroscopy, there are still some obstacles for implementing its clinical use. Future research is now focused on overcoming these challenges. Vigorous ongoing development and further clinical trials are expected to see CEST technology become more widely implemented as a mainstream imaging technology.

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

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 Z-spectra 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 B₁ 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 T₁ -corrected rotating frame relaxation rate maps, amideCEST again was not significantly different for white matter and gray matter.

CONCLUSION

Rapid multi-slice amideCEST mapping can be achieved by the starCEST method (< 5 min) at 3T by combing with the polynomial Lorentzian line-shape fitting method.

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

PURPOSE

To obtain high-sensitivity CEST maps by exploiting the spatiotemporal correlation between CEST images.

METHODS

A postprocessing method accomplished by multilinear singular value decomposition (MLSVD) was used to enhance the CEST SNR by exploiting the correlation between the Z-spectrum for each voxel and the low-rank property of the overall CEST data. The performance of this method was evaluated using CrCEST in ischemic mouse brain at 11.7 tesla. Then, MLSVD CEST was applied to obtain Cr, amide, and amine CEST maps of the ischemic mouse brain to demonstrate its general applications.

RESULTS

Complex-valued Gaussian noise was added to CEST k-space data to mimic a low SNR situation. MLSVD CEST analysis was able to suppress the noise, recover the degraded CEST peak, and provide better CrCEST quality compared to the smoothing and singular value decomposition (SVD)-based denoising methods. High-resolution Cr, amide, and amine CEST maps of an ischemic stroke using MLSVD CEST suggest that CrCEST is also a sensitive pH mapping method, and a wide range of pH changes can be detected by combing CrCEST with amine CEST at high magnetic fields.

CONCLUSION

MLSVD CEST provides a simple and efficient way to improve the SNR of CEST images.

Recovery kinetics of creatine in mild plantar flexion exercise using 3D creatine CEST imaging at 7 Tesla

PURPOSE

Two-dimensional creatine CEST (2D-CrCEST), with a slice thickness of 10-20 mm and temporal resolution (τ_Res ) of about 30 seconds, has previously been shown to capture the creatine-recovery kinetics in healthy controls and in patients with abnormal creatine-kinase kinetics following the mild plantar flexion exercise. Since the distribution of disease burden may vary across the muscle length for many musculoskeletal disorders, there is a need to increase coverage in the slice-encoding direction. Here, we demonstrate the feasibility of 3D-CrCEST with τ_Res of about 30 seconds, and propose an improved voxel-wise B 1 + -calibration approach for CrCEST.

METHODS

The current 7T study with enrollment of 5 volunteers involved collecting the baseline CrCEST imaging for the first 2 minutes, followed by 2 minutes of plantar flexion exercise and then 8 minutes of postexercise CrCEST imaging, to detect the temporal evolution of creatine concentration following exercise.

RESULTS

Very good repeatability of 3D-CrCEST findings for activated muscle groups on an intraday and interday basis was established, with coefficient of variance of creatine recovery constants (τ_Cr ) being 7%-15.7%, 7.5%, and 5.8% for lateral gastrocnemius, medial gastrocnemius, and peroneus longus, respectively. We also established a good intraday and interday scan repeatability for 3D-CrCEST and also showed good correspondence between τ_Cr measurements using 2D-CrCEST and 3D-CrCEST acquisitions.

CONCLUSION

In this study, we demonstrated for the first time the feasibility and the repeatability of the 3D-CrCEST method in calf muscle with improved B 1 + correction to measure creatine-recovery kinetics within a large 3D volume of calf muscle.

Optimized dualCEST-MRI for imaging of endogenous bulk mobile proteins in the human brain

Dual-frequency irradiation chemical exchange saturation transfer (dualCEST) allows imaging of endogenous bulk mobile proteins by selectively measuring the intramolecular spin diffusion. The resulting specificity to changes in the concentration, molecular size, and folding state of mobile proteins is of particular interest as a marker for neurodegenerative diseases and cancer. Until now, application of dualCEST in clinical trials was prevented by the inherently small signal-to-noise ratio and the resulting comparatively long examination time. In this study, we present an optimized acquisition protocol allowing 3D dualCEST-MRI examinations in a clinically relevant time frame. The optimization comprised the extension of the image readout to 3D, allowing a retrospective co-registration and application of denoising strategies. In addition, cosine-modulated dual-frequency presaturation pulses were implemented with a weighted acquisition scheme of the necessary frequency offsets. The optimization resulted in a signal-to-noise ratio gain by a factor of approximately 8. In particular, the application of denoising and the motion correction were the most crucial improvement steps. In vitro experiments verified the preservation of specificity of the dualCEST signal to proteins. Good-to-excellent intra-session and good inter-session repeatability was achieved, allowing reliable detection of relative signal differences of about 16% or higher. Applicability in a clinical setting was demonstrated by examining a patient with glioblastoma. The optimized acquisition protocol for dualCEST-MRI at 3 T enables selective imaging of endogenous bulk mobile proteins under clinically relevant conditions.

Adaptive denoising for chemical exchange saturation transfer MR imaging

High image signal-to-noise ratio (SNR) is required to reliably detect the inherently small chemical exchange saturation transfer (CEST) effects in vivo. In this study, it was demonstrated that identifying spectral redundancies of CEST data by principal component analysis (PCA) in combination with an appropriate data-driven extraction of relevant information can be used for an effective and robust denoising of CEST spectra. The relationship between the number of relevant principal components and SNR was studied on fitted in vivo Z-spectra with artificially introduced noise. Three different data-driven criteria to automatically determine the optimal number of necessary components were investigated. In addition, these criteria facilitate straightforward assessment of data quality that could provide guidance for CEST MR protocols in terms of SNR. Insights were applied to achieve a robust denoising of highly sampled low power Z-spectra of the human brain at 3 and 7 T. The median criterion provided the best estimation for the optimal number of components consistently for all three investigated artificial noise levels. Application of the denoising technique to in vivo data revealed a considerable increase in image quality for the amide and rNOE contrast with a considerable SNR gain. At 7 T the denoising capability was quantified to be comparable or even superior to an averaging of six measurements. The proposed denoising algorithm enables an efficient and robust denoising of CEST data by combining PCA with appropriate data-driven truncation criteria. With this generally applicable technique at hand, small CEST effects can be reliably detected without the need for repeated measurements.

Motion correction of chemical exchange saturation transfer MRI series using robust principal component analysis (RPCA) and PCA

BACKGROUND

Chemical exchange saturation transfer (CEST) MRI requires the acquisition of multiple saturation-weighted images and can last several minutes. Misalignments among these images, which are often due to the inevitable motion of the subject, will corrupt CEST contrast maps and result in large quantification errors. Therefore, the registration of the CEST series is critical. However, registration is challenging since common intensity-based registration algorithms may fail to differentiate CEST signals from motion artifacts. Herein, we studied how different patterns of motion affect CEST quantification and proposed a cascaded two-step registration scheme by utilizing features extracted from the entire Z-spectral image series instead of direct registration to a single image.

METHODS

The proposed approach is conducted in two stages: during the first coarse registration, the Z-spectral image series is decomposed by robust principal component analysis (RPCA) to separate CEST contrast from motion. The recomposed image series using only the low-rank component, which contains minimized motion, are averaged to generate a reference for the alignment of the image series. To further remove residual misalignments, the coarse registration is followed by a refinement stage, which uses PCA iteratively to generate motionless synthetic reference series with the first few principal components (PCs) that correspond to CEST contrast. In the end, the quality check is performed to exclude the images with unsuccessful registration.

RESULTS

The proposed registration scheme (RPCA + PCA_R) was assessed by both phantom experiments and in vivo data of tumor-bearing mouse brain, with simulated random rigid motion in different patterns applied to the acquired static Z-spectral image series. For comparison, previous correction schemes using an explicit image [either S0 or Ssat(∆ω)] as registration reference were also performed, named as S0_R and Ssat_R respectively. To illustrate the advantage of combination of RPCA and PCA, registration was also exploited using either only the RPCA-based method (RPCA_R) or only the PCA-based one (PCA_R). Compared with the above four methods, RPCA + PCA_R allowed for more accurate correction of the corrupted Z-spectral images, exhibiting smaller MTRasym(∆ω) error maps and lower residual Z-spectra referring to the static data. Among all the five correction methods, the corrected Z-spectral image series by RPCA + PCA_R and the resulting MTRasym(∆ω) maps achieved the highest correlation coefficients (CC) with respect to the static ones.

CONCLUSIONS

The registration scheme of RPCA + PCA_R provides robust motion correction between two specific Z-spectral images and among an entire image series, through extraction of the static component from the entire Z-spectra set and inclusion of a PCA-based refinement step. Therefore, this method can help improve CEST acquisition and quantification.

Optimization and repeatability of multipool chemical exchange saturation transfer MRI of the prostate at 3.0 T

BACKGROUND

Chemical exchange saturation transfer (CEST) can potentially support cancer imaging with metabolically derived information. Multiparametric prostate MRI has improved diagnosis but may benefit from additional information to reduce the need for biopsies.

PURPOSE

To optimize an acquisition and postprocessing protocol for 3.0 T multipool CEST analysis of prostate data and evaluate the repeatability of the technique.

STUDY TYPE

Prospective.

SUBJECTS

Five healthy volunteers (age range: 24-47 years; median age: 28 years) underwent two sessions (interval range: 7-27 days; median interval: 20 days) and two biopsy-proven prostate cancer patients were evaluated once. Patient 1 (71 years) had a Gleason 3 + 4 transition zone (TZ) tumor and patient 2 (55 years) had a Gleason 4 + 3 peripheral zone (PZ) tumor.

FIELD STRENGTH

3.0 T. Sequences run: T2 -weighted turbo-spin-echo (TSE); diffusion-weighted imaging; CEST; WASABI (for B0 determination).

ASSESSMENT

Saturation, readout, and fit-model parameters were optimized to maximize in vivo amide and nuclear Overhauser effect (NOE) signals. Repeatability (intrasession and intersession) was evaluated in healthy volunteers. Subsequently, preliminary evaluation of signal differences was made in patients. Regions of interest were drawn by two post-FRCR board-certified readers, both with over 5 years of experience in multiparametric prostate MRI.

STATISTICAL TESTS

Repeatability was assessed using Bland-Altman analysis, coefficient of variation (CV), and 95% limits of agreement (LOA). Statistical significance of CEST contrast was calculated using a nonparametric Mann-Whitney U-test.

RESULTS

The optimized saturation scheme was found to be 60 sinc-Gaussian pulses with 40 msec pulse duration, at 50% duty-cycle with continuous-wave pulse equivalent B1 power (B1CWPE ) of 0.92 μT. The magnetization transfer (MT) contribution to the fit-model was centered at -1.27 ppm. Intersession coefficients of variation (CVs) of the amide, NOE, and magnetization transfer (MT) and asymmetric magnetization transfer ratio (MTRasym ) signals of 25%, 23%, 18%, and 200%, respectively, were observed. Fit-metric and MTRasym CVs agreed between readers to within 4 and 10 percentage points, respectively.

DATA CONCLUSION

Signal differences of 0.03-0.10 (17-43%) detectable depending upon pool, with MT the most repeatable (signal difference of 17-22% detectable).

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1238-1250.

Real-time simultaneous shim and motion measurement and correction in glycoCEST MRI using double volumetric navigators (DvNavs)

PURPOSE

CEST MRI allows for indirect detection of molecules with exchangeable protons, measured as a reduction in water signal because of continuous transfer of saturated protons. CEST requires saturation pulses on the order of a second, as well as repeated acquisitions at different offset frequencies. The resulting extended scan time makes CEST susceptible to subject motion, which introduces field inhomogeneity, shifting offset frequencies and causing distortions in CEST spectra that resemble true CEST effects. This is a particular problem for molecules that resonate close to water, such as hydroxyl group in glycogen. To address this, a technique for real-time measurement and correction of motion and field inhomogeneity is proposed.

METHODS

A CEST sequence was modified to include double volumetric navigators (DvNavs) for real-time simultaneous motion and shim correction. Phantom tests were conducted to investigate the effects of motion and shim changes on CEST quantification and to validate the accuracy of DvNav motion and shim estimates. To evaluate DvNav shim and motion correction in vivo, acquisitions including 5 experimental conditions were performed in the calf muscle of 2 volunteers.

RESULTS

Phantom data show that DvNav-CEST accurately estimates frequency and linear gradient changes because of motion and corrects resulting image distortions. In addition, DvNav-CEST improves CEST quantification in vivo in the presence of motion.

CONCLUSION

The proposed technique allows for real-time simultaneous motion and shim correction with no additional scanning time, enabling accurate CEST quantification even in the presence of motion and field inhomogeneity.