In vivo imaging of glucose uptake and metabolism in tumors

Effect of inhaled oxygen level on dynamic glucose-enhanced MRI in mouse brain

PURPOSE

To investigate the effect of inhaled oxygen level on dynamic glucose enhanced (DGE) MRI in mouse brain tissue and CSF at 3 T.

METHODS

DGE data of brain tissue and CSF from mice under normoxia or hyperoxia were acquired in independent and interleaved experiments using on-resonance variable delay multi-pulse (onVDMP) MRI. A bolus of 0.15 mL filtered 50% D-glucose was injected through the tail vein over 1 min during DGE acquisition. MRS was acquired before and after DGE experiments to confirm the presence of D-glucose.

RESULTS

A significantly higher DGE effect under normoxia than under hyperoxia was observed in brain tissue (p = 0.0001 and p = 0.0002 for independent and interleaved experiments, respectively), but not in CSF (p > 0.3). This difference is attributed to the increased baseline MR tissue signal under hyperoxia induced by a shortened T1 and an increased BOLD effect. When switching from hyperoxia to normoxia without glucose injection, a signal change of ˜3.0% was found in brain tissue and a signal change of ˜1.5% was found in CSF.

CONCLUSIONS

DGE signal was significantly lower under hyperoxia than that under normoxia in brain tissue, but not in CSF. The reason is that DGE effect size of brain tissue is affected by the baseline signal, which could be influenced by T1 change and BOLD effect. Therefore, DGE experiments in which the oxygenation level is changed from baseline need to be interpreted carefully.

Quasi-steady-state (QUASS) reconstruction enhances T1 normalization in apparent exchange-dependent relaxation (AREX) analysis: A reevaluation of T1 correction in quantitative CEST MRI of rodent brain tumor models

PURPOSE

The apparent exchange-dependent relaxation (AREX) analysis has been proposed as an effective means to correct T1 contribution in CEST quantification. However, it has been recognized that AREX T1 correction is not straightforward if CEST scans are not performed under the equilibrium condition. Our study aimed to test if quasi-steady-state (QUASS) reconstruction could boost the accuracy of the AREX metric under common non-equilibrium scan conditions.

THEORY AND METHODS

Numerical simulation and in vivo scans were performed to assess the AREX metric accuracy. The CEST signal was simulated under different relaxation delays, RF saturation amplitudes, and durations. The AREX was evaluated as a function of the bulk water T1 and labile proton concentration using the multiple linear regression model. AREX MRI was also assessed in brain tumor rodent models, with both apparent CEST scans and QUASS reconstruction.

RESULTS

Simulation showed that the AREX calculation from apparent CEST scans, under non-equilibrium conditions, had significant dependence on labile proton fraction ratio, RF saturation time, and T1. In comparison, QUASS-boosted AREX depended on the labile proton fraction ratio without significant dependence on T1 and RF saturation time. Whereas the apparent (2.7 ± 0.8%) and QUASS MTR asymmetry (2.8 ± 0.8%) contrast between normal and tumor regions of interest (ROIs) were significant, the difference was small. In comparison, AREX contrast between normal and tumor ROIs calculated from the apparent CEST scan and QUASS reconstruction was 3.8 ± 1.1%/s and 4.4 ± 1.2%/s, respectively, statistically different from each other.

CONCLUSIONS

AREX analysis benefits from the QUASS-reconstructed equilibrium CEST effect for improved T1 correction and quantitative CEST analysis.

The Proton Resonance Enhancement for CEST imaging and Shift Exchange (PRECISE) family of RF pulse shapes for Chemical Exchange Saturation Transfer MRI

Purpose

To optimize a 100 msec pulse for producing CEST MRI contrast and evaluate in mice.

Methods

A gradient ascent algorithm was employed to generate a family of 100 point, 100 msec pulses for use in CEST pulse trains ('PRECISE'). Gradient ascent optimizations were performed for exchange rates (k ca ) = 500 s -1 , 1,500 s -1 , 2,500 s -1 , 3,500 s -1 and 4,500 s -1 and offsets (Δω) = 9.6, 7.8, 4.2 and 2.0 ppm. 7 PRECISE pulse shapes were tested on an 11.7 T scanner using a phantom containing three representative CEST agents with peak saturation B 1 = 4 μT. The pulse producing the most contrast in phantoms was then evaluated for CEST MRI pH mapping of the kidneys in healthy mice after iopamidol administration.

Results

The most promising pulse in terms of contrast performance across all three phantoms was the 9.6 ppm, 2500 s -1 optimized pulse with ∼2.7 x improvement over Gaussian and ∼1.3x's over Fermi pulses. This pulse also displayed a large improvement in contrast over the Gaussian pulse after administration of iopamidol in live mice.

Conclusion

A new 100 msec pulse was developed based on gradient ascent optimizations which produced better contrast compared to standard Gaussian and Fermi pulses in phantoms. This shape also showed a substantial improvement for CEST MRI pH mapping in live mice over the Gaussian shape and appears promising for a wide range of CEST applications.

Exploring neurodegenerative disorders using advanced magnetic resonance imaging of the glymphatic system

The glymphatic system, a macroscopic waste clearance system in the brain, is crucial for maintaining neural health. It facilitates the exchange of cerebrospinal and interstitial fluid, aiding the clearance of soluble proteins and metabolites and distributing essential nutrients and signaling molecules. Emerging evidence suggests a link between glymphatic dysfunction and the pathogenesis of neurodegenerative disorders, including Alzheimer's, Parkinson's, and Huntington's disease. These disorders are characterized by the accumulation and propagation of misfolded or mutant proteins, a process in which the glymphatic system is likely involved. Impaired glymphatic clearance could lead to the buildup of these toxic proteins, contributing to neurodegeneration. Understanding the glymphatic system's role in these disorders could provide insights into their pathophysiology and pave the way for new therapeutic strategies. Pharmacological enhancement of glymphatic clearance could reduce the burden of toxic proteins and slow disease progression. Neuroimaging techniques, particularly MRI-based methods, have emerged as promising tools for studying the glymphatic system in vivo. These techniques allow for the visualization of glymphatic flow, providing insights into its function under healthy and pathological conditions. This narrative review highlights current MRI-based methodologies, such as motion-sensitizing pulsed field gradient (PFG) based methods, as well as dynamic gadolinium-based and glucose-enhanced methodologies currently used in the study of neurodegenerative disorders.

Deep-learning-based super-resolution for accelerating chemical exchange saturation transfer MRI

Chemical exchange saturation transfer (CEST) MRI is a molecular imaging tool that provides physiological information about tissues, making it an invaluable tool for disease diagnosis and guided treatment. Its clinical application requires the acquisition of high-resolution images capable of accurately identifying subtle regional changes in vivo, while simultaneously maintaining a high level of spectral resolution. However, the acquisition of such high-resolution images is time consuming, presenting a challenge for practical implementation in clinical settings. Among several techniques that have been explored to reduce the acquisition time in MRI, deep-learning-based super-resolution (DLSR) is a promising approach to address this problem due to its adaptability to any acquisition sequence and hardware. However, its translation to CEST MRI has been hindered by the lack of the large CEST datasets required for network development. Thus, we aim to develop a DLSR method, named DLSR-CEST, to reduce the acquisition time for CEST MRI by reconstructing high-resolution images from fast low-resolution acquisitions. This is achieved by first pretraining the DLSR-CEST on human brain T1w and T2w images to initialize the weights of the network and then training the network on very small human and mouse brain CEST datasets to fine-tune the weights. Using the trained DLSR-CEST network, the reconstructed CEST source images exhibited improved spatial resolution in both peak signal-to-noise ratio and structural similarity index measure metrics at all downsampling factors (2-8). Moreover, amide CEST and relayed nuclear Overhauser effect maps extrapolated from the DLSR-CEST source images exhibited high spatial resolution and low normalized root mean square error, indicating a negligible loss in Z-spectrum information. Therefore, our DLSR-CEST demonstrated a robust reconstruction of high-resolution CEST source images from fast low-resolution acquisitions, thereby improving the spatial resolution and preserving most Z-spectrum information.

Unveiling the role of PYGB in pancreatic cancer: a novel diagnostic biomarker and gene therapy target

PURPOSE

Pancreatic cancer (PC) is a highly malignant tumor that poses a severe threat to human health. Brain glycogen phosphorylase (PYGB) breaks down glycogen and provides an energy source for tumor cells. Although PYGB has been reported in several tumors, its role in PC remains unclear.

METHODS

We constructed a risk diagnostic model of PC-related genes by WGCNA and LASSO regression and found PYGB, an essential gene in PC. Then, we explored the pro-carcinogenic role of PYGB in PC by in vivo and in vitro experiments.

RESULTS

We found that PYGB, SCL2A1, and SLC16A3 had a significant effect on the diagnosis and prognosis of PC, but PYGB had the most significant effect on the prognosis. Pan-cancer analysis showed that PYGB was highly expressed in most of the tumors but had the highest correlation with PC. In TCGA and GEO databases, we found that PYGB was highly expressed in PC tissues and correlated with PC's prognostic and pathological features. Through in vivo and in vitro experiments, we found that high expression of PYGB promoted the proliferation, invasion, and metastasis of PC cells. Through enrichment analysis, we found that PYGB is associated with several key cell biological processes and signaling pathways. In experiments, we validated that the MAPK/ERK pathway is involved in the pro-tumorigenic mechanism of PYGB in PC.

CONCLUSION

Our results suggest that PYGB promotes PC cell proliferation, invasion, and metastasis, leading to poor patient prognosis. PYGB gene may be a novel diagnostic biomarker and gene therapy target for PC.

CEST and nuclear Overhauser enhancement imaging with deep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility and reliability studies

PURPOSE

To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine the reproducibility and reliability of the estimates from the DeepEMR.

METHODS

A neural network was designed to predict a direct water saturation and MTC-dominated signal at a certain CEST frequency offset using a few high-frequency offset features in the Z-spectrum. The accuracy, scan-rescan reproducibility, and reliability of MTC, CEST, and relayed nuclear Overhauser enhancement (rNOE) signals estimated from the DeepEMR were evaluated on numerical phantoms and in heathy volunteers at 3 T. In addition, we applied the DeepEMR method to brain tumor patients and compared tissue contrast with other CEST calculation metrics.

RESULTS

The DeepEMR method demonstrated a high degree of accuracy in the estimation of reference MTC signals at ±3.5 ppm for APT and rNOE imaging, and computational efficiency (˜190-fold) compared with a conventional fitting approach. In addition, the DeepEMR method achieved high reproducibility and reliability (intraclass correlation coefficient = 0.97, intersubject coefficient of variation = 3.5%, and intrasubject coefficient of variation = 1.3%) of the estimation of MTC signals at ±3.5 ppm. In tumor patients, DeepEMR-based amide proton transfer images provided higher tumor contrast than a conventional MT ratio asymmetry image, particularly at higher B1 strengths (>1.5 μT), with a distinct delineation of the tumor core from normal tissue or peritumoral edema.

CONCLUSION

The DeepEMR approach is feasible for measuring clean APT and rNOE effects in longitudinal and cross-sectional studies with low scan-rescan variability.

Quantification of Cerebral Glucose Concentrations via Detection of the H1-α-Glucose Peak in 1 H MRS at 7 T

BACKGROUND

Sensitive detection and quantification of cerebral glucose is desired.

PURPOSE

To quantify cerebral glucose by detecting the H1-α-glucose peak at 5.23 ppm in 1 H magnetic resonance spectroscopy at 7 T.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-eight non-fasted healthy subjects (aged 20-28 years).

FIELD STRENGTH/SEQUENCE

Short echo time stimulated echo acquisition mode (short-TE STEAM) and semi-localized by adiabatic selective refocusing (semi-LASER) at 7 T.

ASSESSMENT

Single voxel spectra were obtained from the posterior cingulate cortex (27-mL) using a 32-channel head coil. The H1-α-glucose peak in the spectrum with retrospective removal of the residual water peak was fitted using LCModel with a glucose basis set of only the H1-α-glucose peak. Conventional spectral analysis was performed with a glucose basis set of a full spectral pattern of glucose, also. Fitting precision was evaluated with Cramér-Rao lower bounds (CRLBs). The repeatability of glucose quantification via the semi-LASER sequence was tested.

STATISTICAL TESTS

Paired or Welch's t-test were used for normally distributed values. A P value of <0.05 was considered significant. The repeatability of measures was analyzed using coefficient of variation (CV).

RESULTS

Removal of the residual water peak improved the flatness and stability of baselines around the H1-α-glucose peak and reduced CRLBs for fitting the H1-α-glucose peak. The semi-LASER sequence was superior to the short-TE STEAM in the higher signal-to-noise ratio of the H1-α-glucose peak (mean ± SD 7.9 ± 2.5, P < 0.001). The conventional analysis overfitted the H1-α-glucose peak. The individual CVs of glucose quantification by detecting the H1-α-glucose peak were smaller than the corresponding CRLBs.

DATA CONCLUSION

Cerebral glucose concentration is quantitated to be 1.07 mM by detecting the H1-α-glucose peak in the semi-LASER spectra. Despite requiring long scan times, detecting the H1-α-glucose peak allows true glucose quantification free from the influence of overlapping taurine and macromolecule signals.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY STAGE: 1.

Oxyhaemoglobin saturation NIR-IIb imaging for assessing cancer metabolism and predicting the response to immunotherapy

In vivo quantitative assessment of oxyhaemoglobin saturation (sO2) status in tumour-associated vessels could provide insights into cancer metabolism and behaviour. Here we develop a non-invasive in vivo sO2 imaging technique to visualize the sO2 levels of healthy and tumour tissue based on photoluminescence bioimaging in the near-infrared IIb (NIR-IIb; 1,500-1,700 nm) window. Real-time dynamic sO2 imaging with a high frame rate (33 Hz) reveals the cerebral arteries and veins through intact mouse scalp/skull, and this imaging is consistent with the haemodynamic analysis results. Utilizing our non-invasive sO2 imaging, the tumour-associated-vessel sO2 levels of various cancer models are evaluated. A positive correlation between the tumour-associated-vessel sO2 levels and the basal oxygen consumption rate of corresponding cancer cells at the early stages of tumorigenesis suggests that cancer cells modulate the tumour metabolic microenvironment. We also find that a positive therapeutic response to the checkpoint blockade cancer immunotherapy could lead to a dramatic decrease of the tumour-associated-vessel sO2 levels. Two-plex dynamic NIR-IIb imaging can be used to simultaneously observe tumour-vessel sO2 and PD-L1, allowing a more accurate prediction of immunotherapy response.

Boosting quantification accuracy of chemical exchange saturation transfer MRI with a spatial-spectral redundancy-based denoising method

Chemical exchange saturation transfer (CEST) is a versatile technique that enables noninvasive detections of endogenous metabolites present in low concentrations in living tissue. However, CEST imaging suffers from an inherently low signal-to-noise ratio (SNR) due to the decreased water signal caused by the transfer of saturated spins. This limitation challenges the accuracy and reliability of quantification in CEST imaging. In this study, a novel spatial-spectral denoising method, called BOOST (suBspace denoising with nOnlocal lOw-rank constraint and Spectral local-smooThness regularization), was proposed to enhance the SNR of CEST images and boost quantification accuracy. More precisely, our method initially decomposes the noisy CEST images into a low-dimensional subspace by leveraging the global spectral low-rank prior. Subsequently, a spatial nonlocal self-similarity prior is applied to the subspace-based images. Simultaneously, the spectral local-smoothness property of Z-spectra is incorporated by imposing a weighted spectral total variation constraint. The efficiency and robustness of BOOST were validated in various scenarios, including numerical simulations and preclinical and clinical conditions, spanning magnetic field strengths from 3.0 to 11.7 T. The results demonstrated that BOOST outperforms state-of-the-art algorithms in terms of noise elimination. As a cost-effective and widely available post-processing method, BOOST can be easily integrated into existing CEST protocols, consequently promoting accuracy and reliability in detecting subtle CEST effects.

Imaging of brain clearance pathways via MRI assessment of the glymphatic system

Glymphatic clearance dysfunction may play an important role in a variety of neurodegenerative diseases and the progression of ageing. However, in vivo imaging of the glymphatic system is challenging. In this study, we describe an MRI method based on chemical exchange saturation transfer (CEST) of the Angiopep-2 probe to visualize the clearance function of the glymphatic system. We injected rats with Angiopep-2 via the tail vein and performed in vivo MRI at 7 T to track differences in Angiopep-2 signal changes; we then applied the same principles in a bilateral deep cervical lymph node ligation rat model and in ageing rats. We demonstrated the feasibility of Angiopep-2 CEST for visualizing the clearance function of the glymphatic system. Finally, a pathological assessment was performed. Within the model group, the deep cervical lymph node ligation group and the ageing group showed higher CEST signal than the control group. We conclude that this new MRI method can visualize clearance in the glymphatic system.

Research progress of metabolomics in cervical cancer

INTRODUCTION

Cervical cancer threatens women's health seriously. In recent years, the incidence of cervical cancer is on the rise, and the age of onset tends to be younger. Prevention, early diagnosis and specific treatment have become the main means to change the prognosis of cervical cancer patients. Metabolomics research can directly reflect the changes of biochemical processes and microenvironment in the body, which can provide a comprehensive understanding of the changes of metabolites in the process of disease occurrence and development, and provide new ways for the prevention and diagnosis of diseases.

OBJECTIVES

The aim of this study is to review the metabolic changes in cervical cancer and the application of metabolomics in the diagnosis and treatment.

METHODS

PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2022.

RESULTS

With the emergence of metabolomics, metabolic regulation and cancer research are further becoming a focus of attention. By directly reflecting the changes in the microenvironment of the body, metabolomics research can provide a comprehensive understanding of the patterns of metabolites in the occurrence and development of diseases, thus providing new ideas for disease prevention and diagnosis.

CONCLUSION

With the continuous, in-depth research on metabolomics research technology, it will bring more benefits in the screening, diagnosis and treatment of cervical cancer with its advantages of holistic and dynamic nature.

Metabolic brain imaging with glucosamine CEST MRI: in vivo characterization and first insights

The utility of chemical exchange saturation transfer (CEST) MRI for monitoring the uptake of glucosamine (GlcN), a safe dietary supplement, has been previously demonstrated in detecting breast cancer in both murine and human subjects. Here, we studied and characterized the detectability of GlcN uptake and metabolism in the brain. Following intravenous GlcN administration in mice, CEST brain signals calculated by magnetization transfer ratio asymmetry (MTRasym) analysis, were significantly elevated, mainly in the cortex, hippocampus, and thalamus. The in vivo contrast remained stable during 40 min of examination, which can be attributed to GlcN uptake and its metabolic products accumulation as confirmed using 13C NMR spectroscopic studies of brain extracts. A Lorentzian multi-pool fitting analysis revealed an increase in the hydroxyl, amide, and relayed nuclear Overhauser effect (rNOE) signal components after GlcN treatment. With its ability to cross the blood-brain barrier (BBB), the GlcN CEST technique has the potential to serve as a metabolic biomarker for the diagnosis and monitoring various brain disorders.

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.

Development of a synthetic biosensor for chemical exchange MRI utilizing in silico optimized peptides

Chemical exchange saturation transfer (CEST) MRI has been identified as a novel alternative to classical diagnostic imaging. Over the last several decades, many studies have been conducted to determine possible CEST agents, such as endogenously expressed compounds or proteins, that can be utilized to produce contrast with minimally invasive procedures and reduced or non-existent levels of toxicity. In recent years there has been an increased interest in the generation of genetically engineered CEST contrast agents, typically based on existing proteins with CEST contrast or modified to produce CEST contrast. We have developed an in silico method for the evolution of peptide sequences to optimize CEST contrast and showed that these peptides could be combined to create de novo biosensors for CEST MRI. A single protein, superCESTide, was designed to be 198 amino acids. SuperCESTide was expressed in E. coli and purified with size exclusion chromatography. The magnetic transfer ratio asymmetry generated by superCESTide was comparable to levels seen in previous CEST reporters, such as protamine sulfate (salmon protamine) and human protamine. These data show that novel peptides with sequences optimized in silico for CEST contrast that utilize a more comprehensive range of amino acids can still produce contrast when assembled into protein units expressed in complex living environments.

Learned spatiotemporal correlation priors for CEST image denoising using incorporated global-spectral convolution neural network

PURPOSE

To develop a deep learning-based method, dubbed Denoising CEST Network (DECENT), to fully exploit the spatiotemporal correlation prior to CEST image denoising.

METHODS

DECENT is composed of two parallel pathways with different convolution kernel sizes aiming to extract the global and spectral features embedded in CEST images. Each pathway consists of a modified U-Net with residual Encoder-Decoder network and 3D convolution. Fusion pathway with 1 × 1 × 1 convolution kernel is utilized to concatenate two parallel pathways, and the output of DECENT is noise-reduced CEST images. The performance of DECENT was validated in numerical simulations, egg white phantom experiments, and ischemic mouse brain and human skeletal muscle experiments in comparison with existing state-of-the-art denoising methods.

RESULTS

Rician noise was added to CEST images to mimic a low SNR situation for numerical simulation, egg white phantom experiment, and mouse brain experiments, while human skeletal muscle experiments were of inherently low SNR. From the denoising results evaluated by peak SNR (PSNR) and structural similarity index (SSIM), the proposed deep learning-based denoising method (DECENT) can achieve better performance compared to existing CEST denoising methods such as NLmCED, MLSVD, and BM4D, avoiding complicated parameter tuning or time-consuming iterative processes.

CONCLUSIONS

DECENT can well exploit the prior spatiotemporal correlation knowledge of CEST images and restore the noise-free images from their noisy observations, outperforming state-of-the-art denoising methods.

Noninvasive Glucose Sensing in Dielectrically Equivalent Multilayer Skin Phantoms

The interstitial fluid of the skin contains glucose levels comparable to those of blood. Noninvasive glucose sensing by microwaves has great potential to relieve diabetics from the burden of daily blood sampling, but improving the selectivity of this method remains a challenge. This study reports a dielectrically equivalent multilayer skin phantom and provides insight into the criteria for noninvasive glucose sensing by conducting dielectric analysis. The skin phantom was a hydrogel composed of gelatin, glucose, sodium chloride, and water covered by paraffin-impregnated paper. Investigations conducted on a wide range of component concentrations revealed characteristic relative permittivity and dielectric loss determined by the amount of electrolyte and solution that was independent of the amount of glucose. Since the microwave response due to glucose tends to be buried in noise, we developed a flowchart that first identifies the amounts of electrolytes and proteins, which are the major components other than glucose, and then quantifies the remaining glucose content. This noninvasive glucose sensing method would not be limited to the medical healthcare field; it could potentially be used in food manufacturing processes, livestock farming, and plant cultivation management.

Metabolic Imaging as a Tool to Characterize Chemoresistance and Guide Therapy in Triple-Negative Breast Cancer (TNBC)

After an initial response to chemotherapy, tumor relapse is frequent. This event is reflective of both the spatiotemporal heterogeneities of the tumor microenvironment as well as the evolutionary propensity of cancer cell populations to adapt to variable conditions. Because the cause of this adaptation could be genetic or epigenetic, studying phenotypic properties such as tumor metabolism is useful as it reflects molecular, cellular, and tissue-level dynamics. In triple-negative breast cancer (TNBC), the characteristic metabolic phenotype is a highly fermentative state. However, during treatment, the spatial and temporal dynamics of the metabolic landscape are highly unstable, with surviving populations taking on a variety of metabolic states. Thus, longitudinally imaging tumor metabolism provides a promising approach to inform therapeutic strategies, and to monitor treatment responses to understand and mitigate recurrence. Here we summarize some examples of the metabolic plasticity reported in TNBC following chemotherapy and review the current metabolic imaging techniques available in monitoring chemotherapy responses clinically and preclinically. The ensemble of imaging technologies we describe has distinct attributes that make them uniquely suited for a particular length scale, biological model, and/or features that can be captured. We focus on TNBC to highlight the potential of each of these technological advances in understanding evolution-based therapeutic resistance.

Direct Patlak Reconstruction of [68Ga]Ga-PSMA PET for the Evaluation of Primary Prostate Cancer Prior Total Prostatectomy: Results of a Pilot Study

To investigate the use of kinetic parameters derived from direct Patlak reconstructions of [68Ga]Ga-PSMA-11 positron emission tomography/computed tomography (PET/CT) to predict the histological grade of malignancy of the primary tumor of patients with prostate cancer (PCa). Thirteen patients (mean age 66 ± 10 years) with a primary, therapy-naïve PCa (median PSA 9.3 [range: 6.3-130 µg/L]) prior radical prostatectomy, were recruited in this exploratory prospective study. A dynamic whole-body [68Ga]Ga-PSMA-11 PET/CT scan was performed for all patients. Measured quantification parameters included Patlak slope (Ki: absolute rate of tracer consumption) and Patlak intercept (Vb: degree of tracer perfusion in the tumor). Additionally, the mean and maximum standardized uptake values (SUVmean and SUVmax) of the tumor were determined from a static PET 60 min post tracer injection. In every patient, initial PSA (iPSA) values that were also the PSA level at the time of the examination and final histology results with Gleason score (GS) grading were correlated with the quantitative readouts. Collectively, 20 individual malignant prostate lesions were ascertained and histologically graded for GS with ISUP classification. Six lesions were classified as ISUP 5, two as ISUP 4, eight as ISUP 3, and four as ISUP 2. In both static and dynamic PET/CT imaging, the prostate lesions could be visually distinguished from the background. The average values of the SUVmean, slope, and intercept of the background were 2.4 (±0.4), 0.015 1/min (±0.006), and 52% (±12), respectively. These were significantly lower than the corresponding parameters extracted from the prostate lesions (all p < 0.01). No significant differences were found between these values and the various GS and ISUP (all p > 0.05). Spearman correlation coefficient analysis demonstrated a strong correlation between static and dynamic PET/CT parameters (all r ≥ 0.70, p < 0.01). Both GS and ISUP grading revealed only weak correlations with the mean and maximum SUV and tumor-to-background ratio derived from static images and dynamic Patlak slope. The iPSA demonstrated no significant correlation with GS and ISUP grading or with dynamic and static PET parameter values. In this cohort of mainly high-risk PCa, no significant correlation between [68Ga]Ga-PSMA-11 perfusion and consumption and the aggressiveness of the primary tumor was observed. This suggests that the association between SUV values and GS may be more distinctive when distinguishing clinically relevant from clinically non-relevant PCa.

Biogenic Imaging Contrast Agents

Imaging contrast agents are widely investigated in preclinical and clinical studies, among which biogenic imaging contrast agents (BICAs) are developing rapidly and playing an increasingly important role in biomedical research ranging from subcellular level to individual level. The unique properties of BICAs, including expression by cells as reporters and specific genetic modification, facilitate various in vitro and in vivo studies, such as quantification of gene expression, observation of protein interactions, visualization of cellular proliferation, monitoring of metabolism, and detection of dysfunctions. Furthermore, in human body, BICAs are remarkably helpful for disease diagnosis when the dysregulation of these agents occurs and can be detected through imaging techniques. There are various BICAs matched with a set of imaging techniques, including fluorescent proteins for fluorescence imaging, gas vesicles for ultrasound imaging, and ferritin for magnetic resonance imaging. In addition, bimodal and multimodal imaging can be realized through combining the functions of different BICAs, which helps overcome the limitations of monomodal imaging. In this review, the focus is on the properties, mechanisms, applications, and future directions of BICAs.

Glucose exchange parameters in a subset of physiological conditions

The chemical exchange of labile protons of the hydroxyl groups can be exploited in a variety of magnetic resonance experiments to gain information about the groups and their physicochemical environment. The exchangeable -OH protons provide important contributions to the T2 of water signals thus contributing to the T2-weighted contrast of MRI images. This exchange can be exploited more specifically and sensitively in chemical exchange saturation transfer (CEST) or longitudinal rotating frame relaxation (T1,ρ) experiments. Since glucose is omnipresent in living organisms, it may be seen as a rather universal probe. Even though the potential was first recognized many years ago, practical use has remained scarce due to numerous challenges. The major limitation is the rather low glucose concentration in most tissues. The other obstacles are related to multiple dependencies of the exchange parameters, such as temperature, pH, and concentration of various ions that are not known in sufficient detail for glucose. Thus, we embarked on evaluating the exchange parameters of a model that included every relevant chemical site for all -OH protons in both dominant enantiomers of glucose. We have (1) obtained conventional one-dimensional proton NMR spectra of glucose solutions in suitable temperature ranges, (2) we have iterated through several exchange models with various degrees of freedom determined by the number of distinguishable -OH proton sites and compared their performance, (3) we extrapolated the parameters of the best model of physiological temperature and (4) we demonstrated the use of the parameters in virtual experiments. As the main results, (1) we have obtained the temperature dependence of exchange parameters with reliable confidence intervals in three different pH values, with two of them reaching physiological temperature, and (2) we show how the parameters can be used in virtual experiments, helping to develop new applications for glucose as an NMR/MRI probe.

Detection of tissue pH with quantitative chemical exchange saturation transfer magnetic resonance imaging

Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a novel means for sensitive detection of dilute labile protons and chemical exchange rates. By sensitizing to pH-dependent chemical exchange, CEST MRI has shown promising results in monitoring tissue statuses such as pH changes in disorders like acute stroke, tumor, and acute kidney injury. This article briefly reviews the basic principles for CEST imaging and quantitative measures, from the simplistic asymmetry analysis to multipool Lorentzian decoupling and quasi-steady-state reconstruction. In particular, the advantages and limitations of commonly used quantitative approaches for CEST applications are discussed.

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.

Tissue response curve-shape analysis of dynamic glucose-enhanced and dynamic contrast-enhanced magnetic resonance imaging in patients with brain tumor

Dynamic glucose-enhanced (DGE) MRI is used to study the signal intensity time course (tissue response curve) after D-glucose injection. D-glucose has potential as a biodegradable alternative or complement to gadolinium-based contrast agents, with DGE being comparable with dynamic contrast-enhanced (DCE) MRI. However, the tissue uptake kinetics as well as the detection methods of DGE differ from DCE MRI, and it is relevant to compare these techniques in terms of spatiotemporal enhancement patterns. This study aims to develop a DGE analysis method based on tissue response curve shapes, and to investigate whether DGE MRI provides similar or complementary information to DCE MRI. Eleven patients with suspected gliomas were studied. Tissue response curves were measured for DGE and DCE MRI at 7 T and the area under the curve (AUC) was assessed. Seven types of response curve shapes were postulated and subsequently identified by deep learning to create color-coded "curve maps" showing the spatial distribution of different curve types. DGE AUC values were significantly higher in lesions than in normal tissue (p < 0.007). Furthermore, the distribution of curve types differed between lesions and normal tissue for both DGE and DCE. The DGE and DCE response curves in a 6-min postinjection time interval were classified as the same curve type in 20% of the lesion voxels, which increased to 29% when a 12-min DGE time interval was considered. While both DGE and DCE tissue response curve-shape analysis enabled differentiation of lesions from normal brain tissue in humans, their enhancements were neither temporally identical nor confined entirely to the same regions. Curve maps can provide accessible and intuitive information about the shape of DGE response curves, which is expected to be useful in the continued work towards the interpretation of DGE uptake curves in terms of D-glucose delivery, transport, and metabolism.

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.

A snapshot of the vast array of diamagnetic CEST MRI contrast agents

Since the inception of CEST MRI in the 1990s, a number of compounds have been identified as suitable for generating contrast, including paramagnetic lanthanide complexes, hyperpolarized atom cages and, most interesting, diamagnetic compounds. In the past two decades, there has been a major emphasis in this field on the identification and application of diamagnetic compounds that have suitable biosafety profiles for usage in medical applications. Even in the past five years there has been a tremendous growth in their numbers, with more and more emphasis being placed on finding those that can be ultimately used for patient studies on clinical 3 T scanners. At this point, a number of endogenous compounds present in tissue have been identified, and also natural and synthetic organic compounds that can be administered to highlight pathology via CEST imaging. Here we will provide a very extensive snapshot of the types of diamagnetic compound that can generate CEST MRI contrast, together with guidance on their utility on typical preclinical and clinical scanners and a review of the applications that might benefit the most from this new technology.

Imaging of sugar-based contrast agents using their hydroxyl proton exchange properties

The ability of CEST MRI to detect the presence of millimolar concentrations of non-metallic contrast agents has made it possible to study, non-invasively, important biological molecules such as proteins and sugars, as well as drugs already approved for clinical use. Here, we review efforts to use sugar and sugar polymers as exogenous contrast agents, which is possible based on the exchange of their hydroxyl protons with water protons. While this capability has raised early enthusiasm, for instance about the possibility of imaging D-glucose metabolism with MRI in a way analogous to PET, experience over the past decade has shown that this is not trivial. On the other hand, many studies have confirmed the possibility of imaging a large variety of sugar analogues, each with potentially interesting applications to assess tissue physiology. Some promising applications are the study of (i) sugar delivery and transport to assess blood-brain barrier integrity and (ii) sugar uptake by cells for their characterization (e.g., cancer versus healthy), as well as (iii) clearance of sugars to assess tissue drainage-for instance, through the glymphatic system. To judge these opportunities and their challenges, especially in the clinic, it is necessary to understand the technical aspects of detecting the presence of rapidly exchanging protons through the water signal in MRI, especially as a function of magnetic field strength. We expect that novel approaches in terms of MRI detection (both saturation transfer and relaxation based), MRI data analysis, and sugar design will push this young field forward in the next decade.

The relayed nuclear Overhauser effect in magnetization transfer and chemical exchange saturation transfer MRI

Magnetic resonance (MR) is a powerful technique for noninvasively probing molecular species in vivo but suffers from low signal sensitivity. Saturation transfer (ST) MRI approaches, including chemical exchange saturation transfer (CEST) and conventional magnetization transfer contrast (MTC), allow imaging of low-concentration molecular components with enhanced sensitivity using indirect detection via the abundant water proton pool. Several recent studies have shown the utility of chemical exchange relayed nuclear Overhauser effect (rNOE) contrast originating from nonexchangeable carbon-bound protons in mobile macromolecules in solution. In this review, we describe the mechanisms leading to the occurrence of rNOE-based signals in the water saturation spectrum (Z-spectrum), including those from mobile and immobile molecular sources and from molecular binding. While it is becoming clear that MTC is mainly an rNOE-based signal, we continue to use the classical MTC nomenclature to separate it from the rNOE signals of mobile macromolecules, which we will refer to as rNOEs. Some emerging applications of the use of rNOEs for probing macromolecular solution components such as proteins and carbohydrates in vivo or studying the binding of small substrates are discussed.

Radiofrequency labeling strategies in chemical exchange saturation transfer MRI

Chemical exchange saturation transfer (CEST) MRI has generated great interest for molecular imaging applications because it can image low-concentration solute molecules in vivo with enhanced sensitivity. CEST effects are detected indirectly through a reduction in the bulk water signal after repeated perturbation of the solute proton magnetization using one or more radiofrequency (RF) irradiation pulses. The parameters used for these RF pulses-frequency offset, duration, shape, strength, phase, and interpulse spacing-determine molecular specificity and detection sensitivity, thus their judicious selection is critical for successful CEST MRI scans. This review article describes the effects of applying RF pulses on spin systems and compares conventional saturation-based RF labeling with more recent excitation-based approaches that provide spectral editing capabilities for selectively detecting molecules of interest and obtaining maximal contrast.

Label-Free Chemically and Molecularly Selective Magnetic Resonance Imaging

Biomedical imaging, especially molecular imaging, has been a driving force in scientific discovery, technological innovation, and precision medicine in the past two decades. While substantial advances and discoveries in chemical biology have been made to develop molecular imaging probes and tracers, translating these exogenous agents to clinical application in precision medicine is a major challenge. Among the clinically accepted imaging modalities, magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) exemplify the most effective and robust biomedical imaging tools. Both MRI and MRS enable a broad range of chemical, biological and clinical applications from determining molecular structures in biochemical analysis to imaging diagnosis and characterization of many diseases and image-guided interventions. Using chemical, biological, and nuclear magnetic resonance properties of specific endogenous metabolites and native MRI contrast-enhancing biomolecules, label-free molecular and cellular imaging with MRI can be achieved in biomedical research and clinical management of patients with various diseases. This review article outlines the chemical and biological bases of several label-free chemically and molecularly selective MRI and MRS methods that have been applied in imaging biomarker discovery, preclinical investigation, and image-guided clinical management. Examples are provided to demonstrate strategies for using endogenous probes to report the molecular, metabolic, physiological, and functional events and processes in living systems, including patients. Future perspectives on label-free molecular MRI and its challenges as well as potential solutions, including the use of rational design and engineered approaches to develop chemical and biological imaging probes to facilitate or combine with label-free molecular MRI, are discussed.

A numerical human brain phantom for dynamic glucose-enhanced (DGE) MRI: On the influence of head motion at 3T

PURPOSE

Dynamic glucose-enhanced (DGE) MRI relates to a group of exchange-based MRI techniques where the uptake of glucose analogues is studied dynamically. However, motion artifacts can be mistaken for true DGE effects, while motion correction may alter true signal effects. The aim was to design a numerical human brain phantom to simulate a realistic DGE MRI protocol at 3T that can be used to assess the influence of head movement on the signal before and after retrospective motion correction.

METHODS

MPRAGE data from a tumor patient were used to simulate dynamic Z-spectra under the influence of motion. The DGE responses for different tissue types were simulated, creating a ground truth. Rigid head movement patterns were applied as well as physiological dilatation and pulsation of the lateral ventricles and head-motion-induced B0 -changes in presence of first-order shimming. The effect of retrospective motion correction was evaluated.

RESULTS

Motion artifacts similar to those previously reported for in vivo DGE data could be reproduced. Head movement of 1 mm translation and 1.5 degrees rotation led to a pseudo-DGE effect on the order of 1% signal change. B0 effects due to head motion altered DGE changes due to a shift in the water saturation spectrum. Pseudo DGE effects were partly reduced or enhanced by rigid motion correction depending on tissue location.

CONCLUSION

DGE MRI studies can be corrupted by motion artifacts. Designing post-processing methods using retrospective motion correction including B0 correction will be crucial for clinical implementation. The proposed phantom should be useful for evaluation and optimization of such techniques.

Acyl Hydrazides and Acyl Hydrazones as High-Performance Chemical Exchange Saturation Transfer MRI Contrast Agents

Chemical exchange saturation transfer (CEST) MRI is a versatile molecular imaging approach that holds great promise for clinical translation. A number of compounds have been identified as suitable for performing CEST MRI, including paramagnetic CEST (paraCEST) agents and diamagnetic CEST (diaCEST) agents. DiaCEST agents are very attractive because of their excellent biocompatibility and potential for biodegradation, such as glucose, glycogen, glutamate, creatine, nucleic acids, et al. However, the sensitivity of most diaCEST agents is limited because of small chemical shifts (1.0-4.0 ppm) from water. To expand the catalog of diaCEST agents with larger chemical shifts, herein, we have systematically investigated the CEST properties of acyl hydrazides with different substitutions, including aromatic and aliphatic substituents. We have tuned the labile proton chemical shifts from 2.8-5.0 ppm from water while exchange rates varied from ~680 to 2340 s^-1 at pH 7.2, which allows strong CEST contrast on scanners down to B₀ = 3 T. One acyl hydrazide, adipic acid dihydrazide (ADH), was tested on a mouse model of breast cancer and showed nice contrast in the tumor region. We also prepared a derivative, acyl hydrazone, which showed the furthest shifted labile proton (6.4 ppm from water) and excellent contrast properties. Overall, our study expands the catalog of diaCEST agents and their application in cancer diagnosis.

A Genetic Programming Approach to Engineering MRI Reporter Genes

Here we develop a mechanism of protein optimization using a computational approach known as "genetic programming". We developed an algorithm called Protein Optimization Engineering Tool (POET). Starting from a small library of literature values, the use of this tool allowed us to develop proteins that produce four times more MRI contrast than what was previously state-of-the-art. Interestingly, many of the peptides produced using POET were dramatically different with respect to their sequence and chemical environment than existing CEST producing peptides, and challenge prior understandings of how those peptides function. While existing algorithms for protein engineering rely on divergent evolution, POET relies on convergent evolution and consequently allows discovery of peptides with completely different sequences that perform the same function with as good or even better efficiency. Thus, this novel approach can be expanded beyond developing imaging agents and can be used widely in protein engineering.

Metabolic imaging with deuterium labeled substrates

Deuterium metabolic imaging (DMI) is an emerging clinically-applicable technique for the non-invasive investigation of tissue metabolism. The generally short T1 values of 2H-labeled metabolites in vivo can compensate for the relatively low sensitivity of detection by allowing rapid signal acquisition in the absence of significant signal saturation. Studies with deuterated substrates, including [6,6'-2H2]glucose, [2H3]acetate, [2H9]choline and [2,3-2H2]fumarate have demonstrated the considerable potential of DMI for imaging tissue metabolism and cell death in vivo. The technique is evaluated here in comparison with established metabolic imaging techniques, including PET measurements of 2-deoxy-2-[18F]fluoro-d-glucose (FDG) uptake and 13C MR imaging of the metabolism of hyperpolarized 13C-labeled substrates.

calf - Software for CEST Analysis with Lorentzian Fitting

Analysis of chemical exchange saturation transfer (CEST) MRI data requires sophisticated methods to obtain reliable results about metabolites in the tissue under study. CEST generates z-spectra with multiple components, each originating from individual molecular groups. The individual lines with Lorentzian line shape are mostly overlapping and disturbed by various effects. We present an elaborate method based on an adaptive nonlinear least squares algorithm that provides robust quantification of z-spectra and incorporates prior knowledge in the fitting process. To disseminate CEST to the research community, we developed software as part of this study that runs on the Microsoft Windows operating system and will be made freely available to the community. Special attention has been paid to establish a low entrance threshold and high usability, so that even less experienced users can successfully analyze CEST data.

Development of a Synthetic Biosensor for Chemical Exchange MRI Utilizing In Silico Optimized Peptides

Chemical Exchange Saturation Transfer (CEST) magnetic resonance imaging (MRI) has been identified as a novel alternative to classical diagnostic imaging. Over the last several decades, many studies have been conducted to determine possible CEST agents, such as endogenously expressed compounds or proteins, that can be utilized to produce contrast with minimally invasive procedures and reduced or non-existent levels of toxicity. In recent years there has been an increased interest in the generation of genetically engineered CEST contrast agents, typically based on existing proteins with CEST contrast or modified to produce CEST contrast. We have developed an in-silico method for the evolution of peptide sequences to optimize CEST contrast and showed that these peptides could be combined to create de novo biosensors for CEST MRI. A single protein, superCESTide 2.0, was designed to be 198 amino acids. SuperCESTide 2.0 was expressed in E. coli and purified with size-exclusion chromatography. The magnetic transfer ratio asymmetry (MTR asym ) generated by superCESTide 2.0 was comparable to levels seen in previous CEST reporters, such as protamine sulfate (salmon protamine, SP), Poly-L-Lysine (PLL), and human protamine (hPRM1). This data shows that novel peptides with sequences optimized in silico for CEST contrast that utilizes a more comprehensive range of amino acids can still produce contrast when assembled into protein units expressed in complex living environments.

Demonstration of pH imaging in acute stroke with endogenous ratiometric chemical exchange saturation transfer magnetic resonance imaging at 2 ppm

pH change is often considered a hallmark of metabolic disruption in diseases such as ischemic stroke and cancer. Chemical exchange saturation transfer (CEST) MRI, particularly amide proton transfer (APT), has emerged as a noninvasive pH imaging approach. However, there are changes in multipool CEST effects besides APT MRI. Our study investigated radiofrequency (RF) amplitude-based ratiometric CEST pH imaging in acute stroke. Briefly, adult male Wistar rats underwent CEST MRI under two RF saturation (B₁ ) levels of 0.75 and 1.5 μT following middle cerebral artery occlusion. Magnetization transfer (MT), direct water saturation, CEST at 2 ppm (CEST@2 ppm), amine (2.75 ppm), and APT (3.5 ppm) effects were resolved with the multipool Lorentzian fitting approach. The ratiometric analysis was measured in the ischemic lesion and the contralateral normal area, which was also correlated with pH-specific MT and the relaxation normalized APT (MRAPT) index. MT, amine CEST effect, and their respective ratiometric indices did not show significant changes in ischemic regions (p > 0.05), as expected. Whereas APT decreased in the ischemic lesion for B₁ of 1.5 μT (p < 0.01), the correlation between the amide ratio with MRAPT index was moderate (r = 0.52, p = 0.02). By comparison, the ischemic tissue showed a significantly increased CEST@2 ppm for both saturation levels from the contralateral normal area (p ≤ 0.01). Importantly, the CEST@2 ppm ratio decreased in the ischemic lesion (p < 0.01), which highly correlated with the MRAPT index (r = 0.93, p < 0.001). To summarize, our study demonstrated the feasibility of endogenous CEST@2 ppm ratiometric imaging of pH upon acute stroke, promising to detect pH changes in metabolic diseases.

In vivo methods for imaging blood-brain barrier function and dysfunction

The blood-brain barrier (BBB) is the interface between the central nervous system and systemic circulation. It tightly regulates what enters and is removed from the brain parenchyma and is fundamental in maintaining brain homeostasis. Increasingly, the BBB is recognised as having a significant role in numerous neurological disorders, ranging from acute disorders (traumatic brain injury, stroke, seizures) to chronic neurodegeneration (Alzheimer's disease, vascular dementia, small vessel disease). Numerous approaches have been developed to study the BBB in vitro, in vivo, and ex vivo. The complex multicellular structure and effects of disease are difficult to recreate accurately in vitro, and functional aspects of the BBB cannot be easily studied ex vivo. As such, the value of in vivo methods to study the intact BBB cannot be overstated. This review discusses the structure and function of the BBB and how these are affected in diseases. It then discusses in depth several established and novel methods for imaging the BBB in vivo, with a focus on MRI, nuclear imaging, and high-resolution intravital fluorescence microscopy.

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.

Efficient optimization of chemical exchange saturation transfer MRI at 7 T using universal pulses and virtual observation points

PURPOSE

To optimize the homogeneity of the presaturation module in a Chemical Exchange Saturation Transfer (CEST) acquisition at 7 T using parallel transmission (pTx).

THEORY AND METHODS

An optimized pTx-CEST presaturation scheme based on precomputed universal pulses was designed. The optimization was performed by minimizing the L2-norm between the effective B 1 , RMS + $$ {B}_{1,\mathrm{RMS}}^{+} $$ and a given target while imposing energy constraints under virtual observation points (VOPs) supervision. The proposed method was evaluated through simulations and experimentally, both in vitro, on a realistic human head phantom, and in vivo, on healthy volunteers. The results were compared with circular polarization (CP) presaturation and other pTx approaches previously proposed. All experiments were conducted on a 7 T MRI scanner using a commercial 8Tx/32Rx head coil.

RESULTS

The simulations show that the proposed pTx strategy boosted with VOPs is superior to the CP mode and existent pTx approaches. While the best results are obtained with subject specific pulses, the gain provided by the use of VOPs renders the universal pulses superior to tailored pulses optimized under vendor provided Specific Absorption Rate (SAR) management. In the phantom, the glucose MTR asym $$ {\mathrm{MTR}}_{\mathrm{asym}} $$ map was significantly more homogeneous than with CP (root mean square error [RMSE] 17% vs. 30%). The efficiency of the method for in vivo hydroxyl, glutamate and rNOE weighted CEST acquisitions was also demonstrated.

CONCLUSION

The use of a pTx presaturation scheme based on universal pulses optimized under VOP SAR management is significantly benefiting CEST imaging at high magnetic field.

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.

Imaging of glutamate in acute carbon monoxide poisoning using chemical exchange saturation transfer

Aims

This study adopted the Glutamate Chemical Exchange Saturation Transfer (GluCEST) imaging technique to quantitatively analyze cranial glutamate and discussed the effectiveness of GluCEST values in identifying the pathogenesis of encephalopathy after CO poisoning.

Methods

The routine MRI and functional MRI scans of two cohorts of subjects (CO group, n = 29; Control group, n = 21) were performed. Between-group comparisons were conducted for GluCEST% in regions of interest (ROI), including the basal ganglia, the thalamus, the frontal lobe, the occipital lobe, the genu of corpus callosum, the cingulate gyrus, and the cuneus. Moreover, an age-stratified subgroup analysis was devised, and a correlational analysis was performed for GluCEST% in each ROI, including the time in coma, Simple Mini-Mental State Examination Scale (MMSE) score, Hamilton Anxiety Scale score, and blood COHb%.

Results

As compared to the healthy control, the CO group led to significantly increasing GluCEST% in the basal ganglia, the occipital lobe, the genu of the corpus callosum, the cingulate gyrus, and the cuneus (p < 0.05). In the subgroup analysis for age, adult patients had higher GluCEST% in the basal ganglia, the thalamus, the occipital lobe, the cingulate gyrus, and the cuneus compared to healthy adults (p < 0.05). In addition, the correlational analysis of CO-poisoned patients revealed a statistical association between the GluCEST% and the MMSE in the thalamus and the genu of the corpus callosum.

Conclusion

The GluCEST technique is superior to routine MRI in that it can identify the cerebral biochemical changes sooner after acute CO poisoning, which is significant for our understanding of the role of neurotransmitters in the pathological basis of this disease. Brain injury caused by CO poisoning may be different in adults and children.

Multiple CEST contrast imaging of nose-to-brain drug delivery using iohexol liposomes at 3T MRI

Image guided nose-to-brain drug delivery provides a non-invasive way to monitor drug delivered to the brain, and the intranasal administration could increase effective dose via bypassing Blood Brain Barrier (BBB). Here, we investigated the imaging of liposome-based drug delivery to the brain via intranasal administration, in which the liposome could penetrate mucus and could be detected by chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) at 3T field strength. Liposomes were loaded with a computed tomography (CT) contrast agent, iohexol (Ioh-Lipo), which has specific amide protons exchanging at 4.3 ppm of Z-spectrum (or CEST spectrum). Ioh-Lipo generated CEST contrasts of 35.4% at 4.3 ppm, 1.8% at -3.4 ppm and 20.6% at 1.2 ppm in vitro. After intranasal administration, these specific CEST contrasts were observed in both olfactory bulb (OB) and frontal lobe (FL) in the case of 10% polyethylene glycol (PEG) Ioh-Lipo. We observed obvious increases in CEST contrast in OB half an hour after the injection of 10% PEG Ioh-Lipo, with a percentage increase of 62.0% at 4.3 ppm, 10.9% at -3.4 ppm and 25.7% at 1.2 ppm. Interestingly, the CEST map at 4.3 ppm was distinctive from that at -3.4 pm and 1.2 ppm. The highest contrast of 4.3 ppm was at the external plexiform layer (EPL) and the region between left and right OB (LROB), while the CEST contrast at -3.4 ppm had no significant difference among all investigated regions with slightly higher signal in olfactory limbus (OL, between OB and FL) and FL, as validated with histology. While no substantial increase of CEST contrast at 4.3 ppm, -3.4 ppm or 1.2 ppm was observed in OB and FL when 1% PEG Ioh-Lipo was administered. We demonstrated for the first time the feasibility of non-invasively detecting the nose-to-brain delivery of liposomes using CEST MRI. This multiple-contrast approach is necessary to image the specific distribution of iohexol and liposome simultaneously and independently, especially when designing drug carriers for nose-to-brain drug delivery.

Simultaneous dynamic glucose-enhanced (DGE) MRI and fiber photometry measurements of glucose in the healthy mouse brain

Glucose is the main energy source in the brain and its regulated uptake and utilization are important biomarkers of pathological brain function. Glucose Chemical Exchange Saturation Transfer (GlucoCEST) and its time-resolved version Dynamic Glucose-Enhanced MRI (DGE) are promising approaches to monitor glucose and detect tumors, since they are radioactivity-free, do not require ¹³C labeling and are is easily translatable to the clinics. The main principle of DGE is clear. However, what remains to be established is to which extent the signal reflects vascular, extracellular or intracellular glucose. To elucidate the compartmental contributions to the DGE signal, we coupled it with FRET-based fiber photometry of genetically encoded sensors, a technique that combines quantitative glucose readout with cellular specificity. The glucose sensor FLIIP was used with fiber photometry to measure astrocytic and neuronal glucose changes upon injection of D-glucose, 3OMG and L-glucose, in the anaesthetized murine brain. By correlating the kinetic profiles of the techniques, we demonstrate the presence of a vascular contribution to the signal, especially at early time points after injection. Furthermore, we show that, in the case of the commonly used contrast agent 3OMG, the DGE signal actually anticorrelates with the glucose concentration in neurons and astrocytes.

Theranostic Cancer Treatment Using Lentinan-Coated Selenium Nanoparticles and Label-Free CEST MRI

Selenium nanoparticle (SeNP)-based nanotherapeutics have become an emerging cancer therapy, while effective drug delivery remains a technical hurdle. A theranostic approach, through which imaging companions are integrated with SeNPs, will allow image-guided drug delivery and, therefore, is highly desirable. Traditional methods require the chemical conjugation of imaging agents to the surface of nanoparticles, which may impede the later clinical translation. In this study, we developed a label-free strategy in which lentinan-functionalized SeNPs (LNT-SeNPs) are detected using MRI by the hydroxyl protons carried on LNT molecules. The in vitro phantom study showed that LNT and LNT-SeNPs have a strong CEST signal at 1.0 ppm apart from the water resonance, suggesting an in vivo detectability in the µM concentration range. Demonstrated on CT26 colon tumor cells, LNT-SeNPs exert a strong anticancer effect (IC50 = 4.8 μM), prominently attributed to the ability to generate intracellular reactive oxygen species. However, when testing in a mouse model of CT26 tumors, administration of LNT-SeNPs alone was found unable to deliver sufficient drugs to the tumor, leading to poor treatment responses. To improve the drug delivery, we co-injected LNT-SeNPs and TNF-α, a previously reported drug that could effectively damage the endothelial cells in the tumor vasculature, thereby increasing drug delivery to the tumor. Our results revealed a 75% increase in the intratumoral CEST MRI signal, indicating a markedly increased delivery efficiency of LNT-SeNPs when combined with TNF-α. The combination therapy also resulted in a significantly enhanced treatment outcome, as revealed by the tumor growth study. Taken together, our study demonstrates the first label-free, SeNP-based theranostic system, in which LNT was used for both functional surface coating and CEST MRI signal generating. Such a theranostic LNT-SeNP system is advantageous because it requires chemical labeling and, therefore, has high biocompatibility and low translatable barriers.

Structural and functional imaging of brains

Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological processes. Although neuronal morphology and local distribution of neurons/blood vessels in the brain have been known, the subcellular structures of cells remain challenging, especially in the live brain. In addition, the complicated brain functions involve numerous functional molecules, but the concentrations, distributions and interactions of these molecules in the brain are still poorly understood. In this review, frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), serial-section electron microscopy (ssEM), light microscopy (LM) and synchrotron-based X-ray microscopy (XRM). Specially, XRM for three-dimensional (3D) imaging of large-scale brain tissue with high resolution and fast imaging speed is highlighted. Additionally, the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is outlined. In particular, the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also summarized. We also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability, as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the brain. Moreover, the recent development of brain MRI probes with high contrast-to-noise ratio (CNR) and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is introduced. Furthermore, multiple optical probes and instruments, especially the optophysiological Raman probes and fiber Raman photometry, for imaging and biosensing in live brain are emphasized. Finally, a brief perspective on existing challenges and further research development is provided.

Label-Free Assessment of Mannitol Accumulation Following Osmotic Blood-Brain Barrier Opening Using Chemical Exchange Saturation Transfer Magnetic Resonance Imaging

PURPOSE

Mannitol is a hyperosmolar agent for reducing intracranial pressure and inducing osmotic blood-brain barrier opening (OBBBO). There is a great clinical need for a non-invasive method to optimize the safety of mannitol dosing. The aim of this study was to develop a label-free Chemical Exchange Saturation Transfer (CEST)-based MRI approach for detecting intracranial accumulation of mannitol following OBBBO.

METHODS

In vitro MRI was conducted to measure the CEST properties of D-mannitol of different concentrations and pH. In vivo MRI and MRS measurements were conducted on Sprague-Dawley rats using a Biospec 11.7T horizontal MRI scanner. Rats were catheterized at the internal carotid artery (ICA) and randomly grouped to receive either 1 mL or 3 mL D-mannitol. CEST MR images were acquired before and at 20 min after the infusion.

RESULTS

In vitro MRI showed that mannitol has a strong, broad CEST contrast at around 0.8 ppm with a mM CEST MRI detectability. In vivo studies showed that CEST MRI could effectively detect mannitol in the brain. The low dose mannitol treatment led to OBBBO but no significant mannitol accumulation, whereas the high dose regimen resulted in both OBBBO and mannitol accumulation. The CEST MRI findings were consistent with ¹H-MRS and Gd-enhanced MRI assessments.

CONCLUSION

We demonstrated that CEST MRI can be used for non-invasive, label-free detection of mannitol accumulation in the brain following BBBO treatment. This method may be useful as a rapid imaging tool to optimize the dosing of mannitol-based OBBBO and improve its safety and efficacy.

Quantitative kinetic modelling and mapping of cerebral glucose transport and metabolism using glucoCESL MRI

Chemical-exchange spin-lock (CESL) MRI can map regional uptake and utilisation of glucose in the brain at high spatial resolution (i.e sub 0.2 mm³ voxels). We propose two quantitative kinetic models to describe glucose-induced changes in tissue R_1ρ and apply them to glucoCESL MRI data acquired in tumour-bearing and healthy rats. When assuming glucose transport is saturable, the maximal transport capacity (T_max) measured in normal tissue was 3.2 ± 0.6 µmol/min/mL, the half saturation constant (K_t) was 8.8 ± 2.2 mM, the metabolic rate of glucose consumption (MR_glc) was 0.21 ± 0.13 µmol/min/mL, and the cerebral blood volume (v_b) was 0.006 ± 0.005 mL/mL. Values in tumour were: T_max = 7.1 ± 2.7 µmol/min/mL, K_t = 14 ± 1.7 mM, MR_glc = 0.22 ± 0.09 µmol/min/mL, v_b = 0.030 ± 0.035 mL/mL. T_max and K_t were significantly higher in tumour tissue than normal tissue (p = 0.006 and p = 0.011, respectively). When assuming glucose uptake also occurs via free diffusion, the free diffusion rate (k_d) was 0.061 ± 0.017 mL/min/mL in normal tissue and 0.12 ± 0.042 mL/min/mL in tumour. These parameter estimates agree well with literature values obtained using other approaches (e.g. NMR spectroscopy).

Near-Infrared Optical Transducer for Dynamic Imaging of Cerebrospinal Fluid Glucose in Brain Tumor

Aberrant cerebral glucose metabolism is related to many brain diseases, especially brain tumor. However, it remains challenging to measure the dynamic changes in cerebral glucose. Here, we developed a near-infrared (NIR) optical transducer to sensitively monitor the glucose variations in cerebrospinal fluid in vivo. The transducer consists of an oxygen-sensitive nanoparticle combined with glucose oxidase (GOx), yielding highly sensitive NIR phosphorescence in response to blood glucose change. We demonstrated long-term continuous glucose monitoring by using the NIR transducer. After subcutaneous implantation, the glucose transducer provides a strong luminescence signal that can continuously monitor blood glucose fluctuations for weeks. By using the NIR emission of the transducer, we further observed abnormal dynamic changes in cerebrospinal fluid glucose and quantitatively assessed cerebral glucose uptake rates in transgenic mice bearing brain tumors. This study provides a promising method for the diagnosis of various metabolic diseases with altered glucose metabolism.

Multiscale profiling of protease activity in cancer

Diverse processes in cancer are mediated by enzymes, which most proximally exert their function through their activity. High-fidelity methods to profile enzyme activity are therefore critical to understanding and targeting the pathological roles of enzymes in cancer. Here, we present an integrated set of methods for measuring specific protease activities across scales, and deploy these methods to study treatment response in an autochthonous model of Alk-mutant lung cancer. We leverage multiplexed nanosensors and machine learning to analyze in vivo protease activity dynamics in lung cancer, identifying significant dysregulation that includes enhanced cleavage of a peptide, S1, which rapidly returns to healthy levels with targeted therapy. Through direct on-tissue localization of protease activity, we pinpoint S1 cleavage to the tumor vasculature. To link protease activity to cellular function, we design a high-throughput method to isolate and characterize proteolytically active cells, uncovering a pro-angiogenic phenotype in S1-cleaving cells. These methods provide a framework for functional, multiscale characterization of protease dysregulation in cancer.