Highly accelerated chemical exchange saturation transfer (CEST) measurements with linear algebraic modeling

Highly-accelerated CEST MRI using frequency-offset-dependent k-space sampling and deep-learning reconstruction

PURPOSE

To develop a highly accelerated CEST Z-spectral acquisition method using a specifically-designed k-space sampling pattern and corresponding deep-learning-based reconstruction.

METHODS

For k-space down-sampling, a customized pattern was proposed for CEST, with the randomized probability following a frequency-offset-dependent (FOD) function in the direction of saturation offset. For reconstruction, the convolution network (CNN) was enhanced with a Partially Separable (PS) function to optimize the spatial domain and frequency domain separately. Retrospective experiments on a self-acquired human brain dataset (13 healthy adults and 15 brain tumor patients) were conducted using k-space resampling. The prospective performance was also assessed on six healthy subjects.

RESULTS

In retrospective experiments, the combination of FOD sampling and PS network (FOD + PSN) showed the best quantitative metrics for reconstruction, outperforming three other combinations of conventional sampling with varying density and a regular CNN (nMSE and SSIM, p < 0.001 for healthy subjects). Across all acceleration factors from 4 to 14, the FOD + PSN approach consistently outperformed the comparative methods in four contrast maps including MTRasym, MTRrex, as well as the Lorentzian Difference maps of amide and nuclear Overhauser effect (NOE). In the subspace replacement experiment, the error distribution demonstrated the denoising benefits achieved in the spatial subspace. Finally, our prospective results obtained from healthy adults and brain tumor patients (14×) exhibited the initial feasibility of our method, albeit with less accurate reconstruction than retrospective ones.

CONCLUSION

The combination of FOD sampling and PSN reconstruction enabled highly accelerated CEST MRI acquisition, which may facilitate CEST metabolic MRI for brain tumor patients.

Amide proton transfer-weighted imaging of the abdomen: Current progress and future directions

The chemical exchange saturation transfer technique serves as a valuable tool for generating in vivo image contrast based on the content of various proton groups, including amide protons, amine protons, and aliphatic protons. Among these, amide proton transfer-weighted (APTw) imaging has seen extensive development as a means to assess the biochemical status of lesions. The exchange from saturated amide protons to bulk water protons during and following the saturation ratio frequency pulse contributes to detectable APT signals. While APTw imaging has garnered significant attention in the central nervous system, demonstrating noteworthy findings in cerebral neoplasia, stroke, and Alzheimer's disease over the past decade, its application in the abdomen has been a relatively recent progression. Notably, studies have explored its utility in hepatocellular carcinoma, prostate cancer, and cervical carcinoma within the abdominal context. Despite these advancements, there is a paucity of reviews on APTw imaging in abdominal applications. This paper aims to fill this gap by providing a concise overview of the fundamental theories underpinning APTw imaging. Additionally, we systematically summarize its diverse clinical applications in the abdomen, with a particular focus on the digestive and urogenital systems. Finally, the manuscript concludes by discussing technical limitations and factors influencing APTw imaging in abdominal applications, along with prospects for future research.

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.

Joint K-space and Image-space Parallel Imaging (KIPI) for accelerated chemical exchange saturation transfer acquisition

PURPOSE

To develop an auto-calibrated technique by joint K-space and Image-space Parallel Imaging (KIPI) for accelerated CEST acquisition.

THEORY AND METHODS

The KIPI method selects a calibration frame with a low acceleration factor (AF) and auto-calibration signals (ACS) acquired, from which the coil sensitivity profiles and artifact correction maps are calculated after restoring the k-space by GRAPPA. Then the other frames with high AF and without ACS can be reconstructed by SENSE and artifact suppression. The signal leakage due to the T₂ -decay filtering in k-space compromises the SENSE reconstruction, which can be corrected by the artifact suppression algorithm of KIPI. The 2D and 3D imaging experiments were done on the phantom, healthy volunteer, and brain tumor patient with a 3T scanner.

RESULTS

The proposed KIPI method was evaluated by retrospectively undersampled data with variable AFs and compared against existing parallel imaging methods (SENSE/auto, GRAPPA, and ESPIRiT). KIPI enabled CEST frames with random AFs to achieve similar image quality, eliminated the strong aliasing artifacts, and generated significantly smaller errors than the other methods (p < 0.01). The KIPI method permitted an AF up to 12-fold in both phase-encoding and slice-encoding directions for 3D CEST source images, achieving an overall 8.2-fold speedup in scan time.

CONCLUSION

KIPI is a novel auto-calibrated parallel imaging method that enables variable AFs for different CEST frames, achieves a significant reduction in scan time, and does not compromise the accuracy of CEST maps.

Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors

Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.

Molecular Imaging of Brain Tumors and Drug Delivery Using CEST MRI: Promises and Challenges

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) detects molecules in their natural forms in a sensitive and non-invasive manner. This makes it a robust approach to assess brain tumors and related molecular alterations using endogenous molecules, such as proteins/peptides, and drugs approved for clinical use. In this review, we will discuss the promises of CEST MRI in the identification of tumors, tumor grading, detecting molecular alterations related to isocitrate dehydrogenase (IDH) and O-6-methylguanine-DNA methyltransferase (MGMT), assessment of treatment effects, and using multiple contrasts of CEST to develop theranostic approaches for cancer treatments. Promising applications include (i) using the CEST contrast of amide protons of proteins/peptides to detect brain tumors, such as glioblastoma multiforme (GBM) and low-grade gliomas; (ii) using multiple CEST contrasts for tumor stratification, and (iii) evaluation of the efficacy of drug delivery without the need of metallic or radioactive labels. These promising applications have raised enthusiasm, however, the use of CEST MRI is not trivial. CEST contrast depends on the pulse sequences, saturation parameters, methods used to analyze the CEST spectrum (i.e., Z-spectrum), and, importantly, how to interpret changes in CEST contrast and related molecular alterations in the brain. Emerging pulse sequence designs and data analysis approaches, including those assisted with deep learning, have enhanced the capability of CEST MRI in detecting molecules in brain tumors. CEST has become a specific marker for tumor grading and has the potential for prognosis and theranostics in brain tumors. With increasing understanding of the technical aspects and associated molecular alterations detected by CEST MRI, this young field is expected to have wide clinical applications in the near future.

CEST MRI trackable nanoparticle drug delivery systems

Mounting evidence shows the great promise of nanoparticle drug delivery systems (nano-DDSs) to improve delivery efficiency and reduce off-target adverse effects. By tracking drug delivery and distribution, monitoring nanoparticle degradation and drug release, aiding and optimizing treatment planning, and directing the design of more robust nano-DDSs, image guidance has become a vital component of nanomedicine. Recently, chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as an attempting imaging method for achieving image-guided drug delivery. One of the unbeatable advantages of CEST MRI is its ability to detect diamagnetic compounds that cannot be detected using conventional MRI methods, making a broad spectrum of bioorganic agents, natural compounds, even nano-carriers directly MRI detectable in a high-spatial-resolution manner. To date, CEST MRI has become a versatile and powerful imaging technology for non-invasive in vivo tracking of nanoparticles and their loaded drugs. In this review, we will provide a concise overview of different forms of recently developed, CEST MRI trackable nano-DDSs, including liposomes, polymeric nanoparticles, self-assembled drug-based nanoparticles, and carbon dots. The potential applications and future perspectives will also be discussed.

Repurposing Clinical Agents for Chemical Exchange Saturation Transfer Magnetic Resonance Imaging: Current Status and Future Perspectives

Molecular imaging is becoming an indispensable tool to pursue precision medicine. However, quickly translating newly developed magnetic resonance imaging (MRI) agents into clinical use remains a formidable challenge. Recently, Chemical Exchange Saturation Transfer (CEST) MRI is emerging as an attractive approach with the capability of directly using low concentration, exchangeable protons-containing agents for generating quantitative MRI contrast. The ability to utilize diamagnetic compounds has been extensively exploited to detect many clinical compounds, such as FDA approved drugs, X-ray/CT contrast agents, nutrients, supplements, and biopolymers. The ability to directly off-label use clinical compounds permits CEST MRI to be rapidly translated to clinical settings. In this review, the current status of CEST MRI based on clinically available compounds will be briefly introduced. The advancements and limitations of these studies are reviewed in the context of their pre-clinical or clinical applications. Finally, future directions will be briefly discussed.

Improving Amide Proton Transfer-Weighted MRI Reconstruction Using T2-Weighted Images

Current protocol of Amide Proton Transfer-weighted (APTw) imaging commonly starts with the acquisition of high-resolution T2-weighted (T₂w) images followed by APTw imaging at particular geometry and locations (i.e. slice) determined by the acquired T₂w images. Although many advanced MRI reconstruction methods have been proposed to accelerate MRI, existing methods for APTw MRI lacks the capability of taking advantage of structural information in the acquired T₂w images for reconstruction. In this paper, we present a novel APTw image reconstruction framework that can accelerate APTw imaging by reconstructing APTw images directly from highly undersampled k-space data and corresponding T₂w image at the same location. The proposed framework starts with a novel sparse representation-based slice matching algorithm that aims to find the matched T₂w slice given only the undersampled APTw image. A Recurrent Feature Sharing Reconstruction network (RFS-Rec) is designed to utilize intermediate features extracted from the matched T₂w image by a Convolutional Recurrent Neural Network (CRNN), so that the missing structural information can be incorporated into the undersampled APT raw image thus effectively improving the image quality of the reconstructed APTw image. We evaluate the proposed method on two real datasets consisting of brain data from rats and humans. Extensive experiments demonstrate that the proposed RFS-Rec approach can outperform the state-of-the-art methods.

Frequency-stabilized chemical exchange saturation transfer imaging with real-time free-induction-decay readout

PURPOSE

To correct the temporal B₀ drift in chemical exchange saturation transfer (CEST) imaging in real-time with extra free-induction-decay (FID) readout.

THEORY AND METHODS

The frequency stabilization module of the recently proposed frequency-stabilized CEST (FS-CEST) sequence was further simplified by replacing the original three k-space lines of gradient-echo (GRE) readout with a single k-space line of FID readout. The B₀ drift was quantified using the phase difference between the odd and even parts of the FID signal in the frequency stabilization module and then used to update the B₀ frequency in the succeeding modules. The proposed FS-CEST sequence with FID readout (FID FS-CEST) was validated in phantoms and 16 human subjects on cross-vendor scanners.

RESULTS

In the Siemens experiments, the FID FS-CEST sequence successfully corrected the user-induced B₀ drift, generating consistent amide proton transfer-weighted (APTw) images and magnetization transfer ratio asymmetry (MTR_asym ) spectra with those from the non-frequency-stabilized CEST (NFS-CEST) sequence without B₀ drift. In the Philips experiments, the FID FS-CEST sequence produced more stable APTw images and MTR_asym spectra than the NFS-CEST sequence in the presence of practical B₀ drift. Quantitatively, the SD of the APTw signal values in the deep gray matter from 15 subjects was 0.26% for the FID FS-CEST sequence compared to 1.03% for the NFS-CEST sequences, with the fluctuations reduced by nearly three-quarters.

CONCLUSIONS

The proposed FS-CEST sequence with FID readout can effectively correct the temporal B₀ drift on cross-vendor scanners.

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.

Fast 3D chemical exchange saturation transfer imaging with variably-accelerated sensitivity encoding (vSENSE)

PURPOSE

To extend the variably-accelerated sensitivity encoding (vSENSE) method from 2D to 3D for fast chemical exchange saturation transfer (CEST) imaging, and prospectively implement it for clinical MRI.

METHODS

The CEST scans were acquired from 7 normal volunteers and 15 brain tumor patients using a 3T clinical scanner. The 2D and 3D "artifact suppression" (AS) vSENSE algorithms were applied to generate sensitivity maps from a first scan acquired with conventional SENSE-accelerated 2D and 3D CEST data. The AS sensitivity maps were then applied to reconstruct the other CEST frames at higher acceleration factors. Both retrospective and prospective acceleration in phase-encoding and slice-encoding dimensions were implemented.

RESULTS

Applying the 2D AS vSENSE algorithm to a 2-fold undersampled 3.5-ppm CEST frame halved the scan time of conventional SENSE, while generating essentially identical reconstruction errors (p ≈ 1.0). The 3D AS vSENSE algorithm permitted prospective acceleration by up to 8-fold, in total, from phase-encoding and slice-encoding directions for individual source CEST images, and an overall speed-up in scan time of 5-fold. The resulting vSENSE-accelerated amide proton transfer-weighted images agreed with conventional 2-fold-accelerated SENSE CEST results in brain tumor patients and healthy volunteers. Importantly, the vSENSE method eliminated unfolding artifacts in the slice-encoding direction that compromised conventional SENSE CEST scans.

CONCLUSION

The vSENSE method can be extended to 3D CEST imaging to provide higher acceleration factors than conventional SENSE without compromising accuracy.

Prospective acceleration of parallel RF transmission-based 3D chemical exchange saturation transfer imaging with compressed sensing

PURPOSE

To develop prospectively accelerated 3D CEST imaging using compressed sensing (CS), combined with a saturation scheme based on time-interleaved parallel transmission.

METHODS

A variable density pseudo-random sampling pattern with a centric elliptical k-space ordering was used for CS acceleration in 3D. Retrospective CS studies were performed with CEST phantoms to test the reconstruction scheme. Prospectively CS-accelerated 3D-CEST images were acquired in 10 healthy volunteers and 6 brain tumor patients with an acceleration factor (R_CS ) of 4 and compared with conventional SENSE reconstructed images. Amide proton transfer weighted (APTw) signals under varied RF saturation powers were compared with varied acceleration factors.

RESULTS

The APTw signals obtained from the CS with acceleration factor of 4 were well-preserved as compared with the reference image (SENSE R = 2) both in retrospective phantom and prospective healthy volunteer studies. In the patient study, the APTw signals were significantly higher in the tumor region (gadolinium [Gd]-enhancing tumor core) than in the normal tissue (p < .001). There was no significant APTw difference between the CS-accelerated images and the reference image. The scan time of CS-accelerated 3D APTw imaging was dramatically reduced to 2:10 minutes (in-plane spatial resolution of 1.8 × 1.8 mm² ; 15 slices with 4-mm slice thickness) as compared with SENSE (4:07 minutes).

CONCLUSION

Compressed sensing acceleration was successfully extended to 3D-CEST imaging without compromising CEST image quality and quantification. The CS-based CEST imaging can easily be integrated into clinical protocols and would be beneficial for a wide range of applications.

Improved chemical exchange saturation transfer imaging with real-time frequency drift correction

PURPOSE

To investigate the effects of frequency drift on chemical exchange saturation transfer (CEST) imaging at 3T, and to propose a new sequence for correcting artifacts attributed to B₀ drift in real time.

THEORY AND METHODS

A frequency-stabilized CEST (FS-CEST) imaging sequence was proposed by adding a frequency stabilization module to the conventional non-frequency-stabilized CEST (NFS-CEST) sequence, which consisted of a small tip angle radiofrequency excitation pulse and readout of three non-phase-encoded k-space lines. Experiments were performed on an egg white phantom and 26 human subjects on a heavy-duty clinical scanner, in order to compare the difference of FS-CEST and NFS-CEST sequences for generating the z-spectrum, magnetization transfer ratio asymmetry (MTR_asym ) spectrum, and amide proton transfer weighted (APTw) image.

RESULTS

The B₀ drift in CEST imaging, if not corrected, would cause APTw images and MTR_asym spectra from both the phantom and volunteers to be either significantly higher or lower than the true values, depending on the status of the scanner. The FS-CEST sequence generated substantially more stable MTR_asym spectra and APTw images than the conventional NFS-CEST sequence. Quantitatively, the compartmental-average APTw signals (mean ± standard deviation) from frontal white matter regions of all 26 human subjects were -0.32% ± 2.32% for the NFS-CEST sequence and -0.14% ± 0.37% for the FS-CEST sequence.

CONCLUSIONS

The proposed FS-CEST sequence provides an effective approach for B₀ drift correction without additional scan time and should be adopted on heavy-duty MRI scanners.

APT-weighted MRI: Techniques, current neuro applications, and challenging issues

Amide proton transfer-weighted (APTw) imaging is a molecular MRI technique that generates image contrast based predominantly on the amide protons in mobile cellular proteins and peptides that are endogenous in tissue. This technique, the most studied type of chemical exchange saturation transfer imaging, has been used successfully for imaging of protein content and pH, the latter being possible due to the strong dependence of the amide proton exchange rate on pH. In this article we briefly review the basic principles and recent technical advances of APTw imaging, which is showing promise clinically, especially for characterizing brain tumors and distinguishing recurrent tumor from treatment effects. Early applications of this approach to stroke, Alzheimer's disease, Parkinson's disease, multiple sclerosis, and traumatic brain injury are also illustrated. Finally, we outline the technical challenges for clinical APT-based imaging and discuss several controversies regarding the origin of APTw imaging signals in vivo. Level of Evidence: 3 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019;50:347-364.

Accelerating chemical exchange saturation transfer MRI with parallel blind compressed sensing

PURPOSE

Chemical exchange saturation transfer is a novel and promising MRI contrast method, but it can be time-consuming. Common parallel imaging methods, like SENSE, can lead to reduced quality of CEST. Here, parallel blind compressed sensing (PBCS), combining blind compressed sensing (BCS) and parallel imaging, is evaluated for the acceleration of CEST in brain and breast.

METHODS

The CEST data were collected in phantoms, brain (N = 3), and breast (N = 2). Retrospective Cartesian undersampling was implemented and the reconstruction results of PBCS-CEST were compared with BCS-CEST and k-t sparse-SENSE CEST. The normalized RMSE and the high-frequency error norm were used for quantitative comparison.

RESULTS

In phantom and in vivo brain experiments, the acceleration factor of R = 10 (24 k-space lines) was achieved and in breast R = 5 (30 k-space lines), without compromising the quality of the PBCS-reconstructed magnetization transfer rate asymmetry maps and Z-spectra. Parallel BCS provides better reconstruction quality when compared with BCS, k-t sparse-SENSE, and SENSE methods using the same number of samples. Parallel BCS overperforms BCS, indicating that the inclusion of coil sensitivity improves the reconstruction of the CEST data.

CONCLUSION

The PBCS method accelerates CEST without compromising its quality. Compressed sensing in combination with parallel imaging can provide a valuable alternative to parallel imaging alone for accelerating CEST experiments.

MRI detection of bacterial brain abscesses and monitoring of antibiotic treatment using bacCEST

PURPOSE

To develop a new MRI method to detect and characterize brain abscesses using the CEST contrast inherently carried by bacterial cells, namely bacCEST.

METHODS

Bacteria S. aureus (ATCC #49775) and F98 and 9L glioma cells were injected stereotactically in the brains of F344 rats to form abscesses and tumors. The CEST signals of brain abscesses (n = 4) and tumors (n = 7) were acquired using 2 B1 values (i.e., 1 and 3 µT) and compared. The bacCEST signal of the brain abscesses in the rats (n = 3) receiving ampicillin (intraperitoneal injection 40 mg/kg twice daily) was acquired before, 4 and 10 days after the treatment.

RESULTS

The bacCEST signal of S. aureus was characterized in vitro as a strong and broad signal in the range of 1 to 4 ppm, with the maximum contrast occurring at 2.6 ppm. The CEST signal in S. aureus-induced brain abscesses was significantly higher than that of contralateral parenchyma (p = .003). Moreover, thanks to their different B1 independence, brain abscesses and tumors could be effectively differentiated (p = .005) using ΔCEST(2.6 ppm, 3 µT-1 µT), defined by the difference between the CEST signal (offset = 2.6 ppm) acquired using B1  = 3 µT and that of 1 µT. In treated rats, bacCEST MRI could detect the response of bacteria as early as 4 days after the antibiotic treatment (p = .035).

CONCLUSION

BacCEST MRI provides a new imaging method to detect, discriminate, and monitor bacterial infection in deep-seated organs. Because no contrast agent is needed, such an approach has a great translational potential for detecting and monitoring bacterial infection in deep-seated organs.

High-resolution and accelerated multi-parametric mapping with automated characterization of vessel disease using intravascular MRI

BACKGROUND

Atherosclerosis is prevalent in cardiovascular disease, but present imaging modalities have limited capabilities for characterizing lesion stage, progression and response to intervention. This study tests whether intravascular magnetic resonance imaging (IVMRI) measures of relaxation times (T1, T2) and proton density (PD) in a clinical 3 Tesla scanner could characterize vessel disease, and evaluates a practical strategy for accelerated quantification.

METHODS

IVMRI was performed in fresh human artery segments and swine vessels in vivo, using fast multi-parametric sequences, 1-2 mm diameter loopless antennae and 200-300 μm resolution. T1, T2 and PD data were used to train a machine learning classifier (support vector machine, SVM) to automatically classify normal vessel, and early or advanced disease, using histology for validation. Disease identification using the SVM was tested with receiver operating characteristic curves. To expedite acquisition of T1, T2 and PD data for vessel characterization, the linear algebraic method ('SLAM') was modified to accommodate the antenna's highly-nonuniform sensitivity, and used to provide average T1, T2 and PD measurements from compartments of normal and pathological tissue segmented from high-resolution images at acceleration factors of R ≤ 18-fold. The results were validated using compartment-average measures derived from the high-resolution scans.

RESULTS

The SVM accurately classified ~80% of samples into the three disease classes. The 'area-under-the-curve' was 0.96 for detecting disease in 248 samples, with T1 providing the best discrimination. SLAM T1, T2 and PD measures for R ≤ 10 were indistinguishable from the true means of segmented tissue compartments.

CONCLUSION

High-resolution IVMRI measures of T1, T2 and PD with a trained SVM can automatically classify normal, early and advanced atherosclerosis with high sensitivity and specificity. Replacing relaxometric MRI with SLAM yields good estimates of T1, T2 and PD an order-of-magnitude faster to facilitate IVMRI-based characterization of vessel disease.

Ultrafast compartmentalized relaxation time mapping with linear algebraic modeling

PURPOSE

To dramatically accelerate compartmental-average longitudinal (T₁ ) and transverse (T₂ ) relaxation measurements using the minimal-acquisition linear algebraic modeling (SLAM) method, and to validate it in phantoms and humans.

METHODS

Relaxation times were imaged at 3 Tesla in phantoms, in the abdomens of six volunteers, and in six brain tumor patients using standard inversion recovery and multi-spin-echo sequences. k-space was fully sampled to provide reference T₁ and T₂ measurements, and SLAM was performed using a limited set of phase encodes from central k-space. Anatomical compartments were segmented on scout images post-acquisition, and SLAM reconstruction was implemented using two algorithms. Compartment-average T₁ and T₂ measurements were determined retroactively from fully sampled data sets, and proactively from SLAM data sets at acceleration factors of up to 16. Values were compared with reference measurements. The compartment's localization properties were analyzed using the discrete spatial response function.

RESULTS

At 16-fold acceleration, compartment-average SLAM T₁ measurements agreed with the full k-space compartment-average results to within 0.0% ± 0.7%, 1.4% ± 3.4%, and 0.5% ± 2.9% for phantom, abdominal, and brain T₁ measurements, respectively. The corresponding T₂ measurements agreed within 0.2% ± 1.9%, 0.9% ± 7.9%, and 0.4% ± 5.8%, respectively.

CONCLUSION

SLAM can dramatically accelerate relaxation time measurements when compartmental or lesion-average values can suffice, or when standard relaxometry is precluded by scan-time limitations. Magn Reson Med 79:286-297, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Ultrafast compartmental relaxation time mapping with linear algebraic modeling

Image contrast afforded by tissue longitudinal (T₁) and transverse (T₂) relaxation times is central to the success of modern MRI. Here, a recently-proposed 'spectroscopy with linear algebraic modeling' (SLAM) method is adapted to dramatically accelerate relaxation time imaging at 3 Tesla in phantoms, the abdomens of six volunteers and in six brain tumor patients.. SLAM is validated by omitting up to 15/16^ths (94%) of the data acquired retroactively from inversion recovery and multi-echo spin-echo sequences, and proactively applied to accelerate abdominal and brain tumor T₁ and T₂ measurements by up to 16-fold in humans..

Chemical exchange saturation transfer (CEST) imaging with fast variably-accelerated sensitivity encoding (vSENSE)

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.

Accelerating chemical exchange saturation transfer (CEST) MRI by combining compressed sensing and sensitivity encoding techniques

PURPOSE

To evaluate the feasibility of accelerated chemical-exchange-saturation-transfer (CEST) imaging using a combination of compressed sensing (CS) and sensitivity encoding (SENSE) at 3 Tesla.

THEORY AND METHODS

Two healthy volunteers and six high-grade glioma patients were recruited. Raw CEST image k-space data were acquired (with varied radiofrequency saturation power levels for the healthy volunteer study), and a sequential CS and SENSE reconstruction (CS-SENSE) was assessed. The MTR_asym (3.5 ppm) signals were compared with varied CS-SENSE acceleration factors.

RESULTS

In the healthy volunteer study, a CS-SENSE acceleration factor of R = 2 × 2 (CS × SENSE) was achieved without compromising the reconstructed MTR_asym (3.5 ppm) image quality. The MTR_asym (3.5 ppm) signals obtained from the CS-SENSE reconstruction with R = 2 × 2 were well preserved compared with the reference image (R = 2 for only SENSE). In the glioma patient study, the MTR_asym (3.5 ppm) signals were significantly higher in the tumor region (Gd-enhancing tumor core) than in the normal-appearing white matter (P < 0.001). There was no significant MTR_asym (3.5 ppm) difference between the reference image and CS-SENSE-reconstructed image in the acceleration factor of R = 2 × 2.

CONCLUSION

Combining the SENSE technique with CS (R = 2 × 2) enables considerable acceleration of CEST image acquisition and potentially has a wide range of clinical applications. Magn Reson Med 77:779-786, 2017. © 2016 International Society for Magnetic Resonance in Medicine.