3D APT and NOE CEST-MRI of healthy volunteers and patients with non-enhancing glioma at 3 T

Advances in liquid biopsy and virtual biopsy for care of patients with glioma: a narrative review

INTRODUCTION

The World Health Organization's 2021 classification of central nervous system neoplasms incorporated molecular and genetic features for classifying gliomas. Classification of gliomas located in deep-seated structures became a clinical conundrum given the absence of crucial pathological and molecular data. Advances in noninvasive imaging modalities offered virtual biopsy as a novel solution to this problem by identifying surrogate radiomic signatures. Liquid biopsies of blood or cerebrospinal fluid provided another enormous opportunity for identifying genomic, metabolomic and proteomic signatures.

AREAS COVERED

We summarize and appraise the current state of evidence with regards to virtual biopsy and liquid biopsy in the care of patients with gliomas. PubMed, Embase and Google Scholar were searched on 7/30/2024 for relevant articles published after the year 2013 in the English language.

EXPERT OPINION

A large body of preclinical and preliminary clinical evidence suggests that virtual biopsy is possible with the combined use of multiple novel imaging modalities in conjunction with machine learning and radiomics. Likewise, liquid biopsy in conjunction with focused ultrasound may be a valuable tool to obtain proteomic and genomic data regarding glioma in a minimally invasive manner. These modalities will likely become an integral part of care for patients with glioma in the future.

Improving quantification accuracy of a nuclear Overhauser enhancement signal at -1.6 ppm at 4.7 T using a machine learning approach

Objective.A new nuclear Overhauser enhancement (NOE)-mediated saturation transfer MRI signal at -1.6 ppm, potentially from choline phospholipids and termed NOE(-1.6), has been reported in biological tissues at high magnetic fields. This signal shows promise for detecting brain tumors and strokes. However, its proximity to the water peak and low signal-to-noise ratio makes accurate quantification challenging, especially at low fields, due to the difficulty in separating it from direct water saturation and other confounding signals. This study proposes using a machine learning (ML) method to address this challenge.Approach.The ML model was trained on a partially synthetic chemical exchange saturation transfer dataset with a curriculum learning denoising approach. The accuracy of our method in quantifying NOE(-1.6) was validated using tissue-mimicking data from Bloch simulations providing ground truth, with subsequent application to an animal tumor model at 4.7 T. The predictions from the proposed ML method were compared with outcomes from traditional Lorentzian fit and ML models trained on other data types, including measured and fully simulated data.Main results.Our tissue-mimicking validation suggests that our method offers superior accuracy compared to all other methods. The results from animal experiments show that our method, despite variations in training data size or simulation models, produces predictions within a narrower range than the ML method trained on other data types.Significance.The ML method proposed in this work significantly enhances the accuracy and robustness of quantifying NOE(-1.6), thereby expanding the potential for applications of this novel molecular imaging mechanism in low-field environments.

Assessment of myelination development in neonatal rats using chemical exchange saturation transfer (CEST) 7-T MRI

Myelination is a crucial process in the nervous system. This study aimed to evaluate the progression of myelin sheath development in different brain regions of neonatal rats at distinct developmental stages using Chemical Exchange Saturation Transfer (CEST) 7-T MRI. Male SD rats of different ages (3 days, 1 week, 2 weeks, 3 weeks, 1 month, 2 months) were selected for the study. Advanced in vivo MRI experiments were conducted using a 7-T MRI scanner. Custom MatLab scripts were employed to generate MR images and process the data. Myelin staining was used to assess myelin distribution in various brain regions. Statistical analysis was performed using repeated measures multivariate analysis of variance (MANOVA) and Spearman's rank correlation. The progression of myelination was significantly different in different brain regions (F(5, 30) = 3.34, P < 0.05), with the corpus callosum showing an accelerated rate of myelination. Within the first month alone, there was an increase of 46.1% in myelination (t(35) = 2.29, P < 0.05). The hypothalamus and internal capsule exhibited a more gradual yet consistent increase in myelination over the two-month period, with increases of 47.1% (t(35) = 2.27, P < 0.05) and 39.8% (t(35) = 2.59, P < 0.05), respectively. A substantial positive correlation was found between the MRI-based and histological measurements of myelination (r = 0.31, P < 0.05). This study demonstrates the potential of CEST 7-T MRI as a non-invasive tool for assessing myelination progression and provides insights into the differential myelination rates across various brain regions during early development.

Nonlinear parameter estimation with physics-constrained spectral-spatial priors for highly accelerated chemical exchange saturation transfer MRI

Objective.To develop a nonlinear, model-based parameter estimation method directly from incomplete measurements ink - wspace for robust spectral analysis in highly accelerated chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI).Approach. A CEST-specific, separable nonlinear model, which describes spectral decomposition using multi-pool Lorentzian functions (conventional magnetization transfer (MT), direct saturation of water signals (DS), amide, amine, and nuclear Overhauser effect) derived from the steady-state Bloch McConnel equation, is incorporated into a measurement model in CEST MRI. Furthermore, signal drop in saturation transfer experiments is formulated by an additional, separable nonlinear spectral prior indicating that the symmetric z-spectra synthesized using conventional MT and DS always remain higher or equal to the whole z-spectra with all pools. Given the above considerations, linear and nonlinear parameters in the proposed method are estimated in an alternating fashion directly from highly incomplete measurements ink - wspace by solving a constrained optimization problem with the physics-constrained spectral priors while imposing additional sparsity priors on spatial parameter maps.Main results.Compared with conventional methods, the proposed method yields clearer delineation of tumor-specific CEST maps without apparent artifact and noise.Significance.We successfully demonstrated the feasibility of the proposed method for CEST MRI with highly incomplete measurements thus enabling high-resolution whole brain CEST MRI in clinically reasonable imaging time.

Reproducibility of 3D chemical exchange saturation transfer (CEST) contrasts in the healthy brain at 3T

Chemical exchange saturation transfer (CEST) imaging may provide novel contrast for the diagnosis, prognosis, and monitoring of the progression or treatment of neurological applications. However, the reproducibility of prominent CEST contrasts like amide CEST and nuclear Overhauser enhancement (NOE) CEST must be characterized in healthy brain gray matter (GM) and white matter (GM) prior to clinical implementation. The objective of this study was to characterize the reproducibility of four different CEST contrasts in the healthy human brain. Using a 3T MRI scanner, two 3D CEST scans were acquired in 12 healthy subjects (7 females, mean age (± SD) 26 ± 4 years) approximately 10 days apart. Scan-rescan reproducibility was measured for four contrasts: amine/amide concentration-independent detection (AACID), Amide*, and inverse magnetization transfer ratio (MTRRex) contrast for amide and NOE. Reproducibility was evaluated between- and within-subjects using coefficients of variation (CV) and the percent difference between measurements. AACID and NOE-MTRRex contrasts demonstrated the lowest within-subject CVs (0.8-1.2% and 1.6-2.0%, respectively), between-subject CVs (1.2-2.1% and 3.4-4.2%, respectively), and percent difference (1.2-1.4% and 2.2-2.8%, respectively) for both GM and WM. AACID and NOE-MTRRex contrasts demonstrated the highest reproducibility and represented stable measurements suitable for characterizing changes in brain tissue caused by pathological processes.

Quantitative separation of CEST effect by Rex-line-fit analysis of Z-spectra

The process of chemical exchange saturation transfer (CEST) is quantified by evaluating a Z-spectra, where CEST signal quantification and Z-spectra fitting have been widely used to distinguish the contributions from multiple origins. Based on the exchange-dependent relaxation rate in the rotating frame (Rex), this paper introduces an additional pathway to quantitative separation of CEST effect. The proposed Rex-line-fit method is solved by a multi-pool model and presents the advantage of only being dependent of the specific parameters (solute concentration, solute-water exchange rate, solute transverse relaxation, and irradiation power). Herein we show that both solute-water exchange rate and solute concentration monotonously vary with Rex for Amide, Guanidino, NOE and MT, which has the potential to assist in solving quantitative separation of CEST effect. Furthermore, we achieve Rex imaging of Amide, Guanidino, NOE and MT, which may provide direct insight into the dependency of measurable CEST effects on underlying parameters such as the exchange rate and solute concentration, as well as the solute transverse relaxation.

Improved postprocessing of dynamic glucose-enhanced CEST MRI for imaging brain metastases at 3 T

BACKGROUND

Dynamic glucose-enhanced (DGE) chemical exchange saturation transfer (CEST) has the potential to characterize glucose metabolism in brain metastases. Since the effect size of DGE CEST is small at 3 T (< 1%), measurements of signal-to-noise ratios are challenging. To improve DGE detection, we developed an acquisition pipeline and extended image analysis for DGE CEST on a hybrid 3-T positron emission tomography/magnetic resonance imaging system.

METHODS

This cross-sectional study was conducted after local ethical approval. Static Z-spectra (from -100 to 100 ppm) were acquired to compare the use of 1.2 versus 2 ppm to calculate static glucose-enhanced (glucoCEST) maps in 10 healthy volunteers before and after glucose infusion. Dynamic CEST images were acquired during glucose infusion. Image analysis was optimized using motion correction, dynamic B0 correction, and principal component analysis (PCA) to improve the detection of DGE CEST in the sagittal sinus, cerebrospinal fluid, and grey and white matter. The developed DGE CEST pipeline was applied to four patients diagnosed with brain metastases.

RESULTS

GlucoCEST was strongest in healthy tissues at 2 ppm. Correcting for motion, B0, and use of PCA locally improved DGE maps. A larger contrast between healthy tissues and enhancing regions in brain metastases was found when dynamic B0 correction and PCA denoising were applied.

CONCLUSION

We demonstrated the feasibility of DGE CEST with our developed acquisition and analysis pipeline at 3 T in patients with brain metastases. This work enables a direct comparison of DGE CEST to 18F-fluoro-deoxy-D-glucose positron emission tomography of glucose metabolism in patients with brain metastases.

RELEVANCE STATEMENT

Contrast between brain metastasis and healthy brain tissue in DGE CEST MR images is improved by including principle component analysis and dynamic magnetic field correction during postprocessing. This approach enables the detection of increased DGE CEST signal in brain metastasis, if present.

KEY POINTS

• Despite the low signal-to-noise ratio, dynamic glucose-enhanced CEST MRI is feasible at 3 T. • Principal component analyses and dynamic magnetic field correction improve DGE CEST MRI. • DGE CEST MRI does not consequently show changes in brain metastases compared to healthy brain tissue. • Increased DGE CEST MRI in brain metastases, if present, shows overlap with contrast enhancement on T1-weighted images.

Evaluation of contributors to amide proton transfer-weighted imaging and nuclear Overhauser enhancement-weighted imaging contrast in tumors at a high magnetic field

PURPOSE

The purpose is to evaluate the relative contribution from confounding factors (T1 weighting and magnetization transfer) to the CEST ratio (CESTR)-quantified amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) (-3.5) in tumors as well as whether the CESTR can reflect the distribution of the solute concentration (fs ).

METHODS

We first provided a signal model that shows the separate dependence of CESTR on these confounding factors and the clean CEST/NOE effects quantified by an apparent exchange-dependent relaxation (AREX) method. We then measured the change in these effects in the 9-L tumor model in rats, through which we calculated the relative contribution of each confounding factor. fs was also fitted, and its correlations with the CESTR and AREX were assessed to evaluate their capabilities to reflect fs .

RESULTS

The CESTR-quantified APT shows "positive" contrast in tumors, which arises primarily from R1w at low powers and both R1w and magnetization transfer at high powers. CESTR-quantified NOE (-3.5) shows no or weak contrast in tumors, which is due to the cancelation of R1w and NOE (-3.5), which have opposite contributions. CESTR-quantified APT has a stronger correlation with APT fs than AREX-quantified APT. CESTR-quantified NOE (-3.5) has a weaker correlation with NOE (-3.5) fs than AREX-quantified NOE (-3.5).

CONCLUSION

CESTR reflects a combined effect of T1 weighting and CEST/NOE. Both factors depend on fs , which contributes positively to the dependence of CESTR on fs in APT imaging and enhances its correlation with fs . In contrast, these factors have opposite contributions to its dependence on fs in NOE (-3.5) imaging, thereby weakening the correlation.

CEST2022 - mapping multi-pool CEST signal changes in an animal model of brain tumor with quasi-steady-state reconstruction-empowered CEST quantification

Chemical exchange saturated transfer (CEST) MRI has biomarker potential to assess tissue microenvironment in brain tumors. Multi-pool Lorentzian or spinlock models provides useful insights into the CEST contrast mechanism. However, T₁ contribution to the complex overlapping effects of brain tumors is difficult under the non-equilibrium state. Therefore, this study evaluated T₁ contributions on multi-pool parameters with quasi-steady-state (QUASS) algorithm reconstructed equilibrium data. MRI scans were performed in rat brain tumor models, including relaxation, diffusion, and CEST imaging. A pixel-wise seven-pool spinlock-model was employed to fit QUASS reconstructed CEST Z-spectra and evaluated the magnetization transfer (MT), amide, amine, guanidyl, and nuclear-overhauled effect (NOE) signals in tumor and normal tissues. In addition, T₁ was estimated from the spinlock-model fitting and compared with measured T₁. We observed tumor had a statistically significant increase in the amide signal (p < 0.001) and decreases in the MT and NOE signals (p < 0.001). On the other hand, the differences in amine and guanidyl between the tumor and contralateral normal regions were not statistically significant. The differences between measured and estimated T₁ values were 8% in the normal tissue and 4% in the tumor. Furthermore, the isolated MT signal strongly correlated with R₁ (r = 0.96, P < 0.001). In summary, we successfully unraveled multi-factorial effects in the CEST signal using spinlock-model fitting and QUASS method and demonstrated the effect of T₁ relaxation on MT and NOE.

In vivo reproducibility of 3D relayed NOE in the healthy human brain at 7 T

PURPOSE

Nuclear Overhauser effect (NOE) is based on dipolar cross-relaxation mechanism that enables the indirect detection of aliphatic protons via the water proton signal. This work focuses on determining the reproducibility of NOE magnetization transfer ratio (NOEMTR ) and isolated or relayed NOE (rNOE) contributions to the NOE MRI of the healthy human brain at 7 Tesla (T).

METHODS

We optimized theB 1 + $$ {\mathrm{B}}_1^{+} $$ amplitude and length of the saturation pulse by acquiring NOE images with differentB 1 + $$ {\mathrm{B}}_1^{+} $$ values with multiple saturation lengths. Repeated NOE MRI measurements were made on five healthy volunteers by using optimized saturation pulse parameters including correction of B0 andB 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities. To isolate the individual contributions from z-spectra, we have fit the NOE z-spectra using multiple Lorentzians and calculated the total contribution from each pool contributing to the overall NOEMTR contrast.

RESULTS

We found that a saturation amplitude of 0.72 μT and a length of 3 s provided the highest contrast. We found that the mean NOEMTR value in gray matter (GM) was 26%, and in white matter (WM) was 33.3% across the 3D slab of the brain. The mean rNOE contributions from GM and WM values were 8.9% and 9.6%, which were ∼10% of the corresponding total NOEMTR signal. The intersubject coefficient of variations (CoVs) of NOEMTR from GM and WM were 4.5% and 6.5%, respectively, whereas the CoVs of rNOE were 4.8% and 5.6%, respectively. The intrasubject CoVs of the NOEMTR range was 2.1%-4.2%, and rNOE range was 2.9%-10.5%.

CONCLUSION

This work has demonstrated an excellent reproducibility of both inter- and intrasubject NOEMTR and rNOE metrics in healthy human brains at 7 T.

Generalization of quasi-steady-state reconstruction to CEST MRI with two-tiered RF saturation and gradient-echo readout-Synergistic nuclear Overhauser enhancement contribution to brain tumor amide proton transfer-weighted MRI

PURPOSE

While amide proton transfer-weighted (APTw) MRI has been adopted in tumor imaging, there are concurrent APT, magnetization transfer, and nuclear Overhauser enhancement changes. Also, the APTw image is confounded by relaxation changes, particularly when the relaxation delay and saturation time are not sufficiently long. Our study aimed to extend a quasi-steady-state (QUASS) solution to determine the contribution of the multipool CEST signals to the observed tumor APTw contrast.

METHODS

Our study derived the QUASS solution for a multislice CEST-MRI sequence with an interleaved RF saturation and gradient-echo readout between signal averaging. Multiparametric MRI scans were obtained in rat brain tumor models, including T₁ , T₂ , diffusion, and CEST scans. Finally, we performed spinlock model-based multipool fitting to determine multiple concurrent CEST signal changes in the tumor.

RESULTS

The QUASS APTw MRI showed small but significant differences in normal and tumor tissues and their contrast from the acquired asymmetry calculation. The spinlock model-based fitting showed significant differences in semisolid magnetization transfer, amide, and nuclear Overhauser enhancement effects between the apparent and QUASS CEST MRI. In addition, we determined that the tumor APTw contrast is due to synergistic APT increase (+3.5 ppm) and NOE decrease (-3.5 ppm), with their relative contribution being about one third and two thirds under a moderate B₁ of 0.75 μT at 4.7 T.

CONCLUSION

Our study generalized QUASS analysis to gradient-echo image readout and quantified the underlying tumor CEST signal changes, providing an improved elucidation of the commonly used APTw MRI.

NOE-weighted imaging in tumors using low-duty-cycle 2π-CEST

PURPOSE

Nuclear Overhauser enhancement (NOE)-mediated CEST imaging at -3.5 ppm has shown clinical interest in diagnosing tumors. Multiple-pool Lorentzian fit has been used to quantify NOE, which, however, requires a long scan time. Asymmetric analysis of CEST signals could be a simple and fast method to quantify this NOE, but it has contamination from the amide proton transfer (APT) at 3.5 ppm. This work proposes a new method using an asymmetric analysis of a low-duty-cycle pulsed-CEST sequence with a flip angle of 360°, termed 2π-CEST, to reduce the contribution from APT.

METHODS

Simulations were used to evaluate the capability of the 2π-CEST to reduce APT. Experiments on animal tumor models were performed to show its advantages compared with the conventional asymmetric analysis. Samples of reconstituted phospholipids and proteins were used to evaluate the molecular origin of this NOE.

RESULTS

The 2π-CEST has reduced contribution from APT. In tumors where we show that the NOE is comparable to the APT effect, reducing the contamination from APT is crucial. The results show that the NOE signal obtained with 2π-CEST in tumor regions appears more homogeneous than that obtained with the conventional method. The phantom study showed that both phospholipids and proteins contribute to the NOE at -3.5 ppm.

CONCLUSION

The NOE at -3.5 ppm has a different contrast mechanism from APT and other CEST/NOE effects. The proposed 2π-CEST is more accurate than the conventional asymmetric analysis in detecting NOE, and requires much less scan time than the multiple-pool Lorentzian fit.

Chemical Exchange Saturation Transfer MRI: What Neuro-Oncology Clinicians Need To Know

Chemical exchange saturation transfer (CEST) is a relatively novel magnetic resonance imaging (MRI) technique with an image contrast designed for in vivo measurement of certain endogenous molecules with protons that are exchangeable with water protons, such as amide proton transfer commonly used for neuro-oncology applications. Recent technological advances have made it feasible to implement CEST on clinical grade scanners within practical acquisition times, creating new opportunities to integrate CEST in clinical workflow. In addition, the majority of CEST applications used in neuro-oncology are performed without the use gadolinium-based contrast agents which are another appealing feature of this technique. This review is written for clinicians involved in neuro-oncologic care (nonphysicists) as the target audience explaining what they need to know as CEST makes its way into practice. The purpose of this article is to (1) review the basic physics and technical principles of CEST MRI, and (2) review the practical applications of CEST in neuro-oncology.